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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

共 34316 条记录，以下是4981-4990 订阅

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Self-supervised Bidirectional Synchronization Estimation for Multimodal Deepfake Detection with Short-term Dependency 25

Self-supervised Bidirectional Synchronization Estimation for...

引用

Proceedings of the 2025 international conference on Multimedia Retrieval

作者： Man Xiao Jianbin Ye Bo Liu Zijian Gao Kele Xu Xiaodong Wang National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha China Strategic Assessments and Consultation Institute Academy of Military Science Beijing China

ISBN: (纸本)9798400718779

Deepfake technology induces substantial societal challenges, establishing deepfake detection as an important area of research. However, existing research mainly relies on target deepfake datasets, which limits its generalizability across out-of-distribution tasks to some extent. Also, it often emphasizes visual modalities while neglecting the complementary information of the auditory data. Their autoregressive-based strategies also introduce long-term information interference, further constraining the detection performance. Consequently, the potential to exploit complementary relations between visual and auditory modalities and to leverage strongly correlated short-range information remains underexplored for the detection task. To address these challenges, this paper introduces Self-BiSterm, a novel self-supervised learning framework for deepfake detection. First, we propose a bidirectional synchronization distribution modeling mechanism, which calculates inconsistent distributions for video-to-audio and audio-to-video scenarios. This mechanism effectively measures audio-visual inconsistencies, improving the model's generalization performance in practical applications. Second, to mitigate the issue of long-term information distortion, we develop a short-term temporal dependency module to estimate the adjacent local receptive fields. This module facilitates the estimation of subsequent distributions by capturing short-term temporal dependencies with high precision. The effectiveness of the proposed Self-BiSterm framework is validated on various benchmarks, demonstrating superior performance compared to existing methods.

关键词： bidirectional synchronization estimation

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A distributed Approach for Estimation of Information Matrix in Smart grids and its Application for Anomaly Detection

A Distributed Approach for Estimation of Information Matrix ...

引用

2020 international conference on Communications Control and computing Technologies for Smart grids

作者： Moslemi, Ramin Davoodi, Mohammadreza Velni, Javad Mohammadpour Univ Georgia Sch ECE Athens GA 30602 USA

ISBN: (纸本)9781728161273

Statistical structure learning (SSL)-based approaches have been employed in the recent years to detect different types of anomalies in a variety of cyber-physical systems (CPS). Although these approaches outperform conventional methods in the literature, their computational complexity, need for large number of measurements and centralized computations have limited their applicability to large-scale networks. In this work, we propose a distributed, multi-agent maximum likelihood (ML) approach to detect anomalies in smart grid applications aiming at reducing computational complexity, as well as preserving data privacy among different players in the network. The proposed multi-agent detector breaks the original ML problem into several local (smaller) ML optimization problems coupled by the alternating direction method of multipliers (ADMM). Then, these local ML problems are solved by their corresponding agents, eventually resulting in the construction of the global solution (network's information matrix). The numerical results obtained from two IEEE test (power transmission) systems confirm the accuracy and efficiency of the proposed approach for anomaly detection.

关键词： Complex networks

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Fog computing Based Traffic and Car Parking Intelligent System 19th

Fog Computing Based Traffic and Car Parking Intelligent Syst...

引用

19th international conference on Algorithms and Architectures for parallel Processing (ICA3PP)

作者： Alajali, Walaa Gao, Shang Alhusaynat, Abdulrahman D. Deakin Univ Melbourne Vic 3217 Australia Thi Qar Univ Nasiriyah 64001 Iraq

ISBN: (纸本)9783030389611;9783030389604

Internet of Things (IoT) has attracted the attention of researchers from both industry and academia. Smart city, as one of the IoT applications, includes several sub-applications, such as intelligent transportation system (ITS), smart car parking and smart grid. Focusing on traffic flow management and car parking systems because of their correlation, this paper aims to provide a framework solution to both systems using online detection and prediction based on fog computing. Online event detection plays a vital role in traffic flow management, as circumstances, such as social events and congestion resulting from accidents and roadworks, affect traffic flow and parking availability. We developed an online prediction model using an incremental decision tree and distributed the prediction process on fog nodes at each intersection traffic light responsible for a connecting road. It effectively reduces the load on the communication network, as the data is processed, and the decision is made locally, with low storage requirements. The spatially correlated fog nodes can communicate if necessary to take action for an emergency. The experiments were conducted using the Melbourne city open data.

