Download or read book Testing Big Data in a Big Crisis written by Luca Barbaglia and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the COVID-19 pandemic, economists have struggled to obtain reliable economic predictions, with standard models becoming outdated and their forecasting performance deteriorating rapidly. This paper presents two novelties that could be adopted by forecasting institutions in unconventional times. The first innovation is the construction of an extensive data set for macroeconomic forecasting in Europe. We collect more than a thousand time series from conventional and unconventional sources, complementing traditional macroeconomic variables with timely big data indicators and assessing their added value at nowcasting. The second novelty consists of a methodology to merge an enormous amount of non-encompassing data with a large battery of classical and more sophisticated forecasting methods in a seamlessly dynamic Bayesian framework. Specifically, we introduce an innovative "selection prior" that is used not as a way to influence model outcomes, but as a selecting device among competing models. By applying this methodology to the COVID-19 crisis, we show which variables are good predictors for nowcasting Gross Domestic Product and draw lessons for dealing with possible future crises.

Download or read book Big Crisis Data written by Carlos Castillo and published by Cambridge University Press. This book was released on 2016-07-04 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social media is invaluable during crises like natural disasters, but difficult to analyze. This book shows how computer science can help.

Download or read book Optimization and Control for Systems in the Big Data Era written by Tsan-Ming Choi and published by Springer. This book was released on 2017-05-04 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This “big data” provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Download or read book Big Data written by Hai Jin and published by Springer Nature. This book was released on 2019-11-27 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th CCF Conference on Big Data, BigData 2019, held in Wuhan, China, in October 2019. The 30 full papers presented in this volume were carefully reviewed and selected from 324 submissions. They were organized in topical sections as follows: big data modelling and methodology; big data support and architecture; big data processing; big data analysis; and big data application.

Download or read book On the Inaccuracies of Economic Observations written by Peter A.G. van Bergeijk and published by Edward Elgar Publishing. This book was released on 2024-06-05 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This informative book reveals the pervasive nature of large inaccuracies in economic statistics. Drawing on numerous real-world examples including case studies from advanced and developing countries, Peter van Bergeijk presents profound insights into how downplaying these errors undermines the scientific rigour of economic analysis and outlines how to manage uncertainty in economic analysis moving forward.

Download or read book Principal Component Analysis and Randomness Test for Big Data Analysis written by Mieko Tanaka-Yamawaki and published by Springer Nature. This book was released on 2023-05-23 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the novel approach of analyzing large-sized rectangular-shaped numerical data (so-called big data). The essence of this approach is to grasp the "meaning" of the data instantly, without getting into the details of individual data. Unlike conventional approaches of principal component analysis, randomness tests, and visualization methods, the authors' approach has the benefits of universality and simplicity of data analysis, regardless of data types, structures, or specific field of science. First, mathematical preparation is described. The RMT-PCA and the RMT-test utilize the cross-correlation matrix of time series, C = XXT, where X represents a rectangular matrix of N rows and L columns and XT represents the transverse matrix of X. Because C is symmetric, namely, C = CT, it can be converted to a diagonal matrix of eigenvalues by a similarity transformation SCS-1 = SCST using an orthogonal matrix S. When N is significantly large, the histogram of the eigenvalue distribution can be compared to the theoretical formula derived in the context of the random matrix theory (RMT, in abbreviation). Then the RMT-PCA applied to high-frequency stock prices in Japanese and American markets is dealt with. This approach proves its effectiveness in extracting "trendy" business sectors of the financial market over the prescribed time scale. In this case, X consists of N stock- prices of length L, and the correlation matrix C is an N by N square matrix, whose element at the i-th row and j-th column is the inner product of the price time series of the length L of the i-th stock and the j-th stock of the equal length L. Next, the RMT-test is applied to measure randomness of various random number generators, including algorithmically generated random numbers and physically generated random numbers. The book concludes by demonstrating two applications of the RMT-test: (1) a comparison of hash functions, and (2) stock prediction by means of randomness, including a new index of off-randomness related to market decline.

Download or read book Intelligent Methods and Big Data in Industrial Applications written by Robert Bembenik and published by Springer. This book was released on 2018-05-18 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: The inspiration for this book came from the Industrial Session of the ISMIS 2017 Conference in Warsaw. It covers numerous applications of intelligent technologies in various branches of the industry. Intelligent computational methods and big data foster innovation and enable the industry to overcome technological limitations and explore the new frontiers. Therefore it is necessary for scientists and practitioners to cooperate and inspire each other, and use the latest research findings to create new designs and products. As such, the contributions cover solutions to the problems experienced by practitioners in the areas of artificial intelligence, complex systems, data mining, medical applications and bioinformatics, as well as multimedia- and text processing. Further, the book shows new directions for cooperation between science and industry and facilitates efficient transfer of knowledge in the area of intelligent information systems.

