检索结果-内蒙古大学图书馆

A Vision Based Hardware-Software Real-Time control System for the Autonomous Landing of an UAV 1

学校读者我要写书评

暂无评论

International Conference on computer Vision and Graphics, ICCVG 2020

作者： Blachut, Krzysztof Szolc, Hubert Wasala, Mateusz Kryjak, Tomasz Gorgon, Marek Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (数字)9783030590062

ISBN: (纸本)9783030590055

In this paper we present a vision based hardware-software control system enabling the autonomous landing of a multirotor unmanned aerial vehicle (UAV). It allows for the detection of a marked landing pad in real-time for a 1280 720 @ 60 fps video stream. In addition, a LiDAR sensor is used to measure the altitude above ground. A heterogeneous Zynq SoC device is used as the computing platform. The solution was tested on a number of sequences and the landing pad was detected with 96% accuracy. This research shows that a reprogrammable heterogeneous computing system is a good solution for UAVs because it enables real-time data stream processing with relatively low energy consumption. © 2020, Springer Nature Switzerland AG.

关键词： System-on-chip

Active Wildfires Detection and Dynamic Escape Routes Planning for Humans Through Information Fusion between Drones and Satellites

学校读者我要写书评

暂无评论

Active Wildfires Detection and Dynamic Escape Routes Plannin...

International Conference on Intelligent Transportation

作者： Chang Liu Tamas Sziranyi Department of Networked Systems and Services Budapest University of Technology and Economics Müegyetem rkp. 3 H-1111 Budapest Hungary and Machine Perception Research Laboratory of Institute for Computer Science and Control (SZTAKI) Budapest Hungary Faculty of Transportation Engineering and Vehicle Engineering Machine Perception Research Laboratory of Institute for Computer Science and Control (SZTAKI) Budapest University of Technology and Economics (BME-KJK) Müegyetem rkp. 3 H-1111 Budapest Hungary Budapest Hungary

UAVs are playing an increasingly important role in the field of wilderness rescue by virtue of their flexibility. This paper proposes a fusion of UAV vision technology and satellite image analysis technology for active wildfires detection and road networks extraction of wildfire areas and real-time dynamic escape route planning for people in distress. Firstly, the fire source location and the segmentation of smoke and flames are targeted based on Sentinel 2 satellite imagery. Secondly, the road segmentation and the road condition assessment are performed by D-linkNet and NDVI values in the central area of the fire source by UAV. Finally, the dynamic optimal route planning for humans in real time is performed by the weighted A* algorithm in the road network with the dynamic fire spread model. Taking the Chongqing wildfire on August 24, 2022, as a case study, the results demonstrate that the dynamic escape route planning algorithm can provide an optimal real-time navigation path for humans in the presence of fire through the information fusion of UAVs and satellites.

关键词：

Reduced Network Cumulative Constraint Violation for Distributed Bandit Convex Optimization under Slater’s Condition

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Ding, Jinliang Cao, Ming Johansson, Karl H. Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201800 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cumulative constraint violation, existing distributed bandit online algorithms solving this problem directly use the clipped constraint function to replace its original constraint function. However, the use of the clipping operation renders Slater’s condition (i.e, there exists a point that strictly satisfies the inequality constraints at all iterations) ineffective to achieve reduced network cumulative constraint violation. To tackle this challenge, we propose a new distributed bandit online primal–dual algorithm. If local loss functions are convex, we show that the proposed algorithm establishes an O(T max{c,1−c})network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the total number of iterations and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds, the network cumulative constraint violation bound is reduced to O(T 1−c). In addition, if local loss functions are strongly convex, for the case where strongly convex parameters are unknown, the network regret bound is reduced to O(T1−c), and the network cumulative constraint violation bound is O(T1−c/2) and O(T1−c) without and with Slater’s condition, respectively. For the case where strongly convex parameters are known, the network regret bound is further reduced to O)(log(T)), and the network cumulative constraint violation bound is reduced to O(log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is among the first to establish reduced (network) cumulative constraint violation bounds for (distributed) bandit convex optimization with time-varying constraints under Slater’s condition. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2

关键词： Convex optimization

Weyl-Heisenberg Transform Capabilities in JPEG Compression Standard

学校读者我要写书评

暂无评论

Weyl-Heisenberg Transform Capabilities in JPEG Compression S...

