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Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering
A Book

by Valentina E Balas,Vijender Kumar Solanki,Raghvendra Kumar Mishra,Manju Khari

  • Publisher : Academic Press
  • Release : 2019-11-15
  • Pages : 300
  • ISBN : 9780128183182
  • Language : En, Es, Fr & De
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Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress in alignment with the latest technologies of Big Data and the Internet of Things. The book includes the most current research developments in the field of biomedical engineering applications based on IoT and Big data, including various real-time and offline medical applications that directly or indirectly rely on medical and information technology. The book also includes case studies in the field of medical science, biomedical engineering, computer science, information security, interdisciplinary tools, along with the latest tools and technologies used. Ninety percent of data currently available in the world has been generated in past couple of years, and the volume of data is rapidly increasing day by day. The reason for this growth is the increase in communication via electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, and other aspects of the Internet of Things. This data may come in a continuous flow, may be from various sources, and likely impacts technical systems in real time, which may lead to a problem of managing and processing data using traditional methods. This wide variety of data flows, sources, and types may also overwhelm your systems. Handbook of Data Science Approaches for Biomedical Engineering showcases the most cutting-edge information management tools and technologies to deal with the large volume of real-time data. Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in big data and Internet of Things Discusses big data applications for healthcare management such as predictive analytics andforecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, big data in IoT, and data analytics with machine learning tools

Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering
A Book

by Valentina E. Balas,Vijender Kumar Solanki,Raghvendra Kumar,Manju Khari

  • Publisher : Academic Press
  • Release : 2019-11-13
  • Pages : 318
  • ISBN : 0128183195
  • Language : En, Es, Fr & De
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Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

Impact of AI and Data Science in Response to Coronavirus Pandemic

Impact of AI and Data Science in Response to Coronavirus Pandemic
A Book

by Sushruta Mishra,Pradeep Kumar Mallick,Hrudaya Kumar Tripathy,Gyoo-Soo Chae,Bhabani Shankar Prasad Mishra

  • Publisher : Springer Nature
  • Release : 2021-07-22
  • Pages : 324
  • ISBN : 981162786X
  • Language : En, Es, Fr & De
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The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies. It provides a unique opportunity to present the work on state-of-the-art of modern artificial intelligence tools and technologies to track and forecast COVID-19 cases. It indicates insights and viewpoints from scholars regarding risk and resilience analytics for policy making and operations of large-scale systems on this epidemic. A snapshot of the latest architectures, frameworks in machine learning and data science are also highlighted to gather and aggregate data records related to COVID-19 and to diagnose the virus. It delivers significant research outcomes and inspiring new real-world applications with respect to feasible AI based solutions in COVID-19 outbreak. In addition, it discusses strong preventive measures to control such pandemic.

Data Deduplication Approaches

Data Deduplication Approaches
Concepts, Strategies, and Challenges

by Tin Thein Thwel,G. R. Sinha

  • Publisher : Academic Press
  • Release : 2020-11-25
  • Pages : 404
  • ISBN : 0128236337
  • Language : En, Es, Fr & De
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In the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage. Duplicated data or redundant data is a main challenge in the field of data science research. Data Deduplication Approaches: Concepts, Strategies, and Challenges shows readers the various methods that can be used to eliminate multiple copies of the same files as well as duplicated segments or chunks of data within the associated files. Due to ever-increasing data duplication, its deduplication has become an especially useful field of research for storage environments, in particular persistent data storage. Data Deduplication Approaches provides readers with an overview of the concepts and background of data deduplication approaches, then proceeds to demonstrate in technical detail the strategies and challenges of real-time implementations of handling big data, data science, data backup, and recovery. The book also includes future research directions, case studies, and real-world applications of data deduplication, focusing on reduced storage, backup, recovery, and reliability. Includes data deduplication methods for a wide variety of applications Includes concepts and implementation strategies that will help the reader to use the suggested methods Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable methods for their applications Focuses on reduced storage, backup, recovery, and reliability, which are the most important aspects of implementing data deduplication approaches Includes case studies

