Описание: Concerned with the art rather than the science of Parallel Programming, this volume provides a plain and practical introduction to a subject that has previously been heavily encrypted in computer jargon.
Автор: Li Zhenlong, Huang Qunying, T. Emrich Christopher Название: Social Sensing and Big Data Computing for Disaster Management ISBN: 036761765X ISBN-13(EAN): 9780367617653 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management.
Автор: Mainak Bandyopadhyay, Varun Singh Название: Urban Spatial Data Handling and Computing ISBN: 1799801233 ISBN-13(EAN): 9781799801238 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 31878.00 р. Наличие на складе: Нет в наличии.
Описание: Presents research exploring the theoretical and practical aspects of advanced computing mechanisms and algorithms for handling geospatial data in urban environments. The book features coverage of a broad range of topics, including crowd modeling, location-based services, and cloud-based storage.
Автор: Mainak Bandyopadhyay, Varun Singh Название: Urban Spatial Data Handling and Computing ISBN: 1799801225 ISBN-13(EAN): 9781799801221 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 42134.00 р. Наличие на складе: Нет в наличии.
Описание: Presents research exploring the theoretical and practical aspects of advanced computing mechanisms and algorithms for handling geospatial data in urban environments. The book features coverage of a broad range of topics, including crowd modeling, location-based services, and cloud-based storage.
Автор: Baldi, Pierre (university Of California, Irvine) Название: Deep learning in science ISBN: 1108845355 ISBN-13(EAN): 9781108845359 Издательство: Cambridge Academ Рейтинг: Цена: 7918.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and deep learning, it demonstrates many applications in physics, chemistry, and biomedicine. It includes a full set of exercises and encourages out-of-the-box thinking.
Автор: Walker Название: Mass Notification and Crisis Communications ISBN: 1439874387 ISBN-13(EAN): 9781439874387 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Mass communication in the midst of a crisis must be done in a targeted and timely manner to mitigate the impact and ultimately save lives. Based on sound research, real-world case studies, and the author's own experiences, Mass Notification and Crisis Communications: Planning, Preparedness, and Systems helps emergency planning professionals create a crisis communications plan that works by establishing upfront relationships with responders, enacting protocols, and utilizing technology to effectively message the intended audience.
Providing communication best practices to professionals, the book:
Reviews the challenges organizations face with communications in the face of various types of disasters
Helps to outline the target audience of the communiqu
Describes different communication techniques used throughout history during peace and wartime
Provides methods for getting the right message across the first time
Explores how social media can be a powerful tool in message dissemination
Examines the legal landscape to ensure managers are in compliance with international, federal, state, and local regulatory requirements
Aligned with the U.S. Department of Homeland Security's National Emergency Communications Plan--as well as the U.S. strategic plan to improve emergency response communications--the book provides recommendations to key decision makers given all considerations that must be weighed and factored in during a crisis.
Автор: Castillo, Carlos Название: Big crisis data ISBN: 1108816940 ISBN-13(EAN): 9781108816946 Издательство: Cambridge Academ Рейтинг: Цена: 5069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: During natural disasters people make extensive use of social media. How can this avalanche of messages be processed to extract the information needed to save lives? This book brings together computational methods from many disciplines for processing social media messages under time-critical constraints.
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: Jorg Verstraete Название: Artificial Intelligent Methods for Handling Spatial Data ISBN: 3030002373 ISBN-13(EAN): 9783030002374 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data. It introduces the necessary concepts from spatial data processing and fuzzy rulebase systems and describes the issues experienced when using current regridding algorithms. The main focus of the book is on describing the different modifications needed to make the problem compatible with fuzzy rulebases. It offers a number of examples of out-of-the box thinking to handle aspects such as rulebase construction, defuzzification, spatial data comparison, etc. At first, the emphasis is put on the newly developed method, and additional datasets containing information on the underlying spatial distribution of the data are identified. After this, an artificial intelligent system (in the form of a fuzzy inference system) is constructed using this knowledge and then applied on the input data to perform the regridding. The book offers an example of how an apparently simple problem can pose many different challenges, even when trying to solve it with existing soft computing technologies. The workflow and solutions to solve these challenges are universal and may therefore be broadly applied into other contexts.
Автор: Yang Название: Spatial Cloud Computing ISBN: 1138075558 ISBN-13(EAN): 9781138075559 Издательство: Taylor&Francis Рейтинг: Цена: 9645.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An exploration of the benefits of cloud computing in geoscience research and applications as well as future research directions, Spatial Cloud Computing: A Practical Approach discusses the essential elements of cloud computing and their advantages for geoscience. Using practical examples, it details the geoscience requirements of cloud computing, covers general procedures and considerations when migrating geoscience applications onto cloud services, and demonstrates how to deploy different applications.
The book discusses how to choose cloud services based on the general cloud computing measurement criteria and cloud computing cost models. The authors examine the readiness of cloud computing to support geoscience applications using open source cloud software solutions and commercial cloud services. They then review future research and developments in data, computation, concurrency, and spatiotemporal intensities of geosciences and how cloud service can be leveraged to meet the challenges. They also introduce research directions from the aspects of technology, vision, and social dimensions.
Spatial Cloud Computing: A Practical Approach a common workflow for deploying geoscience applications and provides references to the concepts, technical details, and operational guidelines of cloud computing. These features and more give developers, geoscientists, and IT professionals the information required to make decisions about how to select and deploy cloud services.
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.
Описание: The natural disasters are the killer agents which can/can`t be predicted even though we have modern technology. India is not only vulnerable to natural disasters, it is also experiencing industrial accidents.
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