the proceedings contain 55 papers. the special focus in this conference is on parallel and distributedcomputing: applications and technologies. the topics include: A Meta-reinforcement Learning Framework for Ada...
ISBN:
(纸本)9789819642069
the proceedings contain 55 papers. the special focus in this conference is on parallel and distributedcomputing: applications and technologies. the topics include: A Meta-reinforcement Learning Framework for Adaptive Quadrotor UAV Attitude Control;Securing Energy Transactions for Electric Vehicles: the Blockchain Approach and Encrypted NFTs;optimizing Task Allocation in Heterogeneous Agent Manufacturing Systems;MPG: Multi-modal Personal Health Graph for Alzheimer’s Disease Diagnosis;SMAC: A Secure Multi-authority Access Control Scheme with Attribute Unification for Fog Enabled IoT in E-Health;Convolutional Neural Networks Parameter Training for SCM Algorithm Based on Hausdorff Difference;handling Non-stationarity with Distribution Shifts and Data Dependency in Time Series Forecasting;the Two-Stage Stochastic Facility Location Game;regularized Non-monotone γ-weakly Submodular Maximization;fed-MoE: Efficient Federated Learning for Mixture-of-Experts Models via Empirical Pruning;WaitIO-Hybrid: Communication for Coupling MPI Programs Among Heterogeneous Systems;the Material Delivery Route Prediction Method Based on Deep Reinforcement Learning;privacy-Preserving in Medical Image Analysis: A Review of Methods and applications;research on Task Migration Problem Based on Link Uncertainty in Adversarial Scenarios;optimizing Production Component Scheduling in Multivariate Industrial Networks with Dynamic Changes in Production Costs;multi-agent Collaboration for Time-Sensitive Tasks in Multiple Networked Adversarial Scenarios;containerized Data-Flow Processing for Scalable Real-Time Analytics on Edge Devices;fast Approximation for Scheduling Malleable Jobs on parallel Batch Machines with Rejection;real-Time and In-Situ Temperature Profiling for Determining Detonation of White Dwarf Mergers;accparser: A Standalone OpenACC Parser and Its Usage on Mapping OpenACC to OpenMP Directives;Out-of-Memory GPU Sorting Using Asynchronous CUDA Streams;long-Term and Periodicity-Aware Spatio
the proceedings contain 28 papers. the special focus in this conference is on parallel and distributedcomputing, applications and technologies. the topics include: Insider Trading Detection Algorithm in Industrial Ch...
ISBN:
(纸本)9789819982103
the proceedings contain 28 papers. the special focus in this conference is on parallel and distributedcomputing, applications and technologies. the topics include: Insider Trading Detection Algorithm in Industrial Chain Based on Logistics Time Interval Characteristics;link Attributes Based Multi-service Routing for Software-Defined Satellite Networks;A Fuzzy Logical RAT Selection Scheme in SDN-Enabled 5G HetNets;SSR-MGTI: Self-attention Sequential Recommendation Algorithm Based on Movie Genre Time Interval;fine Time Granularity Allocation Optimization of Multiple Networks Industrial Chains in Task Processing Systems;Ε-Maximum Critic Deep Deterministic Policy Gradient for Multi-agent Reinforcement Learning;effective Density-Based Concept Drift Detection for Evolving Data Streams;an End-to-End Multiple Hyper-parameters Prediction Method for distributed Constraint Optimization Problem;Formalization and Verification of the Zab Protocol Using CSP;dynamic Priority Coflow Scheduling in Optical Circuit Switched Networks;Deep Reinforcement Learning Based Multi-WiFi Offloading of UAV Traffic;Triple-Path RNN Network: A Time-and-Frequency Joint Domain Speech Separation Model;design of Query Based Gallery Selector and Mask-Aware Loss for Person Search;a Privacy-Preserving Blockchain Scheme for the Reliable Exchange of IoT Data;R-RPT-A Reliable Routing Protocol for Industrial Wireless Sensor Networks;action Segmentation Based on Encoder-Decoder and Global Timing Information;Security Challenges and Lightweight Cryptography in IoT: Comparative Study and Testing Method for PRESENT-32bit Cipher;the Prediction Model of Water Level in Front of the Check Gate of the LSTM Neural Network Based on AIW-CLPSO;Using MPIs Non-Blocking Allreduce for Health Checks in Dynamic Simulations;parallelizable Loop Detection using Pre-trained Transformer Models for Code Understanding;list-Based Workflow Scheduling Utilizing Deep Reinforcement Learning.
the proceedings contain 94 papers. the topics discussed include: optimizing deep learning split deployment for IoT edge networks;efficient fault-tolerant syndrome measurement of quantum error-correcting codes based on...
