Автор: Minei Название: MPLS-Enabled Applications ISBN: 0470665459 ISBN-13(EAN): 9780470665459 Издательство: Wiley Рейтинг: Цена: 8229.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With a foreword by Yakov Rekhter "Here at last is a single, all encompassing resource where the myriad applications sharpen into a comprehensible text that first explains the whys and whats of each application before going on to the technical detail of the hows.
Автор: Fadi Al-Turjman Название: Drones in IoT-enabled Spaces ISBN: 0367266385 ISBN-13(EAN): 9780367266387 Издательство: Taylor&Francis Рейтинг: Цена: 18374.00 р. Наличие на складе: Поставка под заказ.
Описание: This book addresses major issues and challenges in drone-based solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations.
Автор: Franco Davoli; Norbert Meyer; Roberto Pugliese; Sa Название: Grid Enabled Remote Instrumentation ISBN: 0387096620 ISBN-13(EAN): 9780387096629 Издательство: Springer Рейтинг: Цена: 39182.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Focuses on a number of aspects related to the exploitation of remote instrumentation on the grid. This book includes middleware architecture, high speed networking in support of grid applications, wireless grid for acquisition devices and sensor networks, quality of service provisioning for real time control, and measurement instrumentation.
Автор: Franco Davoli; Norbert Meyer; Roberto Pugliese; Sa Название: Grid Enabled Remote Instrumentation ISBN: 1441935061 ISBN-13(EAN): 9781441935069 Издательство: Springer Рейтинг: Цена: 32651.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Grid architectures, which are viewed as tools for the integration of distributed resources, play a significant role as managers of computational resources. This book focuses on a number of aspects related to the effective exploitation of remote instrumentation on the grid.
Описание: Integrated System-Level Modeling of Network-on-Chip Enabled Multi-Processor Platforms first gives a comprehensive update on recent developments in the area of SoC platforms and ESL design methodologies. Subsequently this book presents a set of tools for the creation and exploration of timing approximate SoC platform models.
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.
Chapter1: Taking the next step in GaN: bulk GaN substrates and GaN-on-Si epitaxy for electronics.- Chapter2: Lateral GaN HEMT structures.- Chapter3: Vertical GaN Transistors for Power Electronics.- Chapter4: Reliability of GaN-based Power devices.- Chapter5: Validating GaN robustness.- Chapter6: Impact of Parasitics on GaN Based Power Conversion.- Chapter7: GaN in AC/DC Power Converters.- Chapter8: GaN in Switched Mode Power Amplifiers.
Автор: Kourosh Kalantar-zadeh; Benjamin Fry Название: Nanotechnology-Enabled Sensors ISBN: 1441940855 ISBN-13(EAN): 9781441940858 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides information on the current and future uses of nanotechnology enabled sensors in such diverse fields as communications, building and facilities, medicine, safety, and security, including both homeland defense and military operations.
Автор: Al-Turjman Название: Intelligence in IoT-enabled Smart Cities ISBN: 1138316849 ISBN-13(EAN): 9781138316843 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the major challenges in realizing intelligence in smart cities and sensing platforms in the era of cloud computing and IoT varying from cost and energy efficiency to availability and service quality
Название: Cyber-enabled intelligence ISBN: 0367184877 ISBN-13(EAN): 9780367184872 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. Наличие на складе: Поставка под заказ.
Описание: The book provides an advanced vision and trends of computational intelligence in cyberspace and cyber-enabled spaces. It reviews architectures and models, as well as state-of-the-art computational and interpretation capabilities for social, industrial, and multimedia applications.
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.
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