Data mining predicts from relationships found using classical statistics, machine learning, and artificial intelligence, searching for large amounts of data, extracting useful information, finding consistent patterns and trends between variables, An analysis process that builds a model. The result is then applied to a new subset of data and its effectiveness is tested. We perform two basic tasks, description and prediction. Descriptive mining tasks characterize the general characteristics of the data in the database. These methods hidden under buzzwords such as Artificial Intelligence, Big Data, Cognitive Computing, Data Science, Data Mining, Machine Learning, etc. are based on value-based medical in clinical fields including cardiothoracic surgery "Next It has been proved to answer the question. Urology, orthopedics, orthopedics, otolaryngology, general surgery, transplantation, trauma and neurosurgery, cancer prediction and prognosis, and incidence of intensive care units. Empirical evidence for over 20 years shows excellent predictive performance, but these methods are almost monopolistic property in academia. MCS-DS is valuable in statistics and informatics through four core areas of computer science: data visualization, machine learning, data mining, cloud computing, and university statistics and courses developed jointly with iSchool We have developed expertise on skills. . According to the US News and World Report, the internal accounting course (undergraduate course and master's course) of the University of Illinois is the top three. It is estimated that the online course costs $ 272,000 and is the most expensive MSc program offered by the University of Illinois. Dr. Computer Science, National University of Singapore, Senior Research Fellow at the University of Illinois Advanced Digital Science Center. Database queries, indexing of high dimensional data mining and causality analysis, data mining and machine learning in privacy protection, high speed data stream processing, and elastic cloud computing technology. 2008 Singapore National University President 's Award. 2015 IEEE Data Engineering Technical Committee (TCDE) Early Professional Research Award, and 2013 IEEE International Cloud Computing Conference Best Paper Award

Computer Science Terminology: Composite Structure: The size of a typical software system means that you need to divide it into manageable parts of this combination. Abstraction of the process of building a system using simpler components or components: A process ignoring problem-independent details emphasizes immediate need. Abstraction ignores some distinguished detail data. Program information function: program processing data, object processing: most abstract explanation of the basic components of object-oriented system: basic information the program can handle Block chains are essentially a structure for storing data. In computer science terminology, it is often called a data structure. Like other data structures, block chains are a central component of computer systems. It works so decently that it is very unique. Most systems we use everyday store data in a central location, usually large cloud providers (Amazon, Google, Microsoft etc). That is, especially in systems that record transactions, all transaction data is recorded and is the only visible operator that can operate that particular system. The term "data science" has appeared in various contexts over the past thirty years, but it has become the established term only recently. In early use, it was used as an alternative to computer science by Peter Naur in 1960. Naur later introduced the term "data". In 1974, Nauru announced "a brief survey of computer methods". And it freely used the term data science in the study of modern data processing methods used in a wide range of applications. In 1996, members of the International Classification Association Federation (IFCS) held a meeting once every two years in Kobe. Here, the term data science was first included in the title of the meeting ("Data Science, Classification and Related Methods"). This was introduced at Tomoo Hayashi's round table meeting.

Data Mining Overview Data mining is a combination of database and artificial intelligence technology. Although the field of artificial intelligence has made major progress in the past decade, this new field showed that AI can make a big contribution to the existing field of computer science. Indeed, many experts think data mining is the third most popular Internet and data warehouse area in the industry. Data mining is actually just the next step in analyzing data processes. Data mining advances one step further by finding meaningful relationships in the data, rather than getting queries via standard or user-specified relationships. The following example explains how to create a data mining project with SSDT. The data mining structure and the data mining model to create and explore are processing tornado data of the US state in Tornado lane which is known area by many seasonal tornadoes. These states are as follows. The next step is to prepare the source data by simplifying, grouping, aggregating, and cleaning up the source data. Do not underestimate the importance of this step. Data preparation is usually an iterative process. Let's start with a small and simple data set. Do not be afraid to create views, convert source data to separate tables, or create multiple data sets with different structures. Some mining models use optimal values ​​in separate columns, but other mining models are better using different attribute values ​​in the same column. Definition: In a nutshell, data mining is defined as the process of extracting available data from a larger raw dataset. It means using one or more software to analyze the data pattern of large amounts of data. Data mining has applications in various fields such as science and research. As a data mining application, companies can learn more about their customers, develop more effective strategies related to various business functions, and utilize resources in a more optimized, insightful way. This allows companies to approach their goals and make better decisions. Data mining includes efficient data collection and warehousing as well as computer processing. Data mining uses complex mathematical algorithms to segment data and estimate the likelihood of future events. Data mining is also called Knowledge Discovery (KDD) in data.

Scientific view This is a universally accepted truth and his ideas go beyond his time and beyond his companion His compatriots do not understand him, may be criticized, persecuted not. Galilei Galileo, Francis Bacon, and Rene Descartes were in the first person who suggested ways to escape from traditional ideas, find and locate scientific places in society. All three authors agreed on a specific point, This type of recognition of truth attracts the appeal of science, but in the end it does not pay attention to the means. Taking into account this half way of view of science, we accept Plato's decision that "poetry is closer to important truth than history". We learn to support incomplete theories and sentences, including insights into the truth, not digestive systems without valuable suggestions. A smart writer will feel it by announcing an undiscovered thinking area, to best respond to the purpose of learning or writing, and to convey new activities to a foolish spirit by hope. Recently, there has been much debate about data science in Nigerian business circle, and a considerable number of practitioners may ignore their true nature. According to training data on Cloudera's data science, data science is ultimately aimed at clarifying the business value of the organization and conveying it as a practical insight to stakeholders. At a very high level, data science is designed to solve business problems. Reduce costs or generate revenue. This approach to solving business problems is based on research that is highly scientific and highly structured. So, rather than simply talking about using data from several Python / R libraries to attack data. We are working on solving real problems and creating real value. Young researchers easily forget that many of the problems we were trying to solve today were not considered by predecessors quarter century ago. It is also easy to overlook that HGP still provides insights to people pursuing large scale scientific projects. In fact, I believe the success of today's consortium-based science depends on the six important lessons of the Human Genome Project. Accept partnership. If necessary, the Human Genome Project broke the pattern of individual researchers and left it isolated to answer a small number of scientific questions. It also violates hypothetical led research, but focuses on finding basic information that can be useful for many follow-up surveys.

With the spread of data mining technology, interest in data mining is rapidly increasing. The company is currently using its data mining technology to find new models to better customer service, to make their database checking trends, relationships and results, to enhance their overall operation, to enhance their overall behavior It makes them possible. Data mining offers many benefits for business, government, society and individuals. However, as with many technologies, data mining has a negative impact as a violation of such privacy. Understand the general concepts and basic methods and applications of data mining. And a thorough investigation of data mining subdomains: pattern discovery. Detailed data mining concept learning pattern discovery, method and use. We will also introduce some interesting applications based on the classification method and model you have found. In this course you can extend to discuss large scale transaction data, sequence mode and measurement mode of subgraph mode method, excavation and research of various modes Skills to participate in practice and pattern finding methods And the opportunity to learn content Data mining focuses on large-scale data discovery mode processes, including machine learning, statistical and database system intersections. Data mining is understood for further use by focusing on extracting information from the data, the subfield of the subject of computer science is the whole, the overall objective (using a smart way) It is information that makes it easy structure. Data mining is "knowledge discovery in the database," KDD process and analysis step. In addition to the original analysis step, it requires database and data management, preprocessing of data, consideration of model and reasoning, interesting metrics, complexity considerations, discovery postprocessing structures, visualization and online updates Definition: In a nutshell, data mining is defined as the process of extracting available data from a larger raw dataset. It means using one or more software to analyze the data pattern of large amounts of data. Data mining has applications in various fields such as science and research. As a data mining application, companies can learn more about their customers, develop more effective strategies related to various business functions, and utilize resources in a more optimized, insightful way. This allows companies to approach their goals and make better decisions. Data mining includes efficient data collection and warehousing as well as computer processing. Data mining uses complex mathematical algorithms to segment data and estimate the likelihood of future events. Data mining is also called Knowledge Discovery (KDD) in data.

For more than 10 years, "big data" and "analysis" are increasingly becoming part of the educational circle. (Big data is a term used to describe data sets, they can be analyzed only by computers and analyzes are used to describe how data is collected, analyzed and analyzed I will. The biggest obstacle to getting insight from the data is preparation of the data regardless of size. This work gives many unpleasant nicknames such as data verification, data structure, preprocessing, data management work, etc., the most time-consuming and unpleasant work for data engineers, data scientists, and ML / AI experts is. In a distributed data sharing ecosystem, challenging chaotic data is even more serious. PBDE, which enables transmission of unverified data of unknown structure, is a serious obstacle for scientists and developers who wish to use data. The promise of big data is a topic of recent town. But does big data in education mean big insights for educators and educational developers? From the data you can gain rich, bright and practical insight about teaching and learning, but it is a matter of asking the right questions, dealing with noisy and creatively dealing with incomplete data, and limiting analysis It is only by recognizing it. Briefly, this possibility provides useful and reliable insight from educational data - regardless of size, it is part of science and art The role of the term "big data" in education has begun to understand what these data sets mean to learning outcomes, but that is not clean. In the past few years, "big data" has easily become one of the biggest trends in education. Everyone wants more data; we have a huge database, some people support it, others are afraid to oppose it. But what happened to the data after all these were done and done? Through the various products I have seen, the term "educational data" can refer to almost everything learners have. Some of them are very obvious and given. For example, at the time of student registration, employees and teachers need to know who the legal guardian of the learner is, or what their living arrangements are. In other words, they may live in a dormitory and even a distant relative that may be homeless. All of these are essential to their teachers

Smith himself is a full-time father, choosing to become a male by confusing an accessible summary of social science data with anecdotes, or with a couple who was forced to become a primary caregiver by the economic environment It is a journalist in an interview. Children He plays Nerd Herd computer technology expert Chuck Bartowski who buys more stores ... When government data is downloaded to his brain, he knows secret acting I became a person. The better the measurement results and as the data grows, the physicists will put these errors under control and will draw an exciting new field. But for many people, waiting is stress. By studying ambiguous demographics and economic data, he speculates that the Soviets are on the brink - their expenditure on defense is far beyond what they suspect. There are a lot of data showing that people are flying over and this is a reliable and safe way for traveling, but more people are worried that flight does not reach the level of phobia To do. In 2025, 40 billion sensing devices and 100 billion smart devices subdivide information silos for faster, safer and smarter data exchanges. According to the Florida State Economic Opportunities Bureau, Broward County employs 4,300 construction workers throughout the year, with an annual average salary of $ 50,000. According to the Ministry of Health and Social Affairs of the Department of Health and Human Services at the Department of Health and Human Services in 2016, four children out of 1,000 girls aged from 17 to 19 gave birth and a nationwide average of 20.3 people per 1,000 females It is much lower than that. According to the Ministry of Education, in the 2016-2017 academic year, the absenteeism rate of chronic students in Howard County is the lowest, less than 10%. According to the American Cancer Society data and data used on campus, cancer is the leading cause of death for Hispanic women, with one-third of Hispanic women and one-third of Hispanic men having cancer It is diagnosed as. According to the San Antonio Realtors Committee, the median house price in the metropolitan area in May was 231,900 dollars, up 8% from the previous year's 221,300 dollars. There is no data of people type. In other words, this figure also includes black farm workers. These examples are automatically selected from various online news sources to reflect the current usage of the term "data". The views shown in the examples do not represent the views of Merriam-Webster or its editors. Please send feedback By definition, data is a broad abstract term. There are two general definitions of data: "personal facts, statistics or information items" and "series of facts, information". This is very broad, this definition covers everything you do and says online and offline. My position is a data consultant, but I do not think that I am responsible for all "facts and statistics" of people working with my workplace. This is impossible. There is no data I know. Those who deal with the best data will use their skills to convert the data to intelligence as soon as possible. This can be done by selecting the appropriate data source, getting the appropriate data, understanding them through analysis, communicating in a way that provides knowledge, accumulating experience, and over time it gets wiser It means that There is no formal explanation of data science. The mission of "understanding and analyzing actual phenomena using data" differs greatly between industry and academia. My definition of data science with two global experiences is biased towards a combination of scientific methods in the fields of mathematics, programming, communication skills and specific knowledge. I would like to summarize this approach into four different strategic areas. For over a decade, I gained the privilege to work together to bring data science to avant-garde in their field with a team of dreams. MIT's SENSEable City Lab (MIT) has pioneered the analysis of digital traces of human activit

The most common challenge faced by supply chain analysts is data. Multiple source system access is restricted. Various formats and structures lost suspicious quality information. An enormous amount Up to 80% of the analysis projects can be used to handle data problems, spend valuable time and endanger important decisions. Data Guru was created to solve these issues, and Data Guru has been tested and certified to greatly improve the process of verification and mixing of enterprise data. Most importantly, Data Guru is seamlessly integrated with Supply Chain Guru, accelerating and further automating the model building process. In modern supply chains, continuous design processes based on the latest data are needed to ensure that the design model is a clear representation of the supply chain. Data Guru builds a repeatable data conversion workflow that connects users directly to the system running the company and updates model data. Integration with the LLamasoft supply chain design tool enables users to automatically build and run supply chain models "With Data Guru you can shorten model construction time by integrating data extraction and modeling processes so you can extract data more efficiently by connecting directly to the data source." "Our approach to business development means that data is everywhere.DataGuru can connect, get data, clean up, adjust to the appropriate level, and extract data to Tableau It is a very good framework for Data Guru, so the biggest advantage of Data Guru is that you can spend a lot of time analyzing data because you can save a lot of work by pressing a button. " The data is the King. As a product manager, one of our most important roles is to become a data expert. Undoubtedly, PM extracts usage condition data and analyzes it so that we can build better products. Without King's data, we do not understand how people use our products and there is no baseline to guide our development process. It is often said that data and indicators are not mixed with intuition and creativity, but this is a limited dualism. Although these methods may look like two poles, each method has its own advantages, if you support excluding one method from the other, what is in the process Worthless. Derived data products We tend to overlook the fact that our engineering characteristics are themselves and valuable data of itself. As part of model building and engineering, consider not deploying these new data as unique, but as an API and integrating them into appropriate data assets. For example, if the data science team designed a combination of customer data, product data, and financial data, deploy the new function as an API and have the corresponding model use the new API. How does data science improve products? In Windfall Data, our products are data, so the purpose of data science is well harmonized with the company's objective of building the most accurate model for estimating capital. In other organizations such as mobile gaming companies, the answer may not be as simple, and data science may be more useful to understand how to operate a business rather than improving it. However, in such an early stage, it is a good idea to start collecting data on customer behavior. Then you can improve the product in the future.

National Science Foundation PhD Scholarship Biotin is an indispensable vitamin in the body and must be included in infant formulas and intravenous nutrient solutions. It is an important part of our diet, but we do not know the mechanism by which biotin (also known as vitamin H) is synthesized by desulfurized biotin in the body. The enzyme that completes this conversion is called biotin synthase. This enzyme catalyzes the insertion of sulfur between the deactivated biotin inactivation site and carbons C1 and C4 to produce biotin. Scholarship / honor: National Institutes of Health, National Science Foundation, Pew Charitable Trust, Rockefeller Foundation, Russell Sage Foundation Research Grant, National Science Foundation, EQUALSOC, University of Notre Dame, Maryland Knight University News Center, Canada Research Data Center Network, University of Tilburg University Oldendorff University, Swedish Sociological Association, Canadian Population Society, International Science Foundation Keynote Lecture and Excellent Lecture Institute of Justice, Immigration Bureau and National Historical Research Institute, Houston University Public Policy Research Research Fellow, IZA Bon Fellow, Stanford College Poverty and Inequality Center Researcher, Researcher of Behavioral Science Advanced Research Center, Johns Hopkins Scholarship Association, Sociological Research Association, Association of American Science Promotion Association This study was funded by the National Science Foundation Graduate Scholarship Foundation, Mazumdar-Shaw International Oncology Scholarship, National Institutes of Health, Burroughs Welcome Foundation, National Cancer Institute, and Howard Ruth L. Killstein National Research Service Award It was. Hughes Medical School Scholarships will be awarded to Catherine Muencs of the National Institute of Educational Research / Spencer Foundation. Part of this work is supported by the approval of the National Science Foundation No. 1534846. Opinions, findings, conclusions, or recommendations contained in this manuscript are all of the author and do not necessarily reflect the views of the National Science Foundation. . Communication on this article should target Katherine's goals. This structure is defined by Lens (1986) and Husman and Lens (1999) "The degree and manner in which the future of the time series is integrated through incentives into the current living space (Husman & Lens, 1999, p. . 114). How realistic is gravel? Evaluating high school students and their personality traits, self-regulation,

About 40 years ago, construction of the CVM facility was completed. AAVMC has demonstrated the need for 1,641,000 square feet of new facility and 611,000 square feet of refurbishment facility to train additional veterinarians and graduate students to meet the needs of public practice. Every biosafety level classroom, educational research institution, space for animal breeding research is necessary. Existing sources of funds such as state and university funds, donations from foundations and private funders are unlikely to meet domestic needs Recommendation 4: AAVMC and its members need to decide how to economically and logically satisfy the requirements of the CVM facility. They should consider widespread support activities for educating federal and state policy makers on the need to increase facilities to train appropriate veterinary researchers. The Committee was unable to find a useful document on the facility needs of federal or state agencies to effectively fulfill its role in veterinary research, said the Department of Agriculture of the US Department of Agriculture's Research Facilities Strategic Planning Working Group Except for the report of: 10 years strategy plan excluded. Reporting and recommendation reports recommend renovating outdated facilities and point out the need for biological protection facilities for high risk pathogen research. Alternative facilities at the Ames National Animal Disease Center in Iowa State were designed and the first phase was built on the report but did not meet all of the recorded requirements. The expanded biospecimen facility space is one of the unsatisfied recommendations and it is highly appreciated by Homeland Security Director Directive 9 (HSPD - 9). Recommendation 5: Recommendations of the 1999 USDA Department of Research Strategic Planning Working Group and HSPD-9 clause should be implemented immediately. The biological protection laboratory should pay special attention. The validity and deficiencies of federal and non-federal facilities necessary to support veterinary research should be documented and quantified. Other research resources for veterinary research include research materials such as libraries, databases, animal health monitoring and monitoring systems, electronic communication systems for sharing data and clinical information, specialized animal groups, and tissue samples Collections. In order to maximize research value and to use relatively small resources in the veterinary research community, effective communication between organizations involved in veterinary research is necessary. In particular, the database of clinical records exchanged between educational hospitals, private clinics, and diagnostic laboratories will provide data that can be used as a valuable cost-effective tool for retrospective and prospective studies . Likewise, tissue samples from other healthy animals and diseased animals and other specimens (serum, DNA, microorganisms etc.) provide exciting opportunities. Animal science and veterinary medicine to be considered for publication are included: breeding, breeding, genetics, physiology, nutrition, feed science, meat science, animal welfare, ethics and law, animal behavior, endocrinology and metabolism , Veterinary medicine, veterinary medicine, veterinary epidemiology, veterinary public health, livestock management and production, poultry science, horse science, cattle science, small ruminant animals, camels, aquaculture, fish science and fish nutrition, zoo animals Management, clinical research of zoological animals To preserve veterinary medicine or animal science, and disease of wildlife Most veterinary graduates are hired by organizations such as veterinarian occupations, surgery, local practices, or zoos. However, there are more career paths, including animal nutrition caregivers, research and education careers, or science journalists. Graduates in animal science have a variety of career options, including veterinary techn

More than 300 experts from the central government, academia and the private sector gather together, learn about new policies affecting the industry, and explore new opportunities for collaboration. In addition to networking opportunities, the conference also provided important policy updates on the 4.7 billion pound industrial strategic challenge fund announced on November 22, 2017, initiated by the Department of Commerce, Energy and Industrial Strategy I will. Supported by 14 years of major influence including business, energy, industry strategy, science and technology committee, InnovateUK, Nesta, world class academic institution, private enterprise innovation enterprise. On February 19, 2018, Dr. Bastian Halecker, CEO of Nestim and Startup Tour in Berlin, held a conference on innovative start-up companies focused on destructive technology at the DTIM conference in Berlin. Companies participating in the conference applied new technologies in data science, artificial intelligence, th internet, block chains, and consulting, food technology, human resources and other industries. Image (left to right): Jan Schnitker (Fresh Co., Ltd.), Falco Schuett (Next Big Thing AG), Sven Forgber (I like it), Martin Michenfelder (I like it), Dr. Bastian Halecker (Nestim) GmbH, startup tour Berlin), Christin Schafer (acs plus AG), Martin Micko (SearchInk), Tim Vogelsang (Octorank), Franka Birke (METR) In March 2018, the Russian Ministry of Defense, Ministry of Education and Science, Russian Academy of Sciences hosted a meeting entitled "Artificial Intelligence: Problems and Solutions - 2018". As a result of the conference, the Department of Defense announced the list of ten policies recommended at the conference. This list is not an official strategy of the Russian government, but it builds the foundation for national artificial intelligence strategy. The main recommendations include the establishment of a national system for artificial intelligence education and talent maintenance, the establishment of the National Artificial Intelligence Center, and the organization of war games to study the influence of artificial intelligence on military operations.

Since my knowledge is not confined to any specific topic, my four year graduate research has exposed me to many sub-disciplines of computer science. But the graduate course in Computer Science will help me to improve my knowledge of areas of particular interest to me. My main interest lies in the field of data mining and machine learning. I think that pursuing a graduate program at XYZ University will be an ideal step to achieve my career's desire. In August 2014, I entered the computer science online master program (OMSCS) at Georgia Institute of Technology. If all goes well, I will graduate from the end of the term. From this perspective, I think it is a good time to share some of my thoughts and experiences with the plan, and this is still very fresh in my mind. My undergraduate course is geophysics, not computer science. However, I worked in software (including college internship) through my career. As a developer of geophysical software, I quickly noticed that it is good for my career to build a solid foundation for some of the basic computer science concepts and some of the more advanced topics It was. I taught myself the high school course, and I was disappointed with my limited computer science course at high school. During college, I taught many students computer science (CS) as a bachelor's degree in seventh term, organized and executed examples of four high-level programming contests ** Total 1000 or more participants. I spent a lot of time interacting with students and teachers in CS of junior high school and high school. About 40% of teachers said that the biggest challenge facing computer science education is the support and lack of interest of school staff. A further 35% said students' interest and lack of registration are the biggest challenges. Lack of rapidly changing technology and curriculum resources is considered the biggest challenge, with 30.5% and 23.5% of teachers, respectively.

One of the tasks of joining the science fair is to write background research papers for your project. But please do not get nervous. Basically, finding and organizing information, then including drafting and polishing your thesis. Before you actually begin planning your thesis, make sure you know what your teacher needs. Sometimes, he or she wants to summarize one or two pages of what you have found in research but others need a 10 page essay including bibliography and footnotes. Collect all the necessary information from books, magazines, the Internet, government publications and interviews According to your personal situation, the "them" of this expression may be a teacher, a classmate, a judge, etc. Think about who a particular audience is, fill in the blanks. Write your first draft manuscript in your own words (so you will not steal others' work) Writing scientifically fair research papers seems to be a difficult task, but it's not too difficult. Science fair research papers are written in a format you might use to write scientific project reports. If the project contains people, animals, regulated substances or hazardous substances, you can attach an appendix containing special activities that you need to perform for the project. There are other sections in the report, such as bibliographies and abstracts. Analyze information and discussion. Here we need to include all measurements and data in the experiment as well as charts, graphs and figures. Interpret the results and provide a summary of what you found during the observation period. Compare the results with published information found in the survey. If there are too many messages that can be placed on multiple pages, please include them in the appendix. The unpleasant part of the science fair is to write research projects on the results of your research. This is the most important part of your mission. It is necessary to investigate, make a hypothesis, confirm the result, and display it. This article contains your results and your assumptions. To learn how to write scientifically fair research papers, please get a good sample of what you need to include in your project. These papers are different from other papers as we need to provide data based on the tests you are applying and the survey results you get. We need to provide an overview after trying

Once Splunk is up and running, download the sample data file from http://www.splunk.com/base/images/Tutorial/tutorialdata.zip. After downloading sample data, select [Add data] on the [Data] panel and add data to Splunk. Following the remaining steps of the experiment, Splunk should display a message confirming that the upload was successful. Next, move on to Splunk Search and continue the experiment. For searching, there are functions such as a search bar and a time range selector that selects the time range in which events can be drawn. Data collection and analysis: Collect and analyze data and business intelligence from internal sources (such as sales team and marketing team) and external sources (customers, prospects, analysts, market research, competitive analysis, etc.). Analyzing this data gives you the information to create a reasonable strategy and roadmap level decision to increase user satisfaction. At the same time, PM defines and analyzes indicators indicating product success. The work of product marketing is still very ambiguous. In fact, it is one of the few duties that covers both product, marketing and sales. It is a link between the technology and business world, on the one hand technology and products, and on the other hand between sales and marketing. Scientific data collection, analysis and interpretation model on social and cultural systems. Includes scientific research, research design, data recording, computerized qualitative data analysis, field research strategy, ethnography and report preparation, preparation of social science research ethics and fund proposal and other logic. ANTH A631 Site survey method 1-8 CR Contact time: 0 + 3-24 Registration limit: Permitted by instructor in writing. Stacking: ANTH A 431. Special rate Special note: You can repeat it once to gain credit. Graduate students supervise the work of underperforming undergraduate students under the overall supervision of the project directory. They are responsible for drilling down and recording the quality of undergraduate staff. They will be criticized as potential experts. Offer as demand warrant

5 He was an agent of the British Navy and ordered to settle on the southernmost continent. In 1836 seven US exploration was approved by Congress and exploration of five ships will explore the south sea for nearly four years. The voyage provides an observation he compiled in the past ________________________________________________________________________________________________ His observations, especially observations at ________________________________, led to his theory of natural selection and evolution. The collected temperature, salinity and depth information will determine the Atlantic seawater circulation, nutrient diffusion, plankton growth pattern. Larry Brand, a professor of marine biology at the Rosenstill Marine Atmospheric Science Institute at the University of Miami, expert on red tides, says, "But now that wealth is the result of human activity, basically due to the loss of nutrients in the land." Whether the position of the National Wildlife Committee is not related to red tide "Red tide is 1840 It was recorded along the Gulf Coast of Florida in the age and the Spanish explorer's records mention even the death of a fish near Tampa Bay. " Marine biology is a field of biology. It is closely related to oceanography and can be regarded as a subfield of ocean science. It also contains many ideas from ecology. Fisheries science and marine protection can be regarded as part of marine biology (and environmental research). Marine chemistry, physics oceanography, atmospheric science are closely related to this field. Topics that are actively studied in marine biology are the discovery and mapping of various species life cycles and the places they spend their time. Technologies that contribute to this discovery include pop-up satellite archive labels, acoustic labels, and a variety of other data loggers. Marine biologists are studying how ocean currents, tides and many other marine factors affect marine life, including their growth, distribution and health. Due to advances in GPS and more recent underwater vision systems, this has become technically feasible only recently.

An open access peer-reviewed journal covering all the basic and molecular aspects of basic medicine, emphasizing molecular research that provides biomedical problems and molecular mechanisms We are in the open access VHS-Betamax phase, and no one can agree on a single paradigm. From Harvard's open open DASH open sharing platform, various field trials range from open peer review journals in biomedical sciences to academic translation publication formats and mainly scientific history review sources. Needless to say you have to share your content on a social media site like Facebook and then own it. Biomedical science is a suite of applied sciences applying parts of natural sciences or formal sciences, or both, to knowledge, intervention, or technology in the fields of medicine and public health. The field of biomedical science can be defined as application fields of life sciences and natural sciences for the diagnosis, prevention and treatment of human diseases. Medical microbiology, clinical virology, clinical epidemiology, genetic epidemiology and biomedical engineering are medicine. However, when describing the physiological mechanisms acting in the course of pathology, pathophysiology can be regarded as basic science. Biomedical informatics is an interdisciplinary field including computer and information science, cognitive and decision science, medicine and epidemiology, telecommunications, business administration, educational science, and collaborative research in many other fields. In short, biomedical informatics is an intersection of healthcare, technology and people, with the fundamental goal of reducing costs and improving the quality and safety of the world's healthcare systems. Medical Informatics aims to manage personal health data, storage, retrieval, sharing, and optimal use with the aim of providing safer, more efficient, more affordable healthcare is. Integrating sophisticated clinical information systems into healthcare decision-making processes, allowing healthcare professionals to perform tasks in a more efficient and effective way.

In the most modern instrumental method, we need to further analyze the obtained raw data and extract the necessary information. Fortunately, this task is handled automatically by the computer. For example, suppose you want to understand the molecular size by measuring the diffusion coefficient of a protein in an aqueous solution. There is no "diffuser" for this work. Experiments such as ultracentrifugation, dynamic light scattering, pulsed field gradient spin echo NMR, etc. must be performed, and data should be analyzed appropriately to extract diffusion coefficients. In statistics, nonlinear regression is a nonlinear combination of model data and is a type of regression analysis in which observational data is modeled by functions dependent on one or more independent variables. Data is approximated by successive approximation. The following are some important techniques for dealing with nonlinear models. A piecewise function is a function defined by multiple subfunctions, each of which is applied to a specific section of the main function domain. Segmentation is not actually a function that expresses the function itself, but is a method of expressing a function, but if you have additional qualifications, you can express the nature of the function. For example, a piecewise polynomial function is a function that is a polynomial over its respective subdomain, but each subdomain may be different. Generating polynomial features: For myriad regression modeling tasks it is often useful to increase the complexity of the model by considering the nonlinear characteristics of the input data. A simple and generic method is a polynomial feature that obtains higher order and interactive feature terms. Scikit-learn has an off-the-shelf function that can generate such high-order cross terms from a given feature set and user-selected highest order polynomial. Project Jupyter was born outside the IPython project in 2014 and grew rapidly to support interactive data science and scientific computing in all major programming languages. There is no doubt that data scientists had the greatest impact on how to quickly test and build their ideas and publish the results to other users and the open source community.

The Department of Computer Science at Stanford University was founded in 1965. For half a century, the department was the power of innovation, scientific discovery, and global influence. We are particularly proud of our graduates, many of them are academia, industries, and government leaders. To celebrate the 2017 Computer Science Education Week (CSEdWeek), the Computer Science Teachers Association (CSTA) and Code.org announced the first computer science champion. From the development of wristbands and applications to enabling parents to monitor children, as a center for expanding computer science to rural communities nationwide, these winners are at the forefront of computer science movement nationwide Students, teachers, schools, regions and organizations are representative. For us who have worked on computer science for years, today's announcement means a new beginning - a new opportunity for all schools to expand their computer science products. This work has just begun until all states and school districts in the United States have tried to teach high quality computer science to complete the work. Implementing computer science in your area seems to be a tough task, especially when there are too few teachers in computer science. However, the teachers who cooperated to support the implementation of the computer science course are not ready to teach CS. They are teachers of mathematics, science, English and history who have passion for the opportunities computer science brings to students. All students should have the opportunity to learn computer science, regardless of the background or the place of residence. You can give them a chance In my eighth standard, I chose computer science as an elective subject. At that time, I was one of three students of Computer Science. I remember many teachers suggested that I take other subjects instead of computer science. But thank my parents, they told me to choose what you like. My parents love my parents because my parents do not force me. When I was 9, 10, 11 hours, I went to the Internet cafe. So, I fully learned Java, Android, and Web development (CSS, JavaScript, PHP, SQL, bootstrap etc) by saving money. I have encountered many obstacles in this learning process. Sometimes I have to wait to line up Sometimes the internet is slow. Mobile data is also slow. I spend three to four hours a day at a cafe.

Before choosing the answer that best answers your question, please read through all the answer options. Scientific test scientific test measures 40 skills required to explain, analyze, evaluate, infer and solve problems of natural sciences in a 35 minute test. In this test, there are several actual science scenarios with multiple choice questions. The contents of the test include biology, chemistry, earth / space science (geology, astronomy, meteorology, etc.), and physics. Advanced knowledge in these areas is not necessary, but the background knowledge of general introductory science courses may be required to correctly answer several questions Scientific reasoning test is 35 minutes, 40 tests in 35 minutes. There are seven paragraphs, followed by five to seven questions. These paragraphs are provided in three different forms of data representation, summary of the survey, and conflicting perspectives. This form was very easy to predict (that is, a total of 3 data representing paragraphs, 5 questions in each paragraph, 3 survey summary paragraphs, 6 questions in each paragraph, and 7 in conflicting perspective paragraphs 7 I have one question). As the number of paragraphs decreases, in Figures 7 to 6, more changes will start to occur for each channel type. But so far, there is only one contradictory view. These changes are up-to-date and the only reference that has been referenced so far is in a recently released ACT web site simulated test. There are other differences. ACT has a reading section of 35 minutes and a science section of 35 minutes. The SAT has a reading section of 65 minutes, but please keep in mind that this does not mean that SAT does not test science. In fact, SAT candidates are also required to explain numerals, formats, scientific sentences in the SAT reading column. So you know some big differences. For a complete breakdown including the total number of questions, the number of months offered, and the time allowed, see this comparison chart. It is time for your child to take the New Year's resolution and take action. To determine which test is better, ask your child to take a free full-length ACT practice test and a SAT practice test and compare the scores. If students are ranked in the top 10% of ACT and top 25% of SAT, choose ACT.

