Smart Healthcare Analytics in IoT Enabled Environment, Prasant Kumar Pattnaik
Название: Recent trends and advances in wireless and iot-enabled networks ISBN: 3319999656 ISBN-13(EAN): 9783319999654 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book covers a variety of topics in Information and Communications Technology (ICT) and their impact on innovation and business. The authors discuss various innovations, business and industrial motivations, and impact on humans and the interplay between those factors in terms of finance, demand, and competition. Topics discussed include the convergence of Machine to Machine (M2M), Internet of Things (IoT), Social, and Big Data. They also discuss AI and its integration into technologies from machine learning, predictive analytics, security software, to intelligent agents, and many more. Contributions come from academics and professionals around the world.
Covers the most recent practices in ICT related topics pertaining to technological growth, innovation, and business;Presents a survey on the most recent technological areas revolutionizing how humans communicate and interact;Features four sections: IoT, Wireless Ad Hoc & Sensor Networks, Fog Computing, and Big Data Analytics.
Автор: Kendall Ho; Sandra Jarvis-Selinger; Helen Novak La Название: Technology Enabled Knowledge Translation for eHealth ISBN: 1489987487 ISBN-13(EAN): 9781489987488 Издательство: Springer Рейтинг: Цена: 231990.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers the use of information and communication technologies to accelerate the non-linear, complicated process of translating new knowledge into routine health practice. Describes opportunities in health education, service delivery and research.
Автор: Amit P. Sheth Название: Semantic-Enabled Advancements on the Web: Applications Across Industries ISBN: 146660185X ISBN-13(EAN): 9781466601857 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 184800.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Reviews current and future trends in Semantic Web research with the aim of making existing and potential applications more accessible to a broader community of academics, practitioners, and industry professionals. Covering topics including recommendation systems, semantic search, and ontologies, this reference is a valuable contribution to the existing literature in this discipline.
Автор: Connie W. Delaney; Charlotte A. Weaver; Judith J. Название: Big Data-Enabled Nursing ISBN: 3319851209 ISBN-13(EAN): 9783319851204 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Невозможна поставка. Описание: Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors.
Автор: Connie W. Delaney; Charlotte A. Weaver; Judith J. Название: Big Data-Enabled Nursing ISBN: 3319532995 ISBN-13(EAN): 9783319532998 Издательство: Springer Рейтинг: Цена: 167700.00 T Наличие на складе: Невозможна поставка. Описание: Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Автор: Siddhartha Bhattacharyya; Sushmita Mitra; Paramart Название: Intelligence Enabled Research ISBN: 9811520208 ISBN-13(EAN): 9789811520204 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book gathers extended versions of papers presented at DoSIER 2019 (the First Doctoral Symposium on Intelligence Enabled Research, organized by RCC Institute of Information Technology, Kolkata, India).
Автор: Chakraborty Chinmay Название: Smart Medical Data Sensing and IoT Systems Design in Healthcare ISBN: 1799802612 ISBN-13(EAN): 9781799802617 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 246710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Smart healthcare technology improves the diagnosis and treatment of patients, provides easy access to medical facilities and emergency care services, and minimizes the gaps between patients and healthcare providers. While clinical data protection remains a major challenge, innovations such as the internet of medical things and smart healthcare systems increase the efficiency and quality of patient care. Healthcare technology can only become faster, more profitable, and more flexible as additional research on its advancements is conducted and collected.
Smart Medical Data Sensing and IoT Systems Design in Healthcare is an essential reference source that focuses on robust and easy solutions for the delivery of medical information from patients to doctors and explores low-cost, high-performance, highly efficient, deployable IoT system options in healthcare systems. Featuring research on topics such as hospital management systems, electronic health records, and bio-signals, this book is ideally designed for technologists, engineers, scientists, clinicians, biomedical engineers, hospital directors, doctors, nurses, healthcare practitioners, telemedical agents, students, and academicians seeking coverage on the latest technological developments in medical data analysis and connectivity.
Автор: Venkataramani Название: Smart Secure Systems – IoT and Analytics Perspective ISBN: 9811076340 ISBN-13(EAN): 9789811076343 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume constitutes the refereed proceedings of the Second International Conference on Intelligent Information Technologies, ICIIT 2017, held in Chennai, India, in December 2017. The 20 full papers and 7 short papers presented were carefully reviewed and selected from 117 submissions.
Автор: Pedro R. M. In?cio; Ana Duarte; Paulo Fazendeiro; Название: 5th EAI International Conference on IoT Technologies for HealthCare ISBN: 3030303349 ISBN-13(EAN): 9783030303341 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents papers from HealthyIoT 2018, the fifth edition of an international scientific event series dedicated to Internet of Things and Healthcare. The papers discuss leveraging a set of existing and emerging technologies, notions and services that can provide many solutions to delivery of electronic healthcare, patient care, and medical data management. HealthyIoT brings together technology experts, researchers, industry and international authorities contributing towards the design, development and deployment of healthcare solutions based on IoT technologies, standards, and procedures. HealthyIoT 2018 is part of the 4th annual Smart City 360?Summit, promoting multidisciplinary scientific collaboration to solve complex societal, technological and economic problems of emerging Smart Cities. The event is endorsed by the European Alliance for Innovation, an international professional community-based organisation devoted to the advancement of innovation in the field of ICT.
Features practical, tested applications in IoT for healthcare;Includes application domains such as eHealth Systems, smart textiles, smart caring environments, telemedicine, wellness, and health management, etc;Applicable to researchers, academics, students, and professionals.
Автор: Ritika Wason, Dinesh Goyal, Vishal Jain, S. Balamu Название: Applications of Deep Learning and Big IoT on Personalized Healthcare Services ISBN: 1799821013 ISBN-13(EAN): 9781799821014 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 246710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes.
Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
