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检索条件"任意字段=International Symposium on Software Engineering for Parallel and Distributed Systems"

共 10743 条记录，以下是531-540 订阅

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Ball-type Small Objection Algorithm based on YOLOv8

Ball-type Small Objection Algorithm based on YOLOv8

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ACIS international Conference on software engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Xinquan Luo Kaiyi Quan Yilong Liu School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9798350391954

ISBN: (纸本)9798350391961

Object detection is an important computer vision task in digital images for a specific class of phenomena (such as people, animals or ball-type objects). To improve the accuracy of small object detection for high-speed moving balls in sports fields, we researched and tested a small object detection model based on the YOLOv8 algorithm. The YOLO algorithm based on deep learning is fast and accurate in operation, making it suitable for real-time systems. On the basis of the original algorithm, we carried out algorithm fusion and parameter adjustments, added a small object detection head to enhance the capability for detecting small objects, incorporated an attention mechanism to increase the precision of object detection, and achieved ball detection in complex backgrounds on the sports field, which played a guiding role in the switching of broadcast camera angles.

关键词： YOLO Adaptation models Head Attention mechanisms Accuracy Computational modeling Object detection

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Integrating RC6 Stream Cipher to A Chaotic Synchronization System 8

Integrating RC6 Stream Cipher to A Chaotic Synchronization S...

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8th IEEE international Conference on Smart Cloud, SmartCloud 2023

作者： Hsiao, Feng-Hsiag Chiu, Po-Wei Chang, Shou-Wen Dept. of Electrical Engineering National University of Tainan Tainan Taiwan

ISBN: (纸本)9798350313505

This study proposes a new fuzzy control method based on Improved Genetic Algorithm (IGA) that employs the parallel distributed Compensation technology to achieve the exponential synchronization of two chaotic systems with multiple time delays. In addition, combining the chaotic synchronization and cryptography concepts will result in a more secured communication system. To ensure the exponential stability of the error system, the initial message (plaintext) is first encrypted using the Rivest cipher 6 (RC6) algorithm and the key, and the encrypted message (ciphertext) re-encrypted through chaotic synchronization, and exponential stability related to time delay is derived by using the Lyapunov function criterion. Afterward, the exponential stability criterion transformed into linear matrix inequality (LMI). A set of fuzzy controller parameters obtained by using the LMI Toolbox of the numerical simulation software M A T L A B. This parameter by the IGA primitive populations to evolve. Given IGA's ability to randomly search for the best solution in the entire domain, it possible to find a better fuzzy controller feedback gain to accelerate the error system's convergence, allowing the master and slave systems to achieve synchronization quickly. ©2023 IEEE.

关键词： Genetic algorithms

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Rapid Hillshade Analysis Method for Photovoltaic System Design by Contour Lines

Rapid Hillshade Analysis Method for Photovoltaic System Desi...

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Energy Storage and Conversion (ISESC), CPSS & IEEE international symposium on

作者： Qiang Dong Haoshu Shao Zenglu Song School of Electronic Information Engineering/School of Integrated Circuits Nanjing Vocational University of Industry Technology Nanjing China School of Electrical Engineering Nanjing Vocational University of Industry Technology Nanjing China

ISBN: (数字)9798350380514

ISBN: (纸本)9798350380521

For promotion of photovoltaic systems in hill areas, it is crucial to accurately analyze the shadow area throughout the year. Field measurement required a lot of manpower and time in the design stage. It is inefficient to directly use geometric formula for the results cannot be imported into the CAD software inconveniently. The shadow analysis tools of some software have low accuracy and lack the function of hill shade analysis in the target time period that is concerned in the design of photovoltaic systems. In this paper, a method of analyzing shadow area by using hill contour rasterization is proposed. This method supports user-defined calculation accuracy to meet different design requirements, and can be combined with AutoCAD in the form of plugin to achieve the purpose of aided design for photovoltaic plants in hill areas.

