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Becoming Metric-Wise: A Bibliometric Guide for Researchers aims to inform researchers about metrics so that they become aware of the evaluative techniques being applied to their scientific output. Understanding these concepts will help them during their funding initiatives, and in hiring and tenure. The book not only describes what indicators do (or are designed to do, which is not always the same thing), but also gives precise mathematical formulae so that indicators can be properly understood and evaluated. Metrics have become a critical issue in science, with widespread international discussion taking place on the subject across scientific journals and organizations. As researchers should know the publication-citation context, the mathematical formulae of indicators being used by evaluating committees and their consequences, and how such indicators might be misused, this book provides an ideal tome on the topic. - Provides researchers with a detailed understanding of bibliometric indicators and their applications - Empowers researchers looking to understand the indicators relevant to their work and careers - Presents an informed and rounded picture of bibliometrics, including the strengths and shortcomings of particular indicators - Supplies the mathematics behind bibliometric indicators so they can be properly understood - Written by authors with longstanding expertise who are considered global leaders in the field of bibliometrics
Proceedings of the 15th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, Nice, France, 24-27 July 2024.
This volume presents a selection of peer-reviewed papers that address the latest developments in the methodology and applications of data analysis and classification tools to micro- and macroeconomic problems. The contributions were originally presented at the 30th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2021, held online in Poznań, Poland, September 8–10, 2021. Providing a balance between methodological and empirical studies, and covering a wide range of topics, the book is divided into five parts focusing on methods and applications in finance, economics, social issues and to COVID-19 data. The book is aimed at a wide audience, including researchers at universities and research institutions, PhD students, as well as practitioners, data scientists and employees in public statistical institutions.
This book probes the dynamics of academic research and scholarship evaluation. Readers will learn about scholarly metric evolution, impact factors, disruptive technologies, and a myriad of forces affecting policy development at institutions through an examination of widely-used measurements and growing concerns about their influence.
Benefits of book which distinguish it from others: • Strictly as per the latest Syllabus and pattern • Latest Solved Papers 2022 (Shift 1 to 3) with explanations • Three Sections are as follows- Verbal Ability & Reading comprehension (VARC), Data Interpretation & Logical Reasoning (DILR) and Quantitative Aptitude (QA). • Chapter wise and Topic wise introduction to enable quick revision and systematic flow of concepts in Revision Notes on all three sections. • Previous Years’ (1990-2008 & 2017-2022) Exam Questions to facilitate focused study • CAT Success Story • Tips to crack the CAT Exam in the first Attempt • How to use this Book? • CAT Score Vs Percentile • CAT 2022 & 2021 – All three sessions’ papers section wise for understanding pattern and type of the questions. • Focussed Practice from 3 Sample Question Papers of CAT. • CAT Section-wise Trend and Chapter Analysis • Answer key with Explanation for perfect concept understanding • Valuable insights – tips, tricks and short Cuts • Mind Maps to provoke new ideas • Boost Memory skills with Mnemonics • Concept wise Videos in QR codes for Digital Learning Experience
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New digital technologies have transformed how scientific information is created, disseminated—and discovered. The emergence of new forms of scientific publishing based on open science and open access have caused a major shift in scientific communication and a restructuring of the flow of information. Specialized indexing services and search engines are trying to get into information seekers' minds to understand what users are actually looking for when typing all these keywords or drawing chemical structures. Using artificial intelligence (AI), machine learning, and semantic indexing, these "discovery agents" are trying to anticipate users' information needs. In this highly competitive environment, authors should not sit and rely only on publishers, search engines, and indexing services to make their works visible. They need to communicate about their research and reach out to a larger audience. Driving Science Information Discovery in the Digital Age looks through the "eyes" of the main "players" in this "game" and examines the discovery of scientific information from three different, but intertwined, perspectives: - Discovering, managing, and using information (Information seeker perspective) - Publishing, disseminating, and making information discoverable (Publisher perspective) - Creating, spreading, and promoting information (Author perspective). - Presents an overview of the current scientific publishing landscape - Shows how users can search for scientific information more efficiently - Critically analyses the metrics used to measure the quality of journals and the impact of research - Looks at the discovery of scientific information from the perspectives of information seekers, publishers, and authors - Delves into the practices used by specialized indexing services and search engines to process scientific information and make it discoverable - Recommends strategies that authors could use to promote their research
Metrics for software development are usually employed ad-hoc and without clear directions for interpreting the numbers and acting on them. Almost every other engineering discipline has clear guidelines for measuring processes and products and making decisions based on quantified evidence. This practical book describes how to integrate processes and metrics to ensure easier and more effective enterprise software development. It crosses the divide between theory and practice and also discusses why essential processes so often fail to deliver quality industrial software. Enterprise Software Development introduces the techniques for building, applying and interpreting metrics for the workflows across the software development life cycle phases of inception, elaboration, construction and transition. It is a must read for software engineering practitioners (architects, application developers, designers and project managers), academics, and students and apprentices of software engineering.
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