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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 456 | Sprache: Englisch | Produktart: Bücher.

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Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Taschenbuch. Zustand: Neu. Neuware -Examine the synergistic possibilities of combining blockchain, IoT, and AI technologies in supply chain management. This book will address the difficulties and possibilities of integrating these technologies and offer helpful implementation advice.The current state of supply chain management involves several challenges, including lack of transparency, limited visibility into product movements, inefficient inventory management, and difficulty in tracking and tracing products. Blockchain, IoT, and AI can potentially address some of these challenges and improve supply chain management.To help illustrate this, case studies and actual instances of businesses implementing or experimenting with blockchain, IoT, and AI technology in their supply chains are included in the book. Yoüll review helpful advice on implementation and highlight successful deployments, lessons learned, and the impact of these technologies on supply chain visibility, agility, sustainability, and customer experience. This book further elaborates the fundamental concepts of AI and ML algorithms and demonstrates how AI can process enormous volumes of supply chain data to produce actionable insights, improve inventory control, forecast demand, and increase forecasting precision.This collective work will serve as a comprehensive guide for supply chain professionals, researchers, and technology enthusiasts interested in understanding the potential of blockchain, IoT, and AI technologies in revolutionizing supply chain management practices.What You Will LearnDiscuss the evolving landscape of technology, potential advancements, and how Blockchain, IoT, and AI can shape the future of supply chainsGain Insight into upcoming developments and prepare for changing dynamics of the industryUnderstand intricate details of blockchain, IoT, and AI Technologies in real-life scenariosWho Is This Book ForIndustry Professionals working in the domain of supply chain management who would be interested in understanding how these technologies can enhance efficiency, transparency, and optimization in their supply chains.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 568 pp. Englisch.

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Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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Buch. Zustand: Neu. Neuware - Offering a thorough exploration of the symbiotic relationship between data engineering and modern marketing strategies, Data Engineering for Data-Driven Marketing uses a strategic lens to delve into methodologies of collecting, transforming, and storing diverse data sources.

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Taschenbuch. Zustand: Neu. Neuware -orientedapplications,sothatresearchersworkinginthose eldscouldlearnofnew methodstohelpthemtackletheirproblems. Ontheotherhand,wealsohopethat the CI community will nd this book useful by discovering a new and intriguing area of applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 460 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The purpose of this book is to provide an overview of powerful state-of-the-art methodologies that are currently utilized for biomedicine and/ or bioinformatics-oriented applications, so that researchers working in those fields could learn of new methods to help them tackle their problems. On the other hand, the CI community will find this book useful by discovering a new and intriguing area of applications. In order to help fill the gap between the scientists on both sides of this spectrum, the editors have solicited contributions from researchers actively applying computational intelligence techniques to important problems in biomedicine and bioinformatics. The book is divided into three major parts. Part I, Techniques and Methodologies, contains a selection of contributions that provide a review of several theories and methods that could be (or to some extent already are) of great benefit to practitioners in the fields of biomedicine and bioinformatics dealing with problems of data exploration and mining, search-space exploration, optimization, etc. Part II of this book, Computational Intelligence in Biomedicine, contains a collection of contributions on current state-of-the-art biomedical applications of CI in clinical oncology, neurology, pathology, and proteomics. Part II, Computational Intelligence in Biomedicine, contains a collection of chapters treating on applications of CI methods to solving bioinformatics problems including protein structure and function prediction, protein folding, finding ribosomal RNA genes, and microarray analysis.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The purpose of this book is to provide an overview of powerful state-of-the-art methodologies that are currently utilized for biomedicine and/ or bioinformatics-oriented applications, so that researchers working in those fields could learn of new methods to help them tackle their problems. On the other hand, the CI community will find this book useful by discovering a new and intriguing area of applications. In order to help fill the gap between the scientists on both sides of this spectrum, the editors have solicited contributions from researchers actively applying computational intelligence techniques to important problems in biomedicine and bioinformatics. The book is divided into three major parts. Part I, Techniques and Methodologies, contains a selection of contributions that provide a review of several theories and methods that could be (or to some extent already are) of great benefit to practitioners in the fields of biomedicine and bioinformatics dealing with problems of data exploration and mining, search-space exploration, optimization, etc. Part II of this book, Computational Intelligence in Biomedicine, contains a collection of contributions on current state-of-the-art biomedical applications of CI in clinical oncology, neurology, pathology, and proteomics. Part II, Computational Intelligence in Biomedicine, contains a collection of chapters treating on applications of CI methods to solving bioinformatics problems including protein structure and function prediction, protein folding, finding ribosomal RNA genes, and microarray analysis.

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Hardcover. Zustand: Brand New. 292 pages. 9.01x5.98x9.00 inches. In Stock.

Zustand: New. M. G. Sumithra, PhD, is a professor at Anna University Chennai, India. With 25 years of teaching experience, she has published more than 70 technical papers in refereed journals, 3 book chapters, and 130 research papers in national and international confere.

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Buch. Zustand: Neu. Neuware -Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 456 pp. Englisch.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.

Buch. Zustand: Neu. Neuware - BRAIN-COMPUTER INTERFACEIt covers all the research prospects and recent advancements in the brain-computer interface using deep learning.The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding. Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real world, however, some problems remain to be solved.Research focusing on deep learning is anticipated to bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN).AudienceResearchers and industrialists working in brain-computer interface, deep learning, machine learning, medical image processing, data scientists and analysts, machine learning engineers, electrical engineering, and information technologists.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.