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检索条件"任意字段=6th International Conference on Applied Parallel Computing"

共 2709 条记录，以下是31-40 订阅

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Workspace Calculation of the 2(6-UPS) Hybrid Manipulator 12

Workspace Calculation of the 2(6-UPS) Hybrid Manipulator

引用

12th RSI international conference on Robotics and Mechatronics, ICRoM 2024

作者： Gheybi, Mohammad Mahdi Moghimi, Hediye Namazian, Parsa Varshovi-Jaghargh, Payam Masouleh, Mehdi Tale School of Mechanical Engineering University of Tehran Human and Robot Interaction Laboratory Tehran Iran Hamedan University of Technology Department of Mechanical Engineering Hamedan Iran

ISBN: (纸本)9798331529734

this paper presents an algorithm for computing the workspace of the hybrid serial-parallel manipulator. In this method, the inverse kinematics problem and interval analysis are applied to determine the constant-orientation workspace of the 6-UPS parallel manipulator. then, the workspace of the 2(6-UPS) hybrid manipulator is calculated by combining this approach with the discretization method. the results show that the development of this method provides fast and accurate results for calculating the workspace of the hybrid serial-parallel manipulator. © 2024 IEEE.

关键词： Inverse kinematics

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A Float-Point Arithmetic Logic Unit for High Performance RISC-V Processor 6

A Float-Point Arithmetic Logic Unit for High Performance RIS...

引用

6th international conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Wei, Chunyuan Yuan, Chuan Qi, Yu Xu, Bangjian Niu, Xin College of Computer Science and Electronic Engineering Hunan University Changsha China College of Electrical and Information Engineering Hunan University Changsha China College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Laboratory Changsha China

ISBN: (纸本)9798331541750

With the rapid advancement of artificial intelligence, chips have become increasingly important. the emerging RISC-V instruction set gradually provides powerful computing support for this field. In this context, along with the computing requirements of deep learning, this paper presents the design of a high-performance floating-point arithmetic logic unit (FALU) that facilitates calculations with double-precision, single-precision, half-precision, and Bfloat16 precision data. this design is based on a single-channel algorithm with merged rounding. It improves and implements a composite adder that combines high and low bits. It also proposes a tree-like floating-point comparator based on the Kogge-Stone parallel prefix network. To ensure that the FALU components meet performance requirements, we undergo functional verification in the Vivado simulation environment. Operating at 1.47GHz under the 28nm CMOS process, the components achieve the predetermined performance indicators. © 2024 IEEE.

关键词： Computer circuits

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Smart Grid Solutions for Sustainable Mining: A Cost-Effective Energy Management Framework with Optimization Algorithms 6

Smart Grid Solutions for Sustainable Mining: A Cost-Effectiv...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Parvathareddy, Sravani Yahya, Abid Amuhaya, Lilian Livutse Samikannu, Ravi Department of Electrical and Communications Systems Engineering Botswana International University of Science and Technology Palapye Botswana Department of EEE New Era Engineering College South East Botswana

ISBN: (纸本)9798331522667

this research work focuses on conceptualizing and modeling smart grid infrastructure. the project's main objective is to develop a smart grid infrastructure to improve energy management in industrial processes. Regenerate has deployed a system that uses renewable energy sources like solar photovoltaic (PV) arrays and wind turbines combined with batteries for energy storage. this research work describes a method that first creates synthetic data and then uses a polynomial function to precisely model the statistical fluctuations inherent in the output of renewable energy sources. the process is carried out using MATLAB. A simulation model created using Simulink is also applied to build a smart grid that includes dynamic load control, demand side management DSM, and various control system configurations. the simulation demonstrates that it is possible to produce electricity with minimal or no depreciation related to an increased dependency on renewable energy sources. It can also function at a higher ratio of energy output produced by traditional sources than previously credited within New Zealand while having substantially fewer overall expenses associated with carbon emissions. © 2025 IEEE.

关键词： Demand side management

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Network Adaptive Node Acceleration Method based on Pruning Technology 6

Network Adaptive Node Acceleration Method based on Pruning T...