2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information technology, USBEREIT 2021

作者： Asiryan, V.M. Volchkov, V.P. Papulovskaya, N.V. National University of Science and Technology 'Misis' Department of Computer Science Moscow Russia General Communication Theory Chair Moscow Technical University of Communications and Informatics Moscow Russia Ural Federal University Named after First President of Russia B. N. Yeltsin Department of Information Technology and Control Systems Ekaterinburg Russia

ISBN: (纸本)9781728176918

This paper is devoted to the development and research of a new compression technology based on Weyl-Heisenberg bases (WH-technology) for modifying the JPEG compression standard and improving its characteristics. For this purpose, the paper analyzes the main stages of the JPEG compression algorithm, notes its key features and problems that limit further enhancement of its efficiency. To overcome these limitations, it is proposed to use the real version of the two-dimensional discrete orthogonal Weyl-Heisenberg transform (DWHT) instead of the discrete cosine transform (DCT) at the stage of transformation coding. This transformation, unlike DCT, initially has a block structure and is built on the basis of the Weyl-Heisenberg optimal signal basis, the functions of which are orthogonal and well localized both in the frequency and time domains. This feature of DWHT allows for more efficient decorrelation and compression of element values in each block of the image after transformation coding. As a result, it is possible to obtain more efficient selection and screening of insignificant elements at the subsequent stages of quantization and information coding. Based on DWHT, a new version of the JPEG compression algorithm was developed, and convenient criteria for evaluating the compression efficiency and metrics of quality losses were proposed. The results of an experimental study are presented, confirming the higher compression efficiency of the proposed algorithm in comparison with the JPEG compression standard. © 2021 IEEE.

关键词： Discrete cosine transforms

Dragonfly Optimization-based MPPT Algorithm for Standalone PV System under Partial Shading

学校读者我要写书评

暂无评论

Dragonfly Optimization-based MPPT Algorithm for Standalone P...

2021 IEEE International Conference on Emergency Science and Information technology, ICESIT 2021

作者： Lodhi, Ehtisham Yang, Pu Wang, Lina Khan, M. Adil Lodhi, Zeeshan Javed, Usman Saleem, Qasim School of Automation Science and Electrical Engineering Beihang University Beijing100191 China SKL for Management and Control of Complex Systems Institute OfAutomation Chinese Academy of Sciences Beijing100190 China Chang'an University Department of Computer and Technology Xi'an710062 China COMSATS University Department of Electrical and Computer Engineering Islamabad22060 Pakistan Lahore54000 Pakistan

ISBN: (纸本)9781665435314

Currently, Photovoltaic (PV) technology has higher demand in the market and gaining momentum day by day. However, partial shading is the most significant concern as it reduces the efficiency of standalone PV systems. Partially shading is typically induced by non-uniform sunlight and uncertain temperature fluctuations. The maximum power point tracking (MPPT) algorithms play a major role in determining the overall system's efficiency. The PV system creates several peaks in its power voltage (P-V) characteristic curve under partial shadowing. To make the PV system run under partial shading at global maximum power point (GMPP), the dragonfly optimization (DFO) algorithm is put forward in this research article. The proposed DFO technique and other commonly used MPPT techniques, such as Particle swarm optimization (PSO), Perturb and Observe (PO), is investigated through theoretical analysis and simulation using Matlab/Simulink to authenticate the overall performance of the DFO approach under partial shading. Furthermore, the comparison demonstrates that the suggested DFO strategy provides very high reliability, efficiency, robustness, rapid power tracking and lower response time to trace the GMPP than PSO and PO techniques. Hence, the DFO technique's overall performance under partial shading is appropriate and satisfying. © 2021 IEEE.

关键词： Simulink

Vulnerability of Machine Learning Approaches Applied in IoT-based Smart Grid: A Review

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Zhang, Zhenyong Liu, Mengxiang Sun, Mingyang Deng, Ruilong Cheng, Peng Niyato, Dusit Chow, Mo-Yuen Chen, Jiming The State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550000 China The Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS10 2TN United Kingdom The State Key Laboratory of Industrial Control Technology the College of Control Science and Engineering Zhejiang University Hangzhou310027 China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The UM SJTU Joint Institute Shanghai Jiao Tong University Shanghai200240 China