Data Analysis and Interpretation 1) The cost of the product is lower than the rupee value of each consumer's customer, and from the economic point of view the marginal utility of each consumer's currency is different. Therefore, it is difficult for marketers to distinguish money from consumers. Prior to Flipkart, e-commerce was done with credit cards or debit cards and payment had to be made at the time of ordering. Many people consider this to be dangerous and fraudulent when offering high discounts (common in e-commerce). Implement market analytics - Use OLAP data analysis tools to examine data in the data warehouse and analyze customer purchasing habits, product composition, and other strategic information. The system will analyze the best-selling products and confirm that the correct inventory is in the right place at the right time. Trend analysis - Use data warehouse for product category and inventory trend analysis to select customers' purchasing trends, analyze seasonal purchasing patterns, products requiring replenishment to identify bargains and number of responses I will. To be able to predict seasonal sales, the system must search the data warehouse and analyze 1 million products included in the sales data for over a year. All research projects must include data analysis and interaction. You can use your own data or you can use data generated by others. Although it may seem awkward at first, you can not generate your own data, so you can easily compile data from other people's work. What, you may ask !!! Is not that chaotic? This approach is very common in science in studying problems from different perspectives. Everyone has to do is to borrow the original resource of the data and get the data from there. Use whatever data you have found to solve your own research problem As the economy of mobile applications matures, there are some trends that show that it is an urgent matter to provide free open source solutions for migrating unstructured data to the cloud for analysis and data science Yes. This is exactly what we are doing because OneFold is a developer and feels pain of all developers. Recently, the ability to move MonogDB data to Google BigQuery has been added. Trend # 1: Mobile app developers catching everything is capturing everything. Yes, they actually detect the data and capture everything the user does. Whether analyzing is a secondary issue. The first principle is to capture everything. Large amounts of data points captured everyday are huge. Some applications we know capture over 1 billion data points per day

Every year, hurricanes attack Florida affecting the life and money of the company and its workers. People can ask themselves, "How can I prevent this from happening again?" This is usually a question asked by companies and people affected by hurricanes. How is the hospital? How do hospitals react to hurricanes? Even more complicated is how the hospital reacts to hurricanes when the hospital is open 24 hours. The whole conversation about data analysis is terrible for you. However, it is not usually as bad as people think. Data collection is one thing, and data analysis is another thing. You need to do it at the same time. If you want to make your products and services successful on the market, please do not ignore it. If you think that you are not analyzing data, please delegate the work to another person. There are even companies that have many excellent researchers and who want to do this work for you. Depending on the amount of data and the industry, it may be a bit expensive, but it is worth a try. Perform data analysis within the case. Data analysis can follow data collection or overlap. The advantage of duplicate data collection and analysis is to coordinate the data collection process based on topics that appear in data analysis, or to examine these topics in more detail. Data analysis is done in two stages. In the first stage (in-case analysis), researchers need to investigate the emergency concept of each case site and the patterns between these concepts to generate an initial theory of the problem problem. Researchers can "feel" research questions by subjectively interviewing the data and combining personal observations or experiences of her case at the scene. Alternatively, evolution chains and techniques can be acquired using techniques such as open coding, axial coding, and selective coding using coding strategies such as the Glasser and Strauss (1967) grounded approach. Social science research: principle, method and practice Anol Bhattacherjee University of South Florida, abhatt @ usf.edu

After acquiring a bachelor's degree in computer engineering, Pune noticed that my next step is a master's degree in computer science. When the professor of my programming language introduced us Linux operating system, it began to be realized. In the past three years, my preference for research gradually became popular in the system field. I began to experiment with open source tools that greatly improve my programming and data structure skills. My computer science base has been strengthened on courses such as "Operating System", "Advanced Unix Programming", "Data Structures and Algorithms". In the 2017 - 2018 academic year, I am a MScAC MSc student at the University of Toronto. It includes 8 months course followed by 8 month internship. The program will host an internship fair where students can meet with the company through internship exposition and apply for internship. This article is intended to support students in all of the above categories except for the first category. It is intended for students with scientific background but not coding experts. Usually these students know how to code in Matlab and Python and learn object-oriented programming, but do not know how to write C or C ++ code, and most importantly, they are Do not write production level Experience code Jacob Guerra grew up in Texas and served as a teaching designer for the university, and since 2009 began writing as a professional. His work appeared in eHow. He holds a Master of Science in Computer Education and Cognitive System at the University of North Texas and a Masters of Arts in Creative Writing from the University of Texas at Pan American. University of Texas at El Paso, MS in Bilingual Education, MSc in Educational Education, MSc in Science in Nursing Education, MSc in Nursing, MSc in National Defense and Strategic Research: $ 260 - $ 345 / Unit Time, $ 12,000 - full course $ 37,000 Some studies have shown that education does not differ greatly between online and traditional schools. For most online master's programs, especially those of accreditation bodies, those courses are of the same quality as conventional graduate courses. School standards vary from school to school, but like any other school, online instructors and programs need to pass a strict certification process to ensure that online courses meet all academic standards.

The short story "Lapaccini's daughter" can be considered a love story about a young man, but she is toxic but I am determined to be with his loved one. However, when reviewing the text, the basic theme of science has emerged. At the time of writing this, science is evolving rapidly. "All biological sciences must go through the classification phase first, as we need to order the data in order to use them for the analysis level studies" (Shryock 291) Nathaniel Hawthorne's "Rappaccini's Daughter" We use the knowledge of Rappaccini's constant pursuit. His daughter's sorrow is lost, showing scientific productivity and destructive power Interestingly, the story about women, science, and Nathaniel Hawthorne, "The daughter of Lappaccini" was a toxic person whose father made his daughter, but as a "case of minister" It looks like a black veil. This question has been attempted to try this recurrence phenomenon through the story of Hawthorne. Model scholars discussed it and they insisted that one of them had her kindness in their minds, but they were destroyed by them "(Brenzo 155) Nathaniel Hawthorne's "Hidden Birth" and "Lapaccini's Daughter" Theme Comparison: Women, Science, Beauty, and Nature Other articles and article archives related to this topic include the following: Nathaniel Hawthorne's "Fetalmark" Full Episode Summary and Analysis • Nathaniel Hawthorne's "Rappaccini's Daughter" summary and plot summary analysis • Comprehensive summary and analysis of Nathaniel Hawthorne's "Minister's Black Veil" by Nathanael Hawthorne "Young Goodman Brown" analysis and plot summary • Nathaniel Hawthorne used a fable in seven gable houses Nathaniel Hawthorne's "Hidden Birth" and "Lapaccini's Daughter" Theme Comparison: Women, Science, Beauty, and Nature Nathaniel Hawthorne's daughter Rapaccini was an introduction to this story opposed to God, Nathaniel Hawthorne described himself as a trafficker trapped between the two worlds. His alias Aubepine proposes an abstract concept that challenges simple ideas, but it supplements it by designing the dual meaning. His works contain literal meaning and meaning. Usually, he must sacrifice his original concept, and transcendence is called "nature". The name itself expresses the transcendence of the work, but Emerson uses the forest and its constituent elements as a symbol of the spiritual world. In contrast, both Puritans and transcendents are concerned about their own worldview and the existence of human beings. Edwards sermons are called "sinners in the hands of angry gods", reaffirming the fact that God is more powerful than men. Evil and evil described by Edwards

Sociology is the pursuit of knowledge of social research and human social activities, but the validity of entities as science is a worthy argument. Although sociology differs from natural science in sects, there are fundamental similarities between the two, and these similarities are used to identify and interpret the problem. By explaining why sociology is science, the next step is to identify which type of scientific sociology and its relationships with natural science. Early sociological studies suggested that the field of sociology resembles natural science such as physics and biology. Therefore, many researchers believe that the methods used in natural science are very suitable for use in social science. The effect of emphasizing empiricism using scientific methods is the difference between sociology and theology, philosophy and metaphysics. It also leads to sociology as empirical science. This early sociological approach, backed by August Comte, led to positivism, which led the data from the experience of sensation, and the logical and mathematical processing of the data was the only thing of all real knowledge I argued that it is the source of As with natural science, the purpose of positivism is to predict. But in the case of sociology, the purpose of positivism is to predict human behavior, which is a complex proposition. The use of experimental experiments in natural science and sociology is particularly important in natural science since they are devices used to prove or refute hypotheses. Science such as chemistry and physiology works with so-called closed system, which can control all variables. Therefore, this means that such experiments can be performed efficiently. - There are many assumptions that sociology has no value and sociology is science. Because science is an objective or unnoticed assumption. In sociological research, problems arise when unconscious researchers are biased toward assumptions and research topics. Robert Bierstedt said the findings or findings are irrelevant to external variables (race, sex, occupation, etc.). Sociology is the pursuit of knowledge of social research and human social activities, but the validity of entities as science is a worthy argument. Although sociology differs from natural science in sects, there are fundamental similarities between the two, and these similarities are used to identify and interpret the problem. By explaining why sociology is science, the next step is to identify the relationship between what kind of scientific sociology and natural science.

In the movie "Double Helix Competition" we will explain how James Watson and Francis Crick collected information from other scientists and discovered the structure of DNA. This movie shows that there are many ways to do science. Stealing is definitely not appropriate. However, as shown in this movie, it is not always best to follow properly. It is most dishonest, but you can gather information from Watson and Crick and lead to your own conclusion and become famous. This is their real goal. Recent discussions on tones raised all of these to new levels. Well, my feed should not only talk about how to discuss science, but people should talk about how people should talk about how to do science and how science should proceed Whether to talk about whether or not. I think these things are very important, but I am worried that science did not give priority to my time. Data sharing in clinical trials, cohort studies, astronomy and colleagues is far from complete. It is not done just because it should be done. However, they are many years ahead of most "basic" science to find exploratory research to solve the problem. For most basic sciences, there is no clear answer to the question "Who is who?" Who will use it? Regardless of whether we are talking about clinical trials (which can make or break medicine every day by human behavior) or computer science (based on my art and psychology experience) Understanding is the foundation of science. When most people think about the future of humanity, they imagine the universe that advances our species towards a better tomorrow. But science alone is not enough to solve world problems. Science needs to be done by people who understand the meaning of human beings. Several measures are supported easily and unconditionally. Yes, good computer science courses should not be considered elective courses. Yes, more schools should provide computer science courses. Yes, we would like to have more people learn computer science. However, apart from these proposals, which are easier to support, it is not clear what to do. One suggestion is to provide a comprehensive introductory CS course for each student. You only have enough students to see if you can try it. If you are doing it and want to know more, the course has achieved its objective, and we hope to provide a more detailed course. Otherwise, the course should still teach some useful understanding, not just a bunch of programming details that students who are still not interested can never use again.

Buddhism places great emphasis on finding the truth. This basic principle allows acceptance of science as science is regarded as modern truth for most people. In addition, Buddhists believe in the evolution of human consciousness - this evolution, along with the truth presented by science, allows for excessive acceptance of biological evolution. Even more interestingly, in the sacred Buddhist text Agganna Sutta, Buddha interpreted the world as it evolved over time. Although biological evolution is not mentioned, we still emphasize the evolution as a whole physically and mentally. Buddhism and science are considered to be compatible by many writers. Some philosophical and psychological doctrines found in Buddhism have something in common with modern Western science and philosophy. For example, Buddhism encourages fair investigation of nature (known as Dhamma-Vicaya in Pali Classic) - the main objective of this research is itself. Buddhism and science also emphasize the causal relationship. However, Buddhism does not focus on materialism. Thanks to its research and intellectual research, Buddhism naturally synchronizes with the dialogue of scientists. The main obstacle between Buddhism and modern science lies in the study of the essence of consciousness, one of the most complex problems. According to Buddhism consciousness is a major fact, not necessarily related to the function of the brain; of course, this does not represent the view of most neuroscientists. But the Dalai Lama often said that if science uses persuasive evidence to object to a particular Buddhist dissertation, he should not hesitate to give up these arguments. Considering the current scientific knowledge, the Dalai Lama says that the traditional Buddhist cosmology (which itself is based on the same Hindu cosmology as existed in India 2,500 years ago) is now obsolete To argue. This is certainly a bold statement and is similar to the Pope's announcement that it should abandon the idea of ​​creating the world in the sixth day. Karl Sagan is suspected to have asked Dalai Lama what he would do if the basic principle of his religion (reborn) was clearly denied by science. The Dalai Lama replied: 'If Taiwanese Buddhism would give up on reincarnation if science could object to the reborn children of the soul, it would be very difficult to resist reincarnation.' Walter and Review of 1999 research by Waterhouse 30 thorough interviews with the UK people who do not belong to past data and religious reincarnation on the level of reincarnation belief. The authors report that in the survey it was revealed that about a fifth to a quarter of Europeans have some degree of confidence in similar results as in the United States. In the interviewed group, the beliefs about the existence of this phenomenon seem to be unrelated to their age and the type of religion to which these people belong, mostly Christians.

In the previous chapter, I explained about the lack of a healthy diet promotion program at school. As a result, parents and students did not receive education on how to purchase healthy foods that cause childhood obesity. I also explained how to solve problems and the theory of social constructivism. In this chapter, I will explain the concrete method that I am planning and the three kinds of data collection planned for research. This study uses qualitative methods to study and address the lack of healthy dietary promotion at school. The research method used is a combination of quantitative and qualitative methods. The "Methodology" chapter explains the reason for this choice. The collected data was raw data mainly from the questionnaire and the focus group interview. The results were correctly analyzed. Finally, I will present the proposal and conclusion. The paper is divided into six parts. The first part is an introduction. We will briefly explain the purpose and purpose of the research, and the research method. In the second part we will cover all the literature on this topic. In the first part of this article I will detail the attitude theory, in particular the Fishbein multiattribute model, which is the basis of this research questionnaire. We also looked at consumer attitudes towards ethnocentrism among retailers, foreign retailers, and consumers. The qualitative approach is part of the five analytical perspectives that come from the data penetration approach. These methods can be used in combination with quantitative methods, academic or literature reviews, expert interviews, and computer simulations as part of a multi-method approach to data collection and analysis (called triangulation) I will. In order to help navigate the heterogeneous environment of qualitative research, we can further examine qualitative exploration of "means" and "direction". In particular, qualitative researchers often reject truths of natural science models, assuming that the resulting research processes and procedures are likely to examine the meaning rather than behavior (beyond the hypothesis test model) You may argue that you prefer to generalize. I ideally like data in the form of naturally derived words and images (eg detailed observations rather than experiments)

Science, technology, society: Needs, tasks, and limitations are focused on the role of science and technology and the limits of social formation in promoting development. This text outlines the contribution of this field in the fields of health, industry, agriculture, transportation and communications. This book emphasizes the role of engineers and scientists in promoting the development of biology, medicine and others. This text shows how we can cope with these problems through socio-economic problems in the field of food and agriculture and application of agricultural technology. Case studies in this area, including handling and circulation of fish, will improve soil fertility and animal feed feed resources. Focusing on the role of science and technology in water resource management, discuss issues related to the application of science and technology to water resource development. Science and technology have also played an important role in improving the quality of life in human settlements. This text is a source of valuable data for scientists and engineers seeking to improve science and technology and help the benefit of mankind. Science, technology, society: Needs, tasks, and limitations are focused on the role of science and technology and the limits of social formation in promoting development. This text outlines the contribution of this field in the fields of health, industry, agriculture, transportation and communications. This book emphasizes the role of engineers and scientists in promoting the development of biology, medicine and others. This text shows how we can cope with these problems through socio-economic problems in the field of food and agriculture and application of agricultural technology. Case studies in this area, including handling and circulation of fish, will improve soil fertility and animal feed feed resources. Focusing on the role of science and technology in water resource management, discuss issues related to the application of science and technology to water resource development. Science and technology have also played an important role in improving the quality of life in human settlements. This text is a source of valuable data for scientists and engineers seeking to improve science and technology and help the benefit of mankind. 1/18 page Philippines Science and Technology Society Higher Education Science and Technology Committee Preparation Course Title: Number of Science and Technology and Social Units: 3 credits Course Description: Courses dealing with science and technology interactions and shapes and shapes by them Social, cultural, political and economic context. (CMO No. 20, Series 2013) This interdisciplinary program exposes students to the reality that science and technology brings to society. This reality is an integral part of human development through personal, public and global aspects of our lives. Scientific knowledge and technology development are done in social circumstances and have all socio-political, cultural, economic and philosophical foundations. This course contains essential topics on climate change and environmental awareness. Explain how science and technology affect society and the environment, and explain the role of the country in construction. 3. As a part of society, analyze the situation of human beings to deeply reflect philosophical branches meaningful to students and express them. 4. Overall value to clarify and demonstrate the impact of social media on student life and Philippine society 1. Understand the importance of science and technology in environmental protection and the development of the Philippine people. Criticize the development of human prosperity in science and technology, allowing students to define a better life mean for themselves. 3. For comprehensive and sustainable development of society and environmental technology Training the value of a healthy lifestyle Importance and contribution 2

Understand the general concepts of data mining, and basic methods and applications. Next, I will examine the data mining subdomain, pattern discovery. Learn the detailed concepts, methods, and applications of pattern detection in data mining. We also introduce some pattern-based classification methods and some interesting applications of pattern discovery. In this course, you will practice scalable pattern discovery methods for large transaction data, master skills and content to participate, discuss pattern evaluation measurements, and minify various patterns, sequential patterns, and subgraph patterns Provide opportunities to explore ways. In this week's module, you will learn how to visualize graphs that show relationships between data items. It is also possible to draw data using coordinates not specifically provided by the data set. PS: Currently, I am making a video for DATA based on this article. Video production takes about three weeks. Our core designers who graduated from two professional video producers and visual arts schools (SVA) focused on visualizing the data story and providing clear and reliable videos to our investors and audiences I will. Data story focuses on data visualization rather than data science, but there are often interesting duplicates between topics. Biweekly, Enrico Bertini and Moritz Stefaner will talk to guests about various data topics. Recent episodes on data ethics and data viewing from the universe are particularly interesting. LiveEdu Data Science topics include data reasoning, algorithm development, and techniques to solve complex problems. In this topic, there are subcategories of data visualization, data mining, data analysis, text processing, Wolfram, data warehouse, and big data. I have worked on data visualization projects, published papers on data visualization, and developed data visualization software. But to be honest, I am done. Subjectivity and uncertainty are too high - the visualization of data itself is unreliable, not scientific and ultimately insightful insight. It works sometimes, but not as good as other methods (see below). Some may argue that the information in the text is from a wider range of sources than visualization, or that the text may be displayed at various points in the visualization itself. It is fair. But the truth still remains - in the Quartz article text is getting better in changing information into human brains. In this huge dataset, we processed a total of nine dimensions. For people with less than average average intelligence like me, it is difficult to visualize the data in 9 dimensions. Hell, 3D is enough for me. With PCA you can reduce the dimensions needed to visualize the data. For those who have never received a linear algebra or statistics course, this may be something silly for you. That is, PCA can exclude large data sets and convert them to 3D graphics based on what is called covariance matrix. This allows you to visualize the data and see if any patterns are occurring.

(Anthes, 2014) This new software marks the weaknesses of current encryption, greatly enhancing the strength of encryption. These weaknesses will be reviewed and improved to enhance encryption code, and hackers will make it more difficult to decrypt encrypted information. Algorithms developed by French computer scientists and mathematicians do not threaten the current encryption used in credit cards and e-commerce companies. (Anthes, 2014) The encryption technology currently in use has not been threatened by the new algorithm, but it shows that the group has been working on an algorithm for cracking password protected data. One of the best ways to protect information is encrypting data. Data encryption comes from the art and science encryption scheme to send spoofed messages, so only selected people can see impersonation. To others, the news is awkward. Some encryption software includes DES, RSA, and PGP. DES (Data Encryption Standard) is the most famous encryption algorithm. Since the end of 1976, Scott Kieran (2000) pointed out that DES is the official data encryption standard used by the US government to protect confidential, but not confidential data. Then decrypt the information. The most common use of DES is when funds are transferred between banks and when an ATM machine communicates with a central computer. RSA is a world-recognized software encryption algorithm. Unlike DES, RSA uses the public key to encrypt data and the other secret. The encryption algorithm converts and protects data according to the specified operation. For example, a private key algorithm such as the US Department of Defense DES (Data Encryption Standard) uses the same key for data encryption and decryption. As long as the algorithm is sufficiently complex, no one can decrypt the data without a key. Another important data protection technique is encryption. Encryption has been used to protect sensitive data and communications for decades and today's encryption is very affordable, easy to use and efficient to protect data from snooping . Encryption scrambles the information to an advanced level that encrypts or scrambles information so that no one can unlock and use the information without the correct key to unlock the data. Since the key is like a password, it is important to always properly protect the key. Small and medium-sized enterprises have room for encryption, and some encryption software is free. Encryption can be used to encrypt or protect an entire hard drive, a specific folder on a drive, or only a single document. You can also use encryption to protect data on USB or thumb drive or other removable media. Backing up data that is as important as data protection is a backup of data.

I am applying for my master's degree in Computer Science at your respected university and it is a step to achieve my goal of building a successful career at I.T. By acquiring a Master's degree in Computer Science this will greatly help me to improve my existing computer knowledge and extend my overall personality through the essence of I.T. Professional. When I was 10 years old in my 4th graders, I first introduced myself to a fascinating computer world. We practice at school every week, where we learn basic peripherals and computers. Five years have passed since I got a master's degree in Computer Science as a software engineer and I decided to acquire my PhD in Health Information Informatics. I entered a prestigious school and worked as a research assistant for a professor of computer science. The professor also served as my consultant. I like my new jobs and courses and I work hard, but I am beginning to worry that my consultants and bosses will be attracted to me. He laughed and dismissed my concern and pointed out that the consultant is 20 years older than me, married and too kind to confuse with the students. A few weeks later, my consultant took me for lunch, brought me a small gift and acknowledged that he had dreamed of running away with me. I would like to know how to put money into school even if I do not have this job. After graduation, I turned to the most popular engineering process, computer science. I began studying my master's degree in computer applications, and my only motivation was to make money quickly with the hottest process. When I started receiving formal education of computer applications, I started to like computer engineering. In order to start coding as soon as possible, we had to study coding languages ​​(C, C ++, Java, C # etc) and databases. However, I am completely on the other path, I spent more time on assembly, computer organization, operating system, data structure, data analysis and algorithms, compilers, combinations and so on. When I dug in deeply, I noticed that it is very close to learning mathematical concepts again. This is my love for computer engineering. Soon afterwards, I came to acquire masters degree in data science on my own and then realized that I was better suited to me than computer science. I carefully studied the introduction of programming environment. The first article in this series recommended several coding classes for novice data scientists. In this guide we spent over 15 hours on determining each online presentation of the statistics and stochastic courses offered as of November 2016, extracting important information from the syllabus and review, and editing the assessment. This work focused on the open source community center and the database of thousands of course assessment and reviews.

Solving problems using quantitative data may seem daily and common sense, and is another way to solve problems. First of all, what is accurate quantitative data? It is measurable (by appropriate measurements such as US dollars, degrees, inches, millimeters) and verifiable data. However, it is suitable for statistical operation. Quantitative data definition, and qualitative data description (BusinessDictionary.com, 2010). So then why do not we use it anymore - as a society? Two are dotted with 'social science' which uses problem solving methods, highly quantitative, data driven type to understand human behavior. Thus, economics is one of the most important and relevant skills in the world today, as it is the best research area for tracking, researching, forecasting and predicting human behavior, and it is an individual, society, occupation You can make informed choices in your life. Understanding humans and their motives is important for designing initiatives that could impact society and economically on society at the regional, regional, national level. This is not an ideal concept. By incorporating economic principles into policies such as China, Korea, Singapore, the whole country is improving. GMAT consists of four parts. Writing, comprehensive reasoning, quantification, and verbal expression. Over the past decade, the quantitative score scores have increased significantly, with emphasis on problem solving and data satisfaction. In 2004, the quantitative score of 48 reached the 86 th percentile. In other words, more than 86% of candidates are scored in the past 3 years. not bad! However, in 2014, it will reach the 74 th percentile with the same score. This proves the competitiveness of the graduate entrance environment, especially for students from Asia and abroad. Compared with students from other countries, you may have recently reported media performance of American students, especially in mathematics. This is because some American students do not take enough time to prepare for the exam. GMAT - the parent company of GMAT - said the average preparation time for all candidates is about 51 hours. Quantitative reasoning tests are designed to test the ability to solve problems using various quantitative methods. They may include arithmetic, algebra, data analysis, and geometry. Analytical lighting tests the ability to express critical ideas in an easy way by testing the abilities related to critical thinking.

Social science is very complicated, with a focus on anthropology, economics, history, politics, psychology, social psychology, sociology. These major branches also include subdivisions of investigation and other areas including social studies including criminology, demography, education, nursing (Bernard 6). Social science research is divided into empirical (quantitative) methods and interpretation - phenomenological methods (qualitative). In this paper we discuss the social theory that influences qualitative and qualitative research methods in social science, but in principle these theories are separable and even social scientific methods that can not be compatible. It first explains positivism, interpretiveism, and realism, and links these theories to the basis of qualitative and quantitative research methods. Then it shows how they deal with all aspects of qualitative amount division. Finally, the goal is to integrate the combined approach of methodology in a consistent way to increase value and show ways to support the design of a single research project. Stress the weakness by emphasizing the differences and similarities between quantitative and qualitative methods, providing a basis for considering the combination of the two approaches and commenting on each of the traditional complementary advantages 1 It is worth noting that in certain areas such as education and social science, quantitative and qualitative research methods can be used alone or in combination in the implementation of ethnographic research projects. However, the ethnographic journal itself is regarded as a qualitative research method. Records and images during field survey are positive, interpretive and subjective approaches to distinguish ethnographic journals from other methods, especially quantitative methods. Collected data is usually analyzed and interpreted using induction and recursion. Existing literature plays a small role in determining research problems and research direction, but it is important to prepare a written ethnographic report in comparison with what is assumed when promoting research Please be aware that it is. As an academic discipline, cultural analysis includes the use of arts, humanities, social sciences, in particular the use of ethnologically and anthropologically qualitative investigation methods, data collection on cultural phenomena, interpretation of cultural expressions and practices, data and culture By analysis. Process for obtaining new knowledge and understanding. This is particularly useful for understanding and mapping culture trends, impacts, impacts, and impacts. This refers to the extent to which culture adapts to its environment through use and development. Examples of this are food, tools, family, environment, arts and so on. They show how the given culture fits. Furthermore, the purpose of this aspect is to show how a given culture can make the environment more relaxed.

I. INTRODUCTION The concept of sustainable development began in the 1980s with the introduction of different meanings and definitions. One of the definitions quoted most frequently comes from the Brundtland report [1]. The idea, in particular the basic needs of the poor in the world should be given priority, and secondly the idea that technology and social organizations impose restrictions on the capacity of the environment to meet present and future capabilities. Typically, educational data mining (also called EDM) looks for new patterns in the data and analyzes the data gathered during education and learning, using statistics, artificial intelligence, and (of course) data mining . For example, in a learning analysis, we apply a prediction model known to the education system using various knowledge such as information science, sociology, psychology, statistics, artificial intelligence, data mining etc. Educational data mining (EDM) is data mining applied to educational data sets. In most cases, EDM is similar to normal data mining. However, certain characteristics of the educational data set must be considered. Normally, data has multiple layers. Furthermore, since many studies are being conducted at one facility, it is not easy to generalize most of the research. If you want to know more about EDM, please check the paper by Romero and Ventura. Both authors wrote several literature reviews on this subject. It provides a clear outlook on the development of the field over time. Important topics related to EDM forecasting are: Prediction of registration, prediction of student performance, and forecast of exhaustion In order to effectively analyze and control customer cancellation, it is important to establish an effective and accurate customer cancellation prediction model. We use statistical and data mining techniques to construct a churn prediction model. You can use data mining techniques to find interesting patterns and relationships in your data and predict or classify actions. In other words, the overall goal is to predict the outcome and to find hidden patterns, relevance, and anomalies of customer data using complex data processing algorithms. Data mining algorithms are a mechanism for generating data mining models. To generate a data mining model, you need to define a data mining algorithm. The algorithm analyzes specific data sets and examines the identifiable hidden patterns and trend results. The algorithm then uses that result to define the parameters of the mining model. Then use these parameters throughout the data set to extract operational patterns and detailed statistics. Details of the data mining algorithm will be described later.

Cloud computing extends and replaces traditional storage and computing methods. It offers many advantages including greater access and is cheaper than traditional field servers. Cloud computing provides an efficient and economical opportunity for many companies and individuals to store files and information in off-site data centers. By providing access to these offsite data centers, companies and individuals can access their information remotely from a variety of locations, saving money without investing in servers. With a secure calculation method, the model can train the data without displaying the data itself. Today, three main forms of secure computing, homomorphic encryption (HE), secure multiparty computing (MPC), and zero knowledge proof (ZKP) are used and studied. Since homomorphic encryption tends to be too late, multicast computing is currently the most commonly used for private machine learning, as it is not clear how to apply ZKP to machine learning. The safe calculation method is at the forefront of computer science research. They are usually orders of magnitude slower than traditional calculations, representing the main bottleneck of the system, but in recent years they have been improved. It is often said to be more properly defined in literature as security holy grail, computation of encrypted data, or secure calculations and ask questions - how to calculate hidden input functions will you do? In other words, how can we handle invisible information while obtaining understandable results? Just like a chef who prepares meals without looking at ingredients, safety calculations cause seemingly impossible problems. Even if that person is the most advanced supercomputer in the world, how can you understand data that someone can not observe? Fortunately, encryption has a clever trick to ignore intuition. Encryption has been used as a data protection technology, but this vulnerability occurs when the user decrypts the data. By keeping the keys secure, you can save encrypted data in a secure cloud file without hackers. However, whenever a user needs to access data, the user must unlock the data and become vulnerable to hackers. A consensus is a protocol that restricts all parties to comply with aggregated consistency and agreed allocation order to record approved transactions and creates an interconnected data store called a distribution ledger is. Because of the need to reach agreement, in the general block chain protocol rules, hackers must have at least 51% computing power to break the agreement algorithm that can be achieved using quantum computers.

Abstract: This article describes the trends of the data mining industry and the data warehouse industry. It covers applications and new possibilities in the field, as well as possible risks associated with information related risks, marginalities and ethical uses. As computing power has grown over the past few decades, the industry has experienced rapid growth in computing power and innovative solutions that push database and digital and mobile data in reasonable time Many found. scale This article describes the data warehouse and data mining, tools and techniques for data mining and data warehousing, and the advantages of applying this concept to an organization. It also includes data warehousing and data mining trends and applications in the current business community. Organizations use the information system to record and retrieve data from daily transactions. The information system linked to that database provides valuable data to make important and strategic decisions about the company's happiness. Organizations can predict what they have not achieved yet. This data can also be used to provide a possible solution to solve the problem you are facing and you can also use this data to gain a competitive advantage in the business environment. Definition: In a nutshell, data mining is defined as the process of extracting available data from a larger raw dataset. It means using one or more software to analyze the data pattern of large amounts of data. Data mining has applications in various fields such as science and research. As a data mining application, companies can learn more about their customers, develop more effective strategies related to various business functions, and utilize resources in a more optimized, insightful way. This allows companies to approach their goals and make better decisions. Data mining includes efficient data collection and warehousing as well as computer processing. Data mining uses complex mathematical algorithms to segment data and estimate the likelihood of future events. Data mining is also called Knowledge Discovery (KDD) in data. The sections that follow describe the historical evolution of the database and explain the data warehouse and data mining directly. It includes a simple history of data warehousing and data mining. In addition, the concept of data warehousing and data mining, and the problems faced early in implementing both concepts are also useful. The data warehouse began in the IBM lab in the late 1980's and the researchers were Barry Devlin and Paul Murphy. They first developed a business data warehouse for decision support environments. In the early 1990s, organizations tended to satisfy the growing demand for organizational information.