引用

6th IEEE Information Technology, Networking, Electronic and Automation Control conference, ITNEC 2023

作者： Yang, Yihang Dalian University of Technology Leicester International Institute Dalian116024 China

ISBN: (纸本)9781665460033

Network security is an important research direction in today's times. Neural connection-level clipping, taking specific parameters as objects or clear network connections, can make network clipping more refined, improve controllability, and reduce the impact on network performance as much as possible. However, they will obtain a large number of irregular memory in the calculation, which could be better for parallel computing and affect the computing efficiency of the network. the pruning algorithm studied in this paper can effectively improve network transmission efficiency. In real-time network traffic monitoring, the proposed algorithm shows a practical acceleration effect. this algorithm provides strong support for the research of network adaptive node acceleration. © 2023 IEEE.

关键词： Network security

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Research on Task Scheduling Methods in 5G Mobile Edge computing Environments 6

Research on Task Scheduling Methods in 5G Mobile Edge Comput...

引用

6th international conference on Energy, Power and Grid, ICEPG 2024

作者： Zhu, Guangping Liu, Tianji Guo, Yongshan Xia, Danlei Lv, Dongdong Zhang, Xiaohui State Grid Information and Telecommunication Group Co Ltd. Research and Development Center Beijing China State Grid Information and Telecommunication Group Co. Ltd Research Development Center Beijing China

ISBN: (纸本)9798350377798

With the development of smart grids, power data presents characteristics of massive volume, high speed, and high heterogeneity, posing higher requirements for data processing and transmission capabilities. the innovation of 5G technology has made edge computing more widely applied in smart grids, helping to solve data transmission bottlenecks, reduce latency, and enhance real-time monitoring capabilities. this paper combines the FCFS, EDF, and SJF algorithms to propose a new comprehensive scheduling algorithm, DWECS (Dynamic Weighted Edge computing Scheduler). By setting task priorities and resource allocation strategies, DWECS effectively improves task completion efficiency and controls system operating costs. this research provides a new method for edge computing task scheduling in smart grids and supports the intelligent and economic management of distribution networks. © 2024 IEEE.

关键词： Scheduling algorithms

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Disentangled and parallel Fusion Graph Neural Network for Human Motion Prediction 6

Disentangled and Parallel Fusion Graph Neural Network for Hu...

引用

6th international conference on Data Science and Information Technology, DSIT 2023

作者： Li, Zijing Beijing Jiaotong University Institute of Information Science School of Computer and Information Technology Beijing China

ISBN: (纸本)9798350304442

Human motion prediction is an essential problem for many applications in machine intelligence which needs forecasting future body poses given observed pose sequence. Many approaches to this problem tend to look at gestures as a whole, which complicates the problem in elaborate scenarios. In this paper, we propose a disentangled gragh neural network that decouples the whole body into several components to obtain an accurate representation of different human motions. A disentangled multi-scale human representation is proposed to extract multi-scale features of each body part. In order to match the disentangled multi-scale human representation, we propose a disentangled multi-stream graph neural network. To model the motion correlation of different parts of the human body, feature fusion is performed in parallel between different scales of the whole multi-stream network. In order to solve the problem of network degradation, a residual fusion module is proposed to strengthen the feature fusion. On the H3.6M motion prediction dataset, the proposed disentangled and parallel fusion graph neural network improves the human motion prediction performance compared with similar algorithms. © 2023 IEEE.

关键词： Graph neural networks

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Human Motion Prediction via Adaptive Fusing Autoregressive and Non-Autoregressive Attention Networks 6

Human Motion Prediction via Adaptive Fusing Autoregressive a...

