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Optimising Event-Driven Spiking Neural Network with Regularisation and Cutoff

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arXiv 2023年

作者： Wu, Dengyu Jin, Gaojie Yu, Han Yi, Xinping Huang, Xiaowei Department of Computer Science University of Liverpool Liverpool United Kingdom National Mobile Communications Research Laboratory Southeast University Nanjing China State Key Laboratory of Computer Science Institute of Software CAS Beijing China Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden

Spiking neural network (SNN), as the next generation of artificial neural network (ANN), offer a closer mimicry of natural neural networks and hold promise for significant improvements in computational efficiency. However, the current SNN is trained to infer over a fixed duration, overlooking the potential of dynamic inference in SNN. In this paper, we strengthen the marriage between SNN and event-driven processing with a proposal to consider a cutoff in SNN, which can terminate SNN anytime during inference to achieve efficient inference. Two novel optimisation techniques are presented to achieve inference efficient SNN: a Top-K cutoff and a regularisation. The proposed regularisation influences the training process, optimising SNN for the cutoff, while the Top-K cutoff technique optimises the inference phase. We conduct an extensive set of experiments on multiple benchmark frame-based datasets, such as CIFAR10/100, Tiny-ImageNet, and event-based datasets, including CIFAR10-DVS, N-Caltech101 and DVS128 Gesture. The experimental results demonstrate the effectiveness of our techniques in both ANN-to-SNN conversion and direct training, enabling SNNs to require 1.76 to 2.76 × fewer timesteps for CIFAR-10, while achieving 1.64 to 1.95× fewer timesteps across all event-based datasets, with near-zero accuracy loss. These findings affirms the compatibility and potential benefits of our techniques in enhancing accuracy and reducing inference latency when integrated with existing methods. Code available: https://***/Dengyu-Wu/SNNCutoff © 2023, CC BY.

关键词： Computational efficiency

Dynamic 3D UAV Placement Optimization: Improved Bonobo Optimizer for Enhanced Coverage and Communication 35

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Dynamic 3D UAV Placement Optimization: Improved Bonobo Optim...

35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Yahia, Selma Taleb, Sylia Mekhmoukh Loscri, Valeria Saadi, Amylia Ait Ho, Tu Dac Vo, Van Nhan Eldeeb, Hossien Muhaidat, Sami Inria Lille-Nord Europe Lille 59000 France University of m'Hamed Bougara List Laboratory Boumerdes35000 Algeria Esme Engineering School Ivry-sur-Seine94200 France Norwegian University of Science and Technology Department of Information Security and Communication Technology Norway The Arctic University of Norway Department of Electrical Engineering Norway Duy Tan University Faculty of Information Technology Viet Nam Duy Tan University The Institute of Research and Development Viet Nam Khalifa University 6G Research Center Computer and Communication Engineering Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350362244

Unmanned aerial vehicles (UAVs) offer a promising solution for enhancing network coverage, reliability, and data speed in future wireless network generations. However, deploying UAVs as aerial base stations requires careful consideration of crucial design factors, including three-dimensional (3D) placement and performance optimization tailored to specific applications. In this paper, the 3D placement of multiple UAVs, acting as aerial base stations, is investigated in a dynamic user scenario. First, a closed-form expression for the coverage probability is derived. Then, to maximize the network coverage and sum rate while ensuring reliable and energy efficient system, a joint multi-objective optimization problem is formulated considering the real-time user movements. To solve the problem, an improved Chaos-based Bonobo Optimizer (CBO) scheme is proposed which combines chaotic maps with the Bonobo Optimizer (BO) algorithm. The obtained results demonstrate the superior performance of the proposed approach compared with different benchmark algorithms. The results reveal that the proposed CBO algorithm offers a minimum of 1 5 % and 9 0 ~ M b i t / s ~ i m p r o v e m e n t s ~ in coverage and sum rate, respectively. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

Using Deep Reinforcement Learning in Optimal Energy Management for Residential House Aggregators with Uncertain User Behaviors

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Using Deep Reinforcement Learning in Optimal Energy Manageme...

IEEE Student Conference on Electric Machines and systems

作者： Yujun Lin Linfang Yan Hongxun Hui Yin Chen Xia Chen Jinyu Wen State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China State Grid (Suzhou) City & Energy Research Institute Suzhou China Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macau China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow U.K.

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366952

In this study, the home energy management problem, which can be regarded as a high-dimensional optimization problem, for numerous residential houses, is addressed. The concept of the aggregator is utilized to reduce the state and action space and to handle the high dimensionality. A two-stage deep reinforcement learning (DRL)-based approach is proposed for the aggregators to track the schedule from a superior grid and guarantee the operation constraints. In the first stage, a DRL control agent is set to learn the optimal scheduling strategy interacting with the environment based on the soft-actor-critic framework and generate the aggregate control actions. In the second stage, the aggregate control actions are disaggregated to individual appliances considering the users' behaviors. The uncertainty of an electric vehicle's charging demand is quantitatively expressed based on the driver's experience. An aggregate anxiety concept is introduced to characterize the driver's anxiety on the electric vehicle's range and uncertain events. Finally, simulations are conducted to verify the effectiveness of the proposed approach under dynamic user behaviors, and comparisons show the superiority of the proposed approach over other benchmark methods.