Efficient Data Handling for Massive Internet of Medical Things

Efficient Data Handling for Massive Internet of Medical Things
Healthcare Data Analytics

by Chinmay Chakraborty

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 129
  • ISBN : 3030666336
  • Language : En, Es, Fr & De
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Internet of Things for Healthcare Technologies

Internet of Things for Healthcare Technologies
A Book

by Chinmay Chakraborty,Amit Banerjee,Maheshkumar H. Kolekar,Lalit Garg,Basabi Chakraborty

  • Publisher : Springer Nature
  • Release : 2020-06-08
  • Pages : 324
  • ISBN : 9811541124
  • Language : En, Es, Fr & De
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This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical, methodological, well-established, and validated empirical work in these fields. Artificial intelligence and IoT are set to revolutionize all industries, but perhaps none so much as health care. Both biomedicine and machine learning applications are capable of analyzing data stored in national health databases in order to identify potential health problems, complications and effective protocols, and a range of wearable devices for biomedical and healthcare applications far beyond tracking individuals’ steps each day has emerged. These prosthetic technologies have made significant strides in recent decades with the advances in materials and development. As a result, more flexible, more mobile chip-enabled prosthetics or other robotic devices are on the horizon. For example, IoT-enabled wireless ECG sensors that reduce healthcare cost, and lead to better quality of life for cardiac patients. This book focuses on three current trends that are likely to have a significant impact on future healthcare: Advanced Medical Imaging and Signal Processing; Biomedical Sensors; and Biotechnological and Healthcare Advances. It also presents new methods of evaluating medical data, and diagnosing diseases in order to improve general quality of life.

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics
A Book

by Pradeep N,Sandeep Kautish,Sheng-Lung Peng

  • Publisher : Academic Press
  • Release : 2021-06-25
  • Pages : 372
  • ISBN : 0128220449
  • Language : En, Es, Fr & De
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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Web Information Systems Engineering – WISE 2020

Web Information Systems Engineering – WISE 2020
21st International Conference, Amsterdam, The Netherlands, October 20–24, 2020, Proceedings, Part II

by Zhisheng Huang,Wouter Beek,Hua Wang,Rui Zhou,Yanchun Zhang

  • Publisher : Springer Nature
  • Release : 2020-10-20
  • Pages : 610
  • ISBN : 3030620085
  • Language : En, Es, Fr & De
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This book constitutes the proceedings of the 21st International Conference on Web Information Systems Engineering, WISE 2020, held in Amsterdam, The Netherlands, in October 2020. The 81 full papers presented were carefully reviewed and selected from 190 submissions. The papers are organized in the following topical sections: Part I: network embedding; graph neural network; social network; graph query; knowledge graph and entity linkage; spatial temporal data analysis; and service computing and cloud computing Part II: information extraction; text mining; security and privacy; recommender system; database system and workflow; and data mining and applications

