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检索条件"任意字段=Proceedings of the 1996 3rd International Workshop on Real-Time Computing Systems and Applications"

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Platform for visual simulation of UAVs based on 3D holographic display technology 3

Platform for visual simulation of UAVs based on 3D holograph...

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3rd international Symposium on Computer applications and Information systems, ISCAIS 2024

作者： Wang, Ya Hu, Tian Jiangsu Automation Research Institute Lianyungang222006 China

ISBN: (纸本)9781510681316

This paper presents a UAV visual simulation platform based on 3D holographic display technology, designed for UAV simulation training and real-time dynamic simulation of large scenes. The platform involves key modules such as UNIGINE real-time 3D engine, UAV flight simulation, optoelectronic video simulation, SAR image simulation, multispectral image simulation and computational holographic 3D display. The simulation platform has realized the 3D holographic display of UAV flight trajectory, providing immersive simulation training for operators to control the UAV to perform takeoff, flight, reconnaissance and landing tasks. The application requirements of the UAV system have been satisfied, and it has important practical value. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Multi-AGV path planning for yarn cone delivery in twisting workshop 3

Multi-AGV path planning for yarn cone delivery in twisting w...

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3rd international Conference on Advanced Manufacturing Technology and Manufacturing systems, ICAMTMS 2024

作者： Ke, Binbin Xu, Qiao Hubei Digital Textile Equipment Key Laboratory Wuhan Textile University Hubei Wuhan430200 China

ISBN: (纸本)9781510681804

Automation is increasingly utilized in the textile sector, notably the twisting workshop's yarn bobbin distribution. Our research introduces a dynamic multi-automated guided vehicle (AGV) path planning system to enhance the yarn bobbin distribution. A stationary robot palletizes bobbins at the transfer center, while omnidirectional AGVs distribute them based on straight-twisting machine needs. An improved GWO algorithm is at the system's heart, planning paths by considering AGVs' real-time positions, task priorities, layout, and statuses, with real-time adjustments for environmental shifts and AGV conflict minimization. Simulations confirm the system's efficacy in reducing AGV conflicts, boosting efficiency, and cutting task times, outperforming traditional Grey Wolf Optimization (GWO) algorithms. This efficient AGV path planning system offers new perspectives for industrial automation in distribution. © 2024 SPIE.

关键词： Bobbins

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Third international Conference on Optics, Computer applications, and Materials Science, CMSD 2023

Third International Conference on Optics, Computer Applicati...

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3rd international Conference on Optics, Computer applications, and Materials Science, CMSD 2023

ISBN: (纸本)9781510674486

The proceedings contain 57 papers. The topics discussed include: development of an information system of geological monitoring indicators of subsoil use;mathematical model of the formation of transport schedules for regular passenger traffic;social networks as a data source for real-time emergencies detection;breast cancer diagnosis using machine learning techniques;simulation modeling to improve the sustainability of the city's road transport system;information exchange in multi-agent systems;aspects of digital-based fashion design;on stochastic optimization for deep learning;solving the problem of classifying forest cover types based on soil characteristics;and application of a neural network approach for localization of problem areas of a centralized water supply system.

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GABB: The plan-based job scheduling optimized by genetic algorithm for HPC systems with shared burst buffers 3

GABB: The plan-based job scheduling optimized by genetic alg...

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3rd international Symposium on Computer applications and Information systems, ISCAIS 2024

作者： Lv, Shuaizhe Xie, Xuchao Song, Zhenlong College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781510681316

Burst Buffer was proposed to address the growing performance gap between computation and I/O in high-performance computing systems (HPC). However, the introduction of Burst Buffer has brought new issues in system resource management and job scheduling. Resource management systems on HPC platforms lack efficient management of multiple types of resources, and the allocation of computing resources and Burst Buffer resources is independent of each other. This can lead to underutilization of system resources and job blocking. To address these issues, this paper proposes GABB, a plan-based job scheduling strategy for shared Burst Buffer, and utilizes genetic algorithms for optimization. GABB employs a plan-based job scheduling strategy to uniformly schedule all jobs in the waiting queue to generate an execution plan. Furthermore, GABB comprehensively considers changes in system resources and the job's demand for computing and Burst Buffer resources during the job scheduling process. Finally, GABB utilizes an improved genetic algorithm to optimize the job scheduling scheme. We conducted experimental simulations of a shared Burst Buffer system and implemented a plan-based job scheduling algorithm. The experimental results indicate that BBGA significantly reduces the mean waiting time of jobs by over 20% compared to the Shortest Job First (SJF) algorithm, and reduces the mean bounded slowdown of jobs by over 25%. © 2024 SPIE.