Everyone knows that popcorn is a delicious snack, but it is also a fascinating food, a great theme for your science fair and school projects. Please check these sections for useful information. For centuries people have been fascinated by popcorn. Native Americans believe that spiritual lives live in every corner of popcorn. When heated, the spirit became angry, eventually jumping out of the house and being blown into the air as unsatisfactory steam. An attractive but not scientific explanation of the reason popcorn pops Popcorn is scientifically known as Zea mays everta. It is corn or maize and is a member of the grass family. Popcorn is a whole grain consisting of three elements: germ, endosperm, leather (or shell). The four most common types of corn - sweet, sunky (aka field), vermiculite (aka Indian corn), popcorn only popcorn! Popcorn differs from other kinds of cones in that the thickness of the outer skin makes it possible for it to rupture. Each popcorn contains a small amount of water and it is in soft starch. Popcorn needs 13.5 - 14% moisture to become popular. Soft starch is surrounded by hard exterior When the core is heated, the water begins to expand. At about 212 degrees, the water turns into water vapor, and the starch of each core turns into a goose like super gel. The core keeps heating up to about 347 degrees. The grain pressure will reach 135 pounds per square inch before the last ship's blast An explosion releases the steam inside the reactor core. Soft starch in popcorn overflows and overflows, it quickly cools, it becomes a strange shape we know well and love. The kernel is extended to 40 to 50 times the original size. You can try a lot of experiments with popcorn. First of all, we need to compare what we measure and what to measure. For example, When you decide what you want to see, start thinking about the questions you want to ask and answer. For example, Since it is a subjective problem that is difficult to measure, avoid problems such as "which brand is the most suitable" Be sure to copy the experiment. It is important to repeat the test at least three times. In other words, comparing the number of microwave popcorn and undeveloped core, we need to test three different packages for each brand. Of course, this is a lot of popcorn, but that's only meaning that you can eat lots of popcorn. Getting better: Experiment in a few days after planning in advance If there is a dollar every time I ask this question, we are very rich. Every time we answer it we are very poor if we have a dollar. First of all, we do not mention the brand. You may have your favorite popcorn brand, but we do not have it. I like America made popcorn. But we appreciate being a science fair project, you want a quick answer, it brings us a second point: this is your science fair project. The bad news is that there is no quick answer. The good news is that you ate a lot of popcorn on the way. This event is not suitable for use as a science fair project. A good science fairness project will focus more attention on control variables and accurately measure and analyze the data. To find the perfect Science Fair project for yourself, check the creative library for over 1,150 Science Fair projects or use the theme selection wizard to obtain individual project proposals. There is no better way to learn than the actual application of the science fair project. Students who participate in the science fair are given important life skills: The Science Fair provides presentation skills to students, stimulates confidence and belief, research-led exploration ability gives passion to competition, Open the door to infinite possibilities. As a graduate of the Science and Technology Expo, as a judge, as a volunteer, as a teacher, as a student to participate in the science fair for the first time, as a supporter of science, we know the importance of science and all science fields I will. We have saved our lives and th

I grew up in Africa, I saw very few computers. My high school began using the first computer 2 years before graduation, and a famous institution like a hospital used it for data preservation. Despite their lack, such deficiencies in management, anxiety and corruption are obvious around me. This stimulated my passion for technology and encouraged me to find resources to use computers as science for problem solving. I began to get used to those remotely expensive Internet cafes, but the investment is worth it. Virtual reality (VR) is a new field of computer science, which has a close relationship between a wide range of practical applications and artificial life. Both VR and Alife practitioners try to use computers to express life processes that are artificial but operate in a living world. There are major differences between the two domains: users of VR simulators often participate in the activities of the artificial world, which is rare in the Alife simulator. Although Verimimilitude is usually in the VR simulator, the Alife simulator normally allows for basic deviations from natural rules. So, what is computer science? In general, computer science is research on computer technology including hardware and software. However, computer science is a diverse field, and in almost all industries that depend on today's technology, skills are required for application and demand. Therefore, the field of computer science is divided into a series of sub-fields, most of which are full specializations. In the computer science field, there are several core fields such as computer theory, hardware system, software system, scientific calculation, etc. Students select different professional level units from these sub-fields based on the expected use of computer science degree. Computer science or computer science (abbreviated CS) is the theoretical foundation for studying the theoretical basis of information and computing and implementing it on computer systems. Computer scientists invented algorithmic processes to create, describe, and transform information, and developed appropriate abstraction concepts to simulate complex systems. It is different from a computer. Unlike computers, physics has nothing to do with particle accelerators, biology has nothing to do with microscopes or petri dishes. I think computer science and computer related reasons are almost the same as Egyptians think geometry is about measuring instruments. . "

Marine pollution welcomes the submission of the following article types: book reviews, brief research reports, corrections, data reports, editors, general comments, assumptions and theories, methods, mini reviews, opinions, original Survey, opinion, policy review, professional issues, systematic review, technical report All manuscripts must be submitted directly to the "Marine Pollution" section and reviewed by associate editors and peer review editors of the special department. The articles listed in the "Marine Pollution" section will benefit from the frontier impact and hierarchical system after online release. As the author of the original study of the most influential publication judged by the reader, he will be invited by the editor to write articles on cutting edge comments. We call this "democratic stratification". The authors chose the impact analysis of articles based on original research published in all Frontiers' specialized journals and sections. The main comment is to focus on the first discovery, put it in a wider context and tackle wider community issues for all. Environmental science is an interdisciplinary study on all aspects of geophysical and biological environments. It includes environmental chemistry, soil science, ecology, climatology, vegetation covering, marine and freshwater systems, recovery and preservation of the environment, agriculture and land use. This week, lecturer Bill Dennison is a professor of ocean science and a vice president of scientific applications at the University of Maryland Center for Environmental Science (UMCES). Professor Denison studied seaweed and started a career as an ecologist who discovered a new type of phytoplankton (brown tide). Later his career path was influenced by his postdoctoral fellowship at Stony Brook University and his career was used not only for natural research but also for science integration and application. Suzi Spitzer is a doctoral student of the marine estuarine environmental science program at the University of Maryland Environmental Science Center. As a graduate school assistant of Integrated Communication Application Network (IAN), she is studying scientific communication and civil science. She is studying how community participation and scientific communication can effectively promote collaborative learning between scientists and the public in the context of civil science. Marine biology is a field of biology. It is closely related to oceanography and can be regarded as a subfield of ocean science. It also contains many ideas from ecology. Fisheries science and marine protection can be regarded as part of marine biology (and environmental research). Marine chemistry, physics oceanography, atmospheric science are closely related to this field. Topics that are actively studied in marine biology are the discovery and mapping of various species life cycles and the places they spend their time. Technologies that contribute to this discovery include pop-up satellite archive labels, acoustic labels, and a variety of other data loggers. Marine biologists are studying how ocean currents, tides and many other marine factors affect marine life, including their growth, distribution and health. Due to advances in GPS and more recent underwater vision systems, this has become technically feasible only recently.

In the lower extreme table below, only the list of cases with a partial value of the bay is displayed. C. In the upper limit value table, only the list of cases with a partial value of 00 is displayed. (2d) Graphical display of five selection variables (screening and cleanup processing) The bar graph displays variables of exhibition work type, age of participants, and sex. It reveals that the average age of men in the two types of work (PBS v. QRS) are very similar. In contrast, the average age of working women is lower than that of men. Quantitative data were analyzed using a descriptive statistical analysis method that scored data by calculating percentages and averages. Social Science Statistics Package (SPSS) Computer software is designed to analyze quantitative data and provide information on tables, graphs and charts to it. Linear regression analysis is also used to show the relationship between research variables. Qualitative data analysis method for qualitative data collected using unresolved problems Once you have collected the quantitative data, you can start analyzing them. But for many people quantitative data analysis is often frightening. For them, there is a good solution to the SPSS approach. SPSS is software for quantitative statistical analysis of data. SPSS stands for Social Science Statistics Package. This program is widely used by students, marketers, researchers, and data entry experts. Quantitative Data Analysis The SPSS program makes the analysis process easier, now you can get an upgrade version of the software For data analysis technology, Microsoft Excel, IBM SPSS (Social Science Statistics Package) and IBM AMOS (Analysis Torque Structure) software are used. SPSS is a well-known computer program widely used for statistical analysis of social science. AMOS is also a powerful tool for easily analyzing model fitting using graphical interface design. Therefore, with these tools you can quickly complete the results with the highest precision. However, the lack of basic skills in using SPSS and AMOS software can be a problem affecting research progress. Still, because of the rapidly increasing knowledge shared on the Internet, you can get a lot of online guidance video clips on YouTube and on the Internet tutorial. Therefore, these tools can basically be controlled in a short time.

This task explains the general problems in science through a variety of relevant and contemporary literature. It will evaluate the factors and effects that are causing the problem and propose appropriate solutions to overcome it. This problem is the difference between men and women in pursuing science-related professions. It should be noted that most of the existing literature on this subject comes from the details of women's sources. There is no doubt that women are mainly affected by this problem. The five factors above will have a major impact on women's career choice. In short, mathematics and mathematical aspects of K - 12 level have little difference between women and men, but at the beginning of the university women are 2.5 times slower than men. Caucasian women make up 43% of the US population, but they account for only 10% of physics science, mathematics and engineering (Hewitt and Seymour, 1991). Worrying about unfair education faced by girls obscures the difficulties men face in school. In the nationwide educational progress evaluation in 1992, girls won over 12 points in reading and won 17 points in writing. According to other data, boys show that there is a high possibility of entering to lower grades of girls, maintaining grades, dropping out, suffering academic difficulties, and participating in crime, alcohol, drugs. Critics of gender disparity in education tend to focus on the advantages of women's mathematics in science and mathematics, but do not recognize that men are behind women in literacy skills. Indeed, the score of the latest national test collected by the NAEP evaluation shows that girls meet or exceed boys' reading score at all ages. The difference in the literacy rate of the fourth grade is equivalent to the two years growth of men behind the average girl in reading and writing. In junior high school, according to the statistics of the educational test service, the disparity between sexes in the 8th grade is more than 6 times the mathematical reasoning, and mathematical reasoning is beneficial for men. These findings are worldwide, as the International Education Achievement Assessment Association (IEA) has found that gender is the most powerful predictor of research in 14 countries.

Science can be thought of as a system of reasoning and communication that allows us to control our environment from the beginning to our species more and more. Science arises from the knowledge of process practice that has shifted between prehistoric times and generations. Over the past 400 years scientific knowledge stands out in observational, cumulative, and always exploratory ways. Even the most sacred theory still exists in the next series of experiments confirmed or rejected. Over the past 100 years, the complexity of experimentation and analysis has become extremely surprising. Therefore, evolution including cosmology, quantum mechanics, molecular structure, cell system, cell system, etc. Every kind of electronic equipment we use, all kinds of recombinant molecules we deal with, new structural materials for medicine and everyday life , Improved weather forecasting ability, and more efficient and comfortable housing and environment can then benefit from it. Since science is technically effective, we know that science is effective. Since evolution has powerful explanatory power in all biological fields, we know that evolution is realistic. The general public is still confused about conditional reasoning and probabilistic thought, which is the basis of scientific power. However, research is the foundation of law, nutritional recommendations environmental assessment, and understanding of disease. If the research is done scientifically and honesty, they will greatly contribute to general justification and openness of change in Western society. Relying on society by science conveys the great moral responsibility of scientists to study honesty. Increasing the completeness of the research is a claim of the NAS Committee and is part of the following report (). Next Section >> Industry is a practical relationship between human and nature, natural science, and "theoretical relationship". Industry is the basic form of practice, natural science, and humanities. The industry reveals the true power of mankind Natural science is such "real power" and "possibility of production". Marx established the empirical origin and practical function of natural science and assigned a very important social role to natural science. The power of Marx's analysis transcends all analyzes of the importance of natural science to date, and the deciding factor knows how Marx generalizes genius as objective data of the era about it. Marx did not invent theory, but summarized the history and the experience of modern life. He often refers to "scientific gifts" made to humans by David, Liebig and others. In German ideology, Marx did a materialistic analysis of the dynamics of advancement in natural science. "Pure" natural science is not a factor of self-sufficiency, its history is completely independent of society. Social practices have advantages in natural science, industrial and social conditions. Natural science has actually achieved the goals and means to achieve them. If Marx called natural science as "human true power" in his early work, then in German ideology then natural science is like the true power of the ruling class. Through division of labor which is common in class society, natural science cuts into functions independent from "spiritual possibilities" of material production process, production. As a factor in progress at a certain stage, the deepening of science and industry represents the foundation of the idealistic natural science penetration.

The science behind the Bell curve behind the Bell curve has been condemned by the American Psychological Association and the Human Genome Project. The author is not entitled to talk about genetics or intelligence because their expertise is in other areas. Their projects were not realized in ordinary academic publishing systems, and in fact the authors avoided the peer review process. Bell Curve eventually received funding from the large right wing Bradley Foundation. Bradley Foundation launched a large national campaign using media contacts. Steven Jay Gould's classic study of the pseudo-science "human misunderstanding" behind eugenics has completely revealed the Bell curve's claim more than a decade ago. However, the 1994 Bell curve and its general interest in Junk science still exists, especially in the world of white supremacists, some of which are easily used as a fact to persuade others I will. Research data on the central argument that Murray and Herrnstein relied on racial and intellectual relationships were funded by Pioneer Fund. "The mission of the Pioneer Foundation is to promote eugenics, a philosophy that believes that genetically inappropriate individuals and races are a threat to society, but the cited research used in this book is their fund It is as doubtful as it is a realistic way of thinking from the perspective of "exclusion". 6 The science behind the Bell curve behind the Bell curve has been condemned by the American Psychological Association and the Human Genome Project. The author is not entitled to talk about genetics or intelligence because their expertise is in other areas. Their projects were not realized in ordinary academic publishing systems, and in fact the authors avoided the peer review process. Bell Curve eventually received funding from the large right wing Bradley Foundation. Bradley Foundation launched a large national campaign using media contacts.

The missing figures are groundbreaking activities that use geographic data to prevent and reduce natural disasters. However, the flow of technology, such as the difficulty of obtaining appropriate raw data, the lack of an effective graphical user interface, the complexity of the predictive model, and the cost of digitization, are still hindered by many problems Carrara et al., 1999). EM-DAT is a summary of data on natural disasters and technical disasters. It collects not only geographical and temporal information but also data on the impact of disasters on people and the economy. After estimating the economic loss caused by the disaster, the number of deaths and deaths of the injured or injured are provided. Obviously, it is sometimes difficult to obtain reliable data, particularly in countries where the resources required to gather data are insufficient. This weakness of EM-DAT is also seen in the absence of data on specific disaster situations in the database, but this can also be seen in some cases in this project. In order to offset these issues, consider information from UN agencies, governments, and the International Red Cross and Red Crescent Federation (CRED 2017b) In this article, I will explain the natural disaster in Vietnam and the damage caused by the disaster. The geographical location and topographical conditions of Vietnam have produced special features that led to serious diversified disasters. Natural disasters occur almost every year in Vietnam. There is a typical disaster every season, each region has special features. Vietnam is suffering from various disasters such as floods, storms, tropical cyclones, storm surges, floods, cyclones, flash floods, river and coastline erosion, hail, drought, landslides and forest fires. During the past 10 years (1997-2006), natural disasters such as typhoons, floods, droughts, etc. caused a major loss such as over 5,000 missing people and dead, asset loss equivalent to 1% of GDP It was. Natural disasters in Vietnam are getting worse in terms of size, frequency, and volatility. Because of climate, diversity of geographical and natural resources, high population density, poverty, the frequency of disasters is high and exerts a big influence. The deterioration of the environment, climate change and placement of the land at the limit makes the people more vulnerable to natural disasters. The A-P area is affected by almost all natural disasters. In addition, it is becoming increasingly vulnerable to human disasters such as war, civil war, economic crisis, looting of natural resources. In case of natural disasters and human-induced disasters, it is necessary to establish domestic geographic information system, weather forecast, connectivity to regional and world weather data, and appropriate preparation of forecast. V. Science and technology to solve the problem: food security, poverty alleviation and sustainable development

Biomonitoring focuses mainly on effective monitoring, prevention and operational capacity development to detect and respond to biological threats. S & T integrates information into a monitoring architecture using a system level approach, develops and tests advanced inspection systems, and performs cross domain attention to biological, chemical and agricultural threats. The Enhanced Passive Monitoring Program is working to further develop, demonstrate and deliver conceptual demonstration monitoring systems to identify the occurrence of endemic endemic, borderless and newly occurring diseases in livestock. The expanded system can be used to determine baseline morbidity of observed animal health problems, track changes in animal health, and to identify trigger points that warn officials to take actions from different sources Integrate multiple monitoring data streams in real time. The BioThreat Awareness APEX program develops affordable, efficient and fast detection systems and architecture to provide early warning of biological attacks indoors, outdoors, and national security incidents. In this project, the testing of integrated information sharing system also includes local jurisdiction to quickly deliver related data to important decision makers during the event. The bio-monitoring information and knowledge integration program is a prototype of a practical community (COP) platform that integrates multiple data streams to support decision-making during biological events and to provide training tools to state counterparts It is designed to develop. This work focuses on New York City and is working on a nationwide implementation. By validating the workflow and developing the COP platform to include the highest priority information flow, it is possible not only to validate functions close to the ambitious series of stakeholder prototypes but also to enlarge the latency of other metropolitan areas It also functions as a template. By examining NYC biomonitoring, you will learn how to provide bio-defense solutions with limited resources and extreme levels of competitive information and priorities. HITSP also conducts a similar review process on the health information community in the United States and has three key themes to bring innovative opportunities for healthy IT such as biomonitoring and consumer empowerment Select a field. Contractors at HHS develop use cases in these areas, but this also requires standard coordination. HITSP is operated under a three-year contract and can be updated every year for four consecutive years. Mr. Hallamka predicts "the team will talk about how to adjust the standards for competition and redundancy." Adjusting existing criteria will be a major part of the team's work. Halamka said that some requirements, such as exchanging drug lists, may be relatively simple, given that the number of standards used is relatively small. This group will focus on how technology will help open science and its role in creative processes. Naturally, European scientists, ElPeriódico, other physicists and freelance science journalist Michele Catanzaro tried to understand the direction of academic world and how to involve more scholars into open science I will. This gender-balanced group consists of stakeholder research ecosystem representatives, including young and mature researchers, academic publishers, research policy assistants, and academic policy officers. We will discuss the already available and in-use resources, as well as the sharing of data, methods, and interpretations from open peer review to open access publishing, as well as further improvements needed to make open science a part of the research workflow. Scientific research and ongoing (and predecessor) projects of CSIR - IMTECH enable technology development. The focus is science and technology related to microbial products. An important field is based on genetic recombination technology. One initiative involves the development of house

Research on library science has several problems, but one thing in common is data collection. Qualitative and quantitative information supporting actual questions is necessary to verify needs or phenomena or trends (Wildemuth, 2009). Transaction logs and focus groups are two useful data collection techniques. Transaction Log Different types of information are automatically collected in the transaction log each time someone logs in and starts using the computers in the library (Jansen, 2006). For additional information on transactions, you can check the event log. Normally, transactions contain logs that contain additional data - but not all transactions can do this, but depending on other transactions it may be written to multiple event logs. To display the event log of the registerTicker method, return to the transaction information screen you confirmed earlier and click the Event Log (1) tab. You will be taken to the screen shown above where you can see the data in the event log. Since the data of the transaction record is defined by the developer of the smart contract, the above contents may differ from contract to contract. By default, all values ​​are displayed in hexadecimal, but you can also select and change the way each value is displayed. Because the display may be different for each specific event (item arranged in different order), it is difficult to distinguish the data field you are looking for. The event is an inherited contract member. When they are called, they store the parameters in the transaction log (a special data structure in the block chain). These logs are associated with contract addresses and merged into block chains and remain there as long as the block is accessible. Logs and event data can not be accessed from the contract (they can not be accessed from the contract that created them). Solidity supports multiple inheritance (including polymorphism) by copying the code. All function calls are virtual functions. That is, unless the contract name is explicitly specified, it means calling the function with the most derived function. Once a contract is inherited from multiple contracts, only one contract is created on the block chain, and all contract codes are copied to the created contract. The general inheritance system is very similar to Python, especially including multiple inheritance.

From the 17th century to the 18th century, women appeared in the scientific community and I believed they were right. Others have announced their views that women should not practice science, and some believe that women should be able to practice science and practice . Many female scientists advocate and defend their position as knowledgeable scientists. Marie Meurdrac, a French scientist, clearly states in the preface of the publication that women and men do the same if they think in the same way. (Doc 2) Likewise, as Dorothea Erxleben understands and explains why men and women overlook to feel it is an insult, she is doing scientific research about her. Today, many brave and talented women are at the forefront of science and technology. These pioneers stood on the shoulder of the giant: yesterday female scientists have overcome greater obstacles and changed the world. Let's celebrate five female scientists to celebrate the month of women's history. Maria Sibylla Merian (1647-1717) supports myself and his family by teaching how to paint a daughter of a wealthy family in Germany. Her first book, the illustrations of two larva volumes, opposed the general view that insects naturally came out of the mud. A few years later, she sold 255 pictures, so she could take her daughter to Suriname, where they made a catalog of wildlife over two years - Charles Darwin gave ideas 150 years ago In the master's course, women acquired degrees such as biology, psychology, social science etc in 2004. Women receive less than half of the MSc in Computer Science, Earth, Atmosphere, Marine Science, Mathematics and Statistics, Physics Science, Engineering. In addition to psychology and social science, in addition to social science such as psychology, anthropology, social science such as science and sociology, the doctoral course, in addition to psychology and social science women, in 2004 half of science and engineering degrees in all fields I received the following. The woman received 46.3% of the doctorate in bioscience. Unfortunately, the number of positions in the social sciences and life sciences has been increasing and decreasing, the Federal government funds are relatively tight and the competition is intensifying. There is a shortage of women trying to acquire a degree in computer science. Currently, it accounts for only 18% of women who have a degree in computer science. Since 2004, computer science is the only science field that continues to show a decline in the number of girls registered. According to your request, the proportion of women engaged in scientific work is between 12% and 24%, which is expected to get worse. Computer science learning institutions need more female teachers. Since I can not find published data and articles on this topic, I did a drill down on myself by looking at the online teacher directory of the popular computer science course at major American universities. The number I found is even greater than the proportion of national female CS degrees. Since the number of female professors is very small, it is surprising that the computer science school feels difficult to recruit female students. These numbers are approximate.

Nothing happened at the beginning of the science park. According to Genesis, God has created everything from scratch. God created heaven, earth, light, darkness, sea, stars, birds and animals. God made man and was named Adam. God created a woman, he was named the previous night. Adam and Eve were placed in the garden of Eden. Eden is full of fruit trees, animals, and streaming rivers. In the Garden of Eden, Adam and Eve have something to eat a lot. They have no work or money. I hope this part of Saturday's science will help you imagine the microscopic activities that are happening in your garden. Important garden science is usually too small to display or conceal under the soil's surface, away from heat, sunlight, cold. Symbiosis of plants and mycorrhizal fungi is undoubtedly true. The Cornell University Agriculture and Life Sciences University Civil Science program engages students in horticulture and scientific research. Participants in Vvi interviewed the gardeners about their views on vegetable varieties and submitted the findings to the national online vegetable breed data catalog. Gardeners, researchers and others use the reported data to protect knowledge in healthy ecosystems including farms and promote biodiversity. By participating in Vvi, students can gain experience of scientific research, data collection, communication and collaboration. Vvi is for middle school and high school, but it is suitable for other levels. Visit this site and access Teacher 's Toolkit, which includes participation guides and introductory classroom activities to learn about course topics such as product features, biodiversity, interview techniques. We will integrate the garden into other classrooms courses. Many schoolyards are operated by teachers or volunteers, but they can also participate in the whole school. For example, students can predict and experiment in the garden during science, draw the size of the garden in mathematics, and understand the history and politics of food acquisition in social studies. Make your approach culturally relevant and location based. Ellis said: "If we do a FoodCorps project in the Southwestern indigenous community, our approach to food, culture and culture is different from Iowa's countryside with our work in Mississippi delta Regarding the cultivation of climate food, the community's tradition is important and should be -

In my fourth semester and five semester microprocessor, I was mentioned in microcontroller. I like to study them. By being interested in these subjects, I was able to complete the "postgraduate diploma of embedded system" course other than the multi-semester course. This course covers the practical aspects of data structure, Linux operating system, ARM architecture, programming controller, and processor. I have studied various device drivers and various protocols such as I2C, SPI, CAN, TCP and UDP. Five years have passed since I got a master's degree in Computer Science as a software engineer and I decided to acquire my PhD in Health Information Informatics. I entered a prestigious school and worked as a research assistant for a professor of computer science. The professor also served as my consultant. I like my new jobs and courses and I work hard, but I am beginning to worry that my consultants and bosses will be attracted to me. He laughed and dismissed my concern and pointed out that the consultant is 20 years older than me, married and too kind to confuse with the students. A few weeks later, my consultant took me for lunch, brought me a small gift and acknowledged that he had dreamed of running away with me. I would like to know how to put money into school even if I do not have this job. I grew up in Accra, capital of Ghana. After I graduated from high school, I studied at the Kumasi University of Science and Technology (KNUST) and got a BS in computer science. Upon completion, I would like to continue my master's degree, but KNUST has not yet begun offering a master's degree in Computer Science. As a campus teaching assistant, I began looking for schools overseas. Meanwhile, I touched some of the exchange students at the University of Pennsylvania who took part in the KNUST Campus International Development Summer Academy program. They are very enthusiastic, we talk about Pennsylvania University living and American education. At about the same time, the Director of Science was in touch with the University of Pennsylvania and I will contact you. He added that the Philadelphia Region and the school have a vibrant Ghana / African community. MCS degree (Master of Computer Science) is our professional lesson. Most volunteers for this degree are interested in expanding their skills, but they are not interested in computer science research. MCS students are currently working in the US and have been leaving school for a while. Students in the program can complete most courses online (via UNITE) or at night. Due to the limited number of 8000 courses offered by UNITE it is difficult to complete a degree program online. Students must visit the campus for various reasons related to the course and degree acquisition step.

Team projects are difficult to achieve. You are faced with unfamiliar barriers and rely on a new process. Members of your team may not be able to share history, which means they tend to work together. The short-term nature of many projects means that it is difficult to tie everyone around emotional vision. So, how can we guide the success of the next group project? To your surprise, you should raise the difficulty by assigning difficult tasks. This seems counterintuitive, but according to a survey published in the Journal of Leadership and Organizational Research, the task of providing difficult tasks to team members actually enhances the overall commitment to the project . "Individual expectations for my performance will be influenced by the difficulty of the project so individuals will adjust my actions (from the perspective of effort and direction) to ensure the success of the project," researcher Explained. In other words, by receiving a challenge, colleagues can be more interested in the outcome of the project and work harder - you and your team are more likely to achieve the ultimate goal. But for some people it is hard for another person. Please list your team members and include your knowledge about their strengths and weaks before the next project begins. After that, once you divide your project into subtasks you can delegate based on your personal possibilities. Ask the team members throughout the project whether they are satisfied with their work and whether they fit well with their abilities. If someone does not seem to be challenging, please change the role to make it more important or complicated. I understood that everyone likes to challenge. Apply this concept at work and see if your project succeeded The success of almost all group projects begins with an understanding of the task, as well as an understanding of the dynamics of the team or team project. The classic model of the group stage originally developed by Bruce Tackman is what anyone who has been assigned to be a member of the group project must understand. It is almost guaranteed that successful teams will make progress at all stages: formation, rush, specifications and performance. If the team did not succeed, one of the early stages of the process may have resulted in an error. Created by a group of successful Internet entrepreneurs, maintaining the unique excitement and creativity of emerging companies and early business. Perhaps best explained as an intersection between the internet project launcher and the end-to-end new media consulting company, we change our vision to reality and sometimes work with others. Linkedin Innovify is an emerging digital product management company headquartered in London. Innovify offers a wide range of expert services to help develop innovative products that enable customers to focus on key business drivers. Its collaborative model that plays a role in agile concept, it has become a trusted partner for customers. LinkedIn One of the main focuses described in LinkedIn Group Management for Management is a major success factor in the adoption of data science. The team checks employment markets and specific organization opportunities weekly. Team managers regularly interview HR professionals and data science experts and gain insight and debate. In the coming months, the team will share examples of effective recruitment strategies and will support the design of employment interviews with visual resumes and scripts. Join the discussion and practice what data science advertises

The need to acquire a degree in computer science Today, the recruitment market is as diverse as the computer field, and the degree is a very valuable asset even if you can get a job without it. Many students believe that work experience is more beneficial than practical experience. Bill Gates of Harvard University co-founded Microsoft (Morneau). "Whether you are interested in any field, you gain high market value by acquiring a degree in computer science," said Wayne Diesken, Deputy Director of the Department of Computer Science at Purdue University. one I am a black woman, and she will get a degree in Computer Science from Dartmouth University within a year. Every year, thousands of Black and Latinx graduate with a bachelor's degree in computer science. Most of us are not hired in the technology industry. Therefore, Facebook did not try to find us, but ignored the fact that we existed. When I saw this article, I had to fight back with tears. I thought about all the work I did to reach my position today and I wondered if it is important to start a job search within a few months. According to most technology companies, I do not belong if I can not challenge through algorithms, or if it is "culturally incompatible". I have not started my first full-time job, and I am tired of the feeling that it has been eradicated and abused by the technology industry. Over the past few years, I tried to make myself visible, so I grieved to see Facebook face making such an erroneous statement. There is a shortage of women trying to acquire a degree in computer science. Currently, it accounts for only 18% of women who have a degree in computer science. Since 2004, computer science is the only science field that continues to show a decline in the number of girls registered. According to your request, the proportion of women engaged in scientific work is between 12% and 24%, which is expected to get worse. Computer science learning institutions need more female teachers. Since I can not find published data and articles on this topic, I did a drill down on myself by looking at the online teacher directory of the popular computer science course at major American universities. The number I found is even greater than the proportion of national female CS degrees. Since the number of female professors is very small, it is surprising that the computer science school feels difficult to recruit female students. These numbers are approximate. I like computer science. When I attended school in the 1980's, women received about 37% of computer science degrees and law degrees. The law now rises to 47%. In medicine, our proportion in 1984 was 28%. This ratio is also 48%. Computer science rose from 37% to 18%. I began to understand it, my God, said. For me, the technology industry is one of the easiest places to work. If I work again, I will work with biological science, technology, or a combination of them. Every company needs technology, but we graduate with fewer female technicians. This is not good for society. I need to change it

It looks like what seeps around the haunted house you see in horror movies (this means that the kids find it very coolly) It is difficult to imagine science without technology. Science is to gather data, in other words to experiment. Equipment is necessary to conduct experiments. Even the most basic equipment is technology. From wheel to Bunsen burner, and then mirror, everything is technology. Therefore, technology is used in all experiments. However, as technology advances, we can try what was impossible in the past. You can use a spectrometer (for spectrometers) to illuminate the light through the material and see what it is making. We can use a huge telescope to observe the distance of our universe. We can use the MRI scanner to examine the inside of the human body and even the brain itself. Arthur C. Clarke, a British science fiction writer, suggests another idea about the magic point of view. He explained magic and science as a continuum of human experience and concisely expresses it with his third prediction rule: "A sufficiently advanced technique can not be distinguished from magic". This law stipulates that current traditional techniques are not considered magical long ago. Because magic and science are opposite each other, there seems to be no relationship between magic and science, but there are many things in common. The drama fantasy suggested by the magician seems to be in violation of the laws of physics science, but they often use these and other scientific principles to create these illusions. Scientists are very interested in magic because they try to better understand this unique performing arts. The difference between science fiction and magical realism is that in science fiction people can do it through science. But in magical realism, what can not happen. This movie is more magical realism than science fiction. Some aspects of the movie represent magical realism like movie pictures. Things are impossible, but there are frames with organic texture. What I'd like to say is about science fiction. You only implement it in some way! There is little support. The first government movie fund was launched last year. $ 150,000 / year - for everyone - so we only have a few measures. The wonder about Guatemala is that if you say that you have a camera and you are a filmmaker, you are a filmmaker! This is very exciting. This is the moment

In computer science major and course you will learn about software engineering and design, algorithmic thinking, human-computer interaction, programming language, and history of computation. This wide range of courses help you to think abstractly, deal with problems in a regular way, and develop sound solutions. To celebrate the 2017 Computer Science Education Week (CSEdWeek), the Computer Science Teachers Association (CSTA) and Code.org announced the first computer science champion. From the development of wristbands and applications to enabling parents to monitor children, as a center for expanding computer science to rural communities nationwide, these winners are at the forefront of computer science movement nationwide Students, teachers, schools, regions and organizations are representative. For us who have worked on computer science for years, today's announcement means a new beginning - a new opportunity for all schools to expand their computer science products. This work has just begun until all states and school districts in the United States have tried to teach high quality computer science to complete the work. Implementing computer science in your area seems to be a tough task, especially when there are too few teachers in computer science. However, the teachers we cooperated to support the implementation of computer science courses are not ready to teach CS. They are teachers of mathematics, science, English and history who have passion for the opportunities computer science brings to students. All students should have the opportunity to learn computer science, regardless of the background or the place of residence. You can give them a chance In my eighth standard, I chose computer science as an elective subject. At that time, I was one of three students of Computer Science. I remember many teachers suggested that I take other subjects instead of computer science. But thanking my parents, they told me to choose what you like. My parents love my parents because my parents do not force me. When I was 9, 10, 11 hours, I went to the Internet cafe. So, I fully learned Java, Android, and Web development (CSS, JavaScript, PHP, SQL, bootstrap etc) by saving money. I have encountered many obstacles in this learning process. Sometimes I have to wait to line up Sometimes the internet is slow. Mobile data is also slow. I spend three to four hours a day at a cafe.

A reasonable result can be as good as its assumption. When 'x' and 'y' assumptions are made and the result 'z' is derived, rational discussion and science can clarify whether that applies or not. If it matches 'x' and results in 'z', 'y' can be thought of as correct (rational). Otherwise, it is wrong to do 'y'. Therefore, the wrong or correct idea depends on the 'x' assumption and the expected result 'z'. The problem of moral science is that it arbitrarily determines "x" and "z" and then decides whether y is correct or wrong. The Science World Science Parade held all over the world at the end of the week was politicized science and criticized by some people in the scientific community. As science is neither a belief system nor a moral problem, I tend to agree that science is not a political factor. Gravity is something that is not influenced by faith and morality, it is just a thing. However, the feelings of some people are getting stronger and they want to try science through a belief system. So, sorry Science, whether you like it or not, you are political. You should be very skeptical of scientists and scientists who make moral declarations. Science and ethics should not be separated from church and state (or pseudoscientic metaphor of substances and antimatter in spacecraft warships), but more ethical assertions will support science. We try to prove that seeking a specific moral opinion in the world can overcome the critical evaluation necessary for legitimate scholars. In particular, gender research seems academically confused by the highest priority religious belief that men are the source of all evil. According to the evidence, our doubt is reasonable. Critical Bible scholarships provide the most reasonable and long-standing Bible interpretation, utilizing a wide range of fields including literary criticism, archeology, history, linguistics and social science. This is not just a matter of mentioning personal beliefs or the official church doctrine. The word arsenokoites is relatively rare. The scholars have claimed male prostitution or male prostitution, or something else. Translating it to "gays" is a problem for two reasons: Paul is unlikely to have the concept of sexual orientation, and he certainly does not explain the relationship of faithful adults. In her thoughtful paper on the moral reasons of social science, Haan (1982) compares human morals with science. She stated that the fact of consent is the goal of science and agree that the parties are the goals of death. Both are accomplished by a similar dialectic. Hearn stated that the dialectical method of science "accepts and evaluates all the evidence pursued by immediate consideration, hypothesis" and hopes that it is "best suited to data" .... Everyone admits that other people have the same rights and is ready to participate in an exchange that can be done, everyone has to say frankly the request saying what they want. Their first thought was reasonable - (p.1102)

Social Science In the last century scientific discoveries are growing at an exponential rate. Evolution, genetics, physics, chemistry have great influence on how people observe the role of the universe and human beings. Furthermore, the application of scientific discovery physically changed society. For example, humans can not fly in 80 years and can transport using supersonic jets. Rapid scientific change is casting many questions about morality and science. Any editor reads and says this article - divide it into two articles - but this is done to separate art, science and science. Art, science and society will not happen in a vacuum. I remember the chief scientist who was unable to record how the small group of people accomplished the task with the augmented reality headset because he wanted to control each variable to add data to a new perceptual scientific discovery. Although systematic research is important, it is not permitted to obtain intestinal reactions or to observe emotional responses to AR / MR / VR. If we do not know the everyday feelings, experiences of people and create them through emotional observations - people may not see the bright side, so perception time, eye fatigue effect and ergonomics are completely It may not be understood. Technology may make a dark view of where humans are. Society also requires the most innovative scientists to sympathize a little about how to use this discovery. What is the role of science in society? Does science improve our ability to live in a sustainable way? Does science communicate effectively with society? From a social point of view, science should provide solutions to our daily problems and technical and philosophical problems. Science should improve the quality of response to society. Science, on the other hand, requires sophisticated support from society. Financial support is probably the most obvious, certainly an important issue in management science. However, science must also communicate with society. Feedback and understanding from the general public is important for improving science and protecting the natural environment. However, communication between scientists, managers and decision-makers remains a major issue.