引用

6th international conference on Software Engineering and Computer Science, CSECS 2023

作者： Li, Xuanqi Liu, Xianqin Zhang, Yijun Hu, Jianfang Sun Yat-sen University China National Information Center GACC China

ISBN: (纸本)9798350306378

Human motion prediction is a challenging task that aims to predict future human poses based on an observed historical pose sequence. Previous approaches typically use an encoder-decoder model to extract spatiotemporal features of human motion, decode features and generate future poses either in an autoregressive or non-autoregressive manner. the former suffers from the issue of error accumulation, resulting in poor long-term predictions. the latter does not explicitly model temporal dependencies between predicted frames, which may adversely affect overall quality. To address the above issues, in this paper, we propose a novel hybrid framework combining autoregressive and non-autoregressive fashions. It employs a multi-branch parallel architecture to capture temporal dependencies at various time scales and the multi-head self-attention mechanism to encode spatial correlations among different body joints. Besides, we design a time-adaptive fusion module to integrate prediction outputs from each branch. We demonstrate the effectiveness of our proposed approach by surpassing previous state-of-the-art methods on two benchmark datasets. © 2023 IEEE.

关键词： parallel architectures

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A Study of parallel Ant Colony Optimization with CUDA-Based Implementation 6

A Study of Parallel Ant Colony Optimization with CUDA-Based ...

引用

6th IEEE international conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Zeng, Zhi Cai, Yuxing Wu, Zhipan Wang, Huabin Chung, Kwok L. School of Computer Science and Engineering Huizhou University Guangdong516007 China

ISBN: (纸本)9798350399059

this paper introduces Ant Colony Optimization (ACO) algorithms implemented using CUDA technology for parallelization, inspired by the intelligent behavior of ants in nature. the goal is to demonstrate their efficiency in real-world applications, particularly in improving vehicle routing and scheduling in transportation and logistics. the ACO algorithm has proven to enhance operational efficiency and increase customer satisfaction. By integrating ACO principles with CUDA parallel computing, their performance has been extended to include domains like electromagnetic scattering computations and microwave antenna designs. © 2023 IEEE.

关键词： Ant colony optimization

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Rear-End Collision Avoidance Using Multi-Agent Deep Reinforcement Learning 6

Rear-End Collision Avoidance Using Multi-Agent Deep Reinforc...

引用

6th international conference on Advancements in computing, ICAC 2024

作者： Perera, Ranuja Arawwala, Surith Harshamali, Shalika Perera, Yohan Rathnayake, Samadhi Amarasena, Nelum Chathuranga Adikari, Sasadara Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka University of Sri Jayawardenapura Faculty of Applied Sciences Nugegoda Sri Lanka

ISBN: (纸本)9798331517878

this research paper offers a novel approach to detect rear-end collisions and increase the acceleration of the victim car to possibly avoid or minimize the impact of the collision. A Deep Q-Learning model is utilized to predict the collision, the optimum acceleration of the victim car and the optimum braking of the committer car. the study uses a multi-agent reinforcement learning framework in a simulated environment, focusing on synchronized responses between lead and following vehicles. A comprehensive reward function encourages safe driving behaviors, optimized braking, and successful obstacle detection and avoidance. the continuous action space allows for subtle vehicle control, enhancing the system's adaptability to various collision scenarios. Experimental results demonstrate an overall improvement in collision avoidance and impact reduction over 5000 training episodes. this approach addresses a critical gap in existing safety systems by specifically targeting rear-end collisions, offering the potential for a significant reduction in accident rates and severity. Future work includes real-world testing and expansion to more complex traffic scenarios. © 2024 IEEE.

关键词： Deep reinforcement learning

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Event-Triggered Switched Observers for Networked Distributed Multi-Agent Systems via Cloud computing 6

Event-Triggered Switched Observers for Networked Distributed...

引用

6th international conference on Electronic Engineering and Informatics, EEI 2024

作者： Zhang, Chen Ren, Hongru Ma, Hui Zhou, Qi School of Automation Guangdong University of Technology Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China School of Mathematics and Statistics Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9798350353594

this paper designs event-triggered switched observers for the networked distributed multi-agent systems based on the cloud computing systems. Firstly, a novel cloud computing system architecture is designed, in which each group of agents can interact with each others through distributed cloud nodes, and each cloud node also serves as an event-triggered switched observer to observe the topologies of the systems. Secondly, event-triggered switched observers are designed, which can assist distributed agents in accurately obtaining information from the leader, even with continuous switching topologies. then, through stability analysis, we demonstrate the effectiveness of the observers. Finally, we prove the feasibility of the observers through simulation. © 2024 IEEE.

关键词： Distributed cloud

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