AI and Machine Learning Paradigms for Health Monitoring System. Intelligent Data Analytics, Malik, Hasmat, Fatema, Nuzhat, Alzubi, Jafar A. (E
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Автор: Malik Hasmat, Fatema Nuzhat, Alzubi Jafar A. Название: AI and Machine Learning Paradigms for Health Monitoring System: Intelligent Data Analytics ISBN: 9813344113 ISBN-13(EAN): 9789813344112 Издательство: Springer Цена: 25155.00 р. Наличие на складе: Есть у поставщикаПоставка под заказ. Описание: This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques.
Описание: This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques.
Описание: Recent research reveals that socioeconomic factors of the neighborhoods where road users live and where pedestrian-vehicle crashes occur are important in determining the severity of the crashes, with the former having a greater influence. Hence, road safety countermeasures, especially those focusing on the road users, should be targeted at these high risk neighborhoods.Big Data Analytics in Traffic and Transportation Engineering: Emerging Research and Opportunities is an essential reference source that discusses access to transportation and examines vehicle-pedestrian crashes, specifically in relation to socioeconomic factors that influence them, main predictors, factors that contribute to crash severity, and the enhancement of pedestrian safety measures. Featuring research on topics such as public transport, accessibility, and spatial distribution, this book is ideally designed for policymakers, transportation engineers, road safety designers, transport planners and managers, professionals, academicians, researchers, and public administrators.
Автор: Kumar, Pardeep, Singh, Amit Kumar Название: Machine Learning for Intelligent Multimedia Analytics ISBN: 9811594910 ISBN-13(EAN): 9789811594915 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 1. Secure Multimodal Access with 2D and 3D Ears.- Chapter 2. Efficient and Low Overhead Detection of Brain Diseases using Deep Learning based Sparse MRI Image Classification.- Chapter 3. Continual Deep Learning Framework for Medical Media Screening and Archival.- Chapter 4. KannadaRes-NeXt: a Deep Residual Network for Kannada Numeral Recognition.- Chapter 5. Secure Image Transmission in Wireless Network using Conventional Neural Network and DOST.- Chapter 6. Robust General Twin Support Vector Machine with Pinball Loss Function.- Chapter 7. Noise Resilient Thresholding based on Fuzzy Logic and Non-linear Filtering.- Chapter 8. Deep Learning Methods for Audio Events Detection.- Chapter 9. A Framework for Multi-lingual Scene Text Detection using K-means++ and Memetic Algorithms.- Chapter 10. Recent Advancements in Medical Imaging: A Machine Learning Approach.- Chapter 11. Solving Image Processing Critical Problems using Machine Learning.- Chapter 12. Spoken Language Identification of Indian Languages using MFCC Features.- Chapter 13. Performance Evaluation of One-Class Classifiers (OCC) for Damage Detection in Structural Health Monitoring.- Chapter 14. Brain Tumor Classification in MRI Images using Transfer Learning.- Chapter 15. Semantic based Vectorization Technique for Hindi Language.
Описание: This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.
Описание: This thesis introduces a successfully designed and commissioned intelligent health monitoring system, specifically for use on any industrial robot, which is able to predict the onset of faults in the joints of the geared transmissions. However the developed embedded wireless condition monitoring system leads itself very well for applications on any power transmission equipment in which the loads and speeds are not constant, and access is restricted. As such this provides significant scope for future development. Three significant achievements are presented in this thesis. First, the development of a condition monitoring algorithm based on vibration analysis of an industrial robot for fault detection and diagnosis. The combined use of a statistical control chart with time-domain signal analysis for detecting a fault via an arm-mounted wireless processor system represents the first stage of fault detection. Second, the design and development of a sophisticated embedded microprocessor base station for online implementation of the intelligent condition monitoring algorithm, and third, the implementation of a discrete wavelet transform, using an artificial neural network, with statistical feature extraction for robot fault diagnosis in which the vibration signals are first decomposed into eight levels of wavelet coefficients.
Описание: Intelligent Data Sensing and Processing for Health and Well-being Applications uniquely combines full exploration of the latest technologies for sensor-collected intelligence with detailed coverage of real-case applications for healthcare and well-being at home and in the workplace. Forward-thinking in its approach, the book presents concepts and technologies needed for the implementation of today's mobile, pervasive and ubiquitous systems, and for tomorrow’s IoT and cyber-physical systems. Users will find a detailed overview of the fundamental concepts of gathering, processing and analyzing data from devices disseminated in the environment, as well as the latest proposals for collecting, processing and abstraction of data-sets. . In addition, the book addresses algorithms, methods and technologies for diagnosis and informed decision-making for healthcare and well-being. Topics include emotional interface with ambient intelligence and emerging applications in detection and diagnosis of neurological diseases. Finally, the book explores the trends and challenges in an array of areas, such as applications for intelligent monitoring in the workplace for well-being, acquiring data traffic in cities to improve the assistance of first aiders, and applications for supporting the elderly at home.
Описание: This book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intelligent systems and related technologies. These disciplines are strongly related and mutually complementary; accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation. To maximize the dissemination of research findings, the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most.
Intelligent Data-Analytics for Condition Monitoring: Smart Grid Applications looks at intelligent and meaningful uses of data required for an optimized, efficient engineering processes. In addition, the book provides application perspectives of various deep learning models for the condition monitoring of electrical equipment. With chapters discussing the fundamentals of machine learning and data analytics, the book is divided into two parts, including i) The application of intelligent data analytics in Solar PV fault diagnostics, transformer health monitoring and faults diagnostics, and induction motor faults and ii) Forecasting issues using data analytics which looks at global solar radiation forecasting, wind data forecasting, and more.
This reference is useful for all engineers and researchers who need preliminary knowledge on data analytics fundamentals and the working methodologies and architecture of smart grid systems.
Автор: Bhattacharyya, Siddhartha Название: Intelligent Environmental Data Monitoring For Pollution Management ISBN: 0128196718 ISBN-13(EAN): 9780128196717 Издательство: Elsevier Science Рейтинг: Цена: 18528.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Intelligent Environmental Data Monitoring for Pollution Management is centered on evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process oriented data. It may be noted that there are lots of potential applications and prototypes in this field, yet very few real life applications are known so far. This is mainly due to the fact that most of the pollution management procedures still rely on the time consuming batch processes and field study. Thus this book will usher in a new era as far as environmental pollution management is concerned. This book reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. The book will also cover the novel intelligent algorithms for the purpose of effective environmental pollution data management at par with the standards laid down by World Health Organization.
Описание: This thesis introduces a successfully designed and commissioned intelligent health monitoring system, specifically for use on any industrial robot, which is able to predict the onset of faults in the joints of the geared transmissions.
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