ISBN:
(纸本)9781728126166
the proceedings contain 94 papers. the topics discussed include: optimizing deep learning split deployment for IoT edge networks;efficient fault-tolerant syndrome measurement of quantum error-correcting codes based on 'flag';comparison of binary rain prediction on HIMAWARI using MPI and CUDA;effect of parallel processing by duplicating histogram in automatic image binarization for high-level synthesis;joint mobile data collection and energy supply scheme for rechargeable wireless sensor networks;ultra reliable communication: availability analysis in 5G cellular networks;an improved online multidimensional bin packing algorithm;and improving recommender systems accuracy in social networks using popularity.
the proceedings contain 49 papers. the special focus in this conference is on parallel and distributedcomputing, applications and technologies. the topics include: A real-time routing protocol in wireless sensor-actu...
ISBN:
(纸本)9789811359064
the proceedings contain 49 papers. the special focus in this conference is on parallel and distributedcomputing, applications and technologies. the topics include: A real-time routing protocol in wireless sensor-actuator network;privacy preserving classification based on perturbation for network traffic;fault diagnosis of a wireless sensor network using a hybrid method;an optimization theory of home occupants’ access data for determining smart grid service;automatic classification of transformed protocols using deep learning;covert timing channel design for uniprocessor real-time systems;parallelization of the DIANA algorithm in openMP;Flash animation watermarking algorithm based on SWF tag attributes;efficient scheduling strategy for data collection in delay-tolerant wireless sensor networks with a mobile sink;analysis of massive e-learning processes: An approach based on big association rules mining;SGNet: Design of optimized DCNN for real-time face detection;A study on L1 data cache bypassing methods for high-performance GPUs;Memory contention aware power management for high performance GPUs;Dynamic selective warp scheduling for GPUs using L1 data Cache locality information;an efficient model and algorithm for privacy-preserving trajectory data publishing;what makes charitable crowdfunding projects successful: A research based on data mining and social capital theory;A SwarmESB based architecture for an european healthcare insurance system in compliance with GDPR;a study on deriving and simulating pre-risk on complex gas facilities for preventing accidents;body gesture modeling for psychology analysis in job interview based on deep spatio-temporal approach;green vs revenue: Data center profit maximization under green degree constraints;evaluation for two bloom filters’ configuration.
According to Gartner, 95% of workloads will shift to containers by 2025 due to its lightweight feature. Docker is a commonly used container software for binding applications;the container orchestration system Kubernet...
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ISBN:
(数字)9798350385922
ISBN:
(纸本)9798350385939;9798350385922
According to Gartner, 95% of workloads will shift to containers by 2025 due to its lightweight feature. Docker is a commonly used container software for binding applications;the container orchestration system Kubernetes (K8s) manages resources seamlessly across Cloud, Fog, and Edge environments through containers. However, Nodes in the cluster introduces the risk of exceeding node capacity thresholds, leading to failures and potential application loss which degrades the Quality of Service (QoS). In this regard, Multi-Criteria Decision Making (MCDM) strategy for ranking the nodes in the cluster is proposed to achieve the migration decision in the Geo-distributed cluster for both stateful and stateless application servers using K8s. the proposed strategy has achieved a 15.94sec Average service restore time for the Nginx server and 48.99sec for the Zookeeper server. A proactive Deep Learning model BI-LSTM is proposed for resource utilization prediction of the cluster and achieved MAE of 0.01928 and 0.0206 for CPU and Memory utilization.
In Synchronous Reluctance Machines (SynRM), achieving a higher saliency ratio and lower torque ripple is important. While Fractional Slot Concentrated Winding (FSCW) machines have better efficiency because of shorter ...
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ISBN:
(纸本)9798350385939;9798350385922
In Synchronous Reluctance Machines (SynRM), achieving a higher saliency ratio and lower torque ripple is important. While Fractional Slot Concentrated Winding (FSCW) machines have better efficiency because of shorter winding overhang, their saliency is significantly reduced due to the presence of undesirable magnetomotive force (MMF) space harmonics. distributed windings (DW), on the other hand, have lesser torque ripple and higher saliency, but they suffer from lower efficiency because of their higher winding overhang. this paper presents methods of improving saliency by modifying the winding layout of FSCW which helps to reduce or eliminate certain undesired MMF harmonics, while achieving shorter overhang than distributed winding. In addition to saliency, various performance metrics including voltage distortion, efficiency, power factor, and torque ripple have been examined and compared withthose of FSCW and distributed winding configurations.
the rapidly advancing fields of machine learning and mathematical modeling, greatly enhanced by the recent growth in artificial intelligence, are the focus of this special issue. this issue compiles extensively revise...