关键词： Accuracy Layout Programming parallel processing software Time measurement Encoding Solar panels Energy storage

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Empirical Study of Molecular Dynamics Workflow Data Movement: DYAD vs. Traditional I/O systems

Empirical Study of Molecular Dynamics Workflow Data Movement...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Ian Lumsden Hariharan Devarajan Jack Marquez Stephanie Brink David Boehme Olga Pearce Jae-Seung Yeom Michela Taufer Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA Lawrence Livermore National Laboratory Livermore CA USA

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

This experimental work examines data movement in molecular dynamics (MD) workflows, comparing the Dynamic and Asynchronous Data Streamliner (DYAD) middleware with traditional, industry-standard I/O systems such as XFS and Lustre. DYAD moves MD simulation frames to analytics processes, providing enhanced flexibility and efficiency for dynamic data transfers and in situ analytics. At the same time, traditional I/O storage systems provide durability and scalability for high-performance computing (HPC) systems. The study integrates MD workflows with common simulation codes, facilitating immediate capture and transfer of MD frames to a staging area. It explores various molecular models, from simple to complex, assessing data management performance and scalability. Different producer-consumer pairs, molecular models, and data transaction frequency enable testing across small to large-scale HPC scenarios, from single-node configurations to large, distributed environments. The findings reveal that adaptive mechanisms for minimizing synchronization, direct network communication between producer and consumer processes, and optimizations of both data movement and synchronization are crucial for performance and scalability in MD workflows.

关键词： Adaptation models Scalability Computational modeling distributed databases Production Data transfer Aerodynamics

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Machine Learning-based Decision Making for Charging/Discharging Cost Optimization of PREV in Smart City

Machine Learning-based Decision Making for Charging/Discharg...

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parallel Computing and distributed systems (PCDS), international symposium on

作者： Gone Neelakantam dept. Computer Science and Engineering Ecole Centrale School of Engineering Mahindra University Hyderabad India

ISBN: (数字)9798350349658

ISBN: (纸本)9798350349665

Smart cities, equipped with smart grid infrastructure, establish advanced communication networks that facilitate interactions among multiple entities. It is well-known that smart grid technology ensures the reliable transmission of electricity. Additionally, Plug-in Hybrid Electric Vehicles (PHEVs) significantly contribute to the efficient utilization of energy in mobility-aware environments. The Intelligent Transportation System (ITS) enables Vehicle-to-Infrastructure (V2I) communication, which is crucial for providing transportation services and managing PHEV recharging at user-preferred locations. This capability is a key element of smart city infrastructure. To optimize the use of PHEV services in a smart city, addressing the cost minimization of charging and discharging is essential. Therefore, this paper proposes a decision tree machine learning-based algorithm within a fog computing platform aimed at minimizing charging and discharging costs. Performance evaluation demonstrates that the model outperforms existing algorithms in terms of accuracy. These results indicate that our model can accurately predict the costs associated with charging and discharging PHEVs in smart city environments.

关键词： Performance evaluation Costs Machine learning algorithms Smart cities Computational modeling Decision making Prediction algorithms Smart grids Reliability Decision trees

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Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions 20th

Quantum-Inspired Network Optimization in 6G: Opportunities, ...

引用

20th international symposium on distributed Computing and Artificial Intelligence, DCAI 2023

作者： Bouchmal, Oumayma Cimoli, Bruno Stabile, Ripalta Olmos, Juan Jose Vegas Monroy, Idelfonso Tafur Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Software Architecture NVIDIA Corporation Yokneam Israel

ISBN: (纸本)9783031383175

The sixth-generation (6G) wireless networks are envisioned to deliver a paradigm shift in performance, capacity, and complexity compared to the previous generations. The increased complexity, ultra-low latency, and higher data rate requirements of 6G networks require advanced computational capabilities for network optimization, including resource allocation, dynamic slicing, and traffic routing. In this paper, we discuss the need of integrating quantum computing and quantum machine learning for network optimization in 6G. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Resource allocation

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Movie Big Data Intelligent Recommendation System Based on Knowledge Graph 19

Movie Big Data Intelligent Recommendation System Based on Kn...

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19th IEEE international symposium on parallel and distributed Processing with Applications (IEEE ISPA)

作者： Qiu, Gang Guo, Yanli Shandong Univ Sch Software Jinan Peoples R China Changji Univ Changji Peoples R China

ISBN: (纸本)9781665435741

The user-oriented recommendation system enables users to obtain their favorite movie programs from a large number of movies. Knowledge graph is a kind of heterogeneous network information, which provides rich structural knowledge for movie recommendation system. It helps to solve the problem of data sparseness and cold start. Based on this, we designed a movie recommendation model based on the knowledge graph. First, we embed the knowledge graph into the recommendation model, then use the interactive attention network represented by the user/item to update the vector representation, obtain rich neighborhood knowledge through multi-layer interactive information dissemination, and finally make predictions. We test on public data sets, and experiments show that our method is better than existing baseline methods.