Green Computing and Predictive Analytics for Healthcare

Green Computing and Predictive Analytics for Healthcare
A Book

by Sourav Banerjee,Chinmay Chakraborty,Kousik Dasgupta

  • Publisher : CRC Press
  • Release : 2020-12-10
  • Pages : 190
  • ISBN : 1000223949
  • Language : En, Es, Fr & De
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Green Computing and Predictive Analytics for Healthcare excavates the rudimentary concepts of Green Computing, Big Data and the Internet of Things along with the latest research development in the domain of healthcare. It also covers various applications and case studies in the field of computer science with state-of-the-art tools and technologies. The rapid growth of the population is a challenging issue in maintaining and monitoring various experiences of quality of service in healthcare. The coherent usage of these limited resources in connection with optimum energy consumption has been becoming more important. The major healthcare nodes are gradually becoming Internet of Things-enabled, and sensors, work data and the involvement of networking are creating smart campuses and smart houses. The book includes chapters on the Internet of Things and Big Data technologies. Features: Biomedical data monitoring under the Internet of Things Environment data sensing and analyzing Big data analytics and clustering Machine learning techniques for sudden cardiac death prediction Robust brain tissue segmentation Energy-efficient and green Internet of Things for healthcare applications Blockchain technology for the healthcare Internet of Things Advanced healthcare for domestic medical tourism system Edge computing for data analytics This book on Green Computing and Predictive Analytics for Healthcare aims to promote and facilitate the exchange of research knowledge and findings across different disciplines on the design and investigation of healthcare data analytics. It can also be used as a textbook for a master’s course in biomedical engineering. This book will also present new methods for medical data evaluation and the diagnosis of different diseases to improve quality-of-life in general and for better integration of Internet of Things into society. Dr. Sourav Banerjee is an Assistant Professor at the Department of Computer Science and Engineering of Kalyani Government Engineering College, Kalyani, West Bengal, India. His research interests include Big Data, Cloud Computing, Distributed Computing and Mobile Communications. Dr. Chinmay Chakraborty is an Assistant Professor at the Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. His main research interests include the Internet of Medical Things, WBAN, Wireless Networks, Telemedicine, m-Health/e-Health and Medical Imaging. Dr. Kousik Dasgupta is an Assistant Professor at the Department of Computer Science and Engineering, Kalyani Government Engineering College, India. His research interests include Computer Vision, AI/ML, Cloud Computing, Big Data and Security.

Privacy and Security Issues in Big Data

Privacy and Security Issues in Big Data
An Analytical View on Business Intelligence

by Pradip Kumar Das

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 129
  • ISBN : 981161007X
  • Language : En, Es, Fr & De
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Artificial Intelligence Techniques in IoT Sensor Networks

Artificial Intelligence Techniques in IoT Sensor Networks
A Book

by Mohamed Elhoseny,K Shankar,Mohamed Abdel-Basset

  • Publisher : CRC Press
  • Release : 2020-12-18
  • Pages : 221
  • ISBN : 1000318702
  • Language : En, Es, Fr & De
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Artificial Intelligence Techniques in IoT Sensor Networks is a technical book which can be read by researchers, academicians, students and professionals interested in artificial intelligence (AI), sensor networks and Internet of Things (IoT). This book is intended to develop a shared understanding of applications of AI techniques in the present and near term. The book maps the technical impacts of AI technologies, applications and their implications on the design of solutions for sensor networks. This text introduces researchers and aspiring academicians to the latest developments and trends in AI applications for sensor networks in a clear and well-organized manner. It is mainly useful for research scholars in sensor networks and AI techniques. In addition, professionals and practitioners working on the design of real-time applications for sensor networks may benefit directly from this book. Moreover, graduate and master’s students of any departments related to AI, IoT and sensor networks can find this book fascinating for developing expert systems or real-time applications. This book is written in a simple and easy language, discussing the fundamentals, which relieves the requirement of having early backgrounds in the field. From this expectation and experience, many libraries will be interested in owning copies of this work.

Smart Healthcare Analytics: State of the Art

Smart Healthcare Analytics: State of the Art
A Book

by Prasant Kumar Pattnaik

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 129
  • ISBN : 9811653046
  • Language : En, Es, Fr & De
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Big Data Analysis for Green Computing

Big Data Analysis for Green Computing
Concepts and Applications

by Rohit Sharma,Dilip Kumar Sharma,Dhowmya Bhatt,Binh Thai Pham

  • Publisher : CRC Press
  • Release : 2021-10-29
  • Pages : 186
  • ISBN : 1000481778
  • Language : En, Es, Fr & De
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This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics. Big Data Analysis for Green Computing: Concepts and Applications presents the latest technologies and covers the major challenges, issues, and advances of big data and data analytics in green computing. It explores basic as well as high-level concepts. It also includes the use of machine learning using big data and discusses advanced system implementation for smart cities. The book is intended for business and management educators, management researchers, doctoral scholars, university professors, policymakers, and higher academic research organizations.