关键词： Schedules Uncertainty Aggregates Anxiety disorders Optimal scheduling Deep reinforcement learning Electric vehicle charging Temperature control Vehicle dynamics Resistance heating

Pioneering Deterministic Scheduling and Network Structure Optimization for Time-Critical Computing Tasks in Industrial IoT

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arXiv 2024年

作者： Hu, Yujiao Zhu, Yining Zhang, Huayu Pan, Yan Jia, Qingmin Xie, Renchao Yang, Gang Yu, F. Richard Future Network Research Center Purple Mountain Laboratories Nanjing211111 China The School of Computer Science Northwestern Polytechnical University Xi’an710029 China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology China The State Key Laboratory of networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The Department of Systems and Computer Engineering Carleton University Ottawa Canada

The Industrial Internet of Things (IIoT) has become a critical technology to accelerate the process of digital and intelligent transformation of industries. As the cooperative relationship between smart devices in IIoT becomes more complex, getting deterministic responses of IIoT periodic time-critical computing tasks becomes a crucial and nontrivial problem. However, few current works in cloud/edge/fog computing focus on this problem. This paper is a pioneer to explore the deterministic scheduling and network structural optimization problems for IIoT periodic time-critical computing tasks. We first formulate the two problems and derive theorems to help quickly identify computation and network resource sharing conflicts. Based on this, we propose a deterministic scheduling algorithm, IIoTBroker, which realizes deterministic response for each IIoT task by optimizing the fine-grained computation and network resources allocations, and a network optimization algorithm, IIoTDeployer, providing a cost-effective structural upgrade solution for existing IIoT networks. Our methods are illustrated to be cost-friendly, scalable, and deterministic response guaranteed with low computation cost from our simulation results. © 2024, CC BY-NC-ND.

关键词： Internet of things

An Haptic Display for Visually Impaired Pedestrian Navigation 1st

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An Haptic Display for Visually Impaired Pedestrian Navigatio...

1st International Conference of Advanced Computing and Informatics, ICACIN 2020

作者： Alzighaibi, Sara Bouaziz, Rahma Kammoun, Slim Information System Department College of Computer Science and Engineering Taibah University Medina Saudi Arabia Computer Science Department College of Computer Science and Engineering Taibah University Medina Saudi Arabia ReDCAD University of Sfax Sfax Tunisia Research Laboratory of Technologies of Information and Communication & Electrical Engineering University of Tunis Tunis Tunisia

ISBN: (纸本)9789811560477

Sight is one of the major senses that allows people to travel safely, freely, and independently of others. In their daily life, visually impaired people are confronting challenging tasks such as reading or writing. Navigation and direction finding, particularly in the unfamiliar environment, are remaining as one of the main issues for visually impaired (VI) individuals. Several ways have been emerged to help VI orientation and mobility such as electronic orientation aids which can be further studied and developed. This work aims to improve VI navigation by proposing a new tactile interface that will be designed and implemented with the use of vibrators and Arduino board. The proposed interface targets to increase the quality of life and independence for VI. Also, evaluation performed with VI pedestrian will give us further information and knowledge regarding haptic perceptions and effectiveness of such interface and interaction technique. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Navigation

SweepEvGS: Event-Based 3D Gaussian Splatting for Macro and Micro Radiance Field Rendering from a Single Sweep

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arXiv 2024年

作者： Wu, Jingqian Zhu, Shuo Wang, Chutian Shi, Boxin Lam, Edmund Y. Department of Electrical and Electronic Engineering The University of Hong Kong Pokfulam Hong Kong National Key Laboratory for Multimedia Information Processing and National Engineering Research Center of Visual Technology School of Computer Science Peking University Beijing100871 China

—Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However, conventional methods require high-frame-rate dense and high-quality sharp images, which are time-consuming and inefficient to capture, especially in dynamic environments. Event cameras, with their high temporal resolution and ability to capture asynchronous brightness changes, offer a promising alternative for more reliable scene reconstruction without motion blur. In this paper, we propose SweepEvGS, a novel hardware-integrated method that leverages event cameras for robust and accurate novel view synthesis across various imaging settings from a single sweep. SweepEvGS utilizes the initial static frame with dense event streams captured during a single camera sweep to effectively reconstruct detailed scene views. We also introduce different real-world hardware imaging systems for real-world data collection and evaluation for future research. We validate the robustness and efficiency of SweepEvGS through experiments in three different imaging settings: synthetic objects, real-world macro-level, and real-world micro-level view synthesis. Our results demonstrate that SweepEvGS surpasses existing methods in visual rendering quality, rendering speed, and computational efficiency, highlighting its potential for dynamic practical applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Rendering (computer graphics)