Download or read book Macroeconomic Forecasting in the Era of Big Data written by Peter Fuleky and published by Springer Nature. This book was released on 2019-11-28 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

Download or read book Big Data Surveillance and Crisis Management written by Kees Boersma and published by Routledge. This book was released on 2017-08-14 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data, surveillance, crisis management. Three largely different and richly researched fields, however, the interplay amongst these three domains is rarely addressed. Through unique international case studies this book examines the links between these three fields. Considering crisis management as an 'umbrella term' that covers a number of crises and ways of managing them, this book explores the collection of ‘big data’ by governmental crisis organisations, as well as the unintended consequences of using such data. In particular, through the lens of surveillance, the contributions investigate how the use and abuse of big data can easily lead to monitoring and controlling the behaviour of people affected by crises. Readers will understand that big data in crisis management must be examined as a political process, involving questions of power and transparency. A highly topical volume, Big Data, Surveillance and Crisis Management will appeal to postgraduate students and postdoctoral researchers interested in fields including Sociology and Surveillance Studies, Disaster and Crisis Management, Media Studies, Governmentality, Organisation Theory and Information Society Studies.

Download or read book eBook Business Research Methods 5e written by Boris Blumberg and published by McGraw Hill. This book was released on 2024-06-13 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a one stop guide to all your research methods needs. It is tailored specifically towards business and management courses, and central to this edition is the balanced coverage of qualitative and quantitative methods to clearly and concisely lead students through the research process, whatever their project may be. Now in its much anticipated fifth edition, Business Research Methods has been revised and updated to reflect all the latest trends in research methodology. The integration of statistical issues, as well as coverage of web-based surveys, qualitative interviews, big data, and content analysis of social media, aims to support the current student experience. A Running Case Study charts the progression of two student research projects - one qualitative and one quantitative - and shows how the content of each chapter can be used to develop their projects. Thought provoking questions are included to help students consider the issues and decisions involved, and how these might be applied to their own project. Deeper Insight into Research Methods boxes delve further into particular research issues, offering a detailed description to increase understanding of these areas, whilst Real Life examples put research methods into context, by showing how they have been applied in real world situations. New pedagogy features include: Research in Practice boxes provide an insight into situations and research decisions that students may encounter in real life projects. They contain hints, tips and sometimes questions to help think through a project. Theory Explained highlights key theories and demonstrates how these can be applied in practical research examples. Statistics in Action provides practical alternatives to qualitative research methods and gives examples of how statistical data can be presented, analyzed and interpreted to improve students data insights skills. The Online Learning Centre contains a vast amount of extra resources to support lecturers and student, including power points, instructor manuals, and a question bank. New to this edition are short case studies with teaching notes covering current topics and key theories, and worked examples and videos with associated questions for further practical exercises and real world examples. Boris F. Blumberg is Senior Lecturer and Executive Director of UMIO, the postgraduate unit at the Maastricht University School of Business and Economics, the Netherlands. Boris has supervised hundreds of dissertations and teaches courses in strategic management, entrepreneurship and innovation. His research focuses mainly on entrepreneurship, networks and methodology. Claire MacRae is Senior Lecturer in Public Policy at the Centre for Public Policy, University of Glasgow. Claire has taught courses on research methods for undergraduate, masters and Professional Doctorate students. Her research focuses mainly on policymaking, risk and resilience, and the impact of policy design and implementation on society.

Download or read book Handbook of Computational Social Science for Policy written by Eleonora Bertoni and published by Springer Nature. This book was released on 2023-01-23 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access handbook describes foundational issues, methodological approaches and examples on how to analyse and model data using Computational Social Science (CSS) for policy support. Up to now, CSS studies have mostly developed on a small, proof-of concept, scale that prevented from unleashing its potential to provide systematic impact to the policy cycle, as well as from improving the understanding of societal problems to the definition, assessment, evaluation, and monitoring of policies. The aim of this handbook is to fill this gap by exploring ways to analyse and model data for policy support, and to advocate the adoption of CSS solutions for policy by raising awareness of existing implementations of CSS in policy-relevant fields. To this end, the book explores applications of computational methods and approaches like big data, machine learning, statistical learning, sentiment analysis, text mining, systems modelling, and network analysis to different problems in the social sciences. The book is structured into three Parts: the first chapters on foundational issues open with an exposition and description of key policymaking areas where CSS can provide insights and information. In detail, the chapters cover public policy, governance, data justice and other ethical issues. Part two consists of chapters on methodological aspects dealing with issues such as the modelling of complexity, natural language processing, validity and lack of data, and innovation in official statistics. Finally, Part three describes the application of computational methods, challenges and opportunities in various social science areas, including economics, sociology, demography, migration, climate change, epidemiology, geography, and disaster management. The target audience of the book spans from the scientific community engaged in CSS research to policymakers interested in evidence-informed policy interventions, but also includes private companies holding data that can be used to study social sciences and are interested in achieving a policy impact.