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the rapidly advancing fields of machine learning and mathematical modeling, greatly enhanced by the recent growth in artificial intelligence, are the focus of this special issue. this issue compiles extensively revised and improved versions of the top papers from the workshop on Mathematical Modeling and Problem Solving at PDPTA'23, the 29thinternationalconference on parallel and distributed Processing Techniques and applications. Covering fundamental research in matrix operations and heuristic searches to real-world applications in computer vision and drug discovery, the issue underscores the crucial role of supercomputing and parallel and distributedcomputing infrastructure in research. Featuring nine key studies, this issue pushes forward computational technologies in mathematical modeling, refines techniques for analyzing images and time-series data, and introduces new methods in pharmaceutical and materials science, making significant contributions to these areas.
Withthe increasing penetration of renewable sources, distributed Energy Resources (DER) are emerging as a crucial components of modern power systems. In a distribution system integrated withdistributed Generation Sy...
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ISBN:
(纸本)9798350385939;9798350385922
Withthe increasing penetration of renewable sources, distributed Energy Resources (DER) are emerging as a crucial components of modern power systems. In a distribution system integrated withdistributed Generation Systems (DG's), efficient power management is crucial to minimize energy losses and maximize effective utilization of electrical energy. the power losses in distribution system have been on higher side due to low X/R ratio and high AT&C losses. this paper presents the minimization of power losses in a radial distribution system integrated with DG's. the load flow analysis is carried out using Forward-Backward Sweep (FBS) method. the optimal power levels of DG's for power loss reduction are obtained by using Particle Swarm Optimization (PSO) algorithm. the proposed method is efficient on a standard IEEE 15 bus radial distribution system.
the Uniform Manifold Projection and Approximation (UMAP) assisted Feature-type distributed Clustering (FDC) workflow, contrary to the traditional UMAP algorithm, was found to be more informative for dimensionality red...
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ISBN:
(纸本)9798350385939;9798350385922
the Uniform Manifold Projection and Approximation (UMAP) assisted Feature-type distributed Clustering (FDC) workflow, contrary to the traditional UMAP algorithm, was found to be more informative for dimensionality reduction in tabular Clinical and Biomedical Routine Data (CBRD) due to the presence of diverse feature-types in such datasets. However, the prospect of using powerful neural network models for the Feature-type distributed dimensionality reduction task is yet to be explored. Considering the broader applicative potential of neural networks, we compared some autoencoder-based neural networks as an alternative to the UMAP algorithm for the FDC workflow. the study uses standard objective measures such as Silhouette Score and DB-Index to compare the quality of clusters and embeddings generated by the Autoencoder-assisted FDC (FDC-AE) approaches withthe established UMAP-assisted FDC (FDC-UMAP) workflow. the evaluation involved two datasets in each size category from the medical field. the results indicate that for a dimensionality reduction and cluster identification task, the FDC-AE can be more effective compared to the FDC-UMAP, especially on larger datasets. Our research opens up the possibility of feature-distributed multi-label supervised dimensionality reduction, as well as the usage of pre-trained networks for such complex dimensionality reduction tasks.
this research presents a novel wavelet transform and machine learning-based method to microgrid protection, with a focus on the Unified Power Flow Controller (UPFC). Microgrid components such as distribution generator...
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ISBN:
(纸本)9798350385939;9798350385922
this research presents a novel wavelet transform and machine learning-based method to microgrid protection, with a focus on the Unified Power Flow Controller (UPFC). Microgrid components such as distribution generators are critical to enhancing the reliability of electricity networks. For different sources and loads to integrate smoothly, effective defect identification is required. the technique uses wavelet transform to extract meaningful information from failure signals, which is then fed into a machine learning model for real-time identification. this method analyzes current signals from both ends of the transmission line using wavelet-based multi-resolution analysis, and then compares the results to preset thresholds to generate fault indices. this approach offers a reliable microgrid protection solution with lower losses and increased dependability.
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