CoRaiS: Lightweight Real-Time Scheduler for Multi-Edge Cooperative Computing

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arXiv 2024年

作者： Hu, Yujiao Jia, Qingmin Chen, Jinchao Yao, Yuan Pan, Yan Xie, Renchao Yu, F. Richard Future Network Research Center Purple Mountain Laboratories Nanjing211111 China The School of Computer Science Northwestern Polytechnical University Xi'An710029 China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology China The State Key Laboratory of networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The Department of Systems and Computer Engineering Carleton University Ottawa Canada

Multi-edge cooperative computing that combines constrained resources of multiple edges into a powerful resource pool has the potential to deliver great benefits, such as a tremendous computing power, improved response time, more diversified services. However, the mass heterogeneous resources composition and lack of scheduling strategies make the modeling and cooperating of multi-edge computing system particularly complicated. This paper first proposes a system-level state evaluation model to shield the complex hardware configurations and redefine the different service capabilities at heterogeneous edges. Secondly, an integer linear programming model is designed to cater for optimally dispatching the distributed arriving requests. Finally, a learning-based lightweight real-time scheduler, CoRaiS, is proposed. CoRaiS embeds the real-time states of multi-edge system and requests information, and combines the embeddings with a policy network to schedule the requests, so that the response time of all requests can be minimized. Evaluation results verify that CoRaiS can make a high-quality scheduling decision in real time, and can be generalized to other multi-edge computing system, regardless of system scales. Characteristic validation also demonstrates that CoRaiS successfully learns to balance loads, perceive real-time state and recognize heterogeneity while scheduling. © 2024, CC BY-NC-ND.

关键词： Edge computing

Successive Pose Estimation and Beam Tracking for mmWave Vehicular Communication systems

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Successive Pose Estimation and Beam Tracking for mmWave Vehi...

IEEE Globecom Workshops

作者： Cen Liu Guangxu Zhu Fan Liu Yuanwei Liu Kaibin Huang Department of Electrical and Computer Engineering National University of Singapore Singapore Shenzhen Research Institute of Big Data Shenzhen China Peng Cheng Laboratory Shenzhen China Pazhou Laboratory (Huangpu) Guangzhou China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China School of Electronic Engineering and Computer Science Queen Mary University of London London U.K. Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

The millimeter wave (mmWave) radar sensing-aided communications in vehicular mobile communication systems is investigated. To alleviate the beam training overhead under high mobility scenarios, a successive pose estimation and beam tracking (SPEBT) scheme is proposed to facilitate mmWave communications with the assistance of mmWave radar sensing. The proposed SPEBT scheme first resorts to a Fast Conservative Filtering for Efficient and Accurate Radar odometry (Fast-CFEAR) approach to estimate the vehicle pose consisting of 2-dimensional position and yaw from radar point clouds collected by mmWave radar sensor. Then, the pose estimation information is fed into an extend Kalman filter to perform beam tracking for the line-of-sight channel. Owing to the intrinsic robustness of mmWave radar sensing, the proposed SPEBT scheme is capable of operating reliably under extreme weather/illumination conditions and large-scale global navigation satellite systems (GNSS)-denied environments. The practical deployment of the SPEBT scheme is verified through rigorous testing on a real-world sensing dataset. Simulation results demonstrate that the proposed SPEBT scheme is capable of providing precise pose estimation information and accurate beam tracking output, while reducing the proportion of beam training overhead to less than 5% averagely.

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Topic Tracking Algorithm Based on Topic Structure Characteristics 22

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Topic Tracking Algorithm Based on Topic Structure Characteri...

6th High Performance Computing and Cluster Technologies Conference, HPCCT 2022

作者： Li, Shengdong Lv, Xueqiang Shi, Juntao Zhang, Haichuan Wu, Jianwei Wang, Yuan Department of Computer Engineering Langfang Yanjing Vocational Technical College Langfang065200 China Beijing Key Laboratory of Internet Culture and Digital Dissemination Research Beijing Information Science and Technology University Beijing100101 China Department of Mechanical and Electrical Engineering Langfang Yanjing Vocational Technical College Langfang065200 China

ISBN: (纸本)9781450396646

Topic tracking task is used for public opinion monitoring, and its key technology is text classification algorithm. However, existing text classification algorithms need large-scale train corpus during training, while topic tracking task only provides a small amount of train corpus, resulting in that it has poor performance. We analyze story description contents in train corpus, and find that the report description contents of the same topic have the topic structure characteristics of high similarity. We use topic information to represent highly similar topic structure characteristics to make up for the lack of train corpus in text classification algorithm, and fuse topic structure characteristics and text classification algorithm to make the topic tracking algorithm consider topic structure characteristics, and propose Topic Tracking Algorithm based on Topic Structure characteristics (TTATS). To verify its performance, we carry out quantitative and qualitative experiments. The experimental results of multiple dimensions show that it has preferable topic tracking performance. © 2022 ACM.

关键词： Classification (of information)