检索结果-内蒙古大学图书馆

2024 China Automation Congress, CAC 2024

作者： Bao-Lin, Ye Dong, Chen Peng, Wu Weimin, Wu Li, Lingxi Bin, Chen School of Information Science and Engineering Jiaxing University Jiaxing China School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette United States Jiaxing Key Laboratory of Smart Transportations Jiaxing University Jiaxing China

ISBN: (纸本)9798350368604

In order to solve the problem that the existing traffic signal control methods usually need to predefine the phase sequence or phase duration, a single intersection traffic signal control method based on improved deep reinforcement learning Double DQN (DDQN) was proposed. Firstly, a traffic signal control model based on deep reinforcement learning DDQN was constructed to optimize the estimated value of action-value function and the iterative process of target value. Secondly, the original one-dimensional action space was discretized into a three-dimensional action space composed of phase selection, phase duration and loss factor, and the next phase and phase green time to be executed were intelligently decided. Finally, a new loss function is designed based on the loss factor, which can dynamically adjust the loss weight of different actions according to the difference of importance. The simulation test is carried out based on the microscopic simulation platform SUMO. The experimental results show that, compared with the baseline method, the proposed method reduces the average waiting time by 28.1%, the average queue length by 29.7%, and the average number of parking vehicles by 18.8%. © 2024 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Approximately Counting and Sampling Hamiltonian Motifs in Sublinear Time

arXiv

引用

arXiv 2025年

作者： Eden, Talya Levi, Reut Ron, Dana Rubinfeld, Ronitt Department of Computer Science Bar Ilan University Israel Efi Arazi School of Computer Science Reichman University Israel School of Electrical and Computer Engineering Tel Aviv University Israel Computer Science and Artificial Intelligence Laboratory MIT United States

Counting small subgraphs, referred to as motifs, in large graphs is a fundamental task in graph analysis, extensively studied across various contexts and computational models. In the sublinear-time regime, the relaxed problem of approximate counting has been explored within two prominent query frameworks: the standard model, which permits degree, neighbor, and pair queries, and the strictly more powerful augmented model, which additionally allows for uniform edge sampling. Currently, in the standard model, (optimal) results have been established only for approximately counting edges, stars, and cliques, all of which have a radius of one. This contrasts sharply with the state of affairs in the augmented model, where algorithmic results (some of which are optimal) are known for any input motif, leading to a disparity which we term the "scope gap" between the two models. In this work, we make significant progress in bridging this gap. Our approach draws inspiration from recent advancements in the augmented model and utilizes a framework centered on counting by uniform sampling, thus allowing us to establish new results in the standard model and simplify on previous results. In particular, our first, and main, contribution is a new algorithm in the standard model for approximately counting any Hamiltonian motif in sublinear time, where the complexity of the algorithm is the sum of two terms. One term equals the complexity of the known algorithms by Assadi, Kapralov, and Khanna (ITCS 2019) and Fichtenberger and Peng (ICALP 2020) in the (strictly stronger) augmented model and the other is an additional, necessary, additive overhead. Our second contribution is a variant of our algorithm that enables nearly uniform sampling of these motifs, a capability previously limited in the standard model to edges and cliques. Our third contribution is to introduce even simpler algorithms for stars and cliques by exploiting their radius-one property. As a result, we simplify all previo

关键词： Stars

来源：评论

学校读者我要写书评

暂无评论

Experimental assessment of a semi-submersible floating solar platform subjected to wave and wind loading 6th

Experimental assessment of a semi-submersible floating solar...

引用

6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Campbell, M. Baruah, G. Karimirad, M. Van, M. Pakrashi, V. School of Natural and Built Environment Queen’s University Belfast Belfast United Kingdom School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast United Kingdom UCD Centre for Mechanics Dynamical Systems and Risk Laboratory School of Mechanical and Materials Engineering University College Dublin Ireland

ISBN: (纸本)9781032905570

Floating solar platforms are subjected to coupled wave and wind induced responses, straddling the unpredictable wave-wind boundary layer. The simultaneous actions of these coupled responses in real sea conditions are not yet fully investigated for floating solar systems. The fluidstructure interactions are complex due to these coupled responses. The combined response to these wave and wind loads results in a coupled motion and tension in the mooring lines. This paper investigates the wave-only and wave-wind load case scenarios using scaled model wave tank testing. To study these scenarios, the Qualisys motion capture system is used to record the motions of the structure in the tank and load cells to record the mooring loads. This study investigates the correlation of wave, wind, motions, and mooring tension. The contribution of the wind loading component to the coupled wave-wind scenario is assessed and trends are determined for the wind loading contribution effects observed. © 2025 The Author(s).

关键词： Mooring

来源：评论

学校读者我要写书评

暂无评论

Robustness Assessment of Distributed OPF Under Communication Non-Idealities Using Cyber-Physical Co-Simulation Framework

Robustness Assessment of Distributed OPF Under Communication...

