Titlebook: Parallel and Distributed Computing, Applications and Technologies; Proceedings of PDCAT Ji Su Park,Hiroyuki Takizawa,James J. Park Conferen

健談

List-Based Workflow Scheduling Utilizing Deep Reinforcement Learning, random search methods, e.g. genetic algorithm, are the two major categories of scheduling approaches developed to tackle this challenging problem. With the rise of deep reinforcement learning (DRL), this paper tries to apply it to solve the workflow scheduling problem in two different ways. The fir

STAT

Federated Learning for Skin Cancer Classification,erated learning for skin cancer classification. Experimental results demonstrate the potential of the proposed method for enhancing the accuracy of skin cancer classification. The proposed method can achieve 98% accuracy on the HAM10000 [.] dataset.

設想

A Task Offloading and Content Caching Strategy for the Internet of Vehicles in Cloud-Edge Environment,does the number of computational tasks that need to be processed, however, different vehicle users may request the same content, resulting in wasted resources. Therefore, IoV requires better compute offloading and content caching strategies to improve performance with respect to time latency and ene

Pepsin

Privacy-Preserving Retrieval Scheme Over Encrypted Medical Records with Relevance Ranking, concerns, EMRs are usually encrypted before outsourcing them to the cloud storage platform. However, it is difficult to retrieve the encrypted EMRs accurately and efficiently. The existing encrypted data retrieval schemes can hardly achieve the goals of fuzzy multi-keyword search, relevance ranking

orient

A Data-Centric Approach for Efficient and Scalable CFD Implementation on Multi-GPUs Clusters,ly after the single-GPU implementations have achieved optimal performance through numerous optimizations. A novel Data-Centric hybrid MPI-CUDA CFD model is proposed in this paper to enable efficient scalability of CFD applications on large-scale heterogeneous platforms. Based on the Data-Centric app

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同位素

Insider Trading Detection Algorithm in Industrial Chain Based on Logistics Time Interval Characteristics,behavior of conducting insider trading by obtaining insider information. The existing insider trading detection methods of industrial chain do not consider the problems of inefficient industrial chain data characteristics and long trading time span, resulting in poor algorithm effect. Therefore, in

按等級

撕裂皮肉

A Fuzzy Logical RAT Selection Scheme in SDN-Enabled 5G HetNets,an exponential augmentation in mobile data traffic volume. The dense deployment of small base stations and mobile nodes in traffic hotspots is considered one of the potential solutions aimed at satisfying the emerging requirements in 5G/Beyond 5G wireless networks. However, the ultra-densification p

Exposure

SSR-MGTI: Self-attention Sequential Recommendation Algorithm Based on Movie Genre Time Interval,. Traditional movie recommendation systems simply treat user-movie interactions as a time-ordered sequence, without considering the time intervals between movies of the same genre. The genre time interval can reflect the user’s preference for a particular genre and determine whether the algorithm ca