关键词： recommendation systems neural networks Attention interactive big data

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software-Defined, Fast and Strongly-Consistent Data Replication for RDMA-Based PM Datastores

Software-Defined, Fast and Strongly-Consistent Data Replicat...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Haodi Lu Haikun Liu Chencheng Ye Xiaofei Liao Fubing Mao Yu Zhang Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computing Science and Technology Huazhong University of Science and Technology China

Modern storage systems typically replicate data on multiple servers to provide high reliability and availability. However, most commercially-deployed datastores often fail to offer low latency, high throughput, and strong consistency at the same time. This paper presents Whale, a Remote Direct Memory Access (RDMA) based primary-backup replication system for in-memory datastores. Whale achieves both low latency and strong consistency by decoupling metadata multicasting from data replication for all backup nodes, and using an optimistic commitment mechanism to respond to client write requests earlier. Whale achieves high throughput by propagating writes from the primary node to backup nodes asynchronously via RDMA-optimized chain replication. To further reduce the cost of data replication, we design a log-structured datastore to fully exploit the advantages of one-sided RDMA and Persistent Memory (PM). We implement Whale on a cluster equipped with PM and InfiniBand RDMA networks. Experimental results show that Whale achieves much higher throughput and lower latency than state-of-the-art replication protocols.

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parallelized Multi-Agent Bayesian Optimization in Lava

Parallelized Multi-Agent Bayesian Optimization in Lava

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Neuromorphic systems (ICONS), international Conference on

作者： Shay Snyder Derek Gobin Victoria Clerico Sumedh R. Risbud Maryam Parsa Electrical and Computer Engineering George Mason University Fairfax USA Neuromorphic Computing Lab Intel Labs Santa Clara USA

ISBN: (数字)9798350368659

ISBN: (纸本)9798350368666

In parallel with the continuously increasing parameter space dimensionality, search and optimization algorithms should support distributed parameter evaluations to reduce cumulative runtime. Intel's neuromorphic optimization library, Lava-Optimization, was introduced as an abstract optimization system compatible with neuromorphic systems developed in the broader Lava software framework. In this work, we introduce Lava Multi-Agent Optimization (LMAO) with native support for distributed parameter evaluations communicating with a central Bayesian optimization system. LMAO provides an abstract framework for deploying distributed optimization and search algorithms within the Lava software framework. Moreover, LMAO introduces support for random and grid search along with process connections across multiple levels of mathematical precision. We evaluate the algorithmic performance of LMAO with a traditional non-convex optimization problem, a fixed-precision transductive spiking graph neural network for citation graph classification, and a neuromorphic satellite scheduling problem. Our results highlight LMAO's efficient scaling to multiple processes, reducing cumulative runtime and minimizing the likelihood of converging to local optima.

关键词： Runtime Neuromorphics Lava Scalability software algorithms software Scheduling Bayes methods Classification algorithms Optimization

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The Design Space of Emergent Scheduling for distributed Execution Frameworks

The Design Space of Emergent Scheduling for Distributed Exec...

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international symposium on software engineering for Adaptive and Self-Managing systems (SEAMS)

作者： Dean, Paul Porter, Barry Univ Lancaster Sch Comp & Commun Lancaster England

ISBN: (纸本)9781665402897

distributed Execution Frameworks (DEFs) such as Apache Spark have become ubiquitous as a solution for the execution of user-defined jobs to process terabytes of data across hundreds of nodes. One of the key costs of DEFs is scheduling of which parts of each job are placed on each host;better scheduling decisions provide lower overall execution time for each job, more efficient resource usage, and reduced energy consumption. Existing DEFs use a static approach to scheduling, either with a single generalised scheduler which aims to be a good fit for most workloads, or with a special-purpose scheduler which is tuned to optimise for a particular kind of workload. In both cases the scheduling implementation is fixed at design-time such that the DEF is unable to adjust to the actual characteristics of workloads that arrive at deployment time. In this paper we introduce an emergent scheduler for distributed Execution Frameworks. This scheduler can be composed and re-composed at runtime from a set of different building blocks, allowing the system to dynamically provide the benefits of differing scheduling policies over time depending on the actual properties of incoming workloads - with improved performance and resource usage. In this paper we present the overall design of our emergent scheduler, we discuss the theoretical design space of different scheduling approaches, and we examine a specific research question to determine the correlation between workload properties and scheduling performance for different scheduler implementations. Our results are based on a real implementation of our emergent DEF running across multiple hosts in a real datacentre, and our implementation is made available as open-source software.

关键词： Energy consumption Runtime Correlation Processor scheduling distributed databases Dynamic scheduling Data processing

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