引用

2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

作者： Paul, Subho Gray, Nathan Dubey, Anamika Bose, Anjan Touhiduzzaman, Md Ogle, James School of Electrical Engineering and Computer Science Washington State University PullmanWA United States Energy and Environment Directorate Pacific Northwest National Laboratory RichlandWA United States

ISBN: (纸本)9798350320169

In recent years, distributed optimal power flow (OPF) algorithms have paved the way for the operation of distribution systems, where the distribution system is decomposed into multiple small areas each solving its own local optimization problem and sharing values of boundary variables with neighbors periodically. In contrast with the conventional centralized approaches, the performance of distributed algorithms is highly impacted by the non-ideal conditions of the communication infrastructures used for information sharing. Therefore, it is necessary to assess the robustness of distributed algorithms against real-time communication non-idealities. In this regard, this article investigates the performance of a fast distributed algorithm, named Equivalent Network Approximation method (ENApp), for three-phase radial distribution system under three different non-ideal communication scenarios: (1) erroneous data transfer, (2) additive noise effect and (3) communication delays. The non-idealities are modeled considering the physical aspects of two widely used wide-area network mediums, viz. power line communication and optical fiber. The performance characterization of ENApp is done using IEEE 123 bus test system in a HELICS-based cyber-physical co-simulation environment. This analysis provides an insight into the robustness of the ENApp algorithm in terms of the convergence time and success rate. © 2023 IEEE.

关键词： Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Distributed Optimal Contract for Data Rewarding with Network Effects

引用

IEEE Transactions on Control of Network Systems 2024年

作者： Baneshi, Alireza Montazeri, Mina Kebriaei, Hamed University of Tehran School of Electrical and Computer Engineering College of Engineering Tehran Iran Swiss Federal Laboratories for Materials Science and Technology Urban Energy Systems Laboratory Dübendorf Switzerland School of Computer Science Tehran Iran

Data rewarding is a novel business model that leads to an economic trend in mobile networks. In this scheme, the advertiser incentivizes mobile users (MUs) to watch advertisement (ads) and, in return, receive a reward in the form of mobile data. In this work, we model the interaction between an advertiser who has asymmetric information about MUs and MUs who are connected to each other under a network, using the contract theory approach. We obtain the necessary and sufficient conditions for an optimal and practical contract to motivate MUs to participate in the data rewarding scheme and encourage them to declare their private information truthfully. The formulation of this contract is a non-convex-constrained optimization problem. Using lemmas and propositions, we reformulate the initial optimization problem that is challenging to solve as an optimization problem with convex constraints and prove that these two problems are equivalent. Then, with the help of a distributed and non-convex algorithm, we obtain the amount of ads demand and incentive reward. © 2014 IEEE.

关键词： asymmetric information contract theory Data rewarding distributed algorithm incentive compatibility

来源：评论

学校读者我要写书评

暂无评论

Advswap: Covert Adversarial Perturbation with High Frequency Info-Swapping for Autonomous Driving Perception 27

Advswap: Covert Adversarial Perturbation with High Frequency...

引用

27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Huang, Yuanhao Zhang, Qinfan Xing, Jiandong Cheng, Mengyue Yu, Haiyang Ren, Yilong Xiong, Xiao School of Transportation Science and Engineering Beihang University Beijing100191 China State Key Lab of Intelligent Transportation System Beijing100191 China Zhongguancun Laboratory Beijing100094 China University of Alberta Department of Electrical and Computer Engineering Edmonton Canada

ISBN: (纸本)9798331505929

Perception module of Autonomous vehicles (AVs) are increasingly susceptible to be attacked, which exploit vulnerabilities in neural networks through adversarial inputs, thereby compromising the AI safety. Some researches focus on creating covert adversarial samples, but existing global noise techniques are detectable and difficult to deceive the human visual system. This paper introduces a novel adversarial attack method, AdvSwap, which creatively utilizes wavelet-based highfrequency information swapping to generate covert adversarial samples and fool the camera. AdvSwap employs invertible neural network for selective high-frequency information swapping, preserving both forward propagation and data integrity. The scheme effectively removes the original label data and incorporates the guidance image data, producing concealed and robust adversarial samples. Experimental evaluations and comparisons on the GTSRB and nuScenes datasets demonstrate that AdvSwap can make concealed attacks on common traffic targets. The generates adversarial samples are also difficult to perceive by humans and algorithms. Meanwhile, the method has strong attacking robustness and attacking transferability. © 2024 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An efficient data aggregation scheme with local differential privacy in smart grid

引用

Digital Communications and Networks 2022年第3期8卷 333-342页

作者： Na Gai Kaiping Xue Bin Zhu Jiayu Yang Jianqing Liu Debiao He School of Cyber Science and Technology University of Science and Technology of ChinaHefeiAnhui230027China Department of Electronic Engineering and Information Science University of Science and Technology of ChinaHefeiAnhui230027China Department of Electrical and Computer Engineering University of Alabama in HuntsvilleHuntsvilleAL35899USA Key Laboratory of Aerospace Information Security and Trusted Computing of Ministry of Education School of Cyber Science and EngineeringWuhan UniversityWuhanBeihu430072China

By integrating the traditional power grid with information and communication technology, smart grid achieves dependable, efficient, and flexible grid data processing. The smart meters deployed on the user side of the smart grid collect the users' power usage data on a regular basis and upload it to the control center to complete the smart grid data acquisition. The control center can evaluate the supply and demand of the power grid through aggregated data from users and then dynamically adjust the power supply and price, etc. However, since the grid data collected from users may disclose the user's electricity usage habits and daily activities, privacy concern has become a critical issue in smart grid data aggregation. Most of the existing privacy-preserving data collection schemes for smart grid adopt homomorphic encryption or randomization techniques which are either impractical because of the high computation overhead or unrealistic for requiring a trusted third party.