关键词： Genetic algorithms

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Methods of increasing the contrast of images in video information systems 3

Methods of increasing the contrast of images in video inform...

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3rd international Conference on Optics, Computer applications, and Materials Science, CMSD 2023

作者： Beknazarova, S.S. Abdullayev, S.X. Abdullayeva, O.S. Abdullayev, Z.S. Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi 105 A. Temur Tashkent100142 Uzbekistan Namangan State University Namangan Uzbekistan Namangan Engeneering-Construction Institute Namangan Uzbekistan

ISBN: (纸本)9781510674486

In the article describe the methods of increasing the contrast of images in video information systems, the main compression of the video stream is provided by eliminating inter-frame redundancy using motion compensation methods for image fragments of adjacent frames. However, the use of motion compensation methods requires the formation of additional data (metadata) containing information about the types of image blocks used, the coordinates of their movement, etc. At the same time, in order to increase the compression of the video stream without compromising its quality, a higher accuracy of motion compensation is required, which leads to an increase in the number of blocks and, accordingly, to an increase in the volume of metadata that reduces the effectiveness of motion compensation. This is the main problem of compressing streaming video without degrading the quality of images. In addition, the higher accuracy of positioning blocks with motion compensation dramatically reduces the speed of image processing, which is not always feasible in real-time systems. © 2024 SPIE. All rights reserved.

关键词： Information systems

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Collaborative control of intelligent waste discharge and water curtain cooling systems in silk reeling workshop based on fuzzy logic 3

Collaborative control of intelligent waste discharge and wat...

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3rd international Conference on Mechatronics and Mechanical Engineering, ICMME 2024

作者： Huang, Liren Qin, Honghan Wang, Hao Tang, Jun Nanning Cigarette Factory China Tobacco Guangxi Industrial CO. Ltd. Guangxi Nanning530001 China

ISBN: (纸本)9781510681651

In today’s increasingly advanced industrial automation, intelligent manufacturing has become an important means to improve industrial production efficiency and environmental protection. This article adopted a method that combines an intelligent slag removal system based on fuzzy logic and a water curtain cooling system in the silk production workshop to achieve comprehensive optimization of workshop environmental quality and energy consumption. This article aimed to establish a fuzzy control model for the operation status of a slag removal cooling machine based on multiple key factors such as temperature, humidity, and dust concentration. On this basis, a real-time data acquisition and processing system based on sensor networks was developed for on-site monitoring of equipment such as furnaces and water curtains. When the humidity reached 47.5%, the system began to provide 10% cooling power. As the humidity further increased, the cooling power of the system gradually increased from 10% to 70%. Through a combination of simulation and on-site experiments, it has been proven that the adopted collaborative control scheme significantly improves the air quality and working environment of the workshop while reducing energy consumption and improving production efficiency. Through this study, new ideas and methods can be provided for the development of intelligent manufacturing technology. © 2024 SPIE.

关键词： Quality control

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Incremental Perception on real time 3D Data 22

Incremental Perception on Real Time 3D Data

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23rd Annual international workshop on Mobile computing systems and applications (HotMobile)

作者： Sarker, Arup Kumar Lin, Felix Xiaozhu Univ Virginia Charlottesville VA 22904 USA

ISBN: (纸本)9781450392181

Perception based on 3D data in autonomous vehicles (AV) pursues high accuracy at a high computational cost. It delays the downstream modules in an AV pipeline - planning, prediction, and control. This prolongs the AV's time-to-decision and ultimately hurts the vehicle's maneuver and safety. Towards efficient perception, our insight is that the perception module should attend to 3D pixels that are more relevant to the downstream modules. Accordingly, we propose incremental perception: each 3D frame is processed in progressive iterations;early iterations emit inexact perception results to the downstream modules;later iterations incorporate feedback from the downstream modules and accordingly refine a 3D frame's most relevant portions. Our early results show reduction in AV's time-to-decision and therefore safety improvement.

关键词： computer vision autonomous vehicles point cloud

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Deep learning based algorithm for classifying pedestrian behavior at crosswalks 3

Deep learning based algorithm for classifying pedestrian beh...