关键词： Traffic flow Prediction ITS Smart car parking

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Data-driven Energy Theft Detection in Modern Power grids 21

Data-driven Energy Theft Detection in Modern Power Grids

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12th ACM international conference on Future Energy Systems, e-Energy 2021

作者： Althobaiti, Ahlam Jindal, Anish Marnerides, Angelos K. School of Computing and Communications Lancaster University United Kingdom School of Computer Science and Electronic Engineering University of Essex United Kingdom School of Computing Science University of Glasgow United Kingdom

ISBN: (纸本)9781450383332

Energy theft is an old and multifaceted phenomenon affecting our society on a global scale from both an operational as well as from a monetary perspective. The relatively recent decentralisation of the grid infrastructure with the integration of distributed Renewable Energy Resources (DRES) in synergy with the widely adopted demand-response business model, has undoubtedly broadened the spectrum of attack surface enabling energy theft. Conventional data-driven energy theft detection schemes have a strong dependency on assessing the spatio-temporal patterns of SCADA measurements aggregated at the Distribution System Operator (DSO) or Transmission System Operator (TSO) with minimal consideration of the intrinsic weather patterns related to individual DRES deployments. Hence, theft scenarios instrumented by DRES owners consuming the energy they produce (i.e., prosumers) can effectively be stealthy and hard to spot. Therefore, in this work we introduce a data-driven, SCADA-agnostic energy theft detection framework explicit to DRES-based scenarios. We provide a comprehensive formalisation of a DRES-based theft attack model and further assess the performance of our framework by utilising and relating freely available third-party weather measurements with real solar and wind turbine deployments in Australia and France. Evidently, our proposed framework yields an energy theft detection accuracy rate of over 98% with optimal computational costs. Thus, reasonably addressing the highly demanding requirements of low-cost and accurate real-time energy theft detection in modern power grids. © 2021 ACM.

关键词： Smart power grids

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distributed Graph Analytics 16th

Distributed Graph Analytics

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16th international conference on distributed computing and Internet Technology (ICDCIT)

作者： Srikant, Y. N. Indian Inst Sci Bengaluru 560012 India

ISBN: (纸本)9783030369873;9783030369866

Graph Analytics is important in different domains: social networks, computer networks, and computational biology to name a few. This paper describes the challenges involved in programming the underlying graph algorithms for graph analytics for distributed systems with CPU, GPU, and multi-GPU machines and how to deal with them. It emphasizes how language abstractions and good compilation can ease programming graph analytics on such platforms without sacrificing implementation efficiency.

关键词： Graph analytics Social networks parallel algorithms Multi-core processors GPU computation Graph frameworks Graph processing languages

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Communication Avoiding 2D Stencil Implementations over PaRSEC Task-Based Runtime 34

Communication Avoiding 2D Stencil Implementations over PaRSE...

引用

34th IEEE international parallel and distributed Processing Symposium (IPDPS)

作者： Pei, Yu Cao, Qinglei Bosilca, George Luszczek, Piotr Eijkhout, Victor Dongarra, Jack Univ Tennessee Innovat Comp Lab Knoxville TN 37996 USA Univ Texas Austin Texas Adv Comp Ctr Austin TX USA

ISBN: (纸本)9781728174457

Stencil computation or general sparse matrix-vector product (SpMV) are key components in many algorithms like geometric multigrid or Krylov solvers. But their low arithmetic intensity means that memory bandwidth and network latency will be the performance limiting factors. The current architectural trend favors computations over bandwidth, worsening the already unfavorable imbalance. Previous work approached stencil kernel optimization either by improving memory bandwidth usage or by providing a Communication Avoiding (CA) scheme to minimize network latency in repeated sparse vector multiplication by replicating remote work in order to delay communications on the critical path. Focusing on minimizing communication bottleneck in distributed stencil computation, in this study we combine a CA scheme with the computation and communication overlapping that is inherent in a dataflow task-based runtime system such as PaRSEC to demonstrate their combined benefits. We implemented the 2D five point stencil (Jacobi iteration) in PETSc, and over PaRSEC in two flavors, full communications (base-PaRSEC) and CA-PaRSEC which operate directly on a 2D compute grid. Our results running on two clusters, NaCL and Stampede2 indicate that we can achieve 2X speedup over the standard SpMV solution implemented in PETSc, and in certain cases when kernel execution is not dominating the execution time, the CA-PaRSEC version achieved up to 57% and 33% speedup over base-PaRSEC implementation on NaCL and Stampede2 respectively.

关键词： 2D stencil communication avoiding parallel programming models

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3rd EAI international conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

3rd EAI International Conference on Multimedia Technology an...

