The proceedings contain 146 papers. The topics discussed include: trajectory tracking controller design for percutaneous interventional procedures;Bregman divergence based approach for adaptive system identification a...
ISBN:
(纸本)9798350349207
The proceedings contain 146 papers. The topics discussed include: trajectory tracking controller design for percutaneous interventional procedures;Bregman divergence based approach for adaptive system identification and line enhancement;real-time hardware-in-loop testbed for power system analysis;regularized hybrid deep learning for DDoS attack prediction in software defined Internet of Things (SD-IoT);investigation of core loss in electric vehicle induction motor using finite element analysis for performance enhancement;fault-tolerant strategy for asymmetrical half-bridge converter in switched reluctance motor drives;protection coordination impact on reliability of distribution systems.with distributed energy resources;and design and control of shunt active power filter for power quality improvements with PV array.
Recommendation systems.are used widely across many industries, such as e-commerce, multimedia content platforms, and social networks, to provide suggestions that users will most likely consume or connect, thus improvi...
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ISBN:
(纸本)9798400704369
Recommendation systems.are used widely across many industries, such as e-commerce, multimedia content platforms, and social networks, to provide suggestions that users will most likely consume or connect, thus improving the user experience [1]. This motivates people in industry and research organizations to focus on personalization and recommendation algorithms, resulting in many research papers [2, 3]. While academic research mostly focuses on the performance of recommendation algorithms in terms of ranking quality or accuracy, it often neglects key factors that impact how a recommendation system will perform in a real-world environment, including but not limited to business metric definition and evaluation, scalability, recommendation quality control, robustness, fairness, and resource limitations, such as computing and memory resources budgets, engineering workforce cost, etc. The gap in constraints and requirements between academic research and industry limits the broad applicability of many of academia's contributions to industrial recommendation systems. This workshop aspires to bridge this gap by bringing together researchers from both academia and industry. Its goal is to serve as a venue for industrial researchers to share practical insights and for academic researchers to become aware of the additional factors of algorithm adoption in real production systems.
The proceedings contain 43 papers. The topics discussed include: DoA estimation in Ris-assisted network via element sampling and sparse reconstruction;optical- and induction-based data and energy networking in light-b...
ISBN:
(纸本)9798350378597
The proceedings contain 43 papers. The topics discussed include: DoA estimation in Ris-assisted network via element sampling and sparse reconstruction;optical- and induction-based data and energy networking in light-based Internet of Things;a scalable and distributed hierarchical architecture for network monitoring-on-demand;pragmatic semantic communication through quantum channel;ML-based anomaly detection in 6G networks: a survey on the current status, challenges, and future directions;the impact of positional accuracy in 6G networks on urban traffic participant classification;fundamental and practical performance assessment in monostatic ISAC: from sub-6GHz to sub-THz;and profiling ai models: towards efficient computation offloading in heterogeneous edge AI systems.
In order to adapt to the dynamic changes of the network service environment in distributed clusters, achieve more efficient service reconfiguration, and improve the availability, reliability and flexibility of distrib...
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ISBN:
(纸本)9798400716959
In order to adapt to the dynamic changes of the network service environment in distributed clusters, achieve more efficient service reconfiguration, and improve the availability, reliability and flexibility of distributed cluster systems. this paper proposes a QoS-guided distributed cluster service dynamic reconfiguration algorithm based on HBW-GOA (Hybrid Black Widow and Grasshopper Optimization Algorithm). The HBW-GOA algorithm mixes the mutation mechanism in the Black Widow Algorithm and the inter-population influence mechanism in the Locust Algorithm, which improves the overall convergence speed of the algorithm and the quality of the solution. In order to balance the performance of the distributed system and the quality of service for users, this paper designs QoS metrics applicable to distributed cluster systems.as a fitness function to guide the iterative behavior of individuals in the algorithm. Comparative simulation experimental results show that the algorithm proposed in this paper can accelerate the service reconfiguration time, can reduce the overall energy consumption of the system, and improve the resource utilization and service quality.
The effectiveness and reliability of a power distribution system hinge on the establishment and maintenance of efficient coordination between protective relays. Alongside the prevention of unwarranted overloads, inade...
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The development of the national economy cannot be separated from the stable support of the power industry. As an indispensable and important energy source in modern social life and production, the stable supply of ele...
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This paper deeply discusses the storage and query optimization algorithm of distributed database for big data. Firstly, the importance of distributed database storage optimization is analyzed, and key technologies suc...
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With the continuous development of train operation control technology, the iteration of train operation control systems.has been accelerated, leading to an increasing workload of system testing. Currently, most system...
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The generative artificial intelligence-assisted language learning system is a system that utilizes artificial intelligence technology. It provides users with more personalized and efficient language learning services ...
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Aiming at the problem that monitoring data in cross-domain tests face a large amount of data and cross categories, we establish a test monitoring data classification system, study the distributed adaptive data classif...
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