Proceedings of International Conference on Sustainable Expert Systems

Proceedings of International Conference on Sustainable Expert Systems
ICSES 2020

by Subarna Shakya,Valentina Emilia Balas,Wang Haoxiang,Zubair Baig

  • Publisher : Springer Nature
  • Release : 2021-05-01
  • Pages : 715
  • ISBN : 9813343559
  • Language : En, Es, Fr & De
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This book includes papers on intelligent expert systems and sustainability applications in the areas of data science, image processing, wireless communication, risk assessment, healthcare, intelligent social network mining, and energy. The recent growth of sustainability leads to a progressively new era of computing, where its design and deployment leverages significant impact on the intelligent systems research. Moreover, the sustainability technologies can be effectively used in the progressive deployment of various network-enabled technologies like intelligent sensors, smart cities, wearable technologies, robotics, web applications and other such Internet technologies. The thrust of this book is to publish the state-of-the-art research articles that deals with the design, development, implementation and testing of the intelligent expert systems and also to provide an overview of the sustainable management of these systems.

Multimodal Biometric Systems

Multimodal Biometric Systems
Security and Applications

by Rashmi Gupta,Manju Khari

  • Publisher : CRC Press
  • Release : 2021-09-26
  • Pages : 166
  • ISBN : 1000453774
  • Language : En, Es, Fr & De
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Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput. This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding. This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.

Trends in Wireless Communication and Information Security

Trends in Wireless Communication and Information Security
Proceedings of EWCIS 2020

by Mithun Chakraborty

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 129
  • ISBN : 9813363932
  • Language : En, Es, Fr & De
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Internet of Things

Internet of Things
Cases and Studies

by Fausto Pedro García Márquez,Benjamin Lev

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 129
  • ISBN : 3030704785
  • Language : En, Es, Fr & De
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This book provides relevant theoretical frameworks and the latest empirical research findings of Operations Research/Management Science applied to Internet of Things. This book identifies and describes ways in which OR and MS have been applied and influenced the development of IoT. Examples are from smart industry; city; transportation; home and smart devices. It discusses future applications, trends, and potential benefits of this new discipline. It is written for professionals who want to improve their understanding of the strategic role of IoT at various levels of the organization, that is, IoT at the global economy level, at networks and organizations level, at teams and work groups, at information systems and, finally, IoT at the level of individuals, as players in the networked environments. .

Internet of Things and Secure Smart Environments

Internet of Things and Secure Smart Environments
Successes and Pitfalls

by Uttam Ghosh,Danda B Rawat,Raja Datta,Al-Sakib Khan Pathan

  • Publisher : CRC Press
  • Release : 2020-11-05
  • Pages : 474
  • ISBN : 1000198332
  • Language : En, Es, Fr & De
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The main goal of Internet of Things (IoT) is to make secure, reliable, and fully automated smart environments. However, there are many technological challenges in deploying IoT. This includes connectivity and networking, timeliness, power and energy consumption dependability, security and privacy, compatibility and longevity, and network/protocol standards. Internet of Things and Secure Smart Environments: Successes and Pitfalls provides a comprehensive overview of recent research and open problems in the area of IoT research. Features: Presents cutting edge topics and research in IoT Includes contributions from leading worldwide researchers Focuses on IoT architectures for smart environments Explores security, privacy, and trust Covers data handling and management (accumulation, abstraction, storage, processing, encryption, fast retrieval, security, and privacy) in IoT for smart environments This book covers state-of-the-art problems, presents solutions, and opens research directions for researchers and scholars in both industry and academia.

Socio-economic Systems: Paradigms for the Future

Socio-economic Systems: Paradigms for the Future
A Book

by Elena G. Popkova

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 129
  • ISBN : 3030564339
  • Language : En, Es, Fr & De
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Innovative Data Communication Technologies and Application

Innovative Data Communication Technologies and Application
Proceedings of ICIDCA 2020

by Anonim

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 871
  • ISBN : 9811596514
  • Language : En, Es, Fr & De
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This book presents the latest research in the fields of computational intelligence, ubiquitous computing models, communication intelligence, communication security, machine learning, informatics, mobile computing, cloud computing and big data analytics. The best selected papers, presented at the International Conference on Innovative Data Communication Technologies and Application (ICIDCA 2020), are included in the book. The book focuses on the theory, design, analysis, implementation and applications of distributed systems and networks.