Machine learning (ML) sees an increasing prevalence of being used in the internet-of-things (IoT)-based smart grid. However, the trustworthiness of ML is a severe issue that must be addressed to accommodate the trend of ML-based smart grid applications (MLsgAPPs). The adversarial distortion injected into the power signal will greatly affect the system’s normal control and operation. Therefore, it is imperative to conduct vulnerability assessment for MLsgAPPs applied in the context of safety-critical power systems. In this paper, we provide a comprehensive review of the recent progress in designing attack and defense methods for MLsgAPPs. Unlike the traditional survey about ML security, this is the first review work about the security of MLsgAPPs that focuses on the characteristics of power systems. We first highlight the specifics for constructing the adversarial attacks on MLsgAPPs. Then, the vulnerability of MLsgAPP is analyzed from both the aspects of the power system and ML model. Afterward, a comprehensive survey is conducted to review and compare existing studies about the adversarial attacks on MLsgAPPs in scenarios of generation, transmission, distribution, and consumption, and the countermeasures are reviewed according to the attacks that they defend against. Finally, the future research directions are discussed on the attacker’s and defender’s side, respectively. We also analyze the potential vulnerability of large language model-based (e.g., ChatGPT) power system applications. Overall, we encourage more researchers to contribute to investigating the adversarial issues of MLsgAPPs. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

Attack Impact Evaluation by Exact Convexification through State Space Augmentation

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Sasahara, Hampei Tanaka, Takashi Sandberg, Henrik The Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo152-8552 Japan The Department of Aerospace Engineering and Engineering Mechanics Cockrell School of Engineering The University of Texas AustinTX78712 United States The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden

We address the attack impact evaluation problem for control system security. We formulate the problem as a Markov decision process with a temporally joint chance constraint that forces the adversary to avoid being detected throughout the considered time period. Owing to the joint constraint, the optimal control policy depends not only on the current state but also on the entire history, which leads to the explosion of the search space and makes the problem generally intractable. It is shown that whether an alarm has been triggered or not, in addition to the current state is sufficient for specifying the optimal decision at each time step. Augmentation of the information to the state space induces an equivalent convex optimization problem, which is tractable using standard solvers. © 2022, CC BY-NC-ND.

关键词： Markov processes

Influence of Pulse Discharging on Lithium-Ion Battery

学校读者我要写书评

暂无评论

Influence of Pulse Discharging on Lithium-Ion Battery

International Electrical Engineering Congress (iEECON)

作者： Hsu Myat Naing Chinda Charoenphonphanich Masaki Yamakita Pera Tanateerapong Burin Kerdsup Manop Masomtob Department of Mechanical Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan National Astronomical Research Institute of Thailand (NARIT) Chiangmai Thailand National Electronics and Computer Technology Center(NECTEC) National Science and Technology Development Agency Pathum Thani Thailand National Energy and Technology Center(ENTEC) National Science and Technology Development Agency Pathum Thani Thailand

This paper aims to investigate the impact of switching frequencies in pulse discharging of batteries by testing with Lithium-ion cells. Applying lithium-ion batteries in high power applications is needed to be managed according to the demand of load power and current profile. The pulse current discharging technique with different frequencies is expected to improve the charging/ discharging capacity and energy of lithium-ion batteries. In this paper, lithium-ion cells were tested with pulse current at various switching frequencies with 75% duty cycle during discharging. The results of pulse discharging with different switching frequencies were compared with constant current discharging method by evaluating capacity and energy. From this research, the results indicated that pulse discharging at low frequencies generated high discharging capacity than constant current discharging.

关键词： Lithium-ion batteries Electrical engineering Switching frequency Testing

Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic Segmentation

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Zhang, Dengke Tang, Quan Liu, Fagui Mei, Haiqing Chen, C.L. Philip The School of Computer Science and Engineering South China University of Technology Guangzhou510006 China The Department of New Network Pengcheng Laboratory Shenzhen518000 China The China Tobacco Guangdong Industrial Corporation Guangzhou510385 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Semi-supervised semantic segmentation has witnessed remarkable advancements in recent years. However, existing algorithms are based on convolutional neural networks and directly applying them to Vision Transformers poses certain limitations due to conceptual disparities. To this end, we propose TokenMix, a data augmentation technique specifically designed for semi-supervised semantic segmentation with Vision Transformers. TokenMix aligns well with the global attention mechanism by mixing images at the token level, enhancing learning capability for contextual information among image patches. We further incorporate image augmentation and feature augmentation to promote the diversity of augmentation. Moreover, to enhance consistency regularization, we propose a dual-branch framework where each branch applies image and feature augmentation to the input image. We conduct extensive experiments across multiple benchmark datasets, including Pascal VOC 2012, Cityscapes, and COCO. Results suggest that the proposed method outperforms state-of-the-art algorithms with notably observed accuracy improvement, especially under limited fine annotations. Copyright © 2025, The Authors. All rights reserved.

关键词：