Download or read book Cyberdefense written by Marcus Matthias Keupp and published by Springer Nature. This book was released on 2023-09-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book analyzes cyberdefense from a novel and interdisciplinary perspective, offering solutions for problems that have long impeded a more efficient defense. It explains why cyberdefense organized and performed by humans is too slow, too cumbersome, and too ineffective. Combining the analytical capabilities of experts in operations research and management, international security studies, economics, risk analysis, and defense management, the volume addresses these problems of current cyberdefense. The authors present suggestions for the next generation of cyberdefense, explaining why the future defense must focus on speeding up responses, why a single response may not be enough, and why effectiveness requires foresight. This makes the book a must-read for scholars, researchers, intelligence analysts, homeland security staff, and professionals who are interested in learning more about the issues of current cyberdefense, as well as solutions for the next generation of cyberdefense.

Download or read book Big Data BigData 2023 written by Shunli Zhang and published by Springer Nature. This book was released on 2023-09-22 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference, BigData 2023, Held as Part of the Services Conference Federation, SCF 2023, Honolulu, HI, USA, during September 23–26, 2023. The 14 full papers presented together with 2 short papers were carefully reviewed and selected from 27 submissions. The conference focuses on ​research track and application track.

Download or read book The Rise of Artificial Intelligence and Big Data in Pandemic Society written by Kazuhiko Shibuya and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a study of the COVID-19 pandemic using computational social scientific analysis that draws from, and employs, statistics and simulations. Combining approaches in crisis management, risk assessment and mathematical modelling, the work also draws from the philosophy of sacrifice and futurology. It makes an original contribution to the important issue of the stability of society by highlighting two significant factors: the COVID-19 crisis as a catalyst for change and the rise of AI and Big Data in managing society. It also emphasizes the nature and importance of sacrifices and the role of politics in the distribution of sacrifices. The book considers the treatment of AI and Big Data and their use to both "good" and "bad" ends, exposing the inevitability of these tools being used. Relevant to both policymakers and social scientists interested in the influence of AI and Big Data on the structure of society, the book re-evaluates the ways we think of lifestyles, economic systems and the balance of power in tandem with digital transformation.

Download or read book Big Data Analytics and Artificial Intelligence Against COVID 19 Innovation Vision and Approach written by Aboul-Ella Hassanien and published by Springer Nature. This book was released on 2020-10-12 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.

Download or read book Principles and Practice of Big Data written by Jules J. Berman and published by Academic Press. This book was released on 2018-07-23 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition updates and expands on the first edition, bringing a set of techniques and algorithms that are tailored to Big Data projects. The book stresses the point that most data analyses conducted on large, complex data sets can be achieved without the use of specialized suites of software (e.g., Hadoop), and without expensive hardware (e.g., supercomputers). The core of every algorithm described in the book can be implemented in a few lines of code using just about any popular programming language (Python snippets are provided). Through the use of new multiple examples, this edition demonstrates that if we understand our data, and if we know how to ask the right questions, we can learn a great deal from large and complex data collections. The book will assist students and professionals from all scientific backgrounds who are interested in stepping outside the traditional boundaries of their chosen academic disciplines. - Presents new methodologies that are widely applicable to just about any project involving large and complex datasets - Offers readers informative new case studies across a range scientific and engineering disciplines - Provides insights into semantics, identification, de-identification, vulnerabilities and regulatory/legal issues - Utilizes a combination of pseudocode and very short snippets of Python code to show readers how they may develop their own projects without downloading or learning new software

Download or read book Applied Big Data Analytics and Its Role in COVID 19 Research written by Zhao, Peng and published by IGI Global. This book was released on 2022-04-29 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: There has been a multitude of studies focused on the COVID-19 pandemic across fields and disciplines as all sectors of life have had to adjust the way things are done and adapt to the constantly shifting environment. These studies are crucial as they provide support and perspectives on how things are changing and what needs to be done to stay afloat. Connecting COVID-19-related studies and big data analytics is crucial for the advancement of industrial applications and research areas. Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics. Featuring coverage on a broad range of big data technologies such as data gathering, artificial intelligence, smart diagnostics, and mining mobility, this publication provides concrete examples and cases of usage of data-driven projects in COVID-19 research. This reference work is a vital resource for data scientists, technical managers, researchers, scholars, practitioners, academicians, instructors, and students.