Spreadsheet report - for science teachers teaching 10th grade at junior high school. He can not manage all data on the 10X2 exam and attendance. The spreadsheet report spreadsheet is for science teachers teaching junior high school graders. He can not manage all data on the 10X2 exam and attendance. He wondered if the computer will help with the module test data this year is doing. This teacher is not alone. According to a recent report published in Science magazine most teachers in the United States have taught climate change, but spending an average of one to two hours per grade to discuss the problem. In addition, most teachers included in this study turned out to contain erroneous or inaccurate information in their teachings on climate change. A recent article by the New York Times pointed out that the degree of confusion among educators may not be surprising. Many teachers do not include climate change information as part of their science education and training, and some educators may lack the confidence needed to successfully complete the subject education. In order to become a science teacher at a public school it is necessary to obtain a certificate of education or license from the provincial government and qualify for science education. Science teachers usually complete a teacher preparation course that states accepted as part of a bachelor 's degree majoring in subjects that you would like to teach, such as biology or chemistry. A typical way to become a science teacher is as follows: Even if you already have a baccalaureate in the department, if you have not completed your teacher's preparatory course, you can substitute your state I am qualified to qualify. In many states, the master's degree can also qualify for a science teacher license if the degree includes teacher preparation component approved by the degree. I have a bachelor's degree in nutrition and diet and an official teacher in the Philippines. I taught food science and basic nutrition for three years at high school. I decided to teach a kindergarten, and now I have completed my graduate diploma in early childhood at the University of Auckland in New Zealand. I am a teacher assistant for two years at Singapore's international school. I have not had experience of my kindergarten. Am I eligible? Do you need 2 years of practical experience in New Zealand? please tell me. Thank you very much. July 28, 2011 - Zena

Data Envelope Analysis in University Rankings 0 Introduction Data Envelope Analysis (DEA) is a way for an organization's decision unit (DMU) to generate performance indicators with multiple inputs and outputs. (Dyson, 2000, OR Insight Vol 13 Issue 4). The DEA considers each unit in a linear programming sequential order and selects the most suitable weight for it. In this survey, the DMU is a university, the output belongs to another category, ie the selection / hypothesis of one dataset "completion rate" 12 The list of the top 100 universities is the most advanced "computer Science "comes from. Bhagavath, (2006) defines the data envelope analysis as follows. "Data envelope analysis is a linear programming problem that provides a way to calculate the level of service efficiency within an organizational group.The efficiency of the organization is based on what the group observed best.Haq et al. (2010) We are using DEA for a number of reasons.It can use multiple inputs and outputs in the model in the model.It does not need to specify the parametric function form of the production function.This makes it easier for the administrator Finally, in addition to certain scale of sense assumptions, it is also possible to analyze non-profit organizations.This study compared the other non-parametric and parametric methods Because of many advantages, we use DEA. Using Data Envelopment Analysis (DEA) (another technique is Free Disposal Hull, FDH) masks all other methods of nonparametric classes. Charnes, Cooper, and Rhodes (1978) introduced this technology and named it today. Data envelope analysis techniques use linear programming to generate segmented envelopes on data points. Although this method is widely used for research on technical efficiency, it has the disadvantage that randomness is not taken into measurement efficiency. Furthermore, the envelope curve does not exist everywhere. Our focus in this study is parametric technology. A paper on nonparametric and econometric models that can successfully combine data envelope analysis is described in Auditbert et al. It is (2003). Together with data envelope analysis and Tobit model, they infer the social and healthy determinants of the efficiency of cotton farmers in the northern part of Cote d'Ivoire. As representatives of family health, they use high density malaria parasites in the blood of individuals. They use a two-step process; first, they use data envelope analysis to derive relative technical efficiency values, and then what they think they will affect efficiency And compare these efficiency scores. The variable "high density malaria parasite in the blood" entered the model at the second stage. Their findings show that malaria greatly reduces farmers' technical efficiency. They further concluded that the strength of infection is more important than its existence.

Class Note: Data Structure and Algorithm Summer - C Semester 1999 - M WRF Phase 2 CSE / E 119, Section 7344 Issue 1 - Solution (Blue Type) Note: There are many questions about this homework assignment. Therefore, the clarification is published in red below. When answering these questions remember that each question counts only 4 out of 1000 points of the course. Therefore, everyone should have a brief answer. There is no need to write a paper. * This problem assumes you want to find the maximum value of n different integers of columns or vector a. Since programming is a very important part of computer science, this series focuses on programming. But this is not all. After laying the foundation, I begin discussing algorithms and data structures, computer architecture, discrete mathematics, network security / penetration testing / hacking and analysis. Computer science is a very wide field and I think that this essay is not fair. Through this series of processes, I hope that not only will I scratch the surface of this wonderful crazy field, but more things will be possible. There are more than most people can see, I like every aspect of it If you are interested in how to implement the data structure, check Lago (the data structure and algorithm library for JavaScript). It is almost still a WIP, but I will change it to a library that can be used for production, and a reference resource to learn data structures and algorithms. Practice and solve algorithm problems in the selected language. Interview coding interview is a wonderful resource but I prefer to solve problems by inputting and running code and getting feedback right away. There are various online judges such as LeetCode, HackerRank, CodeForces. You can practice questions online and get used to that language. In my experience, the problem of LeetCode is most similar to that presented in the interview. The problem with HackerRank and CodeForces is similar to the problem of competing programming HashMaps is probably the most commonly used data structure for algorithmic problems. If there is a problem, the last approach is to enumerate possible data structures (fortunately not much) and consider whether each can be applied to the problem. This is sometimes useful to me. If you are cutting corners with code, explain it to your interviewer and explain to them about what you do outside the interview setup (no time limit). For example, instead of using split, you want to write a regular expression to parse a string. This does not include everything.

The publication "Science for the People" has reprinted its publication, which was published online in early February 2019 bimonthly from 1969 to 1989. We are presenting a critical and fundamental analysis of the current problems in science and society. Please fill in the form below Science is based on data collection and analysis. Educators, behavioral scientists, and social scientists collect and analyze data on individuals, including individuals and groups. This is the key to possible conflict between research purpose and privacy. In many cases, this type of research seeks to obtain information about attitudes, beliefs, opinions, and actions. Thus pursuing scientific goals has caused complicated problems while preventing unnecessary participants from violating privacy Science makes people involved in research, behavior and science to improve society, improve ecology, protect the environment and meet human needs. Scientific members of people include science, technology, engineering, workers of mathematics (STEM), educators, activists with social and moral interests, science should be a positive force for humans and the earth I believe that. Civil science currently supports conservation and ecology, but more and more researchers recognize the advantages and cooperate with civil scientists. In this special article we will examine how citizen science influences ecological studies and how it affects conservation. In addition to providing data collection, civil science can also be a powerful way to involve the public in science issues and to tackle protection challenges. In an article by McKinley (2017) in the special issue of Citizen Science and Biosafety, a group of experts in civil science is exploring how to use this method and plan how to use this method.

Quantitative surveys include quantitative, logical and objective positions. Quantitative research focuses on numerical invariant data rather than divergent reasoning, and detailed and convergent reasoning. Data exists in numerical and statistical form and is usually placed in a table, graph, graph, or other non-text format. Projects can be used to generalize concepts more broadly, predict future results, and investigate causality. Quantitative methods highlight the operation of existing statistics by using objective measurements and statistical, mathematical or numerical analysis of data collected through polls, questionnaires and surveys, or using computational techniques. The focus of quantitative research is to collect digital data and spread it to a population or explain specific phenomena. Babbie, Earl R. Practice of social investigation. 12 th edition California Belmont: Wadsworth Cengage, 2010; Muijs, Daniel. Quantitative Study on Education Using SPSS Second Edition London: SAGE Press, 2010 "Political Analysis" is a peer-reviewed political magazine of the quarterly journal published by Cambridge University Press Publications and Institute of Political Methods. The journal emphasizes the quantification of political methodology. According to Journal Citation Reports, the impact factor in 2016 is 3.361, ranked fifth in 165 journals in the "Politics" category. Publication of a paper on quantitative social science research and methodology. In this feature article of this magazine, I explain the use of quantitative method to empirically test social science theory. The journal emphasizes research on problems and methods over traditional areas of the route. While paying particular attention to the methods used only in specific social sciences, these approaches are ultimate goals of testing social science theory and may be applicable to a wider range of disciplines Although political science is methodologically diverse, the use of scientific methods has dramatically increased in recent years, ie the establishment of formal deductive models and the dissemination of quantitative hypothesis tests. Discipline methods include rational choice, classical political philosophy, explanatoryism, structuralism and behaviorism, realism, pluralism, and institutionism. As one of the social sciences, political science uses methods and techniques related to the type of questions being sought. Primary materials such as historical documents, interviews, official records, and secondary materials such as academic papers are used in building and testing theory. Empirical methods include survey research, statistical analysis or econometrics, case studies, experiments and model building. While teaching history at Johns Hopkins University, John Burt and Baxter Adams founded a "political department".

The educational mission of computer science and engineering at the University of California at Irvine is to provide students with a comprehensive interdisciplinary computer science and engineering training. This is accomplished through the development and provision of courses that integrate the foundations of computer science, including hardware and software, and the application of engineering concepts, techniques and methods in computer system engineering and design. (1) Establish efficient computer science and engineering professionals in industry, government and academia. (2) Professional practice in computer system engineering and software system engineering (3) Promote the development of innovative systems and solutions using integration of hardware and software. (4) Promoting the design, research and implementation of products and services in the areas of computer science and engineering through strong communication, leadership and entrepreneurship (The goal of the education plan is to help shape the aspects of the computer science and engineering of the curriculum, achieving these goals is the responsibility shared between the students and the UCI. Analyze complicated calculation problems, determine the solution by applying calculation principle and other related fields. Design, implement, and evaluate computing-based solutions to meet a range of computing requirements in a planning rules environment. Recognize occupational responsibility based on legal and ethical principles and make judgment based on sufficient information in computing work Effectively fulfill the role of a team member or leader involved in activities appropriate for the field of the program Ability to identify and solve complex engineering problems by applying engineering, scientific and mathematical principles. Ability to apply engineering to create solutions that meet specific needs, taking account of public health, safety and welfare, as well as global, cultural, social, environmental and economic factors. In order to be able to identify ethical and professional responsibilities in engineering and make informed decisions, it is necessary to consider the impact of engineering solutions in global, economic, environmental and social environments. A team that works effectively. Members will work together to create leadership, build a coordinated and comprehensive environment, set goals, plan tasks, and achieve goals. Ability to develop and implement appropriate experiments, analyze and interpret the data, and use engineering judgment to draw conclusions. Standard student achievements of the Computational Certification Committee (CAC) and the Technical Certification Committee (EAC): [Proposal of changes, revisions, and program standards] (http://www.abet.org/accreditation/accreditation-criteria / accreditation-changes /) 1 STEM field is the mission of NSF to support "all fields of basic science and engineering" including computer science, programming, information technology, engineering, mathematics and statistics, science, biology, earth science, geology, physics It is based on. Chemistry and other major and environmental science NLTS 2 Questionnaire combines psychology, economics, political science, sociology (NSF STEM) with non STEM majors such as history, female research, American studies, ethnic studies, Social science, behavioral science, and economic science are not included. . We did not include them in the STEM field Participation in science, technology, engineering and mathematics (STEM) of undergraduate students with autistic spectrum disorders The educational mission of computer science and engineering at the University of California at Irvine is to provide students with a comprehensive interdisciplinary computer science and engineering training. This is accomplished through the development and provision of courses that integrate the foundations of computer science, including hardware an

The use of experimental experiments in natural science and sociology is particularly important in natural science since they are devices used to prove or refute hypotheses. Science such as chemistry and physiology works with so-called closed system, which can control all variables. Therefore, this means that such experiments can be performed efficiently. It may be difficult to control the variables of physics science and rebuild the daily lives of sociology, but natural science does not face the same top priority problem. Early sociological studies suggested that the field of sociology resembles natural science such as physics and biology. Therefore, many researchers believe that the methods used in natural science are very suitable for use in social science. The effect of emphasizing empiricism using scientific methods is the difference between sociology and theology, philosophy and metaphysics. It also leads to sociology as empirical science. This early sociological approach, backed by August Comte, led to positivism, which led the data from the experience of sensation, and the logical and mathematical processing of the data was the only thing of all real knowledge I argued that it is the source of As with natural science, the purpose of positivism is to predict. But in the case of sociology, the purpose of positivism is to predict human behavior, which is a complex proposition. The use of experimental experiments in natural science and sociology is particularly important in natural science since they are devices used to prove or refute hypotheses. Science such as chemistry and physiology works with so-called closed system, which can control all variables. Therefore, this means that such experiments can be performed efficiently. - There are many assumptions that sociology has no value and sociology is science. Because science is an objective or unnoticed assumption. In sociological research, problems arise when unconscious researchers are biased toward assumptions and research topics. Robert Bierstedt said the findings or findings are irrelevant to external variables (race, sex, occupation, etc.).

When learning the humanities and natural sciences, people may question the validity of the claims and may choose to support the claims without evidence. For many years science has been accepted by many people as a major cognitive paradigm or knowledge model. In fact, some people think that science is the only way to acquire knowledge. If there is something that can not be proven by science, it will not be accepted. You might ask what human science and natural science are making persuasive. Before we begin, in this article I would like to explain the "theory" in these two sciences and the way data collection seems to be more convincing than others. So what is the theory? According to the definition of the dictionary, this theory is "a set of consistent general propositions being tested, usually considered to be correct and can be used as a principle of interpretation and prediction of phenomenon" How to prove the theory Is that? Data, preconditions, experimental testing and observation. But for this reason you need proof of analysis leading to conclusions. What is human science and natural science? In general, human science can be defined as dealing with human behavior in social and cultural conditions such as social science, economics, psychology, data discovery, which mainly focus on emotions and thoughts I will. Physics, biology, chemistry mainly focusing on reason and interpretation Economics is not a natural science, but science is a social science. That theme is human, not electronics and elements: people and their behavioral styles. It is like natural science, but it would be more difficult if not well developed and doing well. The subject of economics is that human facts have an important influence, economics is easier than natural science, it is difficult in other respects than natural science, and in other respects it is clearer is. In addition, economics is essentially quantitative social science. It has evolved into an abstract social science In all social sciences, economics is most similar to natural science. Economic theory is axiomatic, articles and books of economics are full of theorem. In all social sciences, only economists can win the Nobel Prize. Therefore, for those who focus on similarities between natural science and social science, economics is a test case. Those who want to know whether social science is fundamentally different from natural science seem to focus on the following three problems.

Homomorphic encryption allows you to access highly scalable and cheap on-demand computing resources that execute code and store the provided data. This aspect is called data outsourcing computing to reduce consumer burden on IT services. However, because data owners do not want untrusted cloud providers to access outsourced data, the adoption of data outsourcing computing by business is a huge obstacle. With a secure calculation method, the model can train the data without displaying the data itself. Today, three main forms of secure computing, homomorphic encryption (HE), secure multiparty computing (MPC), and zero knowledge proof (ZKP) are used and studied. Since homomorphic encryption tends to be too late, multicast computing is currently the most commonly used for private machine learning, as it is not clear how to apply ZKP to machine learning. The safe calculation method is at the forefront of computer science research. They are usually orders of magnitude slower than traditional calculations, representing the main bottleneck of the system, but in recent years they have been improved. The Pae cryptosystem is an example of an additive homomorphic encryption scheme. Encryption method that supports computational addition and addition of encrypted data. Therefore, this is partially homomorphic encryption scheme. In order to get a fully homomorphic scheme, you need to find an encryption that supports ciphertext addition and multiplication. Since other computing tasks can consist only of these two operators, these two operations are complete. Different levels of homomorphic encryption can be used. Partially homomorphic encryption is commonly used (since 1978). RSA is the first public - key cryptography with homomorphic characteristics, but uses several padding bits to implement semantic security. In a typical RSA implementation, multiplication of ciphertext is the same as multiplication of the original message (but not in case of addition). Therefore, unfilled RSA is a partial homomorphic encryption system. CryptDB is an encrypted database that can be computed without decrypting SQL queries against encrypted data. In 2009, cryptographers built a completely homomorphic encryption scheme. This is an aesthetically pleasing theoretical solution that can calculate any function of encrypted data. However, FHE is very slow in the past and now, and now it is estimated to be six orders of magnitude slower than traditional computing. CryptDB's idea (2011) focuses on one type of function, not all common functions. You can see that there are five basic primitives (get / put, +, =,>, equijoin) that implement most SQL and can support many applications. By specializing in these encryptions you can design practical systems and characterize use cases where it provides strong security. It also shows how to implement such a system without changing it based on an existing database.

Empirical observation is the subject of science. However, the combination of facts and numbers is an assumption that studying ink is one thing. It is another matter to develop a scientific theory harmoniously explaining how all the evidence is combined. After all, science has to prove this theory, even an incorrect theory provides a scientific model for comparing new discoveries. A computer can understand only one, zero is - no. However, human thinking can also correspond to "may". Science (experience observation, data collection, analysis, modeling, prediction, communication, design, presentation, etc.) is important, but there is no clear correlation between observation of weather phenomena and background of the background. This is disappointing. Maybe that is now a timely negligence. There is climate change. I want to change The central concept of scientific and scientific methods is that all evidence must be based on observable evidence by sensory or sensory extension empirically or empirically. It is distinguished from philosophical usage of empirical philosophy by using adjective "experience" or adverb "experience". Experience refers to the use of working assumptions used in combination with natural science and social science and can be tested or experimentally tested. In this sense, the scientific statement is the subject of our experience and observation and is derived from them. The core concept of scientific and scientific methods is that it must be based on empirical evidence based on experience. Both natural science and social science use practical premises that can be observed and tested experimentally. The term "semi-empirical" is used to describe theoretical methods that use basic axioms, established scientific laws, and previous experimental results to participate in rational model building and theoretical exploration It may be done. As long as it does not arise from perceptual based experiences, no philosophical experienceist can correctly infer or infer. This view is often in contrast with rationalism, which believes that knowledge can come from reason regardless of reason. For example, John Rock believes that some knowledge (such as knowledge of God's existence) can be gained through intuition and reasoning. Likewise, Robert Boyle, an excellent supporter of the experimental method, believes that we have natural ideas.

The next article is aimed at discussing whether science is objective or subjective, based on two competing theories. Induction theory and tampering theory. In explaining the main quotes, I will explain how Popper responds to Chalmers' two core ideas and then present their own opinions and reasons. The explanation of science by Chalmers comes from the point of view of inductiveists. He believes that science is achieved by proving a universal statement in a single statement. (Chalmers, 1976) Therefore, these statements are considered to be provable. Any reader who has a small scientific philosophy behind it will be familiar with the arguments of inductionism and counterfeiting. Please note that science is supposed to do a lot of observations and then form generalized problems to fit the observations. In other words, we have not completed all the observations. There is no reason to believe that your assumptions will always be effective. "Black Swan event" is a metaphor that does not exist in "evidence" people generally understand. All the swans seen in northern Europe have been Caucas for centuries. They are all. Therefore, "Black Swan" is used as an impossible term. Then Willem de Vlamingh will travel to Australia, where they are rich in life. In general, we can say that counterfeiting is better than induction, since verifying the facts helps to advance theory to the previous theory. Counterfeiters think science has no inductive meaning, but in fact, inductionism is not a quick way to promote progress by seeking the truth. Karl Poppers' solution for induction problems is to provide an alternative induction forge theory to the scientific community. Popper does not believe that science starts with observations, but scientists try to forge it after making bold guesses. Whenever the theory can endure the test (not counterfeit), the theory becomes stronger. Therefore, the theory is not necessarily correct, never wrong, or not proved to be at least wrong. The theory uses reasoning rather than induction. For example, & Lt, Tab / & GT; Sirkar Popper (1902-1994) of speculation and refutation: Growth of scientific knowledge introduced Falsificationism. The concept of tampering is not only the result of criticism against inductive problems, but the complex version of the above assertion, the observation and observation of statements, is "theoretical burden". Scientific methods include speculation (hypothesis) of design or their systems (Duhem-Quine theory, Pierre MM Duhem (1861-1916) - French physicist Willard van Orman Quine (1908-2001) ) - American Philosophy Home) needs to be based on an extended empirical rationale (massive empirical data), but it is a speculative attempt to analyze every aspect of nature. The general assumption is that the theory precedes experience, otherwise the scientist will not be able to decide which data or facts should be taken into account in empirical science.

Innovative technology changes the way of conducting research, preservation method, and transmission method. In managing scientific information and research data, we will explore how to use these technologies and provide a detailed analysis of the methods and tools developed to manage scientific information and data. After the introduction, the book is divided into 15 chapters, including changes in scientific communication, new models of publication and peer review, ethics of scientific communication, conservation of data, discovery tools, research-specific practices of collecting and using scientific information, and We will discuss ways of scientific communication. Social networking, bibliographic management tools, information literacy and information needs of students and researchers, new opportunities for academic libraries and librarians to participate in e-science, interview of scientific information and expert's announcement Innovative technology changes the way of conducting research, preservation method, and transmission method. In managing scientific information and research data, we will explore how to use these technologies and provide a detailed analysis of the methods and tools developed to manage scientific information and data. After the introduction, the book is divided into 15 chapters, including changes in scientific communication, new models of publication and peer review, ethics of scientific communication, conservation of data, discovery tools, research-specific practices of collecting and using scientific information, and We will discuss ways of scientific communication. Social networking, bibliographic management tools, information literacy and information needs of students and researchers, new opportunities for academic libraries and librarians to participate in e-science, interview of scientific information and expert's announcement We provide practical guidance to researchers, students, librarians about scientific information discovery, filtering and management methods. Describe how to use electronic laboratory books to record, save, share, and manage research data A new field of social media and Altmetrics will increase researcher's awareness and demonstrate ways to measure concerns about research We provide practical guidance to researchers, students, librarians about scientific information discovery, filtering and management methods. Describe how to use electronic laboratory books to record, save, share, and manage research data A new field of social media and Altmetrics will increase researcher's awareness and demonstrate ways to measure concerns about research Excellent data management techniques make it possible to discover, share, and reuse data, reducing redundancy. NOAA's National Environment Information Center (NCEI) maintains, manages and maximizes the usefulness of the Federal government's multi-billion dollar investment for high quality environmental data. NCEI provides data lifecycle management and scientific data management services to provide scientific research and is useful for the public, industrial and scientific community Innovative technology changes the way of conducting research, preservation method, and transmission method. In managing scientific information and research data, we will explore how to use these technologies and provide a detailed analysis of the methods and tools developed to manage scientific information and data. After the introduction, the book is divided into 15 chapters, including changes in scientific communication, new models of publication and peer review, ethics of scientific communication, conservation of data, discovery tools, research-specific practices of collecting and using scientific information, and We will discuss ways of scientific communication. Social networking, bibliographic management tools, information literacy and information needs of students and researchers, new opportunities for academic libraries and libra

In the contemporary film industry, movie theaters nationwide earn billions of dollars by selling tickets alone. When using money on buttery popcorn, soft drinks, desserts containing a small amount of decayed teeth, the theater owner should be satisfied with the money enough. Still, there is no possibility that CEO of billionaire will reject more income. In introduction of "Subconsciously persuaded commodity worship science" by Anthony R. Let's talk about the meaning of cargo cult science for those without experience. Cargo cult science is a phrase made by Richard Feynman and shows that scientific practice can not begin with a fundamentally rational first principle. This is the original paper on "The Science of Goods Cult" by Richard Feynman. If I have never read it, it is very fresh. I have read this article while studying physics. I do not know if I need to read physicists, but most physicists know this concept. Feynman wrote: In 1974, Richard Feynman created the term "commodity worship science" as an analogy of the "food worship" of the Pacific Islands after the Second World War. Please bring back the items that the US military brought during the war. . Although the science of product worship seems like real science, it lacks the rigor of making science function. Likewise, "Cargo Worship Journal" has also undergone these initiatives, but for some reason there are people who implement the science of product worship, because of the lack of a process of true peer-reviewed journals. Therefore, there is no real recognition, others have their own ethical organization and parallel infrastructure for indexing services. Open access to London produces publication integrity and ethics (PIE), and many people are boasting the Copernicus index index or are pretending to be indexed by Scopus or Clarivate's Web of Science Bongo playing, Nobel physicist physicist Richard Feynman accused these people to warn him about "so-called" product worship "and to sell" non scientific science ". He pointed out that people who are excellent storytellers tend to cheat people who do not have scientific rigor and statistical experience. But many of us with these skills recognize that these management and innovation experts are at the expense of the so-called 'choice of choice'. For example, suppose there is a theory that sharks are attacked with red shorts. In order to "prove" the theory, I studied the victim's shark attack with red shorts. Whenever something like this happens, I hit myself to tell everyone how delicious I am. However, with this method, the situation that someone is wearing red shorts and the shark has not been attacked is ignored. These data invalidate my theory, but I could not find them because I never looked for them

Can anyone tell me about science technology and the UK at that time? Discuss. Introduction Doctor Who is one of the most successful television series ever. Produced by BBC, it explained Time Travel Humanoid Aliens, Dr. Adventure, and he encountered various eras, places and parts of the universe on his spacecraft TARDIS (Leach, 2009). This series from 1963 to this day is a science fiction novel that focuses on state-of-the-art technology and extraterrestrial civilization. From the viewpoint of social problems and personal behavior, this series is always the core environment of doctoral companies thinking about. On December 12, Dr. Zou Yunfeng of the China Science and Technology Association (CAST) and its team visited Citylink Technology to discuss the application of big data. Dr. Zou Yunfeng is founder and executive director of Nanjing Yuli Information Technology Co., Ltd and serves as a liaison office of CAST. Lin Herui, CEO of Citylink and Waltonchain's project implementation manager, visited Dr. Zou's interview process and introduced the latest results of Citylink Technology in the systematic management of big data, the details of Urban Internet of Things, the latest I informed the details of the development. Smart application for Waltonchain Dr. Roland Vogl is a lawyer, scholar and media entrepreneur specializing in intellectual property law and media law, innovation and legal informatics. Currently he is a director of law, science and technology at Stanford University, and he is a law instructor at Stanford University law school. His work focuses on legal informatics at the Legal Information Center (Code X), where he serves as a co-director and serves as an executive director. Roland is a visiting professor at the University of Vienna in Austria, a member of the Legal News and Editors Advisory Committee, a publication by ALM (American Lawyers Media), and the Legal Science West Coast Advisory Council. It is also a member of AdviseHub, IPNexus, LegalForce, and LiTIQ Strategic Advisory Committee. #LegalTechLive and CodeX ED and Dr. Roford Vogl and Stanford Law, Science and Technology Project It is worth noting that Dr. Robin M. Black of former Defense Science and Technology Laboratory of Porton Down confirmed the use of Novihok in assassination of Salisbury, a member of the OPCW Scientific Advisory Committee. However, Dr. Black's scientific comment also raised questions about Nobichok, pointed out that its nature and structure have not been verified independently. In recent years, many people speculate that as part of the 'Foliant' program to find ways to compromise defense, the fourth generation nervous agent 'Novichoks' (newcomer) was developed in Russia in the 1970s. Information on these compounds is rarely in the public domain, mainly from Russian military chemist Vil Mirzayanov. Independent confirmation on the structure and properties of these compounds has not been announced.

It taught valuable lessons about the importance of patience in trying to solve the problem. Another important item of my work is to limit duplication of personal data on the Internet. This is accomplished by having only one set of data that can access different subsets from client applications with different access levels. Proof of concept proof is a useful experience. In the summer of my college sophomore, I stand out from hundreds of applicants from the Government Institute's Electronics and Radar Development Authority (LRDE). After acquiring the master's degree, you can acquire a master's degree, master's degree, master's degree in science and master's degree from the graduate school after sometimes acquiring a master's degree in occupational degree for several years. Alternatively, there is a less common master degree such as Master of Education (MEd) and Master of Arts (MFA). Some students acquire postgraduate degrees between master's degree and doctor's degree (education experts) (Ed.S) We usually hold a bachelor's degree in science and technology and a master's degree in technical science. Bachelor's degree is a three-year degree, master's degree equals two-year full-time research. In Finland, the master's degree is called diplomi-insinööri and is similar to Germany (Diplom-Ingenieur). Degrees are awarded by the faculty or department of the university (Aalto University, Oulu, Turku, Vaasa, and Abo Akademi University), or another specialized university (Tampere University and Lappeenranta University). Degree is a scientific, theoretical master's degree. Master's thesis is an important part of master's degree degree research. Master's degree is subject to further research by license or doctorate. Through the Bologna process, a tekniikan kandidaatti ("Bachelor of Technology") degree equivalent to a three-year master's course research was introduced. Graduate degree is advanced degree after bachelor's degree. As an example, there is master of art (MA) or master of science (MS). Students usually obtain a master's degree after two years of study. It takes more than 4 years to study for a Ph.D. (eg Ph.D.). You can also contact an expert working in a field of interest. They can discuss with you how they are from college to the present. It takes time to interview them regardless of whether they are your parents, guardians, family members, or professionals with you. Prepare a series of questions

General science is research on biology, chemistry, physics and environmental science. Students from the 7th grade to the 10th grade are introduced in these different fields, acquire general knowledge on science, and develop into a deeper concept in the future. Science is not just a lab coat for obsessions, Einstein equations, mixed chemicals, large space shuttle, or through a microscope, but to solve critical thinking, data analysis, and actual problems Including application of understanding. The book "Gattaca" and Aldous Huxley's "The Brave New World" book is based on improvements in the future and how science has been achieved in the world. The main characters of Gavinka are more intrinsic than Bernard and John (hero of a brave new world), but they are not satisfied with themselves and are not perfect. Their way of resistance to their society is similar. "Brave New World" and "Gattaca" are similar The 1984 novel by the film "Gutaka" and George Orwell share the aspect of the optic nerve. Both Gattaca and 1984 use propaganda to control citizens in revising social information and persuade people to agree with their boss just by providing specific information. Gataka and the citizens of 1984 live in inhumane provinces. In 1984 and with Gattaka, propaganda was used to rule social citizenship. In Gattaca, infant's DNA modification is common. Several of Gattaca's children are born in a way to discriminate these children in the usual way. Please miss the opportunity. Look at the type of science fiction and the success of the general public. These movies explain how cloning can damage society. The movie Gattaca (plowing the human world in the laboratory, the so-called common-born human being is a second-class citizen), the seed (a scientist who experiments with DNA and releases monsters to the world), and the first part of Star Wars (Satan empire releases target) All warrior cloning teams are drawing a picture of a dark, crazy, life-threatening cloning process.

Now we need to use insert sort on each subarray. If they are not sorted, they will be exchanged in the index. 40 34 35 70 45 57 80 90 75 60 Now use a gap value to further simplify it so that you can get a smaller gap value. Therefore, divide the previous gap value by the gap value = 5/2 = 5 = 2. Using this gap value reapplies the subarrays [40, 35, 45, 80, 75] and [34, 70, 57, 90, insertion order to the two subarrays. 35 34 40 57 45 60 75 70 80 90 Repeat the same procedure as above. In order to understand this data structure, I learned that I learned the tool, the core concept. I was longing for the pleasure of sharing the heap. Because they are actually related to the sorting algorithm. However, as they are a bit more complex, there are a few sorting algorithms that are useful before examining how the heap will be an efficient sorting method. Stick around - I will promise not to sort this week. So, we need to save it now. Instead, let's stick to the basics. For example, what is heap? Where are you from. Who uses them? Should we use them? Do not worry, even if any (or all) of these problems suddenly emerged. All answers will be available soon. But first: We have to learn to love the heap! Computer scientists often face the challenge of finding the fastest and most efficient data retrieval or sorting method. For this purpose, they designed different algorithms with different strengths and weaknesses. Algorithm is a recipe of instructions that a computer must execute when displaying data. As a simple example, considering algorithms of unordered number lists, it takes time to complete. To complete the above process, some steps are required. These steps depend on the original state. In the example above, the fictitious computer running the algorithm must repeat the list multiple times until the list is sorted. Let's say you get a perfect ordered list. After a single pass, the algorithm is complete. Computer scientists say this algorithm will use the best case, worst case, average case time. Continuing the example, the best case is a pre-sorted list. Sorting is a method for enabling easy retrieval of data. To date, many sorting techniques have been implemented to run results faster and manage data comfortably. Sorting and searching is the basic operation of computer science. Sorting is sorting data in a specific order. Search is the process of searching for specific records from existing information. In many cases, information retrieval includes search, sort, and merge. This chapter details the search and sorting techniques. Sorting is very important in all computer applications. Sorting is to arrange data elements in a specific order. Many sorting algorithms can be used to sort a particular set of elements.

The online computer science MSc program is provided by many online universities and universities that are addicted to computer education. This online professional degree program is limited to courses and is designed for qualified students all over the world. In this master's degree we will learn about object-oriented hardware circuit design, software design, software test, network analysis, network security, logic algorithm, and mechanical design. In course work, deepen the detailed understanding of analytical thinking, research skills, and IT functions. According to this article, Georgia Institute of Technology is a respected university offering the first online master's degree in Computer Science. More importantly, this program costs about a quarter of the traditional campus degree. Of course, the university has offered various online courses for many years. However, this movement by the Georgia Institute of Technology greatly changed the competitive environment by providing a complete graduate program with just a small amount of usual costs. Our research on the banking industry shows that these problems are very urgent and can be overcome. Most banks are still paying disproportionate time and attention to traditional goods. We do not ignore these products, but it is important to allocate more resources to new products and business processes. Like reduction of investment in online services and physical infrastructure Soon afterwards, I came to acquire masters degree in data science on my own and then realized that I was better suited to me than computer science. I carefully studied the introduction of programming environment. The first article in this series recommended several coding classes for novice data scientists. In this guide we spent over 15 hours on determining each online presentation of the statistics and stochastic courses offered as of November 2016, extracting important information from the syllabus and review, and editing the assessment. This work focused on the open source community center and the database of thousands of course assessment and reviews. The online computer science MSc program is provided by many online universities and universities that are addicted to computer education. This online professional degree program is limited to courses and is designed for qualified students all over the world. In this master's degree we will learn about object-oriented hardware circuit design, software design, software test, network analysis, network security, logic algorithm, and mechanical design. - In the era of technology, we do almost everything via the internet. You can take classes online, check out bank accounts, shop, and date in the virtual world. If we can do all these things, why not vote online. The idea of ​​online voting has not been accepted as much as people think in this age. Many security risks brought about by computers and technology have made many Americans reluctant to explore this new vision

Taurine (aminoethanesulfonic acid) is an ubiquitous compound found in very high concentrations in the heart and muscle. Taurine is classified as amino acid, but not involved in peptide binding. Shastri acquired a degree in journalism and biomedical sciences and graduated from the University of Marquette in May 2017. After graduation, she spent the summer as an intern at Journal Sentinel. She is sitting next to Johnson in the news' close-up, community weekend talk, news room. Shastri called the newsroom "a playground" where she gained "extensive experience". Scientific reports bring risks. There are lots of healthcare reports in today's media, and the general public receives many plugins about the issues they should focus on. To distinguish between worthy factors and unfavorable factors can pose challenges for the general public. Johnson's series "Occurrence" explains another danger that people consider Biomedical science is a suite of applied sciences applying parts of natural sciences or formal sciences, or both, to knowledge, intervention, or technology in the fields of medicine and public health. The field of biomedical science can be defined as application fields of life sciences and natural sciences for the diagnosis, prevention and treatment of human diseases. Medical microbiology, clinical virology, clinical epidemiology, genetic epidemiology and biomedical engineering are medicine. However, when describing the physiological mechanisms acting in the course of pathology, pathophysiology can be regarded as basic science. Biomedical informatics is an interdisciplinary field including computer and information science, cognitive and decision science, medicine and epidemiology, telecommunications, business administration, educational science, and collaborative research in many other fields. In short, biomedical informatics is an intersection of healthcare, technology and people, with the basic goal of reducing costs and improving the quality and safety of the world's healthcare systems. Medical Informatics aims to manage personal health data, storage, retrieval, sharing, and optimal use with the aim of providing safer, more efficient, more affordable healthcare is. Integrating sophisticated clinical information systems into healthcare decision-making processes, allowing healthcare professionals to perform tasks in a more efficient and effective way.

Because of the era of ubiquitous information that smartphones and technology rely on, our daily life has changed forever. We will leave the data when traveling, shopping, driving, blogging and voting. All of these activities will leave our unique digital signature and we can predict our next move if we do the analysis. Likewise, companies, researchers, and the World Wide Web are also creating massive amounts of data every day. According to government estimates, electronic data of about 2 Zettabytes (250 billion DVD) is generated every year from underground physics experiments and telescopes to retail trading and Twitter postings (Mervis 22). Finding people who know how to use big data is more important than ever as many companies are hoping to use big data analysis. This has proven to be a remarkable task, especially because the gap of data skills is large. Companies have high demand for people with analytical skills, but the actual number of people with these skills is small. This is a problem that will not disappear soon. However, finding a person with a talent for big data may not be enough; in some cases, officers and executives may spend more time looking for different talents. The key to better utilizing Big Data analysis and having more diverse workforce is the exercise capacity of analysis. Demand for "big data" skills is dramatically increasing, and many employees lack the analytical skills necessary to handle such complex data and training. As employees rush through the desire for organization and diversity, we need to increase resources for career development skills. Many people lack the basics for writing good resume and clever interview skills required through career. We will focus on communication skills, critical thinking, collaboration, and creativity. All of these are for improving the long-term productivity of our employees. Indeed.com has revealed that demand for big data skills has increased by 225,000% since 2009. Dr. Data scientists with computer science, statistics, analysis, and current machine learning skills are as rare as unicorns, so gaps with experts as well as filling tasks are unrealistic. Instead, I believe the industry needs to deal with this gap in a variety of ways that can create a variety of skilled experts outside the data scientist that can handle a variety of big data projects. Instead of classifying everything as a "data scientist", a broader classification method is needed to explain the various roles that a successful big data project really needs. You need to take a targeted approach to creating these more specific big data skills and actively use the skills necessary to succeed and reduce the training required for success.

Third, in order to acquire data and analyze the data, a more comprehensive and accurate approach is required. Fourth, behavioral movements are more complicated theoretically than the past. In the past, the theory was essentially philosophical, and behavior theory tried to explain, understand and predict as much as possible how people's political behavior and political system function in an empirical way. Fifth, many behaviorists do not need to include values ​​of researchers and society in the research process. The experimenter of Michael Almereyda belongs to a continuous paradigm shift of scientific behavior, mainly based on two complementary but inconsistent views. What I did What some people think that our current "replication crisis" is a problem, but that actually only emphasizes the dual role of science, expanding our horizons and at the same time Destroy our desire for comprehensive answers. Thought science has its logic, but it is between experimental science and fantasy science. It is scientific but unreliable, or incorrect, a source of miracles, but it can not be regarded as an explanation of the world. However, in recent decades, it is increasingly promoting the imagination of American liberalism. I can not really recommend this book to anyone looking for meaning in outer space. If you find a meaning, I think you are committing a crime "puzzled". ''), I can recommend that insight to any clever reader Descriptive science is a type of science including descriptive research, ie observation, recording, explanation, and classification. Descriptive research is in contrast to hypothetical - driven research, which focuses on validating specific hypotheses through experiments. "Descriptive" in science is a kind of derogatory, in most cases "only" precedes and usually applies to classical research and series. , Various fields of botany, cartography, stratigraphy, and zoology, to name a few. First, organisms, objects, or substances are not described in vacuum, but rather are compared with other organisms, objects, and substances. Second, descriptive science is not necessarily low-tech science, and high-tech science is not necessarily good.

Bryan Enderle grew up in Modesto, California but now he lives in Davis, California with his wife Peggy and his son Isaac. Brian received two bachelor's degrees in chemistry and petroleum engineering, a master's degree in theology, a master's degree and a doctor's degree in chemical engineering. Personally, he likes to study theology and the theme of science as both a personal theme and a cross-cutting theme. Although Edder had not discussed anything, I used modern science to make one wonderful aspect of modern god more rational. By doing so, he created a space where science and religion coexist. In the spirit of ideas worth spreading, TEDx is a local, self-organizing event program that brings people together and shares experiences like TED. In the TEDx event, TEDTalks' video is combined with live presentation to create detailed discussion and connection with a small group of people. These local self-organizing activities are marked as TEDx. Where x is the TED activity for an independent organization. The TED conference provides general guidance for the TEDx program, but individual TEDx events are self-organized. * (* Subject to specific rules and regulations) Rob Enderle is a columnist for ECT News since 2003. His areas of interest include AI, automatic driving, drones, personal technology, emerging technologies, regulations, litigation, M & E, political technology. He has a degree in Commodity Management and Human Resource Management, as well as MBA in Human Resources, Marketing and Computer Science. He is also a registered management accountant. Enderle is currently the President and Principal Analyst of the Enderle Group. He is a senior fellow of the Giga Information Group and Forrester. Email Rob Bryan Enderle was brought up in Modesto, California but now he lives with his wife Peggy and his son Isaac in Davis, California. Brian received two bachelor's degrees in chemistry and petroleum engineering, a master's degree in theology, a master's degree and a doctor's degree in chemical engineering. Personally, he likes to study theology and the theme of science as both a personal theme and a cross-cutting theme. Although Edder had not discussed anything, I used modern science to make one wonderful aspect of modern god more rational. By doing so, he created a space where science and religion coexist. The acquisition of the major data science community Kaggle certainly meets the requirements. In an interview with the E-Commerce Times, Enderle Group's principal analyst Rob Enderle also wants to emphasize the potential of Google's success, while bringing a lot of benefits to the data science community. Through this acquisition, Enderle made it possible for Google to "acquire unique access to information, promote technology development, and efficiently mining information resources over time. It is usually the emergence of pseudoscience, with more and more doubt caused by direct lies and wrong information. Ironically, this adds to the general discomfort and distrust of science. Because the difference between actual science and erroneous science is confusing. Goop and other sites attract the audience who wants a solution that is not available in the appropriate science (and charges the customer for the service). Stem cell clinics promise to treat miracles - Modern snake oil - increasingly exaggerated exaggeration techniques are used in actual scientific organizations to promote their research

• Intellectual and practical activities, including studies of physical and natural structures and behaviors through observation and experimental systems • Systematic organization of knowledge systems on specific topics - criminal science • Systematic knowledge of the physical or physical world obtained through observation and experiments NOS tries to describe the nature of scientific companies and the characteristics of the knowledge they produce. All scientific knowledge will change with new evidence and a new way of thinking. This does not mean that we should not be confident in scientific knowledge, but it may change in the future. Observation includes the use of five senses to gather information, but inference is based on observation and prior knowledge Law is a concise explanation of natural relationships and observation patterns that are usually mathematically expressed. Scientific theory is based on a broad concept that can understand many observations and experiments Scientists strive to be objective and adopt a self-correcting mechanism such as peer review. But intuition, personal beliefs, and social values ​​all play an important role in science. It is the source of scientific innovation and inspiration. Scientists use creativity and imagination through investigation Kindergartens, first and second graders can understand what science is, scientists, how scientists use activities in the classroom, scientists' stories and class discussions I will. Third grade knowledge base and observation skills are improving; raising scientific problems, building reasonable explanations based on evidence; and conveying their own ideas and investigations Bell, R. (2008). At Kurakawa teaching the essence of science through process skills. New Jersey: Pearson Education National Science Teachers Association. (July 2000) essence of science NSTA Search from http://www.nsta.org on July 15, 2012 How will our understanding and awareness of natural science change over time? How is the role of natural science in society evolving? How much has changed the nature of natural science (eg, various forms of natural science)? What is the relationship between natural science today and past science? (In the words of Newton, are they standing on the shoulder of the giant? Industry is a practical relationship between human and nature, natural science, and "theoretical relationship". Industry is the basic form of practice, natural science, and humanities. The industry reveals the true power of mankind Natural science is such "real power" and "possibility of production". Marx established the empirical origin and practical function of natural science and assigned a very important social role to natural science. The power of Marx's analysis transcends all analyzes of the importance of natural science to date, and the deciding factor knows how Marx generalizes genius as objective data of the era about it. Marx did not invent theory, but summarized the history and the experience of modern life. He often refers to "scientific gifts" made to humans by David, Liebig and others. In German ideology, Marx did a materialistic analysis of the dynamics of advancement in natural science. "Pure" natural science is not a factor of self-sufficiency, its history is completely independent of society. Social practices have advantages in natural science, industrial and social conditions. Natural science has actually achieved the goals and means to achieve them. If Marx called natural science as "human true power" in his early work, then in German ideology then natural science is like the true power of the ruling class. Through general division of labor in the class society, natural science cuts into a kind of "spiritual possibility" of function, production which is independent of material production process. As a factor in progress at a certain stage, the deepening of science and industry represents the foundation of the idealistic n

Education.com is a summary of the ideas of numerous science fair projects written by science teachers, professional scientists and educational consultants covering scientific forums from physics, chemistry to biology, even sociology is. We provide free science fair ideas for all grades regardless of kindergarten, kindergarten, elementary school, junior high school, high school. Turn on the checkbox in the sidebar to refine the results or use the search bar to search for a project of the perfect science fair, or do experiments that the child should like. The idea of ​​Education.com's Science Fair project is for reference only. Education.com does not make any warranties or representations concerning science fair ideas and is not responsible for any loss or damage caused directly or indirectly by the use of such information. By accessing the Science Fair Project Ideas you can renounce and abandon the allegations to Education.com. In addition, access to the Education.com website and Science Fair project ideas is governed by Education.com's privacy policy, including restrictions on Education.com's liability, and Web site terms and conditions. Education.com is a summary of the ideas of numerous science fair projects written by science teachers, professional scientists and educational consultants covering scientific forums from physics, chemistry to biology, even sociology is. We provide free science fair ideas for all grades regardless of kindergarten, kindergarten, elementary school, junior high school, high school. Turn on the checkbox in the sidebar to refine the results or use the search bar to search for a project of the perfect science fair, or do experiments that the child should like. We know that finding a topic is the most difficult part of a science fair project, and from time to time you just need some help to focus on topics you are interested in. Science Buddies has developed a theme selection wizard to make it easier to find the concept of interesting scientific fair projects. By answering a series of questions about your day-to-day interests and activities, you will help us determine the best science for you. If your teacher has assigned a specific scientific field (such as "biology" or "earth science") to your science fair, you can also browse our entire project library for each topic . This event is not suitable for use as a science fair project. A good science fairness project will focus more attention on control variables and accurately measure and analyze the data. To find the perfect Science Fair project for yourself, check the creative library for over 1,150 Science Fair projects or use the theme selection wizard to obtain individual project proposals.

I am late, and everyone else here comes up with how computer science can contribute to chemistry. I am going to do something related, but I also point out how chemistry can contribute to some (very carefully selected) CS opportunities. I was in the same position. I recently announced a dual course of chemistry and applied mathematics - Comp.Sci. I like these two subjects. I originally planned to double with pure comp. Sai. However our department of CS is full of terrible lecturers, and the math course is full of wonderful lecturers. Computational chemistry is one of many areas where CS and chemistry have recently overlapped. This is not obvious, but there are many others. Because people who are good at using computer and science do less things than they think. Many laboratories rely on some basic modeling, even laboratories that are not computational. I am currently working on combinations with nanoparticles and PI has recently complained that most of his graduate students can not program something to save their lives. If we can not do that, we can always use some excellent software developers in our field. Although I may be a bit spoiled, some of the so-called "cutting-edge" software suites have to be recompiled partly each time they start up, and in order to crash the communication module voluntarily, some computers It is necessary to restart. It is obvious to me that many things are designed by software developers, not practical scientists - for example, there are millions of button presses required to load data and use it, And the lack of general flexibility of software. Data type Even if you do not want to solve this problem, we are considering ways to share code and model / data issues. Everything is suitable for computers, and research is no exception. Researchers are still trying to elucidate how to easily share, save and publish files (multiple studies are pushed as letters without code). After all, I do not know what you want. Based on the last few paragraphs, this may not be what you want, but you asked about the overlap between the two domains. Here are some examples of interaction possibilities. PS: Although there is an interesting example, Philip Guo's doctoral dissertation focuses on the problem that the same result can be obtained even if the environment is different, even if the same code is executed on different systems. Because of this problem, I now create a tool (I think Python) that can run simulation within the security sandbox (and therefore even) without compromising performance. http://www.pgbovine.net/PhD-memoir.htm Using data as raw material, using code as technology and computer as a tool seems to force overlapping fields. Science, technology, engineering, and mathematics are artists' creative tools. At the same time, the spread of software literacy and the natural coupling between art and computer generation have constrained any opposing arguments. Computational chemistry is one of many areas where CS and chemistry have recently overlapped. This is not obvious, but there are many others. Because people who are good at using computer and science do less things than they think. Many laboratories rely on some basic modeling, even laboratories that are not computational. I am currently working on combinations with nanoparticles, and PI complained recently that most of his graduate students could not program to save their lives. If we can not do that, we can always use some excellent software developers in our field. Although I may be a bit spoiled, some of the so-called "cutting-edge" software suites have to be recompiled partly each time they start up, and in order to crash the communication module voluntarily, some computers It is necessary to restart. Science and humanities are generally considered mutually exclusive. Even if two overlap, it usually affects mathematically inspired pictorial humanities or physics and chemistry applications in sculpture; we talk hardly abou

It is important to clarify the scientific properties that students want to understand. We can first ask ourselves: what is science and how does it work? And: How can we relate our understanding of science and scientist's work to the goal of science essence? Topics under each of the following goals combine views on the nature of science. Each topic extends the explanation, examples, and questions of the teacher's review. Achievement goals are discussed and reflected separately here, but it is slightly arbitrary to recognize that teachers do not mean separately teaching goals. What is the social function of natural science? Does it contain several different forms (eg physics, chemistry, geology, biology etc)? What are their goals? To what extent are the natural sciences influenced by the social and cultural aspects they pursue? How important is natural science? How will our understanding and awareness of natural science change over time? How is the role of natural science in society evolving? How much has changed the nature of natural science (eg, various forms of natural science)? What is the relationship between natural science today and past science? (In the words of Newton, are they standing on the shoulder of the giant? Industry is a practical relationship between human and nature, natural science, and "theoretical relationship". Industry is the basic form of practice, natural science, and humanities. The industry reveals the true power of mankind Natural science is such "real power" and "possibility of production". Marx established the empirical origin and practical function of natural science and assigned a very important social role to natural science. The power of Marx's analysis transcends all analyzes of the importance of natural science to date, and the deciding factor knows how Marx generalizes genius as objective data of the era about it. Marx did not invent theory, but summarized the history and the experience of modern life. He often refers to "scientific gifts" made to humans by David, Liebig and others. In German ideology, Marx did a materialistic analysis of the dynamics of advancement in natural science. "Pure" natural science is not a factor of self-sufficiency, its history is completely independent of society. Social practices have advantages in natural science, industrial and social conditions. Natural science has actually achieved the goals and means to achieve them. If Marx called natural science as "human true power" in his early work, then in German ideology then natural science is like the true power of the ruling class. Through general division of labor in the class society, natural science cuts into a kind of "spiritual possibility" of function, production which is independent of material production process. As a factor in progress at a certain stage, the deepening of science and industry represents the foundation of the idealistic natural science penetration.

For course module introduction, network programming and simulation, modeling and simulation are required as well as input data analysis. Simulation is the implementation of a specific target, test model, or series of models, which is either problem solving, research, or education. Modeling and simulation consists of various fields such as discrete distribution, continuous distribution, modeling and simulation of Monte Carlo, probability distribution. MATLAB® is a software environment for data acquisition (DAQ) and analysis and application development. The MATLAB Data Acquisition Toolbox supports MCC Data Acquisition (DAQ) devices, allowing streaming and analysis of data to be streamed to MATLAB. The collected data can be imported into MATLAB for quick and accurate analysis and operation. MATLAB (Matrix Lab) is a multi-paradigm numerical computing environment and proprietary programming language developed by MathWorks. In MATLAB, interfaces to programs written in other languages ​​such as matrix operations, function and data plots, algorithm implementation, user interface creation, and C, C ++, C #, Java, Fortran, Python Is possible. Cleve Moler, the Department of Computer Science at the University of New Mexico, began developing MATLAB in the late 1970s. He was designed to allow students to access LINPACK and EISPACK without having to learn Fortran. It quickly spread to other universities and found a strong audience in the applied mathematical community. Jack Little is an engineer who visited Steller when he worked at Stanford University in 1983. Recognizing its commercial potential, he joined Moller and Steve Bungart. They rewrote MATLAB in C to continue development and created MathWorks in 1984. Artificial intelligence (AI) - A program that receives input data, stores it, processes it, provides more accurate output data, finds results, predicts and understands human ability. It works faster than the brain, as it is driven by computing power. The more you enter more data in the AI, the more accurate and expanded results are provided to the user. In short, a block chain is a distributed data storage system owned by everyone and everyone. You can get published data from there, and there is a secret key to execute the action from your account. It is managed by each user of the system. Each encryption currency is based on this technology Supervised learning is a kind of learning that uses labeled training data to propose a function corresponding to a desired output. It receives the data set and compares the data with the output it generates. If the system is not trained, it usually produces incorrect answers, but the value "cost" determines the distance of the value. The purpose of supervised learning is to reduce the cost of total training time until the developer is satisfied with the accuracy achieved. One well-known example of learning with teacher is a neural network that recognizes handwritten digits. Network training is as accurate as possible when identifying written numbers and can be used for this purpose once trained

This is a minor bugfix for the 0.23.x series, including some regression fixes, bug fixes, and performance improvements. We recommend that all users upgrade to this version. This is a major version of 0.22.0, including many API changes, new features, enhancements and performance improvements, and a lot of bugfixes. You can install from the development channel using conda (available on osx - 64, linux - 64, win - 64, Python 7, Python 5, Python 6). Python has been suitable for data grooming and preparation for a long time, but it is not so important for data analysis and modeling. Pandas helps fill this gap and allows you to run the entire data analysis workflow in Python without switching to a more specific domain like R. Python's data analysis environment combining the excellent IPython toolkit with other libraries is excellent for performance, productivity, and collaboration. Pandas does not implement significant modeling functions beyond linear regression and panel regression; for this, see statsmodel and scikit-learn. In order to make Python the first-class statistical modeling environment, we still need a lot of work, but we are moving toward this goal. "The giant panda makes it possible to concentrate on research rather than programming.The giant panda was found to be easy to learn, easy to use and easy to maintain.The most important thing is that it improves our productivity That's it. " "Pandas is a great tool to bridge the gap between ad hoc analysis and rapid iteration of production quality code. If you want to use the tool on engineers, mathematicians, and analytic collective teams, There is no need to investigate. " "We use a panda to process time series data on the production server, thanks to the simplicity and elegance of its API and the high performance of a large data set, we are the perfect choice." Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL database and high-speed HDF5 format. Intelligent Data Alignment and Missing Data Integration Processing: Acquires label-based auto alignment in calculations and easily handles messy data into an ordered format. It aggregates or transforms data into a powerful group via the engine so that you can split the combination of applications for the data set. Hierarchical Axis Index provides an intuitive way to process high dimensional data in a low dimensional data structure. Time series - Features: Date range generation and frequency conversion, moving window statistics, moving windows linear regression, date conversion and delay. It is also possible to create domain-specific time offsets and connection time series without losing data. Python with panda is used in various academic and commercial fields such as finance, neuroscience, economics, statistics, advertisement, Web analytics. Pandas is a python data analysis library. This library has all the ways you can use and process your data. Based on the statistical knowledge described in step 2, this will help to split the data into samples. NumPy is a python package that is the basis of the Python Data Science ecosystem. Scipy is another Python library required for various data operations. As part of this field, you also present your project, facts, ideas or reasoning to the business / product team. The data can provide guidance on what to build next, what goes wrong and what goes wrong. However, not everyone understands this by looking at charts and charts. To make decision makers easier and more affordable you need to present the right facts to the correct data. Interview questions have some specific hypothetical questions about specific product features. Pandas is a Python library that provides various tools for data analysis. Data scientists often use data stored in tabular form such as. Csv,. Tsv, or. Xlsx. Pandas handles and analyzes these tabular data very conveniently using query loading

The following information should not be interpreted as an extension of the rule. The official rule of the current "rule manual" takes precedence. Sub-theme of 2019 is physical property, acid and base Recommended C 2019 Event Laboratory Equipment List - (Simply replace "Student Holds" List on Copy of Previous Rules) Official Word Science Olympic Chemistry Laboratory Kit (Laboratory Equipment and Chemicals - School Account for Transporting Controlled Chemicals) Data Acquisition Technology (PDF) - An excellent overview of Texas Instruments' multiple data collection equipment (including sensors and probes), these stations can be included in the game station. Many work and competition in the science Olympics. There are four games that I plan to participate in the competition: forensics, chemistry laboratory, games and electric cars. Many preparations and commitments must be invested. In a small accident of forensic science, only two teams can participate, so we had to quit the team The chemical laboratory mainly concerns basic mechanics and gas laws. game, As one of the best performers of the 2003 National Chemistry Olympic Examination, Allen was one of 20 US students and was qualified to participate in the National Chemistry Olympic National team in the spring of that year. He studies autonomously to assure that we cover all topics not studied in our class and often seeks additional guidance at lunch time and after school. After the practice competition result was announced, Allen was eager to receive one of the 20 participants of the American Chemistry Olympics research and training camp, and he was an organic chemistry, physics chemistry, analytical chemistry, raw Science field encountered at university level exposed to chemistry etc. Science Olympiad is a group competition for high school students (Science Olympics called Group B) and high school students (Group C) students. This guide focuses on the High School Science Olympics, but most of the information applies to Groups B and C. There are over 7,000 scientific Olympic teams in the whole country now. The school team has up to 15 members to participate in regional, state and national competitions. Teams can have alternative members, but will not compete except in special circumstances (details of alternate members will be discussed in the next section).

"Ontology (Information Science)" - Artificial Intelligence, Semantic Web, Machine Learning, System Engineering, Software Engineering, Biomedical Informatics, Library Studies, Corporate Bookmarks, Information Architecture have created ontologies and limited complexity. The idea of ​​becoming a digital nomad who organizes information has caused interest, inspiration, data analysis and the beginning of a social media company. SocialPlan is an application for targeted viewers and interdisciplinary marketing programs, as well as cooperative popups using mobile clouds, along with professional e-mail marketing and automation software. Informatics is a field of information engineering. Including information processing and information system engineering practice, it is an applied form of information science as an academic field. In this field we are considering interactions between people and information, and building interfaces, organizations, technologies, and systems. Therefore, the field of information science has a wide range covering many sub experts, including computer science, information systems, information technology and statistics. Since the advent of computers, individuals and organizations are increasingly processing information digitally. This led to the study of informatics including computational, mathematical, biological, cognitive and social aspects, including research on the social impact of information technology. The difference between informatics and information technology is that informatics includes information science, information systems engineering, and information processing practices. In addition, informatics will also investigate the behavior, structure, and interaction of fairly artificial and natural systems responsible for various responsibilities such as manufacturing, storage, processing and information exchange. Informatics also develops and develops their own conceptual basis as well as theoretical or theoretical basis. Information technology, on the other hand, is the development, research, design, implementation, support and management of computer-based information systems, especially software applications and computer technologies.

Purpose statement I experienced creators' excitement when I was working on his creative work for the first time. The digital data from the three sensors of the Charm robot provides the robot with sufficient peripheral information to automatically track the wall without manual intervention. Since then, my interest in building intelligent systems is rising through my education, projects and practical experience. I grew up in Accra, capital of Ghana. After I graduated from high school, I studied at the Kumasi University of Science and Technology (KNUST) and got a BS in computer science. Upon completion, I would like to continue my master's degree, but KNUST has not yet begun offering a master's degree in Computer Science. As a campus teaching assistant, I began looking for schools overseas. Meanwhile, I touched some of the exchange students at the University of Pennsylvania who took part in the KNUST Campus International Development Summer Academy program. They are very enthusiastic, we talk about Pennsylvania University living and American education. At about the same time, the Director of Science was in touch with the University of Pennsylvania and I will contact you. He added that the Philadelphia Region and the school have a vibrant Ghana / African community. Five years have passed since I got a master's degree in Computer Science as a software engineer and I decided to acquire my PhD in Health Information Informatics. I entered a prestigious school and worked as a research assistant for a professor of computer science. The professor also served as my consultant. I like my new jobs and courses and I work hard, but I am beginning to worry that my consultants and bosses will be attracted to me. He laughed and dismissed my concern and pointed out that the consultant is 20 years older than me, married and too kind to confuse with the students. A few weeks later, my consultant took me for lunch, brought me a small gift and acknowledged that he had dreamed of running away with me. I would like to know how to put money into school even if I do not have this job.

In the third summer, Mathematics and Science Education (MSED) held the Institute for Research Promotion Science Education (IAIBST). Hosted by Intel China, Beijing, and Norma University, this event is a two-week work focusing on scientific topics and their interaction with engineering, science education, scientific exploration and the essence of science It is a shop. More" The pattern of scientific learning is changing. As information becomes easier, the learning environment is becoming more and more with the help of technology, and individuals have more education inside and outside the classroom. For example, manufacturers' movements help a wider range of individuals more easily acquire scientific and engineering behavior. More" A list of the nationwide annual teacher shortages summarized by the US Department of Education will fill the status of many areas in areas such as mathematics, traditional science, foreign languages, special education, reading and English art and history It is demonstrating that you are striving for it. , Art, music, basic education, junior high school education, vocational education, health and computer science. This is not a complete list. Teacher shortage is novelty - Since most data began more than 25 years ago, most states have reported some problems - but in recent years this problem has been a problem with low salaries, unreasonable assessment methods, attacks and morale It became more serious because of its low. About proper process rights, high risk test requirements, insufficient resources, other issues It is not a wonderful math education. This is not a novel observation. The problem of failure in mathematics education is well documented and well understood. If mathematics education continues to fail (as a student of recent computer science, I will confidently keep failing), this failure is not a function of inertia of bureaucracy, so It seems to be. There is no good idea. Just because the problem is well understood does not mean that it can be solved easily. And, beside that, the last sentence is a perfect example of why mathematics is wonderful. The idea that it is difficult to solve well understood problems is what we use to make sense in our own language. It intuitively explains the real world experience at first glance. If you study mathematics long enough, you will find a well understood question, and all tools normally used by us to find a solution will crash. Mathematics is like supporting our intuition These numbers are irritated when evaluating mathematics and science education for American students. Of the 71 countries that evaluated mathematics education, the United States is 38th. In science education, the United States is only 24th in the world. You should review your data yourself. That's terrible. Some of them are particularly relevant to education and our system is outdated and obsolete, but this is also dialogue on poverty. Poverty in children in the United States is horrible. According to UNICEF's assessment, the United States is ranked 36th among children in the richest 41 countries in the world, ranked 36th in poverty measurement for children, and surprisingly, 32% of American children are below the poverty line I am living in. This is one of the nearly one-third of the poor children in our country. This is basically outrageous, especially given that many people prefer to brag about the wealth of this country.

Today, massive data analysis in chemical and biological life science is done automatically by computer. Through this module, you will understand how it is still important to understand how and under what circumstances the use of separate mathematical and statistical techniques and the importance of the results obtained. The main results of scientific experiments usually include data, the number of which varies greatly depending on the type of work being performed. Analysis of acquired data needs to be processed in a way to extract meaning This unit is published in the Chemical and Biological Life Science Code, deepens the prior knowledge and understanding obtained from the study of scientific data and extends it to the level of industry and research. Beginning with the basic procedures of standard information and data expected from the scientific community, much of the content of units focuses on the use of mathematical and statistical methods in the appropriate environment. The processing of these techniques is practical rather than theoretical. It checks how the processing results are used based on the generated values ​​and related errors, and generates valid conclusions. Let's define the terms. "Data" is a unit of information. For my purposes, they are input. Without context, analysis, and applications, the data is stupid. "Smart" is the output processing data. It is an answer to important value and power problems. In this article, we treat data and intelligence as unique assets. In the case of Tesla, the company's market share is much lower than that of Toyota, Ford, General Motors and other major automakers. To date, Tesla has 3 billion miles of data from vehicles equipped with autopilots operating on various roads and weather conditions around the world. More than 150,000 Tesla cars are in operation, sales and production increase, mileage grows rapidly This unit is published in the Chemical and Biological Life Science Code, deepens the prior knowledge and understanding obtained from the study of scientific data and extends it to the level of industry and research. Beginning with the basic procedures of standard information and data expected from the scientific community, much of the content of units focuses on the use of mathematical and statistical methods in the appropriate environment. The processing of these techniques is practical rather than theoretical. It checks how the processing results are used based on the generated values ​​and related errors, and generates valid conclusions.

Purpose of bivariate data The purpose of this survey was generally to examine if more fat is more caloric food. I did this to find out which foods have calories mainly composed of fat, which foods contain many calories and, if any, only a small amount of fat It was. The results I find may be particularly useful for people who are dieting. Normally, people avoid foods that contain fat, this survey will help show which foods are best for this meal. Another convenient way to display bivariate data is a crosstab (often called a crosstab, which is sometimes officially called a split table). A crosstab is a table that represents the frequency (or percentage) of all combinations of two or more nominal or categorical variables. For example, as shown in Figure 14.3, a sample of 20 students has the following sex and grade observations: Gender is a nominal variable (male / female or M / F), rank is a categorical variable with three ranks (A, B, and C). In a simple crosstabulation of data, you can rank the gender and rank it in a 2 x 3 matrix (that is, raw counts or proportions, the number of students per gender in each grade category). This matrix helps to understand if the levels of A, B, C are equal. Social science research: principle, method and practice Anol Bhattacherjee University of South Florida, abhatt @ usf.edu Focusing on business data and economic data, we introduce statistics and probabilities. Descriptive statistics of univariate and bivariate data, basic probability and sampling distribution, estimates of mean, proportional, and simple regression coefficients are included. Students will be introduced one or more computer packages for statistical analysis. Students are in a widely professional work environment and integration of classroom theory and practice and related experience is done over a specific period of time. Directly supervise employers, teachers, and cooperative education departments during student work Understanding how to generate meaningful bivariate tables and interpret them critically is one of the most important tools in data analysis. The simplicity of a bivariate means to examine the relationship between two variables using a table with "two variables" and two variables. For example, if you want to know if white, black, or Hispanic adults report similar home ownership, you can create a crosstab using the variable DWELOWN - "You / your family" I will own you. Or what? - Discuss this relationship with RACEHISP. By analyzing the variables RACEHISP and WRKWAYUP you can also investigate race / ethnic differences in racial inequality beliefs. Does WRKWAYUP correspond to the question "Do you agree strongly to the following statements, approve, disagree, disagree with, to some extent?" Irish, Italian, Jewish and many other minorities overcame prejudice. I work hard â € 8

Objective description "Desire for knowledge increases with acquisition" - Thomas Carlyle. Without computer science, our modern world will be amazing. From technology to business management, medical science to biological science, social and archaeological research, today's research field requires computer science to evaluate those facts and data. Five years have passed since I got a master's degree in Computer Science as a software engineer and I decided to acquire my PhD in Health Information Informatics. I entered a prestigious school and worked as a research assistant for a professor of computer science. The professor also served as my consultant. I like my new jobs and courses and I work hard, but I am beginning to worry that my consultants and bosses will be attracted to me. He laughed and dismissed my concern and pointed out that the consultant is 20 years older than me, married and too kind to confuse with the students. A few weeks later, my consultant took me for lunch, brought me a small gift and acknowledged that he had dreamed of running away with me. I would like to know how to put money into school even if I do not have this job. I initially considered an Associate Degree in Computer Science, but my consultant did not admire it. She proposed to learn the Master of Science - Computer Science course I will progress with my academic career. I am a bit scared of how much "make-up" I need to do to obtain my master's degree, but her enthusiasm inspired me. In the process of becoming a network engineer, I reviewed the following options. My master's degree is most authoritative in my consideration. It shows academic progress, (in theory) I will graduate some qualifications in this field. If I would like to apply for an "elite" company like Amazon or Google I am a master's degree and I will be more competitive. It was also named by Forbes as one of the top ten best graduate programs in 2017.

Class Note: Data structure and algorithm Summer - C semester 1999 - M WRF phase 2 CSE / E 119, section 7344 Issue number 5 - Wednesday 30th June 1999: 09.30am In the revised day class, First - First search (BFS and DFS) algorithm used to scan graphs. Use class notes and text (Chapter 12) as a guide to answer the following questions. Note: The answer is a blue font. * The problem is to write pseudocode (not Java code) for the BFS algorithm described in the class. Outside each step, the number of external inputs / outputs written, memory I / O, increment, comparison, and other types of operations used. If you are not used to data structures and algorithms and do not have a computer science background, Grokking Algorithms' book is the best book on this subject. To illustrate some of the data structures described in this article, I use some intelligible explanations and funny hand-drawn illustrations (the author is Etsy's lead developer). If you are interested in how to implement the data structure, check Lago (the data structure and algorithm library for JavaScript). It is almost still a WIP, but I will change it to a library that can be used for production, and a reference resource to learn data structures and algorithms. Practice and solve algorithm problems in the selected language. Interview coding interview is a wonderful resource but I prefer to solve problems by inputting and running code and getting feedback right away. There are various online judges such as LeetCode, HackerRank, CodeForces. You can practice questions online and get used to that language. In my experience, the problem of LeetCode is most similar to that presented in the interview. The problem with HackerRank and CodeForces is similar to the problem of competing programming HashMaps is probably the most commonly used data structure for algorithmic problems. If there is a problem, the last approach is to enumerate the possible data structures (not fortunately) and consider whether each can be applied to the problem. This is sometimes useful to me. If you are cutting corners with code, explain it to your interviewer and explain to them what you do outside the interview setup (no time limit). For example, instead of using split, you want to write a regular expression to parse a string. This does not include everything.

In this workshop, key experts and administrators involved in the creation, dissemination, and use of science and technology data and information in the public sector and the private sector gather together and (1) explain their roles, advantages, and costs, I will discuss it. - Identify and analyze the legal, economic and technical pressures of STI in the public domain of STI in the context of research and education, (2) the public domain of research and education. (3) describe, discuss and suggest existing STI protection in the United States, and (4) identify problems that may require further analysis National Research Council. 2003. Role of science and technology data and information in public domain: minutes of symposium. Washington, DC: National Academy of Sciences publication. https://doi.org/10.17226/10785 Callahan et al. (2012) 4 depicts a useful distinction between technical review and scientific review. The technical review checks that the dataset is complete, that the description is complete, and whether the two match. Domain expertise is usually not required and many repositories provide at least some technical review. In the scientific evaluation, we evaluate the data collection method, the overall rationality of the data, and possible reuse value. Because scientific reviews require domain expertise, it is more difficult to organize this level of verification, and there are few repositories to offer. Once the data is published with the data file, it can be reviewed between the technical review repository and the scientifically reviewed data journal. Kratz J and Strasser C. Data announced agreement and controversy [2nd edition, referee: 2 people approved, 1 person approved appointment]. In this workshop, key experts and administrators involved in the creation, dissemination, and use of science and technology data and information in the public sector and the private sector gather together and (1) explain their roles, advantages, and costs, I will discuss it. - Identify and analyze the legal, economic and technical pressures of STI in the public domain of STI in the context of research and education, (2) the public domain of research and education. (3) describe, discuss and suggest existing STI protection in the United States, and (4) identify problems that may require further analysis Steering committee on the role of scientific data and information in the public domain

Evolution can be said to be one of the major topics discussed at advanced science institutions. The evaluation theory originally proposed by Charlies Darwin (1990) states that all organisms develop and develop from the original organisms by gradually changing over time. The relevance of this basic theory has witnessed various fields in the field of biomedical science. Biomedicine consists of seven major areas: hematology, transfusion science, clinical chemistry, histology, virology, cytology, immunology, and medical microbiology. Biomedical research - A wide range of scientific fields aimed at finding ways to prevent and treat diseases that cause diseases and deaths in humans and animals. It includes several fields of physics and life science. Biomedical scientists use biotechnology to study biological processes and diseases; their ultimate goal is to develop successful treatments and treatments. Biomedical research requires careful experimentation, development and evaluation involving many scientists, including biologists, chemists, doctors, pharmacologists, etc. This is a process of evolution Biomedical science is a suite of applied sciences applying parts of natural sciences or formal sciences, or both, to knowledge, intervention, or technology used in medical and public health. The field of biomedical sciences can be defined as application fields of life sciences and natural sciences for the diagnosis, prevention and treatment of human diseases. Medical microbiology, clinical virology, clinical epidemiology, genetic epidemiology and biomedical engineering are medicine. However, when describing the physiological mechanisms acting during pathology, pathophysiology can be regarded as basic science. Biomedical informatics is an interdisciplinary field including computer and information science, cognitive and decision science, medicine and epidemiology, telecommunications, business administration, educational science, and collaborative research in many other fields. In short, biomedical informatics is an intersection of healthcare, technology and people with the basic goal of reducing costs and improving the quality and safety of the world's healthcare systems. Medical Informatics aims to manage personal health data, storage, retrieval, sharing, and optimal use with the aim of providing safer, more efficient, more affordable healthcare is. Integrating sophisticated clinical information systems into healthcare decision-making processes, allowing healthcare professionals to perform tasks in a more efficient and effective way.

Therefore, science progresses through experiments and errors just as people learn from their mistakes. Science continues to change, and we are paying attention to the possibility of existence forever. I do not agree with Chalmers, I agree with Popper's dissent opinion. Science is not always reliable. People can not control and things do not always follow their rules. Human beings have proved some natural phenomena, but there is always abnormality in the scientific community. In other words, currently known scientific knowledge, law, theory may fall over in the future. Chalmers recently solved this problem in a speech entitled "First Person in Science of Consciousness" (Consensus Bulletin, Fall 1999, Chalmers' website), but I find wasting examples of research through this article I tried that. . Exceeding the limit in some way or exceeding different phenomenology: I think that first-person data is a natural thing. The idea about ours is the obvious fact that we have something - having subjective experience - and these subjective experiences are totally different at different times. Our direct understanding of subjective experience comes from the fact that our first person visited them. Subjective experience can be said to be core data to explain in conscious science. In addition, I think that first person data can not be represented only by third person data on brain processes etc. From the time of Popper and Kuhn, the philosophy of science has greatly improved, and I was encouraged to read Calmer about 6 months ago. This is a very good book, clear and well-written, and provides a philosophy of science (including all major players: Popper, Kuhn, Lakatos, Laudan) and between science and non science split A good overview on the problem of I have not reached the chapter of Bayesianism and new experimentalism yet. Most scientific philosophers are concerned about the relationship between forgery and proof-of-principle (or deduction and induction). On the other hand, Bayesianism and experimentalism have shown some response to these concerns. Science Americans continue citing the reading of outright scientists as if they were proof. Stupid creationists such as Nick Bostrom, David Chalmers, Max Telemark etc. Pseudoscientific evidence is listed in the section titled Virtual Mind. For those unfamiliar with these areas, the nonsense of these simulated scientists may sound reasonable. But that is not the case. They are excuses for superstition and it is difficult to find technology. Scientists in the United States had a counter-argument in the "skeptical room" section, but it was weak. The explanation of Lisa Randall is like this. In this troublesome group of sons she was shocked by the perceived inferiority feel of others and she did not conduct rigorous analysis because she did not want to seriously insult them. The point of her probability is correct, this is the lack of a fool of understanding probability; it is not a computational or scientific model or something similar

This is the second piece of the Science Review section. This is to help those who take the ACT exam, they have difficulties in the scientific part of the exam. The ACT Science section is one of the biggest mysteries for students, since it is the most different from SAT, PSAT and other tests. Here we will try to solve this mystery by explaining the type of paragraph of ACT and the type of question unique to each paragraph. Next, check the pH and conductivity when adding 0.2 mL titrant. Even if I do not know what the titrant is, I know that the amount of added titrant is on the x axis because I have not read the paragraph. After adding 0.2 ml of titrant to the x axis, it was found that the conductivity is less than 0.5 kS / cm (unless the measured value of the unit is known). According to the key, according to the dotted line of the key, the color is yellow I think the biggest problem in this article is just ... .... You are a tester. We will provide tests to schools primarily preparing for the test (ie schools targeting blacks and brown children). Three paragraphs must be selected for one of the tests. Is this the paragraph you chose? Even if you leave that essay aggressive, are there still 1 million better choices? Black History During the month, did my 22 black and brown students have to read sympathy to really write a portrait of a man who struggled to maintain slavery? Scientific reasoning test is 35 minutes, 40 tests in 35 minutes. There are seven paragraphs, followed by five to seven questions. These paragraphs are provided in three different forms of data representation, summary of the survey, and conflicting perspectives. This form was very easy to predict (that is, a total of 3 data representing paragraphs, 5 questions in each paragraph, 3 survey summary paragraphs, 6 questions in each paragraph, and 7 in conflicting perspective paragraphs 7 I have one question). As the number of paragraphs decreases, in Figures 7 to 6, more changes will start to occur for each channel type. But so far, there is only one contradictory view. These changes are up-to-date and the only reference that has been referenced so far is in a recently released ACT web site simulated test.

Whether science works rapidly The first thing I came up with before I heard the word science was human cloning. But I recently began thinking about this problem more deeply. So far, I thought that everything about science was unnatural. Scientists oppose God and mankind. After reading the articles of Bishop and Rifkins, my view was completely aimed at science. By comparing and contrasting these great scholars, science makes more sense to me. In 1995, J. Michael Bishop wrote an article accusing scientific progress and explorers of exploration. The science of the boy's club is likely to die. Closed science will disappear. All that you represent about "how to succeed" and "how to become a successful scientist" are the ways to navigate the difficult systems that will eventually become their own. It will die again. Perhaps not in your life, perhaps not so fast, but in the long run it will not end. Those things die because we kill them We need to study science and technology twice now. I saw so many families, I saw their pain, and the science knew they were not fast enough to see the treatment. Finding a cure means investing in science. Science is not the only one. All science mathematics, biology, oceanography, atmospheric science, physics, astronomy, chemistry, materials science, computer science, electrical engineering, even data science. We have to invest in all of these. Today, tomorrow, I am moving forward every day I have learned computer science at university, but this is how to build things. But when I moved to Seattle to do programming, I got tired of seeing the computer screen all day. So I gave up Cornell University to study geology. My idea is that it will give me the opportunity to use my hand, but this is not going on. At the time my boyfriend was a carpenter I worked with him for several weeks. But, after all, I do not want to work with him. I do not want to build such a force - he is an expert, I have to learn from him. So I quietly called lots of cupboards and then made some interviews.

We held a wonderful science fair at Method Schools. It is really interesting that children in elementary and junior high school are working hard on their projects. My opinion is how to help the moon influence my father and investigate and decorate the tide of my board. The challenge of the science fair is to pick a theme. Another difficult thing is to find all research at my committee. The night before, I was worried how I could not complete my Science Fair project, but after work my father and I completed the project. My father and I examined what I had to say to my teacher, I explained my research and answered my teacher's question. It is fun to talk with the children, they teach about their experiments and what they want to prove, and they read their data, it's fun to see what everyone is thinking. Although it may have lost, it is very interesting to work on this project, so I hope that you can run this project again soon. Other Logistics Problems In my experience, the Science Fair Project is a "lonely" project where children work outside the school. The annual science fair is time consuming, uses resources intensively, and often does not provide learning, excitement, entertainment to students (and of course parents). It is good news. The new driving force is the STEM exhibition, which allows students to integrate science, mathematics, and in a truthful and appropriate way. Engineering practical STEM project includes a practical process of the child team to solve practical problems I experienced science very soon, and I am fascinated by every new experiment, and I am fascinated by all this chemistry. I was looking forward to it when my brothers and sisters created a project for their science exhibition. I was too young to participate in the school science fair, I brought it to my family. In order for my brothers and sisters and parents to force foods for different animals, I drew their favorite type. I am just six years old, but my family never forgive me; my "experiment" is still a family joke. Nevertheless, I made progress on my dog ​​food days and left a taste test for DNA gel electrophoresis experiments. DNA extraction from fruits is a simple experiment that can provide a good demonstration to the Children's Science Expo. I operated a DNA extraction booth at Oxford Wow! how is it? Family science fair a few years ago. Unfortunately, I did not take pictures at the time, but I had a wonderful time in the kitchen to start the experiment again this weekend! During the busy Science Fair, you may not have time to wait for a 20 minute extraction solution. To avoid latency you can set up a workstation for each of the following steps and prepare the fruit / extraction buffer and alcohol / purified DNA mixture approximately every 30 minutes.

Please click the thumbnail of the original project, the title of the project information, or download PDF or MP3. The resources of this main source set are intended for use in the classroom. If your use goes beyond a single class, please check the copyright and fair use guide Observation is the main source of active information acquisition. In biology, observation uses senses. Science also includes recording data using scientific instruments for observation. This term may also refer to any data collected during scientific activities. Observations are qualitative, ie quantified if only the presence or presence of an attribute is recorded, or if the value is associated with a phenomenon observed by count or measurement. I would like to begin with the observation of scientific methods. This is a wonderful communication framework. Thus, the premise of the entire framework is to observe theory, preconditions, and records so that others can understand and possibly duplicate based on the protocol definitions used to build the recorded events is. The key to this observation is theory. As we understand phenomena, it is usual improvement as we understand observations as we understand it. In many cases, we will modify the original theory we witnessed based on other data. Let's consider two classic works of Galileo and Einstein. They are the theory and the story of improvement to show that everything we have now is a theory, and these theories must be improved. In the scientific approach she began experimenting after scientists proposed a theory based on the observation of something in nature. As the experiment progresses, it is necessary to obey it. Scientists recorded observations of the experiments and gathered data. One form of data collection in this method is quantitative. In the course of the experiment, this form of observation uses a mathematical model and relies on scientists to gather information based on numbers such as the number of apple falling from trees and balconies. Quantitative observation is common in physics, biology, and natural science.

Computer Science Computer Science dates back to around 1960, but the electronic digital computer studied was invented 20 years ago. With the development of computers, the science field has been widely developed. Computers have gone into every part of our daily lives. They are used in education, retail, law enforcement agencies, transportation agencies, agriculture, home, medicine, and many other fields. Scientists need to develop new programs and patches for these computers. To celebrate the 2017 Computer Science Education Week (CSEdWeek), the Computer Science Teachers Association (CSTA) and Code.org announced the first computer science champion. From the development of wristbands and applications to parents' assistance for monitoring infants, as the center for expanding computer science to rural areas throughout the country, these winners are cutting-edge students in the computer science movement nationwide , Teachers, schools, regions and organizations. Today's announcement means a new beginning for us who have spent years spreading computer science - a new opportunity for all schools to expand their computer science products. This work has just begun until all states and school districts in the United States have tried to teach high quality computer science to complete the work. Implementing computer science in your area seems to be a tough task, especially when there are too few teachers in computer science. However, most teachers who have collaborated to support implementation of computer science courses are not ready to teach CS. They are teachers of mathematics, science, English and history who have passion for the opportunities computer science brings to students. All students should have the opportunity to learn computer science, regardless of the background or the place of residence. You can give them a chance In my eighth standard, I chose computer science as an elective subject. At that time, there were only three students in computer science. I was one of them. I remember many teachers suggested that I take other subjects instead of computer science. But thank you for saying that my parents choose what you like. I love my parents because they never force me. When I was 9, 10, 11 hours, I went to the Internet cafe. So I learned Java, Android, and Web development (CSS, JavaScript, PHP, SQL, Bootstrap etc) all by saving money. I have encountered many obstacles in this learning process. Sometimes I have to wait to line up Sometimes the internet is slow. Mobile data is also slow. I spend three to four hours a day at a cafe.

Alternatives are widely used throughout the world and controversial every day. In the eyes of some doctors, alternative drugs are considered "junk science". They are not only considering drugs as "junk science" but they are also worried that they can be extremely dangerous. According to junkscience.com, "junk science" is "wrong scientific data and analysis used to advance special interests and hidden tasks". In other words, "junk science" practices or studies something without scientific evidence or scientific evidence. Pseudoscience is also called "junk science". However, the term "junk science" is associated with anti-environmental nonsense, as its company's mouthpiece Steve Milloy uses this term. Milloy operates a blog called "Junk Science". There, it disrupts and denies global warming, the risk associated with the use of DDT, and other environmental problems. Michael Fumento of another Shilling also used this sentence. Generally, when experts are conducting interviews and writing columns on environmental issues and health issues, the term "junk science" means "a very inconvenient science for my sponsors" and "science" It is just being solved this problem. " Health science encompasses a variety of fields, all of which includes application of science to health. Traditional medicine, Western medicine and alternative medicine can all be regarded as health science. Because human beings need to deal with diseases at all times, it can be said that health science existed in the era of human beings. This area includes research on medicine, nutrition and other health related issues, as well as possible influences on human beings and animals. Knowledge on health is mainly obtained through research. These studies may include evaluating the overall effectiveness and safety of new drugs and treatments. The development of antibiotics and major disease vaccines is a few examples of the benefits of preclinical research. This type of research includes the creation of new treatment methods and treatment methods. Health science also includes studies related to diet, nutrition and health

Copyright: © 2016 Kumar RA. This is an open access article distributed under the Creative Commons Attribution License Terms. Data-intensive fields such as review and medical equipment, atmospheric science, genome research Big data is very important, many analysts are looking for hidden information in big data It brings revolutionary change to business and society. So far, a lot of work has been done on these tools. Software, platform, analysis, etc. for big data. Many organizations are focusing on big data analysis For development, education, disaster management, healthcare, natural resource management Society therefore, actual use cases, benefits, benefits, impacts, and Future challenges of big data UN Global Pulse will work with the public on several research projects And private partners demonstrate the benefits of analysis by monitoring initial indicators Before the official statistics were recorded, the unemployment rate rose to track changes in commodity prices. Unprecedented growth of processing power and software technology like e-commerce Hadoop It can be felt that there is an influence in business planning, research, sales, production etc. These are considered new Industrial Revolution scientists have decoded human DNA in a few minutes, found ways to treat cancer, and accurately predicted Use big data, human behavior, optimize marketing activities, prevent illness, and prevent terrorist attacks. Finally Privacy concerns of experts can not be ignored. Many companies use our personal information This article outlines the big data analysis in the medical field. First, I will define and explain various advantages and features of big data analysis in healthcare. Next, I will explain the big data analysis architecture framework in the healthcare field. Third, a method for developing a big data analysis application is described. Fourth, we provide examples of big data analysis in healthcare reported in the literature. Fifth, challenges were confirmed. Finally, I will explain the conclusion and future directions. GNS Healthcare is a large-scale data analytical company that enables health programs, suppliers, pharmaceutical companies, and foundations to make intelligent decisions based on data. GNS provides an analytical solution that specifically predicts the impact of each individual's intervention to improve overall population health and reduce costs. IDx is a leading artificial intelligence diagnostic company devoted to changing health care quality, accessibility, and affordability. The company 's first product, IDx - DR, is an FDA - approved AI - based diagnostic system designed to detect the forefront of diabetic retinopathy. IDx is developing other AI-based diagnostic algorithms for detecting macular degeneration, glaucoma, Alzheimer's disease, cardiovascular disease and stroke risk A little background on digiAnalytica. In July 2015, I decided to pursue passion for algorithms, big data and digital analysis in healthcare through the initial stage of digiAnalytica. I believe that digital analytics solution integrators are needed in the healthcare field due to the experience of big data and analysis at EY - Society Consulting and years of experience in the healthcare industry. As with IT system integrators, the mission of digiAnalytica is to help healthcare providers and payers deal with collective health care issues and improve patient experience. Medical Challenges We focus on improving patient compliance and patient risk management risk prediction.

"I will discuss how faculty and teachers of the faculty of education interact, how to cooperate, provide opportunities to each student, achieve outstanding results in areas of interest, how to invest in teachers The overall success of each student, which is the difference between this course and the other course I participated or observed. " "My time in this project has exceeded my expectations, my professional skills have dramatically improved, compared with the WSU national conference and other graduate students in other social sciences, I I think we can keep keeping ourselves through the mighty preparation we have made so far. " Dr. mathematics and science education are aimed at nurturing scholars who can make an important contribution to the research foundation, special background and mathematics and / or learning environment related to science education. The main areas include student learning across the PK - 16 spectrum, teacher education, professional development, curriculum and skills. Applicants have advanced degrees in education, mathematics, science, technology or other relevant fields. In addition, they must accept 0 level GPA of 0 level and submit to the graduate school an online application including intention letters, three letters of recommendation, sentence samples, and a GRE score of less than seven years. All mathematics and science education major are graduate students. One of the graduates of science education has a master's degree in physics. One out of the remaining 10 undergraduates is a senior (4th grade), 5 are junior (3rd grade), 4 are 2nd grade. Six of registered 15 students have teacher qualification certificate. Physical inquiries provide kinematic modules including several laboratory experiments, such as rolling the ball over the tracks or observing the fan belts connected to the two pulleys. However, in these experiments it is not necessary to collect and analyze real-time data as an integral part of the build. What is mathematical modeling? Exploring future teachers uses experiments to link mathematics with sports research In the third summer, Mathematics and Science Education (MSED) held the Institute for Research Promotion Science Education (IAIBST). Hosted by Intel China, Beijing, and Norma University, this event is a two-week work focusing on scientific topics and their interaction with engineering, science education, scientific exploration and the essence of science It is a shop. MORE »Science learning patterns are changing. As information becomes easier, the learning environment is becoming more and more with the help of technology, and individuals have more education inside and outside the classroom. For example, manufacturers' movements help a wider range of individuals more easily acquire scientific and engineering behavior. More"

The Internet's Internet, machine learning and block chain technology, and data technology will shape the future in the corner of our industry. A network that supports block chains provides a link between input (IoT receiver) and processing (machine learning) as a basis for data communication while maintaining source and control. As we look at the growth of each technology being used and employed, we can see how they are catalytic to each other. The Internet (IIoT) for industrial use refers to the expansion and use of Mono's Internet (IoT) in industrial fields and applications. IIoT specializes in Machine-to-Machine (M2M) communication, big data, and machine learning, improving the efficiency and reliability of industry and business operations. IIoT covers industrial applications such as robotics engineering, medical equipment, software-defined manufacturing process. IIoT is beyond the network interconnection of physical devices normally associated with regular consumer devices and things of the object. It is a common part between information technology (IT) and operation technology (OT) that makes it stand out. OT refers to a network of business processes and industrial control systems (ICS), including Human Machine Interface (HMI), Monitoring and Data Acquisition (SCADA) systems, Distributed Control System (DCS), and Programmable Logic Controller (PLC) . Data science began with statistics and evolved to include concepts such as artificial intelligence, machine learning, and the Internet's things. Due to the growth of the Internet, the growth of the Internet (IoT), and the exponential growth, the amount of information is increasing. Amount of data available in the enterprise. When a company opens its doors with the aim of increasing revenue and promoting better decision making, the use of big data will begin to be applied in various fields such as medicine, engineering and social science.

For some people, science is the best form of all knowledge. Whether this view is reasonable is accompanied by misunderstanding of science and knowledge. Science is based on facts and theory and science is considered the highest form of all knowledge for many people because it achieves its results by approved scientific methods. Therefore it seems more realistic and reliable as it is objective. However, others think that this is a misunderstanding of science. Therefore, people should wonder what science and knowledge is needed. Political science papers, political journal articles, political science papers, political science papers, political science papers, etc. There are various kinds of political science papers. When trying to write political science papers you should read this topic carefully, and you must do a thorough study of the topic and include the relevant information necessary for writing the manuscript. Students related to the field of political science are responsible for a series of homework. When writing political science papers they face problems. Because teachers associate many hopes with students and their essays. Hope and expectation will also increase as the level of education rises. Students do not have expertise or skills regarding scholarly writing. They make mistakes and mistakes, and they do not score much in political science papers. Normally you can not control the time allocated for posting student papers. Writing scientifically fair research papers seems to be a difficult task, but it's not difficult. Science fair research papers are written in a format you might use to write scientific project reports. If the project contains people, animals, regulated substances or hazardous substances, you can attach an appendix containing special activities that you need to perform for the project. There are other sections in the report, such as bibliographies and abstracts. We analyze information and discussion. Here we need to include all measurements and data in the experiment as well as charts, graphs and figures. Interpret the results and provide a summary of what you found during the observation period. Compare the results with published information found in the survey. If there are too many messages that can be placed on multiple pages, please include them in the appendix. Analysis includes scholars from life science, physics science, engineering and social science. Life science includes biological science, agriculture, food science. Physical science includes mathematics and computer science, chemistry, earth science and physics. Social science includes economics, psychology, sociology and anthropology, and political science. The project includes all engineering disciplines. Special withdrawal rights collected information on PhD in humanities from 1977 to 1995. In the subsequent analysis, we compared three university sections of humanities, science, social science. Successful biological, social and organizational factors of women in academic science and engineering

Reason why the Bible is inconsistent with science "I want to know how God created this world.It is not interested in this phenomenon and its phenomena within this and its elements.I doubt these things Bert Einstein is not alone, he would have asked a detailed question, and obviously the religious answer he received could not satisfy his inquiry thought, but the Bible If it is inspired by the same person who created the universe, it should be able to answer this question satisfactorily. Please answer someone who dislikes discussion. Some people simply refuse to understand that science is science and religion is religion. The Bible is not a textbook of science, science textbooks are not Bibles. One is for the fact and the other is for the faith. There is no conflict. If you think there is a conflict, I have some wetlands in Florida and I want to sell it to you. Several species (especially plants) have more DNA information than humans. For compatibility, the transplant surgeon uses pig heart and kidney. Physiologists and other scientists are studying animals such as giraffes and woodpeckers. Because they give people better ideas on how to treat them. For example, how does the blood spread from the heart of the giraffe to the long neck and into the brain? How can a giraffe bend in order to drink water without fear? For those concerned about the popularity of Christians and Luddites, this is even more worrying. About 17% of Z generations believe that Bible and science are in conflict, but accepting the Bible is a fact. This means that 41% of the members of the Z generation believe that the Bible and science are in conflict. According to the CBN news, these groups submitted a request for information freedom law seeking to find out who is participating in Bible study. In the press release, the Free Religious Foundation (FFRF) and the Washington Responsible Ethics Citizen (CREW) said they complained Carson as not publishing data. Conflict will occur when a religious organization claims absolute authenticity of all statements recorded in the Bible. This means incorporating religious intervention into the field of science; this is where the church fights Galileo and Darwinism. Scientific representatives, on the other hand, are often trying to make basic judgments about values ​​and purposes based on scientific methods, thus opposed to religion. All of these conflicts arise from fatal errors Galileo and the Bible religion and science are always inconsistent works. Religion based on faith depends on supernatural things to explain life and existence. On the other hand, science can not do this. Scientists need to eliminate the possibility of unexplainable to maintain and manage the population used to measure other groups. What I can not explain is a common miracle for all supernatural religions. When the church is in that country, Galileo lives in the era. - Galileo church vs Heroes This is an unstable point in history: the intersection of the science and religion at the peak in the heresy; this is the era of church rule and the people, physicists, life and death, themselves You must choose Science

Class Note: Data structure and algorithm Summer - C Semester 1999 - M WRF Phase 2 CSE / E 119, Section 7344 Issue number 6 - Deadline July 9, 1999: 09:30 am I explained about the AVL tree. Binary search tree and breadth - first search and depth - first search (BFS and DFS) algorithms for graph search or tree search. The purpose of this assignment is to train your knowledge, to acquire the skills necessary for exam and project 4, and to use your class notes and text (Chapter 12) as a guide to answer the following questions . If you are not used to data structures and algorithms and do not have a computer science background, Grokking Algorithms' book is the best book on this subject. To illustrate some of the data structures described in this article, I use some intelligible explanations and funny hand-drawn illustrations (the author is Etsy's lead developer). If you are interested in how to implement the data structure, check Lago (the data structure and algorithm library for JavaScript). It is almost still a WIP, but I will change it to a library that can be used for production, and a reference resource to learn data structures and algorithms. Practice and solve algorithm problems in the selected language. Interview coding interview is a wonderful resource but I prefer to solve problems by inputting and running code and getting feedback right away. There are various online judges such as LeetCode, HackerRank, CodeForces. You can practice questions online and get used to that language. In my experience, the problem of LeetCode is most similar to that presented in the interview. The problem with HackerRank and CodeForces is similar to the problem of competing programming HashMaps is probably the most commonly used data structure for algorithmic problems. If there is a problem, the last approach is to enumerate possible data structures (fortunately not much) and consider whether each can be applied to the problem. This is sometimes useful to me. If you are cutting corners with code, explain it to your interviewer and explain to them about what you do outside the interview setup (no time limit). For example, instead of using split, you want to write a regular expression to parse a string. This does not include everything.

The next article is aimed at discussing whether science is objective or subjective, based on two competing theories. Induction theory and tampering theory. In explaining the main quotes, I will explain how Popper responds to Chalmers' two core ideas and then present their own opinions and reasons. The explanation of science by Chalmers comes from the point of view of inductiveists. He believes that science is achieved by proving a universal statement in a single statement. (Chalmers, 1976) Therefore, these statements are considered to be provable. Any reader who has a small scientific philosophy behind it will be familiar with the arguments of inductionism and counterfeiting. Please note that science is supposed to do a lot of observations and then form generalized problems to fit the observations. In other words, we have not completed all the observations. There is no reason to believe that your assumptions will always be effective. "Black Swan event" is a metaphor that does not exist in "evidence" people generally understand. All the swans seen in northern Europe have been Caucas for centuries. They are all. Therefore, "Black Swan" is used as an impossible term. Then Willem de Vlamingh will travel to Australia, where they are rich in life. In general, we can say that counterfeiting is better than induction, since verifying the facts helps to advance theory to the previous theory. Counterfeiters think science has no inductive meaning, but in fact, inductionism is not a quick way to promote progress by seeking the truth. Karl Poppers' solution for induction problems is to provide an alternative induction forge theory to the scientific community. Popper does not believe that science starts with observations, but scientists try to forge it after making bold guesses. Whenever the theory can endure the test (not counterfeit), the theory becomes stronger. Therefore, the theory is not necessarily correct, never wrong, or not proved to be at least wrong. The theory uses reasoning rather than induction. For example, & Lt, Tab / & GT; Sirkar Popper (1902-1994) of speculation and refutation: Growth of scientific knowledge introduced Falsificationism. The concept of tampering is not only the result of criticism against inductive problems, but the complex version of the above assertion, the observation and observation of statements, is "theoretical burden". Scientific methods include speculation (hypothesis) of design or their systems (Duhem-Quine theory, Pierre MM Duhem (1861-1916) - French physicist Willard van Orman Quine (1908-2001) ) - American Philosophy Home) needs to be based on an extended empirical rationale (massive empirical data), but it is a speculative attempt to analyze every aspect of nature. The general assumption is that the theory precedes experience, otherwise the scientist will not be able to decide which data or facts should be taken into account in empirical science.

Fractal: New era for interpreting our world Mathematical fractal art is a new era of art that attracts eyes and heart through patterns, shapes, colors, and abstract images. Artists once again found ways to take advantage of mathematical abstraction and incorporate it into their work. So where was the new art form of fractal design born? The reality is that the fractal itself is relatively young in the world of mathematics. Of course, since the beginning of art, history, and mathematics, self-similar has already existed, which is interesting to human thinking. Fractals are an iterative field of mathematics where relatively simple expressions are usually evaluated as infinite complex patterns and are repeated many times on different scales. Fractal mathematics is commonly used in technical analysis of foreign exchange markets and frequent trading robots. I have not studied anything about deterministic fractal expressions explaining how bit coin prices behave, but I think there is sufficient evidence to suggest that there is a fractal pattern. It is represented in the form of index bit coin bubbles driven by Gartner Hype Cycles. I would like to have enough things to learn some doctoral dissertations in this field. Fractal: New era for interpreting our world Mathematical fractal art is a new era of art that attracts eyes and heart through patterns, shapes, colors, and abstract images. Artists once again found ways to take advantage of mathematical abstraction and incorporate it into their work. So where was the new art form of fractal design born? The reality is that the fractal itself is relatively young in the world of mathematics. - ... He is looking at mathematical equations as a picture in my mind. After taught in France for a while, he went to work at IBM. There was a problem with data transfer via the telephone line, and I decided to plot the noise data. The graph is the same whether the time interval is 1 hour, 1 day, 1 week. Benoit Mandelbrot was one of the first men who tried fractal In the late 1970s, Benoit Mandelbrot introduced fractal geometry and fractal geometry to the general society and the scientific community. He proved that mathematical and physical objects can have a fractional dimension, not an integer dimension that was used to dominate the geometry. Mandelbrot collects various data and information and shows that fractal self-similarity is revealed in our daily life, microcosm and the universe. Since then, fractal geometry and fractal modeling has been applied to all physics (eg astronomy, physics, meteorology, and geology), life science (eg biology, genetics, medicine, and neurobiology), society It has been used in science. It played an important role such as social science. , Sociology, urban planning, economics), technical science (material science, computer science, logistics etc.), and mathematical science

Human experiments are in science that its basic purpose is to develop or contribute to the generalization of knowledge about physiological, psychological or chemical processes involved in human function as an experimental entity It can be called human use. Unacceptable human experiments can be defined as experiments for subjects whose subjects are unwilling or unknown participants and / or who are exposed to physically unnecessary pain or suffering by the experimental subjects. , Mentally or emotionally. Humanities is research and interpretation of human-related experiences, activities, structures, and artifacts. It is a study of human phenomena. Since human scientific experiments involve human behavior, how does it work? Data collected by human scientific research is language data and digital data. Linguistic data means the formation of meaningful data structures to convey information from the subject to researchers and researchers to the scientific community. Meanwhile, the numerical data provides a means to quantify the collected data and provide a statistical interpretation of the collected data. Because it is a common way of communication for this sort, language data is the most effective type of data in human research. Linguistic data is considered qualitative data because it explains a specific event using words. In this article, Twain gives birth to mankind by explaining a series of experiments he did at the London Zoo. Twain thought that he evolved from Darwin's theory of evolution, that is, an earlier ancestor or "lower animal" and turned them over. He explained what powerful people had made helpless and stated many ideas that made him think about the lack of humanity. "People are inferring animals, this is the claim." Human cognitive abilities provide us with a world of experience that is different from the experiences of other animals. As a reflexive creature, humans try to gain some sense of experience for the emergence of human abilities. These efforts are called myths, religion, magic, or philosophy, or modern English usage, science. Scientifically, the concept of technical reference is normative ideal. We want to invent the concept of photons or verb phrases to choose the real things in the world. Of course, the concept of reference is suitable for formal systems where reference relationships are specified, such as the context invented by modern logic, ie between numbers and numbers. However, human words and thoughts do not seem to do this, and failing to recognize this fact will lead to endless confusion.

As part of my second semester research and its impact, I seek several structured case studies to illustrate my knowledge of selected research, including skepticism, effectiveness, and ethics doing. One case study I studied was Goldacre (2009). Research is frequently distorted, presents erroneous information leading to contradiction, and changes the meaning of the research being done. Therefore, "Sharp, Peters and Howard (2002) is trying to improve knowledge system by improving knowledge system through systematic process, discovering nontrivial facts and insights" (Sharp, Peters and Howard, 2002). This is part of my learning travel series, I have continued to participate in various world themes and began to learn to improve my sentences. Despite being the last published article (the final version), this is actually the second topic I went through after visualizing the data. The concept of basic income, also known as basic income security, citizen income, unconditional basic income, universal primary income (UBI) or general demographics, is strange until I return to the documentary on weekends. "Free Lunch Association" is displayed as part of the 2017 festival design I have quiet for a while since I began learning about data science and its basics, and I am still learning how to improve myself everyday. This is a wonderful journey. Data science and artificial intelligence are a new "industrial revolution" which has drastically increased the demand of skilled experts who draw knowledge from data. Therefore, for those who want to enter the worksite, learn with the desire to become experts in data, increase their employment opportunities, or want to learn to experience new things or to stay new It is actually the best. It's time. In this article, we are carefully choosing the best resources to start learning data science, simply to improve and refine data science. Statistics and machine learning skills In a future article, I will discuss some of the obstacles I encountered while studying and how I skipped them. Also, I will explain obstacles that are known soon. Finally, we record how we learned a specific concept. I hope that it will help my future self remember the basics and help other new programmers start their journey.

Scientific practices should always take precautionary measures to prevent their own prejudice. In scientific research, interpretation of empirical data is based on factors of the data itself, so you can not find an absolute and objective truth. Science relies on the changing principle of shaping just like scientists. In other words, there is a possibility that two scientists who are studying the same data may come up with different theories based on trends of unexperienced philosophy, individuals, society. Scientific investigation Scientific investigation is to do research and experiment to answer the question after asking about the nature of something. Scientists discover what they know by conducting scientific investigations. Biological research involves many scientific investigations. Because the students are observing small plants, this picture is related to scientific investigation. In science, before you start experiments and research, you will ask questions to find your answers yourself. Thanks for watching !! 10 topics of biology Their perception of the nature of scientific exploration (and the ability to participate) and scientific knowledge. These tend to focus on the broader and surveyed nature of the work, and students are free to choose the equipment and method and explain their findings. The main expected learning outcomes may be developed more or less to reflect the scientific nature, but expressed through practical ability (ability to do planning, design, and scientific research) It is an implicit knowledge of the scientific exploration process. Sexual, Declarative Knowledge There is evidence that the experience of conducting a practical project can give students insight into scientific practice and motivate them to continue their interest in science and learning (Jakeways, 1986; Woolnough, 1994). In order to cultivate student 's understanding of the logic of scientific exploration as the goal of the course and the essence of scientific knowledge, it is necessary not only to extend the ability of students to conduct open practice surveys but also to act. At least the survey process, the nature of the generated knowledge, student's own investigation, professional scientist's work, or both are required. The fact that contemporary science is "at the forefront" is always difficult to grasp the problems and evidence contained to support or challenge various perspectives, so when considering problems of theoretical development and theoretical change , It seems to be indispensable to include the history of science. . In order to clarify the meaning of the process of these wishes, we will explore the meaning of "understanding the nature of science" deeper and try to clarify what we want students to understand is needed.

Over the past decade, interest in the generalized linear mixture model (GLMM) has increased. One reason for this popularity is that GLMM combines the Generalized Linear Model (GLM) \ citep {Nelder 1972} with the Gaussian variate effect, enhances the flexibility of the model, makes it complicated data structures such as stratification and iterative measurements It is to adapt. Such as longitudinal direction, often result in additional variability and / or dependency. GLMM can also be regarded as a natural extension of the mixed linear model \ citep {Pinheiro: 2000}, allowing for flexible distribution to response variables. In the last semester of the university, I did independent research on data mining. This course covers three extended teaching materials: Hastie, Tibshirani, Witten, James, Bayesian data analysis (Kruschke), and time series analysis and application (Shumway, Stoffer). We conducted a lot of exercises in Bayesian analysis, Markov chain Monte Carlo, hierarchical modeling, director, and unsupervised learning. This experience has confirmed me to deepen the interest in the disciplines of data mining and further focus on it. Recently, I have completed the online course of Stamford Lagunita 's statistical study. This covers all the materials of the book "Introduction to Statistical Learning" that I read in an independent study. Since I mention the content twice, I would like to share 10 statistical methods in this book. I think that any data scientist should learn to handle big data sets more effectively. The first focal region in applying Bayesian reasoning is Bayesian linear modeling. In this article I am trying to introduce the concept of Bayesian linear regression. We will review the frequency linear regression method easily, introduce the Bayesian interpretation, and look at some of the results applied to a simple data set. I left the code of this article, but it is in the GitHub of the Jupyter notebook. Even after struggling for weeks on Bayesian linear model theory and blog posts, I can not say that I completely understand the concept. Therefore, the way of thinking through practice is the most effective technology. I started using Bayesian linear regression as my selected machine learning model for data science project. This article is the first of two articles that documented the project. I'd like to show you an example of a complete data science pipeline, so the first article will focus on problem definition, exploratory data analysis, and benchmark setup. In Part 2, we will focus on completely achieving Bayesian linear regression and interpreting the results. Therefore, if you already have EDA, proceed. Otherwise, or just want to see a good plot, stay here. I will show you how to start with the problem of data science.

Introduction The purpose of this report is to theoretically cover the tools and techniques for data retention, digital evidence review, data collection, storage and inspection, and a list of recommendations. In modern society, computers and other digital devices are widely used. In the late 1970s, the number of crimes involving digital equipment and computers increased sharply. Therefore, computer experts point out the need to permanently improve the tools and operation methods of digital forensics. What is digital forensics? Digital forensics is the process of revealing and interpreting electronic data. The purpose of this process is to conduct structured surveys by collecting, identifying and verifying digital information and preserving evidence in the most important form to rebuild past events. This is usually related to litigation matters and results are used in the courts, but digital forensics can be used for other purposes as well. https://www.americanbar.org/groups/professional_responsibility/publications/professional_lawyer/2016/volume-24-number-1/forensic_examination_digital_devices_civil_litigation_legal_ethical_and_technical_traps/ Digital forensics (sometimes digital forensic science) is a field of forensic science that involves collection and investigation of materials found in digital devices, often associated with computer crime. Although the term "digital forensic" was originally used as a synonym for computer forensics, it was extended to cover all devices that can store digital data and is now used to describe all fields I will. Did this discipline evolve randomly until the killing in the 1990's? Or, how does the brain work? How is the brain associated with the penal code? In today's society, forensic science provides critical information to the court system. This will help to provide accurate data to help prisoners imprison. In forensic psychology, this is where the brain and legal system arise and combine. With today's criminal law, forensic psychology is rising rapidly. The number of suddenly created education and training methods is amazing. Passed

Focusing on existing technology, recently improved accuracy of environmental data The latest developments of models with marine environmental data and uncertainty are being considered in the design and operation of marine structures. Discussed the wind, wave, ocean current, sea level, ice data and model uncertainty and presented recent results to improve their accuracy. This study includes mathematics, probability, experience, and statistical models. Please pay particular attention to unauthorized waves. Due to the increase in offshore wind energy facilities, the tasks related to wind data and models mainly focus on wind prediction, wind profile information and extreme wind events. Ice is also attracting particular attention as projected climate change opens up new opportunities for the Arctic marine industry. Improvements in the accuracy of environmental descriptions for the design and operation of ships and marine structures have been proposed. Introduction In the Department of Environmental Marine Science, we provide environmental ocean science to naturally interested students, but there are three approaches to marine ecology, environmental science, and environmental research. All routes are designed using either interdisciplinary approach of natural science (marine ecology and environmental science pathway) or natural science, social science, and humanities (pathway of environmental research). As the curriculum includes scientific processes, environmental awareness, and human role in the dynamic earth system, so as to apply scientific methods to study important environmental problems while promoting moral judgment and behavior I will train students. About the University of San Diego ................................................... .. ..................... 8 The latest developments of models with marine environmental data and uncertainty are being considered in the design and operation of marine structures. Discussed the wind, wave, ocean current, sea level, ice data and model uncertainty and presented recent results to improve their accuracy. This study includes mathematics, probability, experience, and statistical models. Please pay particular attention to unauthorized waves. Due to the increase in offshore wind energy facilities, the tasks related to wind data and models mainly focus on wind prediction, wind profile information and extreme wind events. Ice is also attracting particular attention as projected climate change opens up new opportunities for the Arctic marine industry. Improvements in the accuracy of environmental descriptions for the design and operation of ships and marine structures have been proposed.

Problem-based learning Problem-based learning is a student-centered learning approach (Evans, 2006). This kind of learning attempts to expose students to situations unfamiliar to their students (Learning-Theories, 2013). Teachers take more counselor 's approach. It is basically aimed at teaching students, helping to keep on track, and suggesting materials that students can help solve problems. Simplifying this approach is to help students learn by experiencing problems and solving problems. Machine learning is a field of computer science including research and construction technology that enables computers to self-learn based on input data to solve specific problems. Based on learning methods, machine learning techniques generally fall into three categories. Supervised learning, unsupervised learning, and semi supervised learning. Supervised learning is a form of learning where training data is marked. The machine "learns" from the marked pattern, constructs the classifier, and uses it to predict the label of the new data. By contrast, unsupervised learning is a type of learning where training data is not marked. In this format, the machine "learns" by analyzing the characteristics of the data and constructing a classifier. Semi supervised learning is a hybrid approach of supervised learning and unsupervised learning. In semi supervised learning, the input training data set contains both tagged and unlabeled data. In the field of machine learning, there are mainly two types of tasks. It is supervised and unsupervised. The main difference between these two types is that supervised learning is done using the underlying facts, that is, we know in advance how the output value of the sample should be. Therefore, the purpose of supervised learning is to learn functions that best approximate the relationship between a given given data sample and the observable inputs and outputs at the expected output. On the other hand, unsupervised learning has no markup output, so its goal is to infer the natural structure that exists in the set of data points. Machine learning (ML) is a field of artificial intelligence aimed at building and researching a system that can be learned from data. Learning under these circumstances means that you can identify complex patterns and make appropriate decisions based on previously viewed data. The main challenge of machine learning is how to provide a summary of knowledge gained from limited past experience to make useful decisions for new events that were not previously seen. In order to solve this problem, the machine learning field has developed a series of algorithms to discover knowledge from specific data and experience based on sound statistical and computational principles. Machine learning is based on concepts and results in various fields such as statistics, artificial intelligence, information theory, philosophy, cognitive science, control theory, biology etc.

One thing that seems to be missing from this article is a solid structure. President Obama also welcomed the country to discuss ways of balancing security and freedom at the recent announcement of the National Security Agency's telephone surveillance program (Hagerott and Sarewitz) 1). The first sentence usually sets the tone of the entire paper, but as the article goes forward, more relaxed tones are needed. The first paragraph is about the President Obama and the National Security Agency scandal in the next few paragraphs, but it talks about untrustworthy movies like Psycho, Thelma and Louise du. Daniel Sarewitz is a co-director of Arizona State University's innovation and society's future school science and society professor and university science, policy and results association association. He is also a collaborator for "Science and Technology Issues" and a columnist for "Nature" magazine. I talked to Daniel Sarewitz, Professor of Science and Society at Arizona State University, about the problems of post-normal science and what the uncertainties of giving advice to policy makers mean. The interview was held between the 28th and 29th September 2016, the 2nd Government Science Advisory Council held in Brussels, Belgium. Sarewitz: Whatever science you do for usual problems, it is always incomplete. It can always change and is very uncertain. It can be seen from many scientific points of view. Therefore, many scientific researches can produce different outcomes, so it can create many truths that can be mobilized for different values. Values ​​and facts can be combined with each other in different ways. But collecting data and knowledge is not enough to make science plans successful, said Daniel Sarewitz, a law analyst at Arizona State University. Last year's New Atlantis article, Mr. Sarewitz criticized the BRAIN Initiative and PMI as part of a "dataset" where big data projects attempt to solve the complex problem of large datasets, and nearly unlimited possibilities Sex was assumed. Test 4 is executed in the system. Therefore, the results obtained from these data sets seem to be meaningful, but Sarewitz said, it does not actually apply to medicine. In a complex system like the brain, "Science seems to make great progress, actually only noise increases." In this article, Daniel explains the central problem of the world suitable for all. I am worried that it is anti-commercial and probably considered to be understandable, but basically it shows mistakes in economics and big company mistakes. Until to a certain extent, you and others are accusing a large scale due to the large business. But this is inconsistent with the basic economic theory mentioned in this article. The major mistake in existing economic systems is that few people understand the first principles of the economist you mentioned and the Austrians who develop these basic principles further than others. If you do not understand the first principle, what will happen later will not go smoothly. Therefore, the "first" mistake is that there is no basic economics education in the population, of course politicians vote and adopt.

Data for all countries are being updated. For the latest data (including the data for 2013), download the "2015 National Child Statistics Statistics Table" [Excel] and select the country. You can also download all the datasheets by topic [PDF] Prevention of young people (15-24 years old), condoms used by young people with multiple partners (%) 2008-2012 *, men Prevention of young people (15-24 years), young people with multiple partners use condoms (%) 2008-2012 *, women Statistics 210 Introduction to social science and mathematics 314 Econometrics probability and statistics. If you have AP statistics or if you need to open another statistical course for another measure, or if you take a high level statistical course, consult the undergraduate research director and replace it with statistics 210 is needed. There is only one course going to level 100. The following departments and planned courses meet this requirement: anthropology, business organization, general engineering 205 engineering analysis, history, mathematics, political science, sociology, statistics and the Kellogg department of business administration. The approval of the undergraduate research director is necessary for other undergraduate courses. In fact, statistics are the first and most important course in starting data science. I also started descriptive and speculative statistics courses in R from DataCamp. Links on various data science related groups on Facebook, data science specialists, influencers to github, links, tracking and connection There are several my favorite courses here. Statistics and Probabilistic Statistics Introductory is the best statistical skill course that teaches the complete basis of statistics using R, so here are all sub-courses. If you do not want to go here and there, adhere to a single source of information, learn from the basics and go ahead and it will save you a lot of time.

Scientific methods are experimental processes used to investigate observations and answer questions. Does this mean that all scientists follow this process? Certain areas of science are easier to test than other areas. For example, scientists who study how stars change with age, or how dinosaur digest food, can not push the star's life faster a million years. If direct experimentation is impossible, scientists will modify scientific methods. Indeed, the version of the scientific method may be about the same as scientists! But even if it changes, see if you can ask questions, carefully gather and examine the evidence, and see if you can combine all available information into a logical answer to find a causal relationship The goal does not change. Although scientific methods are shown as a series of steps, keep in mind that new information and thinking may cause scientists to back up and repeat steps at any time during the process. The process of scientific method including such backup and duplication is called an iterative process. Whether you are doing science fair projects, classroom science activities, independent research, or other practical scientific investigations, the step of understanding the scientific approach focuses on scientific issues and you We will help you answer your questions through observations and data. Through the Science Fair Project, you should maintain a journal containing all important ideas and information. That journal is called a laboratory. For details, refer to the Lab Notebook of Science Buddies Resource Science and Engineering Project. Using integration with Google Classroom, educators can design student quizzes for beginners or quizzes for intermediate users and try to understand students' scientific ways. Tests can be used before or after evaluation, or both. The Google Classroom integration page has an additional quiz and submission form of assignable scientific exhibition project. There is no correct way to enumerate the steps of a scientific method. Regardless of how the steps are recorded, the purpose of the scientific approach is to gather data to validate or invalidate causal relationships. Scientific methods are usually done linearly, but this method can also be done on a regular basis, since once it is terminated it usually causes more problems. Experiments according to scientific methods are characterized by independent variables and dependent variables. An independent variable is a factor that changes between tests or groups, and the dependent variable changes accordingly. In this example, the argument is the registration box to be displayed and the dependent variable is the number of registered members. Scientific methods include a series of procedures that scientists use to conduct experiments. The term "observation" has two meanings in the scientific way. Firstly, there are scientists who observe the world as it leads to hypothetical theory. This is the first step in the scientific approach and can be presented in two ways: nature observation and gradual observation. Secondly, there are two kinds of observations, qualitative and quantitative, when collecting data in experiments using scientific methods. Based on positivistic methodology, early positivists completed the scientific method. As a representative of the enlightenment philosopher, Bacon created a science of methods with three steps. First, repeat the observation based on the experiment. Next, classify observations. Finally, observations are subject to law through inductive reasoning (Porter, 2007, p. 21 - 22). Comte and Durkheim inherit the scientific method, 1) observe, 2) ask questions, 3) make a hypothesis in addition to the summary, 4) verify the hypothesis by the experimental method, 5) analyze the data and 6) Develop a universal law (Cohen et al., 2007). Positism implements the process of scientific method by inserting "hypothesis" and "experiment"

Because remote sensing technology can provide data and information across a wide range of topics, it is a valuable tool for researchers, scientists, and many people all over the world. A very valuable use of remote sensing is forestry use. In the past, scientists collected terrestrial data from relatively small forest areas and assumed that the data accurately reflected the entire forest. Today, research on forest management is a fundamental truth as data collected originally by remote sensing. Over the past few decades, traditional remote sensing technology has played an important role in the Malaysian forestry industry. For forest inventory and forest management, monochrome full color applications have been widely used for stratification and positioning of forests. Due to the lack of specialized equipment and materials, the remote sensing application in Malaysia 's forestry industry has not exceeded the usual use of Aps. Based on the rapid development of experience and technology elsewhere, it is believed that the scope of remote sensing applications in Malaysian forestry can be extended to include other non - traditional systems. In addition to satellite images for small inventory, color, black and white infrared, and false color photographs are several systems, to name a few. Applications of satellite remote sensing systems are limited by differences in spatial resolution Over the last few years, the IORA team covered most Indian biodiversity, built the foundation for ecological investigation, analyzed changes in forest cover through remote sensing and GIS, formulated cutting-edge work plans, intentions We have created decision support. A tool for building public and private partnerships and creating enterprise toolkits that are effectively involved in forestry. We can participate in all aspects of forestry value chain through collaboration with government and non-government departments. The forest is our greatest teacher and we will deeply deteriorate. Only policies or business approaches can save or enhance these powerful creatures. For us it is clear that if we consider forest protection seriously, we need to change the behavior of the whole country. Forestry has been regarded as an independent science for the past several centuries. Due to the rise of ecology and environmental science, applied science has been relocated. According to this view, forestry is the main land use science comparable to agriculture. Under these headings, the basic principle behind natural forest management is natural ecology. Forests and plantations, the main objective is to extract forest products using a combination of ecological and agricultural ecological principles for planning and management

Data quest: Multicourse series containing about 12 hours of content. I need to subscribe. One of two courses / series of educational statistics, focus is on writing an example in Python. Note from Dataquest: "The statistics course is now fully rewritten and will be released at the end of November." This is the second of a series of six, the highest MOOC introduced in the field of data science I will cover it. I introduced programming in the first article. The remainder of this series will introduce the core capabilities of several other data sciences such as data science process, visualization of data, and machine learning. In fact, statistics are the first and most important course in starting data science. I also started descriptive and speculative statistics courses in R from DataCamp. Links, tracking, and connections such as participation in various data science related groups on Facebook, data science experts, influencers to github etc. Here are some of my favorite courses. Statistics and Probabilistic Statistics Introductory is the best statistical skill course that teaches the complete basis of statistics using R, so here are all sub-courses. If you do not want to go here and there, adhere to a single source of information, learn from the basics and go ahead and it will save you a lot of time. M510 | AP | Statistics This course provides students with detailed and rigorous statistical research aimed at improving student statistical fluency and interpretation of statistics and thinking. The course follows the course approved by the University Council Prerequisite Committee. The topics treated as part of the course are distribution analysis, probability and simulation, sampling method and data-based reasoning. The AP statistical exam question is used to complement the course topic. Students taking this course are encouraged to take the AP Statistics exam in May. Grade: 11, first 12 requirements: before poisoning or teacher recommend B or more

Biomedicine and health informatics apply the principles of computer and information science to advances in life science research, health specialized education, public health and patient care. This interdisciplinary and comprehensive field focuses on health information technology (HIT) including computer, cognitive and social sciences. Informatics is the science of how to use data, information, and knowledge to improve human health and provide healthcare services. Health information technology is a part of informatics and is an important aspect of AMIA, but technical and technical considerations are only a part of the association's activities. Health IT has advanced healthcare by providing tools for setting knowledge on sports. Biomedical Informatics (BMI) is an interdisciplinary science field that studies and pursues biomedical data, information and science. Motivation of effective use of knowledge, problem solving, decision making, and efforts to improve human health BMI develops, researches and applies biomedical data, theories, methods and processes for the generation, preservation, retrieval, use and sharing of information and knowledge. BMI is built on computing, communications and information science and technology, and its applications in biomedicine BMI is a tool for inference, modeling, simulation, experimentation and conversion from molecules to groups of various biological systems, processing of various biological systems, bridging basic and clinical research and practice, and health care companies We do research and support. BMI recognizes that humans are end users of biomedical information. Use social and behavioral science to inform the design and evaluation of technical solutions and the evolution of complex economics, ethics, society, education, and organizational systems. As the role of HIT becomes increasingly important, organizations can effectively invest in information technology to increase the likelihood of significant improvements in safety, quality, efficiency, and efficiency . Take care. Biomedical and health information providers understand the possibilities and limitations of the organization's workflow and information technology. Information scientists conduct research, apply research results to improve the process, propose solutions to solve successful technology implementation, clinical and organizational issues What is Health Informatics in Canadian health system? Health informatics transforms health care by evaluating, analyzing, integrating and applying health communication and information systems (Anderson, 2007). Health informatics programs are funded by the federal government and are being implemented at the Canadian state level and each state improves population and personal health outcomes, enhances patient care, strengthens patients and carers We have our own dynamic program to do. Relations that understand to some extent their health. As health literacy. "Health literacy is the degree to which individuals have the ability to access, process and understand basic health information and services necessary to make appropriate health decisions" (US Department of Health and Human Services, 2000). One of the main population affected by a decline in health literacy is the elderly. Several factors that affect health literacy include age, reading skills, and belief in health. Health informatics has existed for a long time, but over the course of ten years, this profession increased as demand increased. Health informatics is one of the largest growing industries in the United States. Health informatics has evolved into disciplines specializing in the field of health. Research fields include procedures, theories and concepts of computer information science. As the medical industry grows, the security and privacy of health data become mainstream. Health informatics (HI) is a science that defines ways to technically collect, transmit, and use health information. Health info

Education and computers are hard to imagine a classroom without a computer right now. Computers are indispensable for education and learning, but is that good or bad thing? In this article I will explain the positive and negative ways of how computers affect education systems. There are many ways that computers can affect education. One way is the ability of students and teachers to write papers using Microsoft's word processor. [1] This allows you to save paper and make corrections without having to rewrite the paper each time problems occur. Spell check and grammar check are done just by clicking the button, spell check is not done, spelling check and grammar proofing will not be done. For us, education on computers (as basic as Microsoft Word, as complex as computer programming), efficiency improvement, and / or cost reduction is considered "technical or innovative" education can do. Education is provided in the form of lunch and study, Hackathon, conference, online / third-party training, book club, case study analysis, and so on. Executive Vice President to discuss topics of interest to a successful CEO / founder and share their experiences with the team by inviting them to exclusively educate the community's potential emerging EVP speaker series We recommend. I'm very happy that I could work with Techweek Toronto this summer. In addition, I was invited to a one week technical education course covering topics such as VC, entrepreneurial spirit, social media, block chains and so on. To celebrate the 2017 Computer Science Education Week (CSEdWeek), the Computer Science Teachers Association (CSTA) and Code.org announced the first computer science champion. From the development of wristbands and applications to parents' assistance for monitoring infants, as the center for expanding computer science to rural areas throughout the country, these winners are cutting-edge students in the computer science movement nationwide , Teachers, schools, regions and organizations. Because of the growing demand for computer science education at K-12, CurricuPi makes it easy to prepare project-based computer science learning for the next generation technology-driven workforce. We will give the educator a power by providing necessary tools and support to effectively provide practical education in classrooms and after school programs. Datashark is a platform on which companies can purchase data from people like you. Let's access your entertainment viewing history, position data, social media graph, etc. You can provide revenue generated by selling this information to a data-driven company for $ 500 a year. All data is verified, and enterprises can search unnecessarily necessary data on blockchain-based machine learning quality assurance network platform.

Introduction Video streaming services are one of the growing businesses in recent years. There are many streaming service providers in the market, and there are many competitive advantages among them. There are providers such as Amazon Prime Instant, Hulu, Vudu, ITunes, etc. Each provider has its own function. Netflix is ​​one of the largest movie rental services in the United States as well as providing users with Internet-based video streaming services. (Netflix 's competitive advantage, 2010). Beginning in 1997, headquartered in Los Gatos, California. When you are watching Netflix, have you thought about the source of the video? It provides video streaming through content distribution network (CDN) called Open Connect. This has been tailored to the specific application. Internet TV can be used by members all over the world. This system is the foundation of all Netflix video experiences and delivers 100% of the video to over 100 million members worldwide over 125 million hours daily. In this article we will introduce some issues in the field of content distribution. In addition, the data science and engineering team work together to optimize the Netflix service. How NetScope delivers Netflix content worldwide (Netflix Technology Blog): Netflix is ​​a deeply innovative solution to perform very innovative tasks, such as dynamically optimizing images to the available bandwidth It is a famous data science company using learning method. In this article, we will explain how enterprises use data science to predict the popularity of content and allow CDN to cache appropriate content in the right place and at the right time. In only three years, OptimiCDN has become one of the major players of European CDN (Content Delivery Network) participants. Absolutely innovative and destructive integrated technical service: Optimi CDN 's Multi - CDN. Multi-CDN optimizes part of infrastructure costs while participants in e-commerce, marketing, digital advertising, media, and other network / application businesses improve network performance, security, and data availability It is a service that can be reduced. NUMA and OptimiCDN recently partnered to provide emerging companies with integrated multi-CDN service to enhance local and global content delivery for global network / application services. To know the details and to apply for our startup plan, please feel free to contact our team: contact@optimicdn.com

There are all kinds of organizational structure whether it is school, church, society, sports or labor, issue of organization, culture and management change. In the world of organization development (OD), specialized methods of strengths and weaknesses to convert negative results to positive results and to develop strategies to promote productivity, effective growth, profitability We propose. "To make organizational transformations successful, leadership is necessary for specific purposes" (Brown, 2012, p. I'm interested in reading Dialogic OD in a way distinctly different from conventional OD. Is Dialogic OD a traditional variant or a next-generation substitute? Does it apply to all typical OD cases, or specific subsets? Should it be equally effective for small and large OD? I would like to find the answer. Conventional OD usually has a diagnostic stage and subsequent intervention. Since I have not read about Dialogic OD in detail, it may be lacking a deep understanding of Dialogic OD's approach. That is, it is difficult to distinguish it from traditional focus groups, interviews, and other tasks that may be valuing organizational problems. Preliminary research is usually based on the principles of scientific methods, which was the first research theory advocated by John Stuart Mill in his book "Scientific Methodology" in the 19th century. Although the application of scientific methods varies from field to field, the general principles of scientific methods allow researchers to learn more about the world and observable phenomena. Using scientific methods, researchers develop research questions or assumptions to gather data about measurable, observable, reproducible events, things, or people. The ultimate goal of conducting a preliminary survey is to learn new things that others can see and to remove our bias in the process. Engineering is to apply the principles of science and mathematics to the real world. Therefore, engineers must have a solid foundation of mathematics and science. People who are interested in engineering career should not be frightened by the prospect of having a number of challenging mathematics and science courses. But becoming an engineer is more than just understanding mathematical concepts and scientific principles. Other steps necessary to obtain the degree of online engineering are as follows. This book, written by Foster Provost and Tom Fawcett, two world-renowned data science experts, explains the foundation of data science. We will gradually lead the reader about the "idea of ​​data analysis" necessary to extract the actual business value from the data collected by the organization. It can be used as a guide to understand many of the data mining techniques used today. It is based on the MBA program, and one of the authors taught at New York University for over a full 10 years of real world business problems.

The judges and the jurors who heard the incident already have familiarity with some of the terms used because they have the type of equipment used for crime. In the early stages of digital recovery, law enforcement agencies seize equipment and bring it home for analysis. They immediately noticed that some data could be lost when the device was turned off. This new process is still in the crime scene and emphasizes the arrest of as many people as possible while the equipment is still working (Office of Justice Programs, 2010). Briefly, a computer or digital forensic evidence analysis is a scientific collection of data retrieved or stored by computer storage devices that may be used by criminals in a court. Since information used in the courts should be collected before submission, recommendations were made to ensure that the information gathered is as expected. Information gathered digitally from a computer or media store What is digital forensics? Digital forensics is the process of revealing and interpreting electronic data. The purpose of this process is to conduct structured surveys by collecting, identifying and verifying digital information and preserving evidence in the most important form to rebuild past events. This is usually related to litigation matters and results are used in the courts, but digital forensics can be used for other purposes as well. https://www.americanbar.org/groups/professional_responsibility/publications/professional_lawyer/2016/volume-24-number-1/forensic_examination_digital_devices_civil_litigation_legal_ethical_and_technical_traps/ Today more and more computers and electronic components require digital forensics, which indicates that digital forensics can be implemented in specialized areas such as law enforcement agencies, computer security, and defense. In the information technology era, the information stored in the device is digital because most organizations use computer storage media compared to the paper used by writers, scholars, scientists, musicians, and public figures . This brings new challenges to people involved in accessing and preserving information, recovering data, and maintaining trust. This article describes the currently available search process, method, various tools used by forensic experts, and the final conclusions. Digital forensics (sometimes digital forensic science) is a field of forensic science that involves collection and investigation of materials found in digital devices, often associated with computer crime. Although the term "digital forensic" was originally used as a synonym for computer forensics, it was extended to cover all devices that can store digital data and is now used to describe all fields I will. Did this discipline evolve randomly until it was killed in the 1990's? Or, how does the brain work? How is the brain associated with the penal code? In today's society, forensic science provides critical information to the court system. This will help to provide accurate data to help prisoners imprison. In forensic psychology, this is where the brain and legal system arise and combine. With today's criminal law, forensic psychology is rising rapidly. The number of suddenly created education and training methods is amazing. Passed

4. Experiment (control; variable related to independent variable [manipulated variable] [response variable], control variable) Only one test variable can be created Collected data (quantitative and qualitative data 1. [Data collection method]; you can have both qualitative and quantitative in the laboratory) Scene 1 (current time). Mr. Du Bois high school biological teacher is using model skeleton, I pointed out in the process of scientific name different from human bones Her 27 students in grade 10 biology, the course is on October 10 in 11 Was held. 00 Mr. Mr. Du Bois lecture, most students see, listen. Some people take notes. Mr. Dubois pointed out various bones in the skeleton model, so others studied illustration of skeletal biology textbooks. Some ZZZ. Scenario 2 (after a year). Mr. Dubois will be at 10:25 at Ben and her biology course at one meeting of 72 students (S). She reviewed the success of his teaching module in the past three weeks in order to master the module. Ben expects human anatomy research in the next three weeks because he is mastering all the preconditions. Electronic DuBoa Provided Human Anatomy Education Laboratory Ben-copy of Computer Disk to the list of Science Learning Modules. She and Ben discuss the order that he should start learning the teaching module First Step: High School Graduation (or GED) (4 Years) - This person, interested in high school etc, academic profession need to be done as soon as possible. Academic research will be useful beyond biology and other science courses. Step 2: Bachelor's degree (4 years) - Bachelor's degree in areas such as anthropology, biology and forensic science are important foundations of profession. A powerful GPA is required to obtain a competitive master's course for admission. It is worth noting that, like in 2018, no school offers a specific undergraduate course in forensic anthropology

Qualitative Survey and Quantitative Survey Quantitative survey data is a formal, objective and systematic process that uses digital data to obtain information from the world. Quantitative research is to quantify relationships between variables such as height and weight. It is obtained through questionnaires, official statistics, and planned interviews, then we can identify trends and correlations from the digital data and understand the attitudes of many people that can be very useful. The most common differences between various research methods are quantitative and qualitative research methods. Quantitative studies include quantifiable data that can be repeatedly objectively measured anywhere, as all parameters that may affect the measurement process are analyzed and specified in the study design. This is the main research method of all natural sciences (Myers, 1997), eg mathematical modeling (also used in computer science), test performance scores, measurements (weighing, counting etc), and contextual freedom Survey responses are included. Quantitative and qualitative studies are two types of EBP studies that nurses implement, evaluate and use to guide intervention and improve patient care (see "Quantitative and Qualitative Studies"). The test can be a specific quantitative or qualitative, or a combination of both. When research projects use both quantitative and qualitative data, it is often referred to as hybrid approach research. Quantitative studies include information expressed in terms of numbers, variables, and percentages. It tries to prove that all problems, dilemmas or assumptions have clear, concrete and objective solutions that can be expressed in digital format. This type of research focuses on specific narrow problems in double-blind trials, and in many cases there are large random groups and variables. For explanation, explanation, or prediction, the collected data can be analyzed with unbiased statistical data. However, qualitative and quantitative survey refers to empirical or data-oriented considerations on the type of data being collected and how to analyze the data. Qualitative research relies mainly on non-digital data such as interviews and observations, but quantitative research using numerical data (score, indicators, etc.) is contrary. Therefore, qualitative research does not apply to statistical procedures such as regression analysis, but it is encoded using techniques such as content analysis. Sometimes, the coded qualitative data is quantified as code frequency, but the data is not statistically analyzed. Many Puritan interpretive researchers reject this coding method and think that it is a waste effort to pursue agreement or objectivity in social phenomena. Social science research: principle, method and practice Anol Bhattacherjee University of South Florida, abhatt @ usf.edu

Statisticians must use mathematical techniques to analyze the data and overcome the problem of data collection. Many economic, political and military decisions rely on statistical organized data. These people designed various investigations and experiments and gathered the data they received. Based on the collected data, we make recommendations on various things, forecasting needs of various products. Team work and excellent communication skills are key to becoming a successful statistician. Because they have to cooperate to discuss the findings. In order for the federal government to buy things, statisticians rely on the US Treasury Department. The annual census gathers information on state and local government. Since most of government spending at all levels involves provision of services by hiring staff, most government expenditures are also tracked through wage records collected by the state government and the Social Security Administration. All this information will arrive in various formats at different time intervals. BEA combines these to calculate GDP estimates every three months. Then multiply these numbers by 4 for age calculation. These estimates are updated and modified as more information becomes available. The quarterly estimated GDP will be announced one month after the quarter. The first estimate will be announced one month later. The final quotation will be announced one month later, it is not final https://www.khanacademy.org/economics-finance-domain/macroeconomics/macro-economic-indicators-and-the-business-cycle/macro-the-circular-flow-and-gdp/a/measuring-the- The most economical size of hair, domestic product CNX The reason why physicists are more successful than statisticians at the Data Science Center / Institute / Department is not entirely clear. As discipline, the statistics have a longer, more complex history. Many universities do not have a department of statistics, statisticians often write in other core fields. They cooperate with other departments, but they can not be called colonization. Methodologically, causality reasoning and other advanced statistical methods should play an important role in data science. Does the difficulty of integrating statistical data relate to the roles often undertaken by undergraduates in the broader organizational environment of the university? Is the limit more intelligent? Statisticians feel uneasy about some techniques and assumptions inherent in data science, but are not physicists like that?

The abstract uncertainty of Bayesian learning is a problem of artificial intelligence. Bayesian learning outlines a mathematically reliable way to handle uncertainty based on Bayes' theorem. The theory establishes a way to calculate the probability of occurrence of future events and gives some posterior probabilities for predicting events based on evidence and evidence of past events. Its application in artificial intelligence has been successful in many research fields and applications, including the development of cognitive models and neural networks. Basis of CrowdSmart method is Bayesian learning. Let's say you have heard of new startups in the field of knowledge. Friends will ask you about the likelihood of your success, or the return on investment. If you know this field, you may get a successful estimate (probability) based on the story. Bayesian learning is a rigorous and rigorous way to correct beliefs and knowledge based on new data. In the case of example, you ask several questions, obtain data and evidence, then update the estimate. This is Bayesian learning: Always evaluate evidence and update beliefs. When data is collected from evaluators, investors, and customers, the system collects and organizes data and creates the latest estimates. The first focal region in applying Bayesian reasoning is Bayesian linear modeling. In this article I am trying to introduce the concept of Bayesian linear regression. We will review the frequency linear regression method easily, introduce the Bayesian interpretation, and look at some of the results applied to a simple data set. I left the code of this article, but it is in the GitHub of the Jupyter notebook. Even after struggling for weeks on Bayesian linear model theory and blog posts, I can not say that I completely understand the concept. Therefore, the way of thinking through practice is the most effective technology. I started using Bayesian linear regression as my selected machine learning model for data science project. This article is the first of two articles that documented the project. I'd like to show you an example of a complete data science pipeline, so the first article will focus on problem definition, exploratory data analysis, and benchmark setup. In Part 2, we will focus on completely achieving Bayesian linear regression and interpreting the results. So, if you already have EDA please go on. Otherwise, or just want to see a good plot, stay here. I will show you how to start with the problem of data science.

East Tennessee State University not only tackled the understanding of important biological concepts but also conducted experimental exercises specifically to promote the use of specific aspects of scientific methods and verification of multiple hypotheses (Johnson et al. 2006). Heritability is the proportion of phenotypic variation in a population that can be attributed to genetic differences among individuals rather than environmental factors. The main steps to introduce this concept are as follows. Phase 1: Convert the question ("weight / height inherited") into a series of hypotheses and predictions (HW stands for heritability of weight). Next, we will explain the difference between the statistical null hypothesis and the scientific null hypothesis. If we use the logic (such as inductive reasoning and deductive reasoning) as a tool, verifiable requirements (predictions) are derived from the following assumptions. Note: We created a similar hypothesis prediction tree for high heritability. Our goal is to create at least one specific forecast from each hypothesis. What do you need to measure? What are the costs and benefits of different experimental methods? If the parents' age is the same as the age of today's students, we will discuss and develop plans to select the basic data for investigation, using the parent's weights In order to send data anonymously to the database we used the online data collection form developed earlier. Data submission is homework, optional. Student regression analysis uses multiple parallel classes and long-term data from multiple databases. To that end, you need instructions and instructions on programmed Excel worksheets and how to process the data. The results we got in a particular category were male body weight h 2 = 86%, female body weight h 2 = 57% (Johnson et al., 2006). We compare these results with our initial assumptions and projections and conclude that P2 is supported (and does not support P 0 or P 1). We performed the same procedure on advanced genetics and reached a similar conclusion. We compare our results with specialized literature (Brown et al. 2003) and discuss differences in method and results. Now, we discuss possible reasons for important differences between men and women. We have developed a new verifiable hypothesis for further research (eg how the peer's pressure affects girls and boys in different ways to control their weight). Jon D. Miller, a political scientist at the University of Michigan, is studying adult citizen science literacy in the United States. In a survey of basic scientific facts, he discovered that less than 30% had scientific literacy (Miller, 2010). Anthony · Carneville, Research Director of Georgetown University Education and Labor Force Center, believes as follows. "It is easier to obtain and respond than the gap between people who have cultural and scientific knowledge and those who do not have math ... You can meet the needs of all citizens "(Steen 2004, 65). One way to achieve this literacy rate may be by emphasizing more quantitative reasoning at the university. Education of all levels affects early childhood education for universities, but our focus is on undergraduate courses. Scientific literacy or scientific literacy involves writing, digital, and digital literacy as it relates to understanding of science, methodology, observation, and theory. Scientific literacy is based on the understanding of scientific methods, units and measurement methods, empirical understanding and understanding of statistics, especially related and qualitative and quantitative observations and comprehensive statistics, as well as basic science of core science I focus on understanding. Chemistry, Biology, Ecology, Geology and Computing Scientific investigations are mainly in the fields of natural science - biology, physics, engineering, mathematics, chemistry etc -. Certain elements of scientific methods such as the need for empiri

Purpose and power of language If you are able to speak fluent language, you may not think much about your ability to dialogue with others and understand and understand your world. But what happens when you lose your voice? Or, suddenly enough for your language ability, reading, writing and speaking ability is not enough to understand TV or newspaper, enough to talk about what you want to eat for waitresses or what the doctor has. lose. What if your words really make others discriminate against you? It is very powerful. I am not talking about low-level programming languages ​​that can provide you the ultimate pointer function. It is a versatile language with all the tools you need to express your mind. If you think that C ++ is only useful for system programming, look at the GitHub project and look at the wide range of fields in which it has been used. Perl is known as "Swiss Army Knife for Programming Language" because of versatility as a general purpose scripting language. This has much in common with Python, it is a dynamic type scripting language. However, I do not think that Python is popular in the field of data science. Given the application in quantitative fields such as bioinformatics, this is somewhat surprising. Perl has several important drawbacks in data science. It is inconspicuous, its syntax is famous and famous. There is no similar motivation to develop a library specialized for data science. Power is key in any field In collaboration with the University of Chicago, CNRI recommends developing a new course of computer science, using Python as a programming language for all levels of programming instructions. Python is a language that is particularly suitable for this purpose. Easy to learn, read and use, but powerful enough to explain the basic aspects of programming languages ​​and software engineering. So young students can learn the basics of programming using Python, but their application fields are not as restricted as the use of Logo. With Python, each student can explore and progress at your own pace. Particularly exciting is that if a talented student is motivated to learn sooner or faster, a powerful programming language and environment can be used immediately.

Scientific murder: Nazi experiment by human beings Nazis is famous for cruel and rare experiments against humans. They played a small role in attempts to try ethnic health in Nazi Germany, but these experiments wiped out thousands of people (Lifton 269). "Nazi medical examination in the 1930s and 1940s was the most famous example of ignorance of recent ethical behavior" (Polit & Hungler 127). Thousands of people die for science. In order to achieve their "goal", Nazi scientists conducted human experiments, and almost all of them ended with the murder of the subjects. How can I find the answer to the "legal scientific goals" of murder? Should these experiments be considered "scientific"? Furthermore, should these experiments be allowed to provide descriptive data to the modern scientific community? Discussion as to whether science should allow reference to Nazi's data is fierce. Those who disagree with Nazi's data point out that researchers not only support but also promote future unethical research by using data from Nazi human experiments. In addition, opponents believe that the design of Nazi's research is poor and coincidental, and that it does not even qualify as "science". They say, "Scientific results depend on a solution that is saturated with sin, in many experiments it is the" control subject "that denies treatment the most suffering it dies. By the establishment of the UK 's murder law in 1951, the body of a murderer executed before it was put to death was allowed to be used for scientific experiments without consent, and the scientists turned from animals to the human body. While most people are satisfied with the horrifying puppet role, Ure seeks to achieve Frankenstein's actual goal of resurrecting the dead. His most famous experiment was about the executioner murderer Matthew Clydesdale sent to his exhibition within an hour from the death penalty. His battery is filled with dilute nitric acid and sulfuric acid, incising the neck, buttocks and heel of the body to expose various nerves, and he is ready to return to life. After the shock, when the chest of a man vibrates in the lateral direction, I feel that "its success is really wonderful."

The medical field is a very interesting career. There are various occupations in this field, from saving lives of fragile newborns to prescribing antibiotics to relatively healthy adults. The two occupations are not exactly the same, but all occupations are equally important. There are several working differences in medicine, but they have at least one thing in common. All occupations in the medical field depend heavily on mathematics. Mathematics, geometry and algebra in elementary school are clearly critical for advances in new technologies, salvation of lives, and treatment of diseases. Most occupations in the medical field include mathematics. Doctors and pharmacists use mathematics to accurately calculate and prescribe the amount of medicine. The medical staff also uses mathematics to analyze medical examination data such as blood counts. Nurses need mathematical skills to calculate the flow rate and dosage of drugs flowing into the IV. Public health educators conduct research to educate public society about health problems such as the relationship between smoking and lung diseases and use statistical data. Cryptographers use mathematics to encode and protect data. Their jobs protect not only government information but also confidential information such as financial data and medical data. If you suspect a crime, you can decrypt the intercepted message and analyze the hidden data. Knowledge mathematical algorithms are essential for coding and designing effective encryption. It takes time to solve a probe with a complicated expression or computer program Biomathematics - Application of mathematics in health science. This is an emerging field that has become a major trend of mathematics in recent years. The Mathematical Biology Society has undergraduate and postgraduate programs. Bio mathematics includes the fields of bioinformatics, cs / mathematics / biological hybrids. The bioinformatics organization has a working list of bioinformatics. There is much information on color base pairs. Computer Science - This is an independent field and there are many research fields that are almost indistinguishable from mathematics. One of the most practical parts is graphics and animation. A good example is Pixar. To prevent animation costumes from intersecting, employees are publishing research papers using differential equations. Another particularly important part is encryption including cyber security; think about e-commerce and mathematical algorithms like RSA and Rijndael

The parameters of the beta blending effect model can be estimated from Bayesian method. Since the posterior distribution can not be used analytically, Bayesian estimation of the β mixture model is not easy. Markov chain Monte Carlo (MCMC) technology is the standard way for these models \ citep {zuniga: 2013}. In fact, this method has a wide range of problems regarding convergence and calculation time. In addition, there may be problems with the implementation itself. In particular, it is problematic for end users who may not be programming experts. In the last semester of the university, I did independent research on data mining. This course covers three extended teaching materials: Hastie, Tibshirani, Witten, James, Bayesian data analysis (Kruschke), and time series analysis and application (Shumway, Stoffer). We conducted a lot of exercises in Bayesian analysis, Markov chain Monte Carlo, hierarchical modeling, director, and unsupervised learning. This experience has confirmed me to deepen the interest in the disciplines of data mining and further focus on it. Recently, I have completed the online course of Stamford Lagunita 's statistical study. This covers all the materials of the book "Introduction to Statistical Learning" that I read in an independent study. Since I mention the content twice, I would like to share 10 statistical methods in this book. I think that any data scientist should learn to handle big data sets more effectively. The first focal region in applying Bayesian reasoning is Bayesian linear modeling. In this article I am trying to introduce the concept of Bayesian linear regression. We will review the frequency linear regression method easily, introduce the Bayesian interpretation, and look at some of the results applied to a simple data set. I left the code of this article, but it is in the GitHub of the Jupyter notebook. Even after struggling for weeks on Bayesian linear model theory and blog posts, I can not say that I completely understand the concept. Therefore, the way of thinking through practice is the most effective technology. I started using Bayesian linear regression as my selected machine learning model for data science project. This article is the first of two articles that documented the project. I'd like to show you an example of a complete data science pipeline, so the first article will focus on problem definition, exploratory data analysis, and benchmark setup. In Part 2, we will focus on completely achieving Bayesian linear regression and interpreting the results. Therefore, if you already have EDA, proceed. Otherwise, or just want to see a good plot, stay here. I will show you how to start with the problem of data science.

The past is gone, but in the boring days when the world is not too boring for us, the best is carved into your heart, certainly brought to the future and used. Like the sand on the sieve, the worst thing falls on our open fingers, then it returns to Earth and it becomes convenient and unforgettable. Even if HBR articles are repeated, they jump into the data. However, they seem to be sifting sand on the beach, knocking out millions, possibly even billions of particles, to find useful data, or it seems that the useful structure is not worth separate values It is easier to say that you are assembling particles. In data science, you can do all of the above. how is it? You can create practical insights by organizing all available data and applying analytical methods (very glossy and cool methods such as machine learning). By having the data science function in-house, you can do smarter and more accurate exploration, especially with account-based marketing, without relying on brokers and marketing automation platforms. Everyone has two ways of thinking: absorbing information (such as a sponge absorbing water) and thinking about information (sifting sand etc.). Those who use the first approach will try to remember the given information in detail, but others will actively interact with the knowledge they have learned. This does not mean that one method is bad; critical thinking combines these two characteristics. It is difficult to nurture critical thinking. Because it is easy to accept friends, family, public opinion position. Your friend may think the vaccine will have a significant impact on your child's health. But if you are going to study available information on this issue, you can change your mind or simply reconfirm your beliefs.

As a passive scientist, I need to ask myself a woman who is not interested in science (in fact, never dissected like a high school frog). Students, and most importantly, I hate them. In other words, in a science class full of students in elementary school fourth grade, mouse bones are made from the pill of graduate students. Well, this is not easy, let me tell you. About two years ago, when my ten year old little girl came home she was passionate about the latest science project in her class. Most scientists do not want to admit that the answer to the question of science persistence is obvious. They are more than they are willing to do. The primary reason is that the answer to the stubborn problem is that people do not want to hear and bad news can lead them to kill messenger science. People are paying for science by supporting the National Institutes of Health, the National Science Foundation, and most of the universities studying. Therefore, scientists have incentives to conceal them. Science is wrong, scientists are taught that it will never be revealed even in their own conclusions; since the persistent problem is so extensive that scientists' research plans are based on these Do not solve the problem directly. Few people are ready to stretch their heads from their profession when they do not need it. For scientists who are silent about science, the real answer to the problem of persistence is not definitive. I saw a future that scientists have a mission to make their interests and the world a better place. Scientists pay attention to environmental, medical, social problems in society. Scientists are reluctant to negotiate with the public and negative. Scientists represent their community and their communities represent science. I can see the future where scientists cross over the border. Scientists of all gender and color, cultural and social background. Science does not care about school district lines, neighbors, border walls, visas, or citizenship documents. Science is focusing on evidence. Evidence is higher and stronger than any boundary. There is no passport in the evidence The career of scientists is closely related to the number of publications of magazines. These same journals may be reluctant to announce negative findings. Researchers are also fighting for limited grants and positions that are almost always wanted. As a result, researchers face the situation of "publication or demise" that gives priority to the reliability of publications. They fail to experiment, that they can not record data, overlook the details of key protocols, use statistical data improperly, and publish so that they can not handle bureaucrats in the laboratory focusing. In many cases, there are differences in reagents, it is difficult to reproduce expertise. Researchers use data and results consistent with experimental goals and ideas. This saves time and money and keeps them steady for regular releases

Statistics is a mathematical science as a field of data collection, analysis, interpretation, interpretation, expression, or mathematics. Some people believe that statistics is a unique mathematical science and not a field of mathematics. Many scientific investigations use data, but the statistics include the use of data in the context of decision-making that faces uncertainty and uncertainty. Ideally, statisticians prepare data on the entire population (called census actions). It can be organized by government statistical agencies. Using descriptive statistics, you can summarize demographic data. The digital descriptor contains the mean and standard deviation of consecutive data types (such as income), but the frequency and percentage are useful for describing category data (such as race). Statistics is a field of mathematics that processes data collection, organization, analysis, interpretation, and display. For example, when applying statistics to scientific, industrial or social problems, research is usually initiated from a statistical population or statistical model process. Population is various subjects such as "everyone lives in the country", "all atoms constitute crystals". Statistically process all aspects of the data, including data collection plans for research and experimental design. See vocabulary of probability and statistics Statistics are a very broad field of mathematics, including everything related to data, from data collection and configuration to analysis, display and interpretation. As the amount of data continues to increase, statistics have become an important tool in all areas where data must be processed or handled. Whenever you process or process a small amount of data, you can discuss the data items from an individual perspective. However, when dealing with large-scale data or large-scale data based on scenarios that are actually problematic, some functions are required to make it easy to express the data in the required format.

Nursing informatics is "science and practice (intention)" combined with care, information and knowledge to promote the health of people, families and communities around the world, and information and communication technology "(IMIA Nursing Informatics Special Interest From Group 2009). . Application of nursing informatics knowledge allows all healthcare professionals to achieve patient-centered care Nurse informatics is a developer of communications and information technology, educators, researchers, chief administrators, chief information officers, software engineers, implementation consultants, policy makers and business owners to promote health care. Main tasks are as follows. Information communication technology that meets cross-pro workflow needs in every medical field Development, design and implementation of communication and information technology vision and management AMIA 's Nursing Informatics Working Group is representative of IMIA special interest groups on nursing informatics. Introduction Nursing informatics is a combination of nursing, technology and data assimilation. Nursing information processing uses technology to organize and provide healthcare in the most effective and safe way. Nursing informatics includes a myriad of tools aimed at organizing and distributing information, from simple computers to complex electronic medical record systems (EMR). - Certified Nursing Assistant Certified Nursing Assistant is a member of the Health Care Team. It is also known as CNA or nursing assistant. They refer to people they care as occupants or patients. In the medical field, CNA is the minimum income, but people who do all the work such as physical labor. They are in contact with the inhabitants more than others, and they are major caregivers. I have been involved in nursing informatics for nearly 30 years and I have seen many developments in this field. In the early 1980s, nursing informatics was defined as "computer technology applied to care in every field - nursing service, nurse education and nursing research" (Scholes & Barber, 1980, p. 73). Since then, we have completed the breakthrough definition provided by Graves and Corcoran (1989). Then, it identifies three important points in information science: "care data, information, and knowledge support nursing practice and nursing (p.227), and we will identify three key points in nursing informatics: basic computer skills, information Academic knowledge, and information literacy (Hart, 2011) Nursing informatics combines nursing science, computer science, and information science to better manage and disseminate information, data, and knowledge in nursing science. Nursing informatics experts promote data integration, information and knowledge to better support patients, nurses and other health care providers. Literature is the main focus of the field of nursing informatics. The reason is that high quality medical care relies entirely on close communication between various health care providers. Nurse informatics analysts want to improve the speed and accuracy of chart processing when health care providers communicate via notes on charts. This means that healthcare workers can access better patient records and better determine treatment.

I am a young woman in my twenties and I think that he is always teasing my "old" husband in the early 30s. However, it is difficult to concentrate on one event that may change the idea of ​​reading and writing, so please tell me how to read and write. When first thinking about how to learn to read before my fall asleep, my grandmother and my mother read a picture of my sleeping story. My passion for books and funny magazines comes from the story of my grandmother, and I get intensified that my mother encourages reading. Recently I gained the privilege to interview two young ladies, and I am very pleased (and learned) to lead the two young women this summer. I asked these women the question I asked frequently in the interview - what you learned will allow you to overcome the challenge and succeed in engineering research. Both women have similar answers - the importance of having your community and supporting you while you are studying. They speak openly about the danger that truly excellent engineers can succeed on their own. If you do not seem to be successful, you are not really smart. Two years ago, Courtenay Cotton hosted a seminar on machine learning, I participated in a women's and surveillance program in New York. This is a general introduction of this theme, a rare opportunity to understand the value of machine learning and the complexity of research in this field through hype. In a recent interview, Cotton, the lead data scientist of n - Join, announced a clear idea of ​​machine learning and its direction. This is a group of women who are interested in machine learning and data science. In order to build a community centered on women in these fields, we discuss socializing machine learning and data science in an informal setting. Although men gather almost every time at 12 meetings, our basic vision is to build a community of women's experts in the field of machine learning and data science in Kenya and elsewhere. It is not a fact that we do not know the gap of skills that we can not fill ourselves, but we continue to strengthen community capacity, working with men like past.

For centuries researchers have used research methods to support the creation of reliable knowledge based on empirical evidence and logical arguments. This chapter will outline established research strategies and methods with emphasis on empirical research in social science. In this chapter, we will explain research strategies such as experiments, surveys, case studies, ethnographic journals, basic theory, behavioral research, phenomenology. It also explains how to collect data, including questionnaires, interviews, focus groups, findings, and documentation. Discuss qualitative and quantitative data analysis methods. Finally, I will study the use of research strategies and methods in design science. The next page is about methodology. This section describes research strategies, research methods, and data collection. Because each study has a different term, research strategy, research method and data collection will be separate. Finally, the conclusions will include which studies will be adjusted, and the reasons for those studies will be decided. Survey is a strategy to apply to information and to compare in the form of questionnaire and status. According to Uma Sekaran (Commercial Research Method), they tend to be used for exploratory and descriptive research. Surveys are usually conducted in the form of application forms, telephone interviews, and magazine staff questionnaires. Survey is the simplest research strategy. Data and information can be collected easily and better from the crowd. For centuries researchers have used research methods to support the creation of reliable knowledge based on empirical evidence and logical arguments. This chapter will outline established research strategies and methods with emphasis on empirical research in social science. In this chapter, we will explain research strategies such as experiments, surveys, case studies, ethnographic journals, basic theory, behavioral research, phenomenology. It also explains how to collect data, including questionnaires, interviews, focus groups, findings, and documentation. Discuss qualitative and quantitative data analysis methods. Finally, I will study the use of research strategies and methods in design science. Quantitative psychologists and measurement psychologists focus on methods and techniques for planning experiments and analyzing spiritual data. Certain people have developed a new method for analysis; others have developed research strategies to evaluate the effectiveness of social and educational programs and psychotherapy. They develop and evaluate mathematical models of psychological tests. They also proposed ways to evaluate the quality and fairness of the test. Social psychologists study how people interact and how they are affected by the social environment. These psychologists often try to identify attribution, attitudes, beliefs, and social norms that often influence the behavior of various interpersonal relationships. This research may include studies on individuals and groups that may include observing observable behaviors and evaluating personal thoughts.

The integration of information technology and medical technology is a rewarding process for huge variables related to health information data. Doctors are taught to use evidence-based medicine during medical training. This means using the latest scientific research data that has been analyzed and accepted as facts. (Sharon Bahrych, 2011) There are various factors that define quality care elements and expectations for individuals, ultimately determining the patient's treatment process. New technology is indispensable to medical science, health information science is no exception. With detailed patient records, clinics and hospitals have access to more information and can search this information faster than ever. The development and integration of computer science and medicine has opened doors to give healthcare professionals better opportunities to receive the best treatment for their patients. In many organizations, the Chief Medical Information Officer (CMIO) is also referred to as President of Health Information or President of Medical Information. As an intermediary between physician and IT department, CMIO is responsible for designing the technology and integrating it into the physician's workflow, spanning the medical and technical aspects of medicine. Health data analysis experts who can track and gain insight from health informatics information are used by health care systems to track and improve the condition of people with chronic diseases such as diabetes, hypertension, obesity It is becoming increasingly important for group health management programs In the history of modern medicine and technology, it has always been the lifeblood of medicine, so it is difficult to obtain past information. Information is a precious and scarce source of information and is the basis for decision-making at all levels. Many sophisticated diagnostic techniques, such as CAT scanning and magnetic resonance imaging, generate information similar to various laboratory tests and then process it in the computer's brain, the clinician's brain . Therefore, information is a basic comprehensive technology.

Subjectivity of artists and scientists on the surface, subjectivity and perception of art complement each other. However, if science is mentioned, it seems to be related to objectivity. Science is about objective truth, and art is about making subjective truths clear. But the subjective advantages of the artist are limited, especially when judging the art. Likewise, subjectivity is not always a barrier to scientists, especially in research. In the field of art, people think that subjective experience does not necessarily spread through words. Artists are confronted with limitations of specific expressions. In other words, scientists also understand that languages ​​are crude instruments that do not convey abstract concepts. Therefore, science explores the limits of abstract thinking. Art and science are not satisfied with verbal communication. In order to cause a miracle, artists may give up language. To gain knowledge, scientists often abandon their languages. Ahmed Alkhateeb, a molecular cancer biologist at Harvard Medical School of Medicine, proposes outsourcing research to artificial intelligence in his article "Science transcended the human mind and its limited ability". It is because "human thought can not reproduce very complicated natural phenomena effectively." The age problem of big data is that language is a tool for society as a whole to collect knowledge and understand beauty. We combine two different themes to redefine the definition of beautiful natural world and its structured art. The Swiss scientist / photographer / artist, Fabian Oefner, applies scientific attributes to create colorful art to draw attention to the beauty of nature and how it works. His mission is to draw persuasive art from everyday science. His work is exhibited in various countries all over the world and has received requests for famous brands such as LG, Tropicana and Ferrari. Fabian's goal is to combine art and science British artist and computer scientist Julie Freeman creates dynamic sculptures, works and animations based on naturally generated data such as fish swimming movements and moth feather vibrations. "I will use digital technology as a bridge between nature and ourselves," she said. "The art I made shared nature curiosity naturally in various ways and shared this curiosity.What is persuasive natural system is a phenomenon beyond our sense perception How can you understand? "Freeman's online data driven artwork" We Need Us "explores the nature of metadata and the human nature of data life.

Publishing and editing by Douglas Cunningham. 845-265-2468. Main news sources of Carmel, Mahopac, Kent, Brewster, Patterson, Southeast Copying, reprinting and reprinting of materials are forbidden without permission by copyright. The past is gone, but in the boring days when the world is not too boring for us, the best is carved into your heart, certainly brought to the future and used. Like the sand on the sieve, the worst thing falls on our open fingers, then it returns to Earth and it becomes convenient and unforgettable. Even if HBR articles are repeated, they jump into the data. However, they seem to be sifting sand on the beach, knocking out millions, possibly even billions of particles, to find useful data, or it seems that the useful structure is not worth separate values It is easier to say that you are assembling particles. In data science, you can do all of the above. how is it? You can create practical insights by organizing all available data and applying analytical methods (very glossy and cool methods such as machine learning). By having the data science function in-house, you can do smarter and more accurate exploration, especially with account-based marketing, without relying on brokers and marketing automation platforms. Everyone has two ways of thinking: absorbing information (such as a sponge absorbing water) and thinking about information (sifting sand etc.). Those who use the first approach will try to remember the given information in detail, but others will actively interact with the knowledge they have learned. This does not mean that one method is bad; critical thinking combines these two characteristics. It is difficult to nurture critical thinking. Because it is easy to accept friends, family, public opinion position. Your friend may think the vaccine will have a significant impact on your child's health. But if you are going to study available information on this issue, you can change your mind or simply reconfirm your beliefs.

I have expanded my engineering skills through internship experience in three major industries. My first internship took place at the Karachi shipyard and engineering factory where I gained experience in repairing and maintaining (modifying and planning) oceanic equipment including diesel engines and generators. We also experienced the production of an intermediate class ship F-22 P built for the Pakistan Navy. My second internship was held at Bin Qasim Thermal Power Station of K - Electric (formerly KESC), the largest power station established by K - Electric. This article was written by Ignacio Arranz, a first grader in the Data Science Program (DATS), a member of the first DATS cohort. The DATS program is the latest MSc program at the University of Pennsylvania College of Engineering and offers students a wide range of data-centered careers, including technology and engineering, consulting, science, policy planning, literature, arts or understanding of communication. Mode In 1896, at the age of 30, the painter Vasily Kandinsky abandoned promising career education law and economics at Munich's art school. I like to think that I made the same choice at the same age. After more than six years as a management consultant, I decided to obtain a master's degree in data science from the University of Pennsylvania. On my 31st birthday a week after class, I first made a wireless oximeter at the University of Pennsylvania classmates Garvit Gupta, Yu-Ho Hsieh, Abhijeet Singh and PennApps. The Master of Science (MEM) program is located at the McCormick Engineering department at Northwestern University and is designed for experienced engineering and scientific experts who wish to refine core management and leadership skills while maintaining leading edge technology It has been. This course combines the basic management principles of MBA and comprehensive quantitative analysis tools so that engineers can communicate in business language and transform from tactical thinking to strategic thinking. Graduates leave the program to take on the best leaders role for today's technically advanced enterprises First commercial deployment in the United States by Power Ledger & Clean Energy block chain network partners and Northwestern University

Engineering camp is a very recommended professional introduction. These summer camps are usually hosted by engineering schools nationwide and include engineering applications such as guitar making, manufacturing sports equipment, designing alternative energy equipment, manufacturing gliders, airplanes and rockets, creating video games, etc. there is. To see the engineering or engineering college or engineering camp directory near your university, please visit engineeringingedu.com. Engineering is to apply the principles of science and mathematics to the real world. Therefore, engineers must have a solid foundation of mathematics and science. People who are interested in engineering careers should not be frightened by the prospect of taking up challenging maths and science courses in large quantities. But becoming an engineer is more than just understanding mathematical concepts and scientific principles. Other steps necessary to obtain an online engineering degree are as follows. It is very independent in experimental reasoning and analysis. The topic of this course highlights problem solving activities and engineering applications in chemistry. Lesson 10 - Engineering, Mathematics, and Computer Applications H In this course, students learn mathematics, statistics, and computer skills and apply them to scientific and engineering applications. Students extend the knowledge of mathematical concepts to real engineering tasks. If you frequently use Microsoft Excel, you can organize data in a specialized way and analyze data about patterns and relationships. Basic programming knowledge is introduced through the use of Excel 's prefabricated functions and the introduction of the Python programming language. Programming focuses on the use of common Python data types, loops, and conditional statements. Computer data collection and mathematical analysis are at the center of the program