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Deep Learning: Convergence to Big Data Analytics
This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classif...
Applied Artificial Intelligence
This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems. Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample ...
Hybrid Intelligent Approaches for Smart Energy
HYBRID INTELLIGENT APPROACHES FOR SMART ENERGY Green technologies and cleaner energy are two of the most important topics facing our world today, and the march toward efficient energy systems, smart cities, and other green technologies, has been, and continues to be, a long and intricate one. Books like this one keep the veteran engineer and student, alike, up to date on current trends in the technology and offer a reference for the industry for its practical applications. Energy optimization and consumption prediction are necessary to prevent energy waste, schedule energy usage, and reduce the cost. Today, smart computing technologies are slowly replacing the traditional computational metho...
Blockchain-enabled Fog and Edge Computing: Concepts, Architectures and Applications
This comprehensive book unveils the working relationship of blockchain and the fog/edge computing. The contents of the book have been designed in such a way that the reader will not only understand blockchain and fog/edge computing but will also understand their co-existence and their collaborative power to solve a range of versatile problems. The first part of the book covers fundamental concepts and the applications of blockchain-enabled fog and edge computing. These include: Internet of Things, Tactile Internet, Smart City; and E-challan in the Internet of Vehicles. The second part of the book covers security and privacy related issues of blockchain-enabled fog and edge computing. These i...
Data Analytics, Computational Statistics, and Operations Research for Engineers
With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.
Deep Learning and Parallel Computing Environment for Bioengineering Systems
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning ...
Advancements in Business for Integrating Diversity, and Sustainability
This book is the collection of selected articles that appeared at the First International Analytics Conference 2023 held in Hyderabad in virtual mode on February 2nd the 3rd 2023. In the fast-paced, ever-changing world of business, the pursuit of diversity and sustainability has emerged as a dynamic catalyst for progress. This illuminating volume takes you on a journey through the evolving realm of business, where innovative approaches are redefining corporate strategies and values.
Digitalisierung der Arbeitswelten
Diese Open Access Publikation bündelt Ergebnisse aus der ersten Förderphase des interdisziplinären DFG-Schwerpunktprogramms 2267 „Digitalisierung der Arbeitswelten“. Digitalisierung verändert Arbeit mit vielfältigen Konsequenzen für Arbeit(smarkt) und Qualifizierung. Wie dramatisch und grundsätzlich diese Veränderungen sind, wird seit Jahren kontrovers diskutiert und anwendungsbezogen erforscht. Das Schwerpunktprogramm nimmt die Veränderung der Arbeitsgesellschaft als Ganzes in den Blick – Geschichts-, Sozial- und Wirtschaftswissenschaften analysieren die vielschichtigen und widersprüchlichen Dynamiken als eine systemische Transformation. Leitend ist dabei die These von drei Bewegungsdynamiken: die Durchdringung (z.B. von digitalen Arbeitsprozessen), die Verfügbarmachung (z.B. von Daten über einzelne Arbeitshandlungen) und die Verselbständigung (z.B. von datengetriebenen Wertschöpfungsketten). Methodische Reflexionen zu Erfassbarkeit der Transformation runden den Band ab.