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2024 3rd international Conference on Image Processing, Object Detection, and Tracking, IPODT 2024

作者： Li, Menghao Liu, Miao Shanghai China

ISBN: (数字)9781510685529

ISBN: (纸本)9781510685512

In intelligent transportation systems, pedestrian intentions at intersections must be classified to enhance pedestrian safety and optimize traffic flow. Accurately predicting pedestrian actions can significantly reduce traffic accidents and improve overall traffic management efficiency. An improved YOLOv5 model is proposed to efficiently and accurately identify pedestrian intentions. The model combines the Multi-scale Diluted Attention (MSDA) mechanism, which extends attention to different scales to capture the subtle movements of pedestrians, and the GhostNet lightweight module, which reduces the number of computational parameters and makes the model suitable for real-time applications. In addition, a new loss function, ACFloss, which combines adaptive weight-focusing loss based on contextual relationships and spatio-temporal consistency loss, is designed to understand the behavioral intent of actions better. Experimental results show that the improved YOLOv5 model achieves a classification accuracy of 93.7%, 4.5% higher than the benchmark, and the inference speed is improved by 35%. This improvement provides a reliable solution for intelligent transportation systems in complex intersection scenarios. © 2024 SPIE.

关键词： Intelligent systems

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Reasoning-Learning systems Based on Non-Axiomatic Reasoning System Theory 3

Reasoning-Learning Systems Based on Non-Axiomatic Reasoning ...

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3rd Annual international workshop on Self-Supervised Learning (IWSSL)

作者： Hammer, Patrick Stockholm Univ Dept Psychol S-11347 Stockholm Sweden

In this paper a strong motivation for real-time reasoning-learning systems based on Non-Axiomatic Reasoning System (NARS) Theory as an approach to build intelligent systems with agency is given. This contains the requirement to work under the Assumption of Insufficient Knowledge and Resources which demands open-ended adaptation while obeying to strict computational resource restrictions to allow for real-time response. We show how this aligns with the phenomenon of intelligence as found in nature, allowing for systems which can both react instantly, and plan ahead deliberately dependent on implicitly outcome-dependent time pressures. In this context a specific implementation design is considered, OpenNARS for applications (ONA), and how its learning and reasoning abilities lead to data-efficient adaptation in novel circumstances in various domains, whereby we compare with a reinforcement learning method, Q-Learning, in Space Invaders, Pong and a grid robot environment. We will see that both techniques perform comparably well for reactive tasks in Markovian environments, while the uncertainty reasoner performs better when the Markov property is violated, with the additional property that it can plan ahead to exploit task compositionality, also taking explicit background knowledge into account.

关键词： Reasoning Under Uncertainty Reinforcement Learning Non-Axiomatic Reasoning Procedure Learning Practical Reasoning

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Multiresource allocation in dynamic MEC systems: a continual learning-based approach 3

Multiresource allocation in dynamic MEC systems: a continual...

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3rd international Conference on Electronic Information Engineering, Big Data, and Computer Technology, EIBDCT 2024

作者： Zhan, Shutao Mao, Jin Chu, Zhipeng Xiong, Ke Fan, Pingyi Letaief, Khaled B. Eng. Res. Center of Network Management Technology for High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing100044 China Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China Department of Electronic Engineering Tsinghua University Beijing100084 China Department of Electrical and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9781510680449

Recently, mobile edge computing (MEC) has been considered as a promising solution to address the challenges arising from the growing computationally intensive applications and limited computation capability of mobile devices. Thus, the resource allocation is crucial for ensuring the system performance of MEC. Recent deep learning-based resource allocation (DLRA) methods achieve preferable performance in real-time. However, in practical scenarios, the number of users often changes, which leads to a decrease in the performance of DLRA methods. Thus, once the number of users changes, the traditional DLRA methods need to retrain their neural networks, which consumes a lot of computing resources. To address this issue, this paper proposes a continual learning-based resource allocation (CLRA) method to jointly optimize multiple resource including offloading decision, power control, time slot assignment and computation resource distribution in MEC system. Our CLRA method is able to avoid forgetting previous knowledge when the number of users in the MEC system changes by selecting a small number of the most representative samples from the past and relearning. Experimental results show that, our proposed CLRA method achieves a better performance than the traditional DLRA method in terms of the higher quality of service's (QoS's) satisfaction rate and the less energy consumption. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Resource allocation

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