This book provides a comprehensive picture of fog computing technology, including of fog architectures, latency aware application management issues with real time requirements, security and privacy issues and fog analytics, in wide ranging application scenarios such as M2M device communication, smart homes, smart vehicles, augmented reality and transportation management.
This book explores the research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics. It surveys global research advances in extending the conventional unsupervised or clustering algorithms, extending supervised and semi-supervised algorithms and association rule mining algorithms to big data Scenarios. Further it discusses the deep learning applications of big data analytics to fields of computer vision and speech processing, and describes applications such as semantic indexing and data tagging. Lastly it identifies 25 unsolved research problems and research directions in fog computing, as well as in the context of applying deep learning techniques to big data analytics, such as dimensionality reduction in high-dimensional data and improved formulation of data abstractions along with possible directions for their solutions.
Автор: Himansu Das; Rabindra K. Barik; Harishchandra Dube Название: Cloud Computing for Geospatial Big Data Analytics ISBN: 3030033589 ISBN-13(EAN): 9783030033583 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud computing and big data, such as scheduling, security issues using different techniques, which researchers from industry and academia have been attempting to solve in virtual environments. Some of these problems are of an intractable nature and so efficient technologies like fog, edge and mist computing play an important role in addressing these issues. By exploring emerging advances in cloud computing and big data analytics and their engineering applications, the book enables researchers to understand the mechanisms needed to implement cloud, edge, fog, and mist computing in their own endeavours, and motivates them to examine their own research findings and developments.
Автор: Sharma Название: Computing, Analytics and Networks ISBN: 9811307547 ISBN-13(EAN): 9789811307546 Издательство: Springer Рейтинг: Цена: 9502.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the revised selected papers from the First International Conference on Computing, Analytics and Networks, ICAN 2017, held in Rajpura, India, in October 2017.The 20 revised full papers presented in this volume were carefully reviewed and selected from 56 submissions.
Описание: This two-volume set LNCS 11578 and 11579 constitutes the refereed proceedings of the 11th International Conference on Social Computing and Social Media, SCSM 2019, held in July 2019 as part of HCI International 2019 in Orlando, FL, USA. HCII 2019 received a total of 5029 submissions, of which 1275 papers and 209 posters were accepted for publication after a careful reviewing process. The 81 papers presented in these two volumes are organized in topical sections named: Social Media Design and Development, Human Behaviour in Social Media, Social Network Analysis, Community Engagement and Social Participation, Computer Mediated Communication, Healthcare Communities, Social Media in Education, Digital Marketing and Consumer Experience.
Описание: This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling.
Автор: Anandakumar Haldorai, Arulmurugan Ramu Название: Big Data Analytics for Sustainable Computing ISBN: 1522597506 ISBN-13(EAN): 9781522597506 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 32987.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science.
Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.
Автор: Anandakumar Haldorai, Arulmurugan Ramu Название: Big Data Analytics for Sustainable Computing ISBN: 1522597514 ISBN-13(EAN): 9781522597513 Издательство: Mare Nostrum (Eurospan) Цена: 27027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.
Описание: The two volumes set LNCS 10913-10914 of SCSM 2018 constitutes the proceedings of the 10th International Conference on Social Computing and Social Media, SCSM 2018, held as part of the International Conference on Human-Computer Interaction, HCII 2018, held in Las Vegas, NV, USA, in July 2018.
Автор: Prasant Kumar Pattnaik; Siddharth Swarup Rautaray; Название: Progress in Computing, Analytics and Networking ISBN: 981107870X ISBN-13(EAN): 9789811078705 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book focuses to foster new and original research ideas and results in three broad areas: computing, analytics, and networking with its prospective applications in the various interdisciplinary domains of engineering. This is an exciting and emerging interdisciplinary area in which a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging real world problems. It also provides insights into the International Conference on Computing Analytics and Networking (ICCAN 2017) which is a premier international open forum for scientists, researchers and technocrats in academia as well as in industries from different parts of the world to present, interact, and exchange the state of art of concepts, prototypes, innovative research ideas in several diversified fields. The book includes invited keynote papers and paper presentations from both academia and industry to initiate and ignite our young minds in the meadow of momentous research and thereby enrich their existing knowledge. The book aims at postgraduate students and researchers working in the discipline of Computer Science & Engineering. It will be also useful for the researchers working in the domain of electronics as it contains some hardware technologies and forthcoming communication technologies.
Автор: K. R. Venugopal; K.G Srinivasa; L. M. Patnaik Название: Soft Computing for Data Mining Applications ISBN: 3642101259 ISBN-13(EAN): 9783642101250 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph presents recent research in the fields of data mining in combination with soft computing methodologies. It provides valuable research directions in the field of specialization.
Автор: Zongmin Ma; Li Yan Название: Soft Computing in XML Data Management ISBN: 3642264018 ISBN-13(EAN): 9783642264016 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers in a great depth the fast growing topic of techniques, tools and applications of soft computing in XML data management. It shows how XML data management (like model, query, integration) can be covered with a soft computing focus.
Автор: Sourav De; Siddhartha Bhattacharyya; Susanta Chakr Название: Hybrid Soft Computing for Multilevel Image and Data Segmentation ISBN: 3319475231 ISBN-13(EAN): 9783319475233 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures.This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.
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