Connected Autonomous Vehicle (CAV) Driving, as a data-driven intelligent driving technology within the Internet of Vehicles (IoV), presents significant challenges to the efficiency and security of real-time data manag...
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Connected Autonomous Vehicle (CAV) Driving, as a data-driven intelligent driving technology within the Internet of Vehicles (IoV), presents significant challenges to the efficiency and security of real-time data management. The combination of Web3.0 and edge content caching holds promise in providing low-latency data access for CAVs’ real-time applications. Web3.0 enables the reliable pre-migration of frequently requested content from content providers to edge nodes. However, identifying optimal edge node peers for joint content caching and replacement remains challenging due to the dynamic nature of traffic flow in IoV. Addressing these challenges, this article introduces GAMA-Cache, an innovative edge content caching methodology leveraging Graph Attention Networks (GAT) and Multi-Agent Reinforcement Learning (MARL). GAMA-Cache conceptualizes the cooperative edge content caching issue as a constrained Markov decision process. It employs a MARL technique predicated on cooperation effectiveness to discern optimal caching decisions, with GAT augmenting information extracted from adjacent nodes. A distinct collaborator selection mechanism is also developed to streamline communication between agents, filtering out those with minimal correlations in the vector input to the policy network. Experimental results demonstrate that, in terms of service latency and delivery failure, the GAMA-Cache outperforms other state-of-the-art MARL solutions for edge content caching in IoV.
The relations between the parameters describing a lattice defect and those that can be derived from a field-ion image of the same defect are discussed in the light of the smooth section approximation for the field-eva...
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The relations between the parameters describing a lattice defect and those that can be derived from a field-ion image of the same defect are discussed in the light of the smooth section approximation for the field-evaporated surface. Methods for analysing field-ion images are outlined and applied to the specific case of an image of dislocation loops. Excellent agreement has been obtained from computer simulation by using the calculated defect parameters.
This book gathers papers presented at the 2019 Movement, Health & Exercise (MoHE) Conference and International Sports Science Conference (ISSC). The theme of this year’s conference was "Enhancing Health and ...
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ISBN:
(数字)9789811532702
ISBN:
(纸本)9789811532696;9789811532726
This book gathers papers presented at the 2019 Movement, Health & Exercise (MoHE) Conference and International Sports Science Conference (ISSC). The theme of this year’s conference was "Enhancing Health and Sports Performance by Design". The content covers (but is not limited to) the following topics: exercise science; human performance; physical activity & health; sports medicine; sports nutrition; management & sports studies; and sports engineering & technology.
This volume brings together the advanced research results obtained by the European COST Action 2102 "Cross Modal Analysis of Verbal and Nonverbal Communication", primarily discussed at the PINK SSPnet-COST21...
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ISBN:
(数字)9783642257759
ISBN:
(纸本)9783642257742
This volume brings together the advanced research results obtained by the European COST Action 2102 "Cross Modal Analysis of Verbal and Nonverbal Communication", primarily discussed at the PINK SSPnet-COST2102 International Conference on Analysis of Verbal and Nonverbal Communication and Enactment: The Processing Issues, held in Budapest, Hungary, in September 2010.
The 40 papers presented were carefully reviewed and selected for inclusion in the book. The volume is arranged into two scientific sections. The first section, Multimodal Signals: Analysis, Processing and Computational Issues, deals with conjectural and processing issues of defining models, algorithms, and heuristic strategies for data analysis, coordination of the data flow and optimal encoding of multi-channel verbal and nonverbal features. The second section, Verbal and Nonverbal Social Signals, presents original studies that provide theoretical and practical solutions to the modelling of timing synchronization between linguistic and paralinguistic expressions, actions, body movements, activities in human interaction and on their assistance for an effective human-machine interactions.
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