Feng lyu (67 resultados)

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Paperback. Condición: new. Paperback. This book, LNCS 16193, constitutes the proceedings of the First International Workshop on Digital Twin for Healthcare, DT4H 2025, held in conjunction with MICCAI 2025, in Daejeon, South Korea, during September 23, 2025.The 15 full papers included in the book were carefully reviewed and selected from 24 submissions. They deal with integrating Digital Twin frameworks with conventional medical imaging and computational tools, focusing on topics such as organ- and disease-specific DT modeling; multi-modal data integration; AI-driven simulation and prediction; DT-guided diagnostic and treatment planning; etc. This book, LNCS 16193, constitutes the proceedings of the First International Workshop on Digital Twin for Healthcare, DT4H 2025, held in conjunction with MICCAI 2025, in Daejeon, South Korea, during September 23, 2025.The 15 full papers included in the book were carefully reviewed and selected from 24 submissions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Condición: Brand New. 100 pages. 9.25x6.10x0.21 inches. In Stock.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book investigates compressive sensing techniques to provide a robust and general framework for network data analytics. The goal is to introduce a compressive sensing framework for missing data interpolation, anomaly detection, data segmentation and activity recognition, and to demonstrate its benefits. Chapter 1 introduces compressive sensing, including its definition, limitation, and how it supports different network analysis applications. Chapter 2 demonstrates the feasibility of compressive sensing in network analytics, the authors we apply it to detect anomalies in the customer care call dataset from a Tier 1 ISP in the United States. A regression-based model is applied to find the relationship between calls and events. The authors illustrate that compressive sensing is effective in identifying important factors and can leverage the low-rank structure and temporal stability to improve the detection accuracy. Chapter 3 discusses that there are several challenges in applying compressive sensing to real-world data. Understanding the reasons behind the challenges is important for designing methods and mitigating their impact. The authors analyze a wide range of real-world traces. The analysis demonstrates that there are different factors that contribute to the violation of the low-rank property in real data. In particular, the authors find that (1) noise, errors, and anomalies, and (2) asynchrony in the time and frequency domains lead to network-induced ambiguity and can easily cause low-rank matrices to become higher-ranked. To address the problem of noise, errors and anomalies in Chap. 4, the authors propose a robust compressive sensing technique. It explicitly accounts for anomalies by decomposing real-world data represented in matrix form into a low-rank matrix, a sparse anomaly matrix, an error term and a small noise matrix. Chapter 5 addresses the problem of lack of synchronization, and the authors propose a data-driven synchronization algorithm.It can eliminate misalignment while taking into account the heterogeneity of real-world data in both time and frequency domains. The data-driven synchronization can be applied to any compressive sensing technique and is general to any real-world data. The authors illustrates that the combination of the two techniques can reduce the ranks of real-world data, improve the effectiveness of compressive sensing and have a wide range of applications.The networks are constantly generating a wealth of rich and diverse information. This information creates exciting opportunities for network analysis and provides insight into the complex interactions between network entities. However, network analysis often faces the problems of (1) under-constrained, where there is too little data due to feasibility and cost issues in collecting data, or (2) over-constrained, where there is too much data, so the analysis becomes unscalable. Compressive sensing is an effective technique to solve both problems. It utilizes the underlying data structure for analysis.Specifically, to solve the under-constrained problem, compressive sensing technologies can be applied to reconstruct the missing elements or predict the future data. Also, to solve the over-constraint problem, compressive sensing technologies can be applied to identify significant elementsTo support compressive sensing in network data analysis, a robust and general framework is needed to support diverse applications. Yet this can be challenging for real-world data where noise, anomalies and lack of synchronization are common. First, the number of unknowns for network analysis can be much larger than the number of measurements. For example, traffic engineering requires knowing the complete traffic matrix between all source and destination pairs, in order to properly configure traffic and avoid congestion. However, measuring the flow between all source and destination pairs is very expensive or even in. …

Paperback. Condición: new. Paperback. This book, LNCS 16193, constitutes the proceedings of the First International Workshop on Digital Twin for Healthcare, DT4H 2025, held in conjunction with MICCAI 2025, in Daejeon, South Korea, during September 23, 2025.The 15 full papers included in the book were carefully reviewed and selected from 24 submissions. They deal with integrating Digital Twin frameworks with conventional medical imaging and computational tools, focusing on topics such as organ- and disease-specific DT modeling; multi-modal data integration; AI-driven simulation and prediction; DT-guided diagnostic and treatment planning; etc. This book, LNCS 16193, constitutes the proceedings of the First International Workshop on Digital Twin for Healthcare, DT4H 2025, held in conjunction with MICCAI 2025, in Daejeon, South Korea, during September 23, 2025.The 15 full papers included in the book were carefully reviewed and selected from 24 submissions. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - To support smart vehicular services especially in the future driverless era, the vehicular networks are expected to support high-bandwidth content delivery and reliable accessibility of multifarious applications. However, the limited radio spectrum resources, the inflexibility in accommodating dynamic traffic demands, and the geographically constrained fixed infrastructure deployment of current terrestrial networks pose great challenges in ensuring ubiquitous, flexible, and reliable network connectivity. This book investigates mobile edge content caching and delivery in heterogeneous vehicular networks (HetVNets) to provide better service quality for vehicular users with resource utilization efficiency enhancement. Specifically, this book introduces the background of HetVNets and mobile edge caching, provides a comprehensive overview of mobile edge caching-assisted HetVNet techniques in supporting vehicular content delivery, and proposes/designs mobile edge content caching and delivery schemes in different HetVNet scenarios respectively to enhance vehicular content delivery performance. Afterward, this book outlines open issues and research directions in future mobile edge caching-assisted space-air-ground integrated vehicular networks.The topics addressed in this book are crucial for both the academic community and industry, since mobile edge caching in heterogeneous networks has become an essential building block for the communication systems. The systematic principle of this book provides valuable insights on the efficient exploitation of heterogeneous network resources to fully unleash their differential merits in supporting vehicular applications. In addition, this book considers different HetVNet scenarios from terrestrial HetVNets to air-ground HetVNets and space-air-ground HetVNets, which can provide a general overview for interested readers with a comprehensive understanding of applying mobile edge caching techniques inenhancing vehicular content delivery performance, and offer a systematized view for researchers and practitioners in the field of mobile edge caching to help them design and optimize the desired vehicular content delivery systems.Provides in-depth studies on mobile edge content caching and delivery scheme design for three typical HetVNet scenarios;Comprehensively covers the analysis, design, and optimization of the mobile edge content caching-assisted HetVNets;Systematically addresses vehicle mobility, network service interruptions, and dynamic service request distribution issues in the mobile edge content caching and delivery. …

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book, LNCS 16193, constitutes the proceedings of the First International Workshop on Digital Twin for Healthcare, DT4H 2025, held in conjunction with MICCAI 2025, in Daejeon, South Korea, during September 23, 2025.The 15 full papers included in the book were carefully reviewed and selected from 24 submissions. They deal with integrating Digital Twin frameworks with conventional medical imaging and computational tools, focusing on topics such as organ- and disease-specific DT modeling; multi-modal data integration; AI-driven simulation and prediction; DT-guided diagnostic and treatment planning; etc. …

Condición: New.

Condición: New.

Condición: New. In English.

Condición: New. In English.

Taschenbuch. Condición: Neu. Digital Twin for Healthcare | First International Workshop, DT4H 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings | Lei Li (u. a.) | Taschenbuch | Lecture Notes in Computer Science | x | Englisch | 2025 | Springer | EAN 9783032076939 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

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Condición: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.