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design and implementation of unmanned aerial vehicle localization and light tracking system

The Journal of China Universities of Posts and Telecommunications 2023年第4期30卷 67-74页

作者： Xu Ming Dong Chen Li Hanlu Luo Qiming Wang Lizi Zhang Wanru Liu Huixin School of Digital Media and Design Arts Beijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing 100876China

Unmanned aerial vehicles(UAV)are applied widely and profoundly in various ***,high-precision positioning and tracking in multiple scenarios are the core requirements for UAV *** ensure stable communication of UAVs in denial environments with substantial electromagnetic interference,a systematic solution is proposed based on a deep learning algorithm for target detection and visible light for UAV *** the cost and computational power limitations on the hardware,the you only look once(YOLO)v4-Tiny model is used for static target detection of the UAV *** UAV tracking,and a light tracker that can adjust the angle of emitted light and focus it on the target is used for dynamic tracking ***,achieving the primary conditions of UAