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Author : Arthur D. Chapman
Publisher : GBIF
Page : 75 pages
File Size : 52,7 Mb
Release : 2005
Category : Biodiversity
ISBN : 9788792020048
Author : Arthur D. Chapman
Publisher : Unknown
Page : 72 pages
File Size : 47,7 Mb
Release : 2005
Category : Biology
ISBN : OCLC:183150775
Author : Arthur D. Chapman
Publisher : GBIF
Page : 61 pages
File Size : 50,6 Mb
Release : 2005
Category : Biodiversity
ISBN : 9788792020031
Author : Sofia Mougiakou,Dimitra Vinatsella,Demetrios Sampson,Zacharoula Papamitsiou,Michail Giannakos,Dirk Ifenthaler
Publisher : Springer Nature
Page : 249 pages
File Size : 50,9 Mb
Release : 2022-10-28
Category : Education
ISBN : 9783031152665
Educational Data Analytics (EDA) have been attributed with significant benefits for enhancing on-demand personalized educational support of individual learners as well as reflective course (re)design for achieving more authentic teaching, learning and assessment experiences integrated into real work-oriented tasks. This open access textbook is a tutorial for developing, practicing and self-assessing core competences on educational data analytics for digital teaching and learning. It combines theoretical knowledge on core issues related to collecting, analyzing, interpreting and using educational data, including ethics and privacy concerns. The textbook provides questions and teaching materials/ learning activities as quiz tests of multiple types of questions, added after each section, related to the topic studied or the video(s) referenced. These activities reproduce real-life contexts by using a suitable use case scenario (storytelling), encouraging learners to link theory with practice; self-assessed assignments enabling learners to apply their attained knowledge and acquired competences on EDL. By studying this book, you will know where to locate useful educational data in different sources and understand their limitations; know the basics for managing educational data to make them useful; understand relevant methods; and be able to use relevant tools; know the basics for organising, analysing, interpreting and presenting learner-generated data within their learning context, understand relevant learning analytics methods and be able to use relevant learning analytics tools; know the basics for analysing and interpreting educational data to facilitate educational decision making, including course and curricula design, understand relevant teaching analytics methods and be able to use relevant teaching analytics tools; understand issues related with educational data ethics and privacy. This book is intended for school leaders and teachers engaged in blended (using the flipped classroom model) and online (during COVID-19 crisis and beyond) teaching and learning; e-learning professionals (such as, instructional designers and e-tutors) of online and blended courses; instructional technologists; researchers as well as undergraduate and postgraduate university students studying education, educational technology and relevant fields.
Author : Geertrui van Overwalle
Publisher : Cambridge University Press
Page : 517 pages
File Size : 52,5 Mb
Release : 2009-06-11
Category : Law
ISBN : 9780521896733
The cost of patent licenses needed to design a new genetic test or treatment may ultimately prevent research projects getting started, as individual components are protected by different patent owners. This book examines legal measures which might be used to solve the problem of fragmentation of patents in genetics.
Author : Anonim
Publisher : Frontiers E-books
Page : 158 pages
File Size : 51,6 Mb
Release : 2024-06-30
Category : Electronic
ISBN : 9782889191550
Author : Hulin Wu,Jose Miguel Yamal,Ashraf Yaseen,Vahed Maroufy
Publisher : CRC Press
Page : 268 pages
File Size : 40,5 Mb
Release : 2020-12-10
Category : Business & Economics
ISBN : 9781000260960
The use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.
Author : Cynthia Clamp,Stephen Gough,Lucy Land
Publisher : SAGE
Page : 432 pages
File Size : 51,8 Mb
Release : 2005-01-11
Category : Medical
ISBN : 9781847877369
′The 4th edition of this extensive text is an outstanding resource prepared by nurses (and a librarian) for nurses. In a structured and helpful style it presents thousands of items from the literature - published papers, reports, books and electronic resources - as a clear, accessible, and most of all useful collection. The efforts to signpost and lead the reader to the sought-for information are effective and well-conceived, and the "How to use this book" section is remarkably simple...the book should be found in every nursing and health library, every research institute and centre, and close to many career researchers′ desks′ - RCN Research This latest edition of Resources for Nursing Research provides a comprehensive bibliography of sources on nursing research, and includes references for books, journal papers and Internet resources. Designed to act as a ′signpost′ to available literature in the area, this Fourth Edition covers the disciplines of nursing, health care and the social sciences. Entries are concise, informative and accessible, and are arranged under three main sections: · ′Sources of Literature′ covers the process of literature searching, including using libraries and other tools for accessing literature · ′Methods of Inquiry′ includes an introduction to research, how to conceptualize and design nursing and health research, measurement and data collection, and the interpretation and presentation of data · ′The Background to Research in Nursing′ encompasses the development of nursing research; the profession′s responsibilities; the role of government; funding; research roles and careers; and education for research. Fully revised and updated, the Fourth Edition includes just under 3000 entries, of which 90% are new. It has extensive coverage of US, UK literature and other international resources. This new edition will be an essential guide for all those with an interest in nursing research, including students, teachers, librarians, practitioners and researchers.
Author : Guan Gui,Ying Li,Yun Lin
Publisher : Springer Nature
Page : 482 pages
File Size : 53,9 Mb
Release : 2024-01-13
Category : Education
ISBN : 9783031515033
This four-volume set constitutes the post-conference proceedings of the 9th EAI International Conference on e-Learning, e-Education, and Online Training, eLEOT 2023, held in Yantai, China, during August 17-18, 2023. The 104 full papers presented were selected from 260 submissions. The papers reflect the evolving landscape of education in the digital age. They were organized in topical sections as follows: IT promoted teaching platforms and systems; AI based educational modes and methods; automatic educational resource processing; educational information evaluation.
Author : Mykhailo Ilchenko,Leonid Uryvsky,Larysa Globa
Publisher : Springer Nature
Page : 602 pages
File Size : 41,6 Mb
Release : 2022-11-17
Category : Technology & Engineering
ISBN : 9783031163685
This book highlights the most important research areas in information and communication technologies, namely the research in fields of modern information technologies that deal with various aspects of the analysis and solution of practically important issues of information systems in general, and contains discussion about the progression from big data to smart data, development of cloud-based architecture, practical implementation of Internet of Things (IoT), the fundamentals of information and analytical activities; studying of modern communication technologies contains original works dealing with many aspects of construction, using research and forecasting of technological and services characteristics of communication systems, as well as research of modern radio electronics technologies that contains actual papers, which show some effective technological solutions that can be used for the implementation of novel radio electronics systems. These results can be used in the implementation of novel systems and to promote information exchange in e-societies. This book offers a valuable resource for scientists, lecturers, specialists working at enterprises, and graduate and undergraduate students who engage with problems in information and communication technologies.
Author : John P. Hoffmann
Publisher : Univ of California Press
Page : 282 pages
File Size : 48,9 Mb
Release : 2017-07-04
Category : Social Science
ISBN : 9780520289956
Why research? -- Developing research questions -- Data -- Principles of data management -- Finding and using secondary data -- Primary and administrative data -- Working with missing data -- Principles of data presentation -- Designing tables for data presentations -- Designing graphics for data presentations
Author : Anonim
Publisher : Elsevier
Page : 537 pages
File Size : 52,7 Mb
Release : 2018-08-27
Category : Mathematics
ISBN : 9780444640437
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more. The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important. Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more
Author : Ramjan, Sarawut,Sunkpho, Jirapon
Publisher : IGI Global
Page : 326 pages
File Size : 54,7 Mb
Release : 2023-05-09
Category : Computers
ISBN : 9781668447321
The demand for skilled data scientists is rapidly increasing as more organizations recognize the value of data-driven decision- making. Data science, data management, and data mining are all critical components for various types of organizations, including large and small corporations, academic institutions, and government entities. For companies, these components serve to extract insights and value from their data, empowering them to make evidence-driven decisions and gain a competitive advantage by discovering patterns and trends and avoiding costly mistakes. Academic institutions utilize these tools to analyze large datasets and gain insights into various scientific fields of study, including genetic data, climate data, financial data, and in the social sciences they are used to analyze survey data, behavioral data, and public opinion data. Governments use data science to analyze data that can inform policy decisions, such as identifying areas with high crime rates, determining which regions need infrastructure development, and predicting disease outbreaks. However, individuals who are not data science experts, but are experts within their own fields, may need to apply their experience to the data they must manage, but still struggle to expand their knowledge of how to use data mining tools such as RapidMiner software. Principles and Theories of Data Mining With RapidMiner is a comprehensive guide for students and individuals interested in experimenting with data mining using RapidMiner software. This book takes a practical approach to learning through the RapidMiner tool, with exercises and case studies that demonstrate how to apply data mining techniques to real-world scenarios. Readers will learn essential concepts related to data mining, such as supervised learning, unsupervised learning, association rule mining, categorical data, continuous data, and data quality. Additionally, readers will learn how to apply data mining techniques to popular algorithms, including k-nearest neighbor (K-NN), decision tree, naïve bayes, artificial neural network (ANN), k-means clustering, and probabilistic methods. By the end of the book, readers will have the skills and confidence to use RapidMiner software effectively and efficiently, making it an ideal resource for anyone, whether a student or a professional, who needs to expand their knowledge of data mining with RapidMiner software.
Author : Yan Jia,Zhaoquan Gu,Aiping Li
Publisher : Springer Nature
Page : 255 pages
File Size : 46,5 Mb
Release : 2021-03-06
Category : Computers
ISBN : 9783030715908
Knowledge representation is an important task in understanding how humans think and learn. Although many representation models or cognitive models have been proposed, such as expert systems or knowledge graphs, they cannot represent procedural knowledge, i.e., dynamic knowledge, in an efficient way. This book introduces a new knowledge representation model called MDATA (Multi-dimensional Data Association and inTelligent Analysis). By modifying the representation of entities and relations in knowledge graphs, dynamic knowledge can be efficiently described with temporal and spatial characteristics. The MDATA model can be regarded as a high-level temporal and spatial knowledge graph model, which has strong capabilities for knowledge representation. This book introduces some key technologies in the MDATA model, such as entity recognition, relation extraction, entity alignment, and knowledge reasoning with spatiotemporal factors. The MDATA model can be applied in many critical applications and this book introduces some typical examples, such as network attack detection, social network analysis, and epidemic assessment. The MDATA model should be of interest to readers from many research fields, such as database, cyberspace security, and social network, as the need for the knowledge representation arises naturally in many practical scenarios.
Author : Venkatesh Ganti,Anish Das Sarma
Publisher : Morgan & Claypool Publishers
Page : 87 pages
File Size : 49,8 Mb
Release : 2013-09-01
Category : Computers
ISBN : 9781608456789
Data warehouses consolidate various activities of a business and often form the backbone for generating reports that support important business decisions. Errors in data tend to creep in for a variety of reasons. Some of these reasons include errors during input data collection and errors while merging data collected independently across different databases. These errors in data warehouses often result in erroneous upstream reports, and could impact business decisions negatively. Therefore, one of the critical challenges while maintaining large data warehouses is that of ensuring the quality of data in the data warehouse remains high. The process of maintaining high data quality is commonly referred to as data cleaning. In this book, we first discuss the goals of data cleaning. Often, the goals of data cleaning are not well defined and could mean different solutions in different scenarios. Toward clarifying these goals, we abstract out a common set of data cleaning tasks that often need to be addressed. This abstraction allows us to develop solutions for these common data cleaning tasks. We then discuss a few popular approaches for developing such solutions. In particular, we focus on an operator-centric approach for developing a data cleaning platform. The operator-centric approach involves the development of customizable operators that could be used as building blocks for developing common solutions. This is similar to the approach of relational algebra for query processing. The basic set of operators can be put together to build complex queries. Finally, we discuss the development of custom scripts which leverage the basic data cleaning operators along with relational operators to implement effective solutions for data cleaning tasks.
