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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
International Journal of Neutrosophic Science (IJNS), Volume 0/2019
International Journal of Neutrosophic Science (IJNS) is a peer-review journal publishing high quality experimental and theoretical research in all areas of Neutrosophics and its Applications.
Smart Computing with Open Source Platforms
Focuses on the concept of open source prototyping and product development and designing sensor networks and covers IoT base applications This book will serves as a single source of introductory material and reference for programming smart computing and Internet of Things (IoT) devices using Arduino with the use of Python It covers number of comprehensive DIY experiments through which the reader can design various intelligent systems
The Encyclopedia of Neutrosophic Researchers, 3rd volume
This is the third volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books.
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Social Network Analytics
Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling, and more. As analyzing social network data is rapidly gaining interest in the scientific research community because of...
Soft Computing Based Medical Image Analysis
Soft Computing Based Medical Image Analysis presents the foremost techniques of soft computing in medical image analysis and processing. It includes image enhancement, segmentation, classification-based soft computing, and their application in diagnostic imaging, as well as an extensive background for the development of intelligent systems based on soft computing used in medical image analysis and processing. The book introduces the theory and concepts of digital image analysis and processing based on soft computing with real-world medical imaging applications. Comparative studies for soft computing based medical imaging techniques and traditional approaches in medicine are addressed, providing flexible and sophisticated application-oriented solutions. - Covers numerous soft computing approaches, including fuzzy logic, neural networks, evolutionary computing, rough sets and Swarm intelligence - Presents transverse research in soft computing formation from various engineering and industrial sectors in the medical domain - Highlights challenges and the future scope for soft computing based medical analysis and processing techniques
Thermal Ablation Therapy
Thermal Ablation Therapy: Theory and Simulation includes detailed theoretical and technical concepts of thermal ablation therapy in different body organs. Concepts of ablation technology based on different thermal ablation methods are introduced, along with changes in the tissues' mechanical properties due to thermal denaturation. The book emphasizes the mathematical and engineering concepts of RF and MW energy propagation through tissues and where high heating rates produced by MW systems can overcome the heat-sink effects from nearby vessels. The design and tuning of the MW antennas to deliver energy efficiently to specific organ systems such as the liver or lung is also covered. Other sec...
Histopathological Image Analysis in Medical Decision Making
Medical imaging technologies play a significant role in visualization and interpretation methods in medical diagnosis and practice using decision making, pattern classification, diagnosis, and learning. Progressions in the field of medical imaging lead to interdisciplinary discovery in microscopic image processing and computer-assisted diagnosis systems, and aids physicians in the diagnosis and early detection of diseases. Histopathological Image Analysis in Medical Decision Making provides emerging research exploring the theoretical and practical applications of image technologies and feature extraction procedures within the medical field. Featuring coverage on a broad range of topics such as image classification, digital image analysis, and prediction methods, this book is ideally designed for medical professionals, system engineers, medical students, researchers, and medical practitioners seeking current research on problem-oriented processing techniques in imaging technologies.
Parametric and Nonparametric Techniques in Medical Image De-noising and Restoration
Despite advancements in medical imaging modalities, build-up of noise and distortion is still an issue faced by users of medical imaging technology. Consequently, de-noising procedures are developed to preserve the quality of the textured image by removing the noise encountered. Parametric and Nonparametric Techniques in Medical Image De-noising and Restoration explores the different medical image de-noising techniques for medical image quality enhancement. It introduces soft computing and optimization techniques and reports on the challenges of medical image denoising, also highlighting artifacts and noise sources in different imaging modalities and discussing performance evaluation metrics. This is a key reference for anyone involved in medical imaging who is looking to learn about both the parametric and non-parametric approaches available and apply them to their own work and research. Explores the types of denoising and restoration with different noise sources of each medical modality Emphasizes the different approaches of denoising and restoration, including parametric and nonparametric techniques Provides applied examples of medical image denoising
