Author: Said Ali Hassan
Publisher: Springer Nature
ISBN: 3030870197
Category : Business & Economics
Languages : en
Pages : 475
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Book Description
This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises’ productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.
Author: Joao Alexandre Lobo Marques
Publisher: Springer Nature
ISBN: 3030619133
Category : Technology & Engineering
Languages : en
Pages : 103
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Book Description
COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.
Author: Chkoniya, Valentina
Publisher: IGI Global
ISBN: 1799869865
Category : Computers
Languages : en
Pages : 653
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Book Description
The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030697444
Category : Technology & Engineering
Languages : en
Pages : 594
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Book Description
This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309680077
Category : Education
Languages : en
Pages : 115
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Book Description
The COVID-19 pandemic has presented unprecedented challenges to the nation's K-12 education system. The rush to slow the spread of the virus led to closures of schools across the country, with little time to ensure continuity of instruction or to create a framework for deciding when and how to reopen schools. States, districts, and schools are now grappling with the complex and high-stakes questions of whether to reopen school buildings and how to operate them safely if they do reopen. These decisions need to be informed by the most up-to-date evidence about the SARS-CoV-2 virus that causes COVID-19; about the impacts of school closures on students and families; and about the complexities of operating school buildings as the pandemic persists. Reopening K-12 Schools During the COVID-19 Pandemic: Prioritizing Health, Equity, and Communities provides guidance on the reopening and operation of elementary and secondary schools for the 2020-2021 school year. The recommendations of this report are designed to help districts and schools successfully navigate the complex decisions around reopening school buildings, keeping them open, and operating them safely.
Author: Jie-Ming Qu
Publisher: Elsevier
ISBN: 0128242515
Category : Science
Languages : en
Pages : 116
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Book Description
COVID-19: The Essentials of Prevention and Treatment elaborates on the ethology, pathogenesis, epidemiology, clinical characteristics, treatment principles, rehabilitation and prevention, and prevention and control measures for COVID-19. Aimed at healthcare workers, and written to be a practical guide, six chapters cover the following aspects of COVID-19: respiratory viruses; pathogenesis; case definitions and diagnosis; treatment; prevention and disease control; and prospects for the management and research of respiratory virus infections. This book gives first-hand information on the prevention, control, diagnosis and treatment of COVID-19.COVID-19 was recognized as a pandemic in March 2020 by the World Health Organization. It is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Physicians working in China, particularly where the outbreak was first identified in Wuhan, have built up knowledge of prevention and control measures, and diagnosis and treatment of this disease. These insights are now globally relevant. The authors of this book are senior physicians specializing in respiratory diseases, pulmonary diseases and critical care medicine, and are all clinical and scientific research experts working in China, with particular experience in Wuhan. - Describes the prevention, control, diagnosis and treatment of COVID-19 - Offers practical guidance to healthcare professionals for COVID-19 - Gives clinical insights in a question and answer format - Details first-hand experience in Chinese cities during the initial outbreak - Presents insights that healthcare professionals need to prevent, diagnose, and treat COVID-19
Author: S. Sumathi
Publisher: Nova Science Publishers
ISBN: 9781685072070
Category : Computers
Languages : en
Pages : 367
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Book Description
"Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms: A Practical Approach Using Python describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalize these strategies. The book will benefit information professionals, programmers, consultants, professors, students, and industry experts who seek a variety of real-world illustrations with an implementation based on machine learning algorithms"--
Author: Scott L Greer
Publisher: University of Michigan Press
ISBN: 0472902466
Category : Political Science
Languages : en
Pages : 416
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Book Description
COVID-19 is the most significant global crisis of any of our lifetimes. The numbers have been stupefying, whether of infection and mortality, the scale of public health measures, or the economic consequences of shutdown. Coronavirus Politics identifies key threads in the global comparative discussion that continue to shed light on COVID-19 and shape debates about what it means for scholarship in health and comparative politics. Editors Scott L. Greer, Elizabeth J. King, Elize Massard da Fonseca, and André Peralta-Santos bring together over 30 authors versed in politics and the health issues in order to understand the health policy decisions, the public health interventions, the social policy decisions, their interactions, and the reasons. The book’s coverage is global, with a wide range of key and exemplary countries, and contains a mixture of comparative, thematic, and templated country studies. All go beyond reporting and monitoring to develop explanations that draw on the authors' expertise while engaging in structured conversations across the book.
Author: Cass R. Sunstein
Publisher: NYU Press
ISBN: 1479808482
Category : Social Science
Languages : en
Pages : 175
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Book Description
Best-selling author Cass R. Sunstein examines how to avoid worst-case scenarios The world is increasingly confronted with new challenges related to climate change, globalization, disease, and technology. Governments are faced with having to decide how much risk is worth taking, how much destruction and death can be tolerated, and how much money should be invested in the hopes of avoiding catastrophe. Lacking full information, should decision-makers focus on avoiding the most catastrophic outcomes? When should extreme measures be taken to prevent as much destruction as possible? Averting Catastrophe explores how governments ought to make decisions in times of imminent disaster. Cass R. Sunstein argues that using the “maximin rule,” which calls for choosing the approach that eliminates the worst of the worst-case scenarios, may be necessary when public officials lack important information, and when the worst-case scenario is too disastrous to contemplate. He underscores this argument by emphasizing the reality of “Knightian uncertainty,” found in circumstances in which it is not possible to assign probabilities to various outcomes. Sunstein brings foundational issues in decision theory in close contact with real problems in regulation, law, and daily life, and considers other potential future risks. At once an approachable introduction to decision-theory and a provocative argument for how governments ought to handle risk, Averting Catastrophe offers a definitive path forward in a world rife with uncertainty.
Author: National Academies Of Sciences Engineeri
Publisher: National Academies Press
ISBN: 9780309268370
Category : Political Science
Languages : en
Pages :
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Book Description
The spring of 2020 marked a change in how almost everyone conducted their personal and professional lives, both within science, technology, engineering, mathematics, and medicine (STEMM) and beyond. The COVID-19 pandemic disrupted global scientific conferences and individual laboratories and required people to find space in their homes from which to work. It blurred the boundaries between work and non-work, infusing ambiguity into everyday activities. While adaptations that allowed people to connect became more common, the evidence available at the end of 2020 suggests that the disruptions caused by the COVID-19 pandemic endangered the engagement, experience, and retention of women in academic STEMM, and may roll back some of the achievement gains made by women in the academy to date. Impact of COVID-19 on the Careers of Women in Academic STEMM identifies, names, and documents how the COVID-19 pandemic disrupted the careers of women in academic STEMM during the initial 9-month period since March 2020 and considers how these disruptions - both positive and negative - might shape future progress for women. This publication builds on the 2020 report Promising Practices for Addressing the Underrepresentation of Women in Science, Engineering, and Medicine to develop a comprehensive understanding of the nuanced ways these disruptions have manifested. Impact of COVID-19 on the Careers of Women in Academic STEMM will inform the academic community as it emerges from the pandemic to mitigate any long-term negative consequences for the continued advancement of women in the academic STEMM workforce and build on the adaptations and opportunities that have emerged.