引用

3rd EAI international conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

ISBN: (纸本)9783030825614

The proceedings contain 97 papers. The special focus in this conference is on Multimedia Technology and Enhanced Learning. The topics include: Research on the Method of Eliminating Duplicated Encrypted Data in Cloud Storage Based on Generated Countermeasure Network;design of distributed Hybrid Pipeline Multimedia Aided Scheduling System;intelligent Scheduling of distributed Displacement Pipeline Based on Hybrid Discrete Drosophila Optimization Algorithm;research on grid Planning Method of Distribution Network Based on Artificial Intelligence Technology;intelligent Monitoring Method for Backstage Data Security of Tourism Information Promotion Platform Based on Cloud computing;preface;research on Multithreaded Data Scheduling Control Method for Power Communication Based on Wireless Sensor;research on Industrial Product Modeling Design Method Based on Deep Learning;a Frequency Conversion Circuit for Piezoelectric Vibrating Energy Harvesting;an Adaptive Optimization Strict Reverse Navigation Algorithm for Ship Fine Alignment Process;research on Load Feature Extraction Method of Typical Users Based on Deep Learning;enterprise Financial Risk Early Warning System Based on Catastrophe Progression Method;research on Transportation Route Planning Method of Regional Logistics Network Based on Transfer Learning;simultaneous Localization of Multiple Defects in Software Testing Based on Reinforcement Learning;Design of Embedded Network Human Machine Interface Based on VR Technology;Design of Information Security System Based on JSP Technology and Reinforcement Model;sliding Mode Adaptive Control for Sensorless Permanent Magnet Synchronous Motor;recognition Method of Metal Material Pitting Defect Based on Visual Signal Processing;an Improved Detection Method of Safety Helmet Wearing Based on CenterNet;influence Maximization Based on True Threshold in Social Networks;arabic Question-Answering System Using Search Engine Techniques.

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DROAllocator: A Dynamic Resource-Aware Operator Allocation Framework in distributed Streaming Processing 17th

DROAllocator: A Dynamic Resource-Aware Operator Allocation ...

引用

17th IFIP WG 10.3 international conference on Network and parallel computing, NPC 2020

作者： Liu, Fan Jin, Zongze Mu, Weimin Zhu, Weilin Zhang, Yun Wang, Weiping Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030794774

With the rapid development of Internet services and the Internet of Things (IoT), many studies focus on operator allocation to enhance the DSPAs’ (data stream processing applications) performance and resource utilization. However, the existing approaches ignore the dynamic changes of the node resources to allocate the operator instances to guarantee the performance, which increasing the number of migration leads to the waste of resources and the instability. To address these issues, we propose a framework named DROAllocator to select the appropriate nodes to allocate the operator instances. By capturing the change tendency of the node resources and the operator performance, our allocation mechanism decreases the number of migration to enhance the performance. The experimental results show the DROAllocator not only decrease the number of migrations to allocate the operator instances to ensure the end-to-end throughput and the latency, but also enhance the resource utilization. © 2021, IFIP international Federation for Information Processing.

关键词： Internet of things

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On-line monitoring system of grounding wire condition based on data acquisition technology

On-line monitoring system of grounding wire condition based ...

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The international conference on Forthcoming Networks and Sustainability (FoNeS 2022)

作者： H. Li Q. Wang S. Xie State Grid Jibei Electric Power Company Limited Skills Training Center Baoding Technical College of Electric Power Baoding Hebei People's Republic of China

In the power system, the transmission lines are scattered and difficult to protect and repair. The traditional safety measures for maintenance of transmission lines are very monotonous. Most of the task process is directly involved in manual work, and there is no testing facility for hanging ground wires, which is inefficient and unsafe. The main purpose of this paper is to design and improve the monitoring of the state of the ground wire based on the data acquisition technology. A simulation model considering the grounding wire is built, and the influence of different frequency signal injection, multi-branch line, transformer no-load input, the same pole in parallel, the earth-coupled grounding equivalent resistance and other factors are analyzed by simulation. Experiments show that when the frequency of the detection signal is 120 Hz, if the length of the detected line is longer and the grounding resistance is greater, the measured value of the response current when the grounding wire is in the grounding state and the measured value of the response current when there is no grounding wire is the same the smaller the difference.

关键词： computerised monitoring data acquisition earthing Internet power engineering computing wires (electric)

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TorqueDB: distributed Querying of Time-Series Data from Edge-local Storage 26th

TorqueDB: Distributed Querying of Time-Series Data from Edge...

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26th international conference on parallel and distributed computing (Euro-Par)

作者： Garg, Dhruv Shirolkar, Prathik Shukla, Anshu Simmhan, Yogesh Ericsson Res Bangalore Karnataka India Indian Inst Sci Bangalore Karnataka India

ISBN: (纸本)9783030576752;9783030576745

The rapid growth in edge computing devices as part of Internet of Things (IoT) allows real-time access to time-series data from 1000's of sensors. Such observations are often queried to optimize the health of the infrastructure. Recently, edge storage systems allow us to retain data on the edge rather than moving them centrally to the cloud. However, such systems do not support flexible querying over the data spread across 10-100's of devices. There is also a lack of distributed time-series databases that can run on the edge devices. Here, we propose TorqueDB, a distributed query engine over time-series data that operates on edge and fog resources. TorqueDB leverages our prior work on ElfStore, a distributed edge-local file store, and InfluxDB, a time-series database, to enable temporal queries to be decomposed and executed across multiple fog and edge devices. Interestingly, we move data into InfluxDB on-demand while retaining the durable data within ElfStore for use by other applications. We also design a cost model that maximizes parallel movement and execution of the queries across resources, and utilizes caching. Our experiments on a real edge, fog and cloud deployment show that TorqueDB performs comparable to InfluxDB on a cloud VM for a smart city query workload, but without the associated monetary costs.

关键词： Edge storage Time-series database distributed querying Internet of Things Cloud computing

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