Download or read book Data to Knowledge written by Tofael Ahamed and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a sound understanding for creating new knowledge, which takes three main forms: Exploratory research, which structures and identifies new problems; constructive research, which develops solutions to a problem; and empirical research, which tests the feasibility of a solution using empirical evidence. This book encompasses both qualitative and quantitative research and analysis. The reader should gain an understanding of the skills needed to design and undertake a research project, including legal and ethical requirements in planning research projects, choosing the best experimental design and analytical methods, and how to present data for extension to the wider community and establish the knowledge. Hands-on exercises are provided to improve reasoning skills, emphasising agricultural problems and issues to solve and interpret the experimental data to knowledge. The book covers research methods within these three forms with basic knowledge of research methodology. Design of experiments and significant results are interpreted through the scientific organisation and information in each of the chapters. The inherent discussion should help interdisciplinary graduate students and researchers accomplish their scientific experiments and write research articles. The cognitive writing style to interpret the observed data from experiments and surveys is emphasised in this book. The cognitive summary for each of the chapters is provided in the form of wording and graphics to focus on the chapter highlights as well as the use of analytical tools in the research. The utmost care is taken to present a varied range of research problems along with their solutions in agriculture and its allied fields, which should be of immense use to the readers interested in this topic.

Download or read book Facilitating Interdisciplinary Research written by Institute of Medicine and published by National Academies Press. This book was released on 2005-04-04 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Facilitating Interdisciplinary Research examines current interdisciplinary research efforts and recommends ways to stimulate and support such research. Advances in science and engineering increasingly require the collaboration of scholars from various fields. This shift is driven by the need to address complex problems that cut across traditional disciplines, and the capacity of new technologies to both transform existing disciplines and generate new ones. At the same time, however, interdisciplinary research can be impeded by policies on hiring, promotion, tenure, proposal review, and resource allocation that favor traditional disciplines. This report identifies steps that researchers, teachers, students, institutions, funding organizations, and disciplinary societies can take to more effectively conduct, facilitate, and evaluate interdisciplinary research programs and projects. Throughout the report key concepts are illustrated with case studies and results of the committee's surveys of individual researchers and university provosts.

Download or read book Data Science and Interdisciplinary Research Recent Trends and Applications written by Brojo Kishore Mishra and published by Bentham Science Publishers. This book was released on 2023-09-27 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Interdisciplinary Research: Recent Trends and Applications is a compelling edited volume that offers a comprehensive exploration of the latest advancements in data science and interdisciplinary research. Through a collection of 10 insightful chapters, this book showcases diverse models of machine learning, communications, signal processing, and data analysis, illustrating their relevance in various fields. Key Themes: Advanced Rainfall Prediction: Presents a machine learning model designed to tackle the challenging task of predicting rainfall across multiple countries, showcasing its potential to enhance weather forecasting. Efficient Cloud Data Clustering: Explains a novel computational approach for clustering large-scale cloud data, addressing the scalability of cloud computing and data analysis. Secure In-Vehicle Communication: Explores the critical topic of secure communication in in-vehicle networks, emphasizing message authentication and data integrity. Smart Irrigation 4.0: Details a decision model designed for smart irrigation, integrating agricultural sensor data reliability analysis to optimize water usage in precision agriculture. Smart Electricity Monitoring: Highlights machine learning-based smart electricity monitoring and fault detection systems, contributing to the development of smart cities. Enhanced Learning Environments: Investigates the effectiveness of mobile learning in higher education, shedding light on the role of technology in shaping modern learning environments. Coastal Socio-Economy Study: Presents a case study on the socio-economic conditions of coastal fishing communities, offering insights into the livelihoods and challenges they face. Signal Noise Removal: Shows filtering techniques for removing noise from ECG signals, enhancing the accuracy of medical data analysis and diagnosis. Deep Learning in Biomedical Research: Explores deep learning techniques for biomedical research, particularly in the realm of gene identification using Next Generation Sequencing (NGS) data. Medical Diagnosis through Machine Learning: Concludes with a chapter on breast cancer detection using machine learning concepts, demonstrating the potential of AI-driven diagnostics.

Download or read book Data Science and Interdisciplinary Research written by Brojo Kishore Mishra and published by Bentham Science Publishers. This book was released on 2023-09-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Interdisciplinary Research: Recent Trends and Applications is a compelling edited volume that offers a comprehensive exploration of the latest advancements in data science and interdisciplinary research. Through a collection of 10 insightful chapters, this book showcases diverse models of machine learning, communications, signal processing, and data analysis, illustrating their relevance in various fields. Key Themes: -Advanced Rainfall Prediction: Presents a machine learning model designed to tackle the challenging task of predicting rainfall across multiple countries, showcasing its potential to enhance weather forecasting. -Efficient Cloud Data Clustering: Explains a novel computational approach for clustering large-scale cloud data, addressing the scalability of cloud computing and data analysis. -Secure In-Vehicle Communication: Explores the critical topic of secure communication in in-vehicle networks, emphasizing message authentication and data integrity. -Smart Irrigation 4.0: Details a decision model designed for smart irrigation, integrating agricultural sensor data reliability analysis to optimize water usage in precision agriculture. -Smart Electricity Monitoring: Highlights machine learning-based smart electricity monitoring and fault detection systems, contributing to the development of smart cities. -Enhanced Learning Environments: Investigates the effectiveness of mobile learning in higher education, shedding light on the role of technology in shaping modern learning environments. -Coastal Socio-Economy Study: Presents a case study on the socio-economic conditions of coastal fishing communities, offering insights into the livelihoods and challenges they face. -Signal Noise Removal: Shows filtering techniques for removing noise from ECG signals, enhancing the accuracy of medical data analysis and diagnosis. -Deep Learning in Biomedical Research: Explores deep learning techniques for biomedical research, particularly in the realm of gene identification using Next Generation Sequencing (NGS) data. -Medical Diagnosis through Machine Learning: Concludes with a chapter on breast cancer detection using machine learning concepts, demonstrating the potential of AI-driven diagnostics.

