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Applied Machine Learning for Smart Data Analysis
The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results. Key Features Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning, machine learning, Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health, transportation and Internet applications
AI, IoT, Big Data and Cloud Computing for Industry 4.0
This book presents some of the most advanced leading-edge technology for the fourth Industrial Revolution -- known as “Industry 4.0.” The book provides a comprehensive understanding of the interconnections of AI, IoT, big data and cloud computing as integral to the technologies that revolutionize the way companies produce and distribute products and the way local governments deliver their services. The book emphasizes that at every phase of the supply chain, manufactures are found to be interweaving AI, robotics, IoT, big data/machine learning, and cloud computing into their production facilities and throughout their distribution networks. Equally important, the authors show how their research can be applied to computer vision, cyber security, database and compiler theory, natural language processing, healthcare, education and agriculture. Presents the fundamentals of AI, IoT, and cloud computing and how they can be incorporated in Industry 4.0 applications Motivates readers to address challenges in the areas of speech communication and signal processing Provides numerous examples, case studies, technical descriptions, and approaches of AI/ML
Biomedical Sensors and Smart Sensing
Biomedical Sensors and Smart Sensing: A Beginner's Guide, a book in the 10-volume Primers in Biomedical Imaging Devices and Systems series, covers a wide range of interdisciplinary applications in imaging modalities, nuclear medicine, computed tomographic systems, x-ray systems, magnetic resonance imaging, ultrasound, and virtual reality. The series explores the essential fundamental techniques required to analyze and process signals and images for diagnosis, scientific discovery and medical applications. Volumes in this series cover a wide range of interdisciplinary areas, combining foundational content with practical case studies to demonstrate the applications of these technologies in real-world situations. In addition, the 10-volume series considers various medical devices, electronics, circuits, sensors and algorithms. Several applications ranging from basic biological science to clinical practice are included to facilitate ongoing research. - Covers a variety of sensing and signal processing techniques - Introduces different approaches relating to communication and intelligent data processing for early detection and prediction of diseases - Includes practical case studies
Soft Computing in Wireless Sensor Networks
This book focuses on the suitable methods to solve optimization problems in wireless network system utilizing digital sensors like Wireless Sensor Network. This kind of system has been emerging as the cornerstone technology for all new smart devices and its direct application in many fields in life.
Digital Image Watermarking
The Book presents an overview of newly developed watermarking techniques in various independent and hybrid domains Covers the basics of digital watermarking, its types, domain in which it is implemented and the application of machine learning algorithms onto digital watermarking Reviews hardware implementation of watermarking Discusses optimization problems and solutions in watermarking with a special focus on bio-inspired algorithms Includes a case study along with its MATLAB code and simulation results
Cognitive IoT
This book deals with a different research area of cognitive IoT and explains how machine learning algorithms can be applied for cognitive IoT. It deals with applications of cognitive IoT in this pandemic (COVID-19), applications for student performance evaluation, applications for human healthcare for chronic disease prediction, use of wearable sensors and review regarding their energy optimization and how cognitive IoT helps in farming through rainfall prediction and prediction of lake levels. Features: Describes how cognitive IoT is helpful for chronic disease prediction and processing of data gathered from healthcare devices Explains different sensors available for health monitoring Explores application of cognitive IoT in COVID-19 analysis Discusses pertinent and efficient farming applications for sustaining agricultural growth Reviews smart educational aspects such as student response, performance, and behavior and instructor response, performance, and behavior This book aims at researchers, professionals and graduate students in Computer Science and Engineering, Computer Applications and Electronics Engineering, and Wireless Communications and Networking.
Proceedings of the Ninth International Symposium on Consumer Electronics 2005 (ISCE 2005), 14-16 June 2005, Macau SAR
Issues for 1998-2003, 2008-2011, 2014- cataloged as a serial in LC.