关键词： Local differential privacy Data aggregation Smart grid Privacy preserving

来源：评论

学校读者我要写书评

暂无评论

Transferring fashion to surveillance with weak labels

引用

Neural Computing and Applications 2023年第18期35卷 13021-13035页

作者： Zheng, Qi He, Zheng Liang, Chao Chen, Jun Lin, Chia-Wen Tao, Dapeng National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan430072 China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan430072 China Collaborative Innovation Center of Geospatial Technology Wuhan430079 China Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan School of Information Science and Engineering Yunnan University Yunnan Kunming650504 China

In this paper, we address the problem of automatic clothing parsing in surveillance images using the information from user-generated tags, such as "jeans" and "T-shirt." Although clothing parsing has achieved great success in the fashion domain, it is quite challenging to parse target under practical surveillance conditions due to the presence of complex environmental interference, such as that from low resolution, viewpoint variations and lighting changes. Our method is developed to capture target information from the fashion domain and apply this information to a surveillance domain by weakly supervised transfer learning. Most target tags convey strong location information (e.g., "T-shirt" is always shown in the upper region), which can be used as weak labels for our transfer method. Both quantitative and qualitative experiments conducted on practical surveillance datasets demonstrate the effectiveness of the proposed surveillance data enhancing method. © 2020, Springer-Verlag London Ltd., part of Springer Nature.

关键词： Monitoring

来源：评论

学校读者我要写书评

暂无评论

Semantic Feature Division Multiple Access for Digital Semantic Broadcast Channels

引用

IEEE Internet of Things Journal 2025年第11期12卷 17123-17136页

作者： Ma, Shuai Sun, Zhiye Shen, Bin Wu, Youlong Li, Hang Shi, Guangming Li, Shiyin Al-Dhahir, Naofal Peng Cheng Laboratory Shenzhen518066 China China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China ShanghaiTech University School of Information Science and Technology Shanghai201210 China Shenzhen Research Institute of Big Data DIIS Guangdong Shenzhen518172 China Xidian University School of Artificial Intelligence Shaanxi Xi’an710071 China The University of Texas at Dallas Department of Electrical and Computer Engineering RichardsonTX75080 United States

In this article, we propose a digital semantic feature division multiple access (SFDMA) paradigm in multiuser broadcast (broadcast communication (BC)) networks for the inference and the image reconstruction tasks. In this SFDMA scheme, the multiuser semantic information is encoded into discrete approximately orthogonal representations, and the encoded semantic features of multiple users can be simultaneously transmitted in the same time-frequency resource. Specifically, for inference tasks, we design a SFDMA digital BC network based on robust information bottleneck (RIB), which can achieve a tradeoff between inference performance, data compression and multiuser interference. Moreover, for image reconstruction tasks, we develop a SFDMA digital BC network by utilizing a Swin Transformer, which significantly reduces multiuser interference. More importantly, SFDMA can protect the privacy of users’ semantic information, in which each receiver can only decode its own semantic information. Furthermore, we establish a relationship between performance and signal to interference plus noise ratio (SINR), which is fitted by an Alpha-Beta–Gamma (ABG) function. Furthermore, an optimal power allocation method is developed for the inference and reconstruction tasks. Extensive simulations verify the effectiveness and superiority of our proposed SFDMA scheme. © 2014 IEEE.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Deep Neural Networks for the Qualitative Analysis of Myocardial Perfusion Emission Computed Tomography Images 15

Deep Neural Networks for the Qualitative Analysis of Myocard...

引用

15th International Conference on Information Technology and electrical engineering, ICITEE 2023

作者： Pruthipanyasakul, Nareekarn Kanungsukkasem, Nont Urruty, Thierry Leelanupab, Teerapong Bangkok10520 Thailand University of Poitiers Xlim Laboratory Umr Cnrs 7252 Poitiers France School of Electrical Engineering and Computer Science The University of Queensland BrisbaneQLD4072 Australia

ISBN: (纸本)9798350304466

Integrating AI into medical diagnosis can provide a more accurate diagnosis when medical staff make treatment decisions. This paper studied on several deep neural networks, re-used with further training for a specific task in classifying the stenosis of a patient's coronary artery. From a 4DM-SPECT application, we collected polar map images that report, for example, myocardial perfusion, function and defect severity from cardiac emission computed tomography examination. We conducted a comparative study to identify the optimal combination of various state-of-the-art pre-trained models (i.e., VGG19, ResNet50, DenseNet121, and EfficientNetB0-B3) and eight different modalities of the myocardial perfusion images for classifying the stenosis of the coronary artery. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：