Download or read book Routledge Handbook of Interdisciplinary Research Methods written by Celia Lury and published by Routledge. This book was released on 2018-07-06 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: The landscape of contemporary research is characterized by growing interdisciplinarity, and disciplinary boundaries are blurring faster than ever. Yet while interdisciplinary methods, and methodological innovation in general, are often presented as the ‘holy grail’ of research, there are few examples or discussions of their development and ‘behaviour’ in the field. This Routledge Handbook of Interdisciplinary Research presents a bold intervention by showcasing a diversity of stimulating approaches. Over 50 experienced researchers illustrate the challenges, but also the rewards of doing and representing interdisciplinary research through their own methodological developments. Featured projects cover a variety of scales and topics, from small art-science collaborations to the ‘big data’ of mass observations. Each section is dedicated to an aspect of data handling, from collection, classification, validation to communication to research audiences. Most importantly, Interdisciplinary Methods presents a distinctive approach through its focus on knowledge as process, defamiliarising and reworking familiar practices such as experimenting, archiving, observing, prototyping or translating.

Download or read book Introduction to Data Science for Social and Policy Research written by Jose Manuel Magallanes Reyes and published by Cambridge University Press. This book was released on 2017-09-21 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Download or read book Applied Data Science in Tourism written by Roman Egger and published by Springer Nature. This book was released on 2022-01-31 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau

Download or read book Applications of AI for Interdisciplinary Research written by Sukhpal Singh Gill and published by CRC Press. This book was released on 2024-09-13 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applying artificial intelligence (AI) to new fields has made AI and data science indispensable to researchers in a wide range of fields. The proliferation and successful deployment of AI algorithms are fuelling these changes, which can be seen in fields as disparate as healthcare and emerging Internet of Things (IoT) applications. Machine learning techniques, and AI more broadly, are expected to play an ever-increasing role in the modelling, simulation, and analysis of data from a wide range of fields by the interdisciplinary research community. Ideas and techniques from multidisciplinary research are being utilised to enhance AI; hence, the connection between the two fields is a two-way street at a crossroads. Algorithms for inference, sampling, and optimisation, as well as investigations into the efficacy of deep learning, frequently make use of methods and concepts from other fields of study. Cloud computing platforms may be used to develop and deploy several AI models with high computational power. The intersection between multiple fields, including math, science, and healthcare, is where the most significant theoretical and methodological problems of AI may be found. To gather, integrate, and synthesise the many results and viewpoints in the connected domains, refer to it as interdisciplinary research. In light of this, the theory, techniques, and applications of machine learning and AI, as well as how they are utilised across disciplinary boundaries, are the main areas of this research topic. This book apprises the readers about the important and cutting-edge aspects of AI applications for interdisciplinary research and guides them to apply their acquaintance in the best possible manner This book is formulated with the intent of uncovering the stakes and possibilities involved in using AI through efficient interdisciplinary applications The main objective of this book is to provide scientific and engineering research on technologies in the fields of AI and data science and how they can be related through interdisciplinary applications and similar technologies This book covers various important domains, such as healthcare, the stock market, natural language processing (NLP), real estate, data security, cloud computing, edge computing, data visualisation using cloud platforms, event management systems, IoT, the telecom sector, federated learning, and network performance optimisation. Each chapter focuses on the corresponding subject outline to offer readers a thorough grasp of the concepts and technologies connected to AI and data analytics, and their emerging applications

Download or read book Interdisciplinary Research written by Allen F. Repko and published by SAGE. This book was released on 2008-05-29 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Interdisciplinary Research offers comprehensive treatment of the interdisciplinary research process commonly used by interdisciplinarians. The concise and guided resource on the most commonly accepted interdisciplinary studies principles as applied to the research process covers topics such as: deciding how to choose disciplines relevant to the problem or topi; dealing with disciplinary and ideological bias; making explicit the rationale for taking an interdisciplinary approach, and choosing research methods appropriate to the problem or topic.

Download or read book Guide to Teaching Data Science written by Orit Hazzan and published by Springer Nature. This book was released on 2023-03-20 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry. This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people. This book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach). Professor Orit Hazzan is a faculty member at the Technion’s Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations. Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University.

Download or read book Introduction to Interdisciplinary Studies written by Allen F. Repko and published by SAGE Publications. This book was released on 2016-10-12 with total page 577 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Second Edition provides a comprehensive introduction to interdisciplinary studies with an approach that is succinct, conceptual, and practical. Completely updated to reflect advances in the literature on research, learning, and assessment, the book describes the role of both disciplines and interdisciplinarity within the academy, and how these have evolved. Authors Allen F. Repko, Rick Szostak, and Michelle Phillips Buchberger effectively show students how to think like interdisciplinarians in order to facilitate their working with topics, complex problems, or themes that span multiple disciplines.

Download or read book Work at the Boundaries of Science written by C.L. Palmer and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interdisciplinary inquiry has become more pervasive in recent decades, yet we still know little about the conduct of this type of research or the information problems associated with it. This book is one of few empirical studies of interdisciplinary knowledge practices. It examines how interdisciplinary scientists discover and exchange information and knowledge, highlighting how the boundaries between disciplines affect how information is used and how knowledge is constructed. It is written for scholars and practitioners with an interest in developing information systems and research environments to foster innovative scientific work. Target groups include researchers in information science, science studies, communication, as well as research administrators and information professionals.

Download or read book Exploring Advances in Interdisciplinary Data Mining and Analytics New Trends written by Taniar, David and published by IGI Global. This book was released on 2011-12-31 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is an updated look at the state of technology in the field of data mining and analytics offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining"--Provided by publisher.

Download or read book Case Studies in Interdisciplinary Research written by Allen F. Repko and published by SAGE Publications. This book was released on 2011-02-07 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Case Studies in Interdisciplinary Research successfully applies the model of the interdisciplinary research process outlined by author Allen F. Repko in Interdisciplinary Research, (SAGE ©2008) to a wide spectrum of challenging research questions. Self-contained case studies, written by leaders in interdisciplinary research, and utilizing best-practice techniques in conducting interdisciplinary research shows students how to apply the interdisciplinary research process to a variety of problems.

Download or read book Human Centered Data Science written by Cecilia Aragon and published by MIT Press. This book was released on 2022-03-01 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns.

Download or read book Data Science From Research to Application written by Mahdi Bohlouli and published by Springer Nature. This book was released on 2020-01-28 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents outstanding theoretical and practical findings in data science and associated interdisciplinary areas. Its main goal is to explore how data science research can revolutionize society and industries in a positive way, drawing on pure research to do so. The topics covered range from pure data science to fake news detection, as well as Internet of Things in the context of Industry 4.0. Data science is a rapidly growing field and, as a profession, incorporates a wide variety of areas, from statistics, mathematics and machine learning, to applied big data analytics. According to Forbes magazine, “Data Science” was listed as LinkedIn’s fastest-growing job in 2017. This book presents selected papers from the International Conference on Contemporary Issues in Data Science (CiDaS 2019), a professional data science event that provided a real workshop (not “listen-shop”) where scientists and scholars had the chance to share ideas, form new collaborations, and brainstorm on major challenges; and where industry experts could catch up on emerging solutions to help solve their concrete data science problems. Given its scope, the book will benefit not only data scientists and scientists from other domains, but also industry experts, policymakers and politicians.

Download or read book Bridging Disciplines in the Brain Behavioral and Clinical Sciences written by Institute of Medicine and published by National Academies Press. This book was released on 2000-09-24 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interdisciplinary research is a cooperative effort by a team of investigators, each an expert in the use of different methods and concepts, who have joined in an organized program to attack a challenging problem. Each investigator is responsible for the research in their area of discipline that applies to the problem, but together the investigators are responsible for the final product. The need for interdisciplinary training activities has been detailed over the last 25 years in both public and private reports. The history of science and technology has even shown the important advances that arose from interdisciplinary research, including plate tectonics which brought together geologists, oceanographers, paleomagnetists, seismologists, and geophysicists to advance the ability to forecast earthquakes and volcanic eruptions. In recognition of this, the need to train scientists who can address the highly complex problems that challenge us today and fully use new knowledge and technology, and the fact that cooperative efforts have proved difficult, the National Institute of Mental Health (NIMH), the National Institutes of Health (NIH) Office of Behavioral and Social Sciences Research (OBSSR), the National Institute on Nursing Research (NINR), and the National Institute on Aging (NIA) requested that an Institute of Medicine (IOM) Committee be created to complete several tasks including: examining the needs and strategies for interdisciplinary training in the brain, behavioral, social, and clinical sciences, defining necessary components of true interdisciplinary training in these areas, and reviewing current educational and training programs to identify elements of model programs that best facilitate interdisciplinary training. Bridging Disciplines in the Brain, Behavioral, and Clinical Sciences provides the conclusions and recommendations of this committee. Due to evaluations of the success of interdisciplinary training programs are scarce, the committee could not specify the "necessary components" or identify the elements that "best facilitate" interdisciplinary training. However, after reviewing existing programs and consulting with experts, the committee identified approaches likely to be successful in providing direction for interdisciplinary endeavors at various career stages. This report also includes interviews, training programs, and workshop agendas used.