AI and Big Data’s Potential for Disruptive Innovation
AI and Big Data’s Potential for Disruptive Innovation

Author: Strydom, Moses

Publisher: IGI Global

Published: 2019-09-27

Total Pages: 427

ISBN-13: 1522596895

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Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.

AI and Big Data
AI and Big Data

Author: Mark Findlay

Publisher: Edward Elgar Publishing

Published: 2023-09-06

Total Pages: 155

ISBN-13: 1802209522

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This provocative and timely book identifies and disrupts the conventional regulation and governance discourses concerning AI and big data. It suggests that, instead of being used as tools for exclusionist commercial markets, AI and big data can be employed in governing digital transformation for social good.

Digital Technologies, Ethics, and Decentralization in the Digital Era
Digital Technologies, Ethics, and Decentralization in the Digital Era

Author: Verma, Balraj

Publisher: IGI Global

Published: 2024-02-08

Total Pages: 383

ISBN-13:

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Digital disintermediation, or the elimination of “middle-men” in a traditional market setting, has had profound effects on global economies. The rise of peer-to-peer networks and decentralized marketplaces has also led to some market destabilization, and the discussion on data sovereignty and privacy challenges raises concerns surrounding business in the digital age. Digital Technologies, Ethics, and Decentralization in the Digital Era is a research-based book which boldly tackles a myriad of ethical dilemmas, including bias, privacy, and inclusivity, and advocates for a future where digital access is fair and equitable. Academic scholars and industry professionals will embark on an enlightening journey through the digital revolution's transformative power. This book delves into the very core of digital technologies, shedding light on their role as catalysts for decentralization and de-globalization. Readers will gain invaluable insights into how these technologies disrupt established systems, paving the way for innovative alternatives. The exploration of blockchain and decentralized finance shines a light on how individuals and communities can harness technology to empower themselves, reshaping the dynamics of power in an increasingly interconnected world.

Vegetation Dynamics and Crop Stress
Vegetation Dynamics and Crop Stress

Author: Dipanwita Dutta

Publisher: Elsevier

Published: 2024-07-10

Total Pages: 317

ISBN-13: 0323956173

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Vegetation Dynamics and Crop Stress: An Earth-Observation Perspective focuses on vegetation dynamics and crop stress at both the regional and country levels by using earth observation (EO) data sets. The book uniquely provides a better understanding of natural vegetation and crop failure through geo-spatial technologies. This book covers biophysical control of vegetation, deforestation, desertification, drought, and crop-water efficiency, as well as the application of satellite-derived measures from optical, thermal, and microwave domains for monitoring and modeling crop condition, agricultural drought, and crop health in contrasting monsoon/weather episodes. - Provides a quantitative analysis of vegetation and crop stress based on EO datasets - Offers descriptions of the spatially explicit vegetation and crop model development, implementation, and validation - Covers the impact of soil-water stress on crop performance and vegetation response to climate change using earth observation techniques

Research Anthology on Artificial Neural Network Applications
Research Anthology on Artificial Neural Network Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2021-07-16

Total Pages: 1575

ISBN-13: 1668424096

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Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.

Deep Learning for Medical Decision Support Systems
Deep Learning for Medical Decision Support Systems

Author: Utku Kose

Publisher: Springer Nature

Published: 2020-06-17

Total Pages: 185

ISBN-13: 981156325X

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This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.

AI Techniques for Reliability Prediction for Electronic Components
AI Techniques for Reliability Prediction for Electronic Components

Author: Bhargava, Cherry

Publisher: IGI Global

Published: 2019-12-06

Total Pages: 330

ISBN-13: 1799814661

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In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.

Next-Generation Applications and Implementations of Gamification Systems
Next-Generation Applications and Implementations of Gamification Systems

Author: Portela, Filipe

Publisher: IGI Global

Published: 2021-10-22

Total Pages: 281

ISBN-13: 1799880915

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Gamification is being used everywhere; despite its apparent plethora of benefits, the unbalanced use of its main mechanics can end up in catastrophic results for a company or institution. Currently, there is a lack of knowledge of what it is, leading to its unregulated and ad hoc use without any prior planning. This unbalanced use prejudices the achievement of the initial goals and impairs the user's evolution, bringing potential negative reflections. Currently, there are few specifications and modeling languages that allow the creation of a system of rules to serve as the basis for a gamification engine. Consequently, programmers implement gamification in a variety of ways, undermining any attempt at reuse and negatively affecting interoperability. Next-Generation Applications and Implementations of Gamification Systems synthesizes all the trends, best practices, methodologies, languages, and tools that are used to implement gamification. It also discusses how to put gamification in action by linking academic and informatics researchers with professionals who use gamification in their daily work to disseminate and exchange the knowledge, information, and technology provided by the international communities in the area of gamification throughout the 21st century. Covering topics such as applied and cloud gamification, chatbots, deep learning, and certifications and frameworks, this book is ideal for programmers, computer scientists, software engineers, practitioners of technological companies, managers, academicians, researchers, and students.

The Elements of Big Data Value
The Elements of Big Data Value

Author: Edward Curry

Publisher: Springer Nature

Published: 2021-08-01

Total Pages: 399

ISBN-13: 3030681769

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This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.