9781032426372 - heterogenous computational intelligence in internet of things (15 risultati)
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Heterogenous Computational Intelligence in Internet of Things
Singh, Pawan (EDT); Singhal, Prateek (EDT); Mishra, Pramod Kumar (EDT); Vatsa, Avimanyou K. (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 20,77
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Condizione: As New. Unread book in perfect condition.
Heterogenous Computational Intelligence in Internet of Things
Singh, Pawan (EDT); Singhal, Prateek (EDT); Mishra, Pramod Kumar (EDT); Vatsa, Avimanyou K. (EDT)
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 169,34
EUR 17,57 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 10 disponibili
Condizione: New.
Heterogenous Computational Intelligence in Internet of Things
Singh, Pawan (EDT); Singhal, Prateek (EDT); Mishra, Pramod Kumar (EDT); Vatsa, Avimanyou K. (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 190,08
EUR 2,32 spedizioneSpedito in U.S.A.Quantità: 1 disponibili
Condizione: New.
Heterogenous Computational Intelligence in Internet of Things
Singh, Pawan (EDT); Singhal, Prateek (EDT); Mishra, Pramod Kumar (EDT); Vatsa, Avimanyou K. (EDT)
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 180,75
EUR 17,57 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 10 disponibili
Condizione: As New. Unread book in perfect condition.
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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EUR 186,35
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Condizione: New. In.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 209,45
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Condizione: New.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 216,45
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Condizione: New.
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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 240,12
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Hardcover. Condizione: Brand New. 320 pages. 9.19x6.13x0.90 inches. In Stock.
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 159,10
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We have seen a sharp increase in the development of data transfer techniques in the networking industry over the past few years. We can see that the photos are assisting clinicians in detecting infection in patients even in the current CO…VID-19 pandemic condition. With the aid of ML/AI, medical imaging, such as lung X-rays for COVID-19 infection, is crucial in the early detection of many diseases. We also learned that in the COVID-19 scenario, both wired and wireless networking are improved for data transfer but have network congestion. An intriguing concept that has the ability to reduce spectrum congestion and continuously offer new network services is providing wireless network virtualization. The degree of virtualization and resource sharing varies between the paradigms. Each paradigm has both technical and non-technical issues that need to be handled before wireless virtualization becomes a common technology. For wireless network virtualization to be successful, these issues need careful design and evaluation. Future wireless network architecture must adhere to a number of Quality of Service (QoS) requirements. Virtualization has been extended to wireless networks as well as conventional ones. By enabling multi-tenancy and tailored services with a wider range of carrier frequencies, it improves efficiency and utilization. In the IoT environment, wireless users are heterogeneous, and the network state is dynamic, making network control problems extremely difficult to solve as dimensionality and computational complexity keep rising quickly. Deep Reinforcement Learning (DRL) has been developed by the use of Deep Neural Networks (DNNs) as a potential approach to solve high-dimensional and continuous control issues effectively. Deep Reinforcement Learning techniques provide great potential in IoT, edge and SDN scenarios and are used in heterogeneous networks for IoT-based management on the QoS required by each Software Defined Network (SDN) service. While DRL has shown great potential to solve emerging problems in complex wireless network virtualization, there are still domain-specific challenges that require further study, including the design of adequate DNN architectures with 5G network optimization issues, resource discovery and allocation, developing intelligent mechanisms that allow the automated and dynamic management of the virtual communications established in the SDNs which is considered as research perspective. 316 pp. Englisch.
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Da: moluna, Greven, Germaniamoluna
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EUR 135,38
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Pawan Singh is an Associate Professor in the Department of Computer Science & Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Lucknow, India. He has completed Ph.D. deg…ree in Computer Science from M.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 189,63
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HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 196,89
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 159,10
EUR 63,20 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We have seen a sharp increase in the development of data transfer techniques in the networking industry over the past few years. We can see that the photos are assisting clinicians in detecting infection in patients even in the current COVID-1…9 pandemic condition. With the aid of ML/AI, medical imaging, such as lung X-rays for COVID-19 infection, is crucial in the early detection of many diseases. We also learned that in the COVID-19 scenario, both wired and wireless networking are improved for data transfer but have network congestion. An intriguing concept that has the ability to reduce spectrum congestion and continuously offer new network services is providing wireless network virtualization. The degree of virtualization and resource sharing varies between the paradigms. Each paradigm has both technical and non-technical issues that need to be handled before wireless virtualization becomes a common technology. For wireless network virtualization to be successful, these issues need careful design and evaluation. Future wireless network architecture must adhere to a number of Quality of Service (QoS) requirements. Virtualization has been extended to wireless networks as well as conventional ones. By enabling multi-tenancy and tailored services with a wider range of carrier frequencies, it improves efficiency and utilization. In the IoT environment, wireless users are heterogeneous, and the network state is dynamic, making network control problems extremely difficult to solve as dimensionality and computational complexity keep rising quickly. Deep Reinforcement Learning (DRL) has been developed by the use of Deep Neural Networks (DNNs) as a potential approach to solve high-dimensional and continuous control issues effectively. Deep Reinforcement Learning techniques provide great potential in IoT, edge and SDN scenarios and are used in heterogeneous networks for IoT-based management on the QoS required by each Software Defined Network (SDN) service. While DRL has shown great potential to solve emerging problems in complex wireless network virtualization, there are still domain-specific challenges that require further study, including the design of adequate DNN architectures with 5G network optimization issues, resource discovery and allocation, developing intelligent mechanisms that allow the automated and dynamic management of the virtual communications established in the SDNs which is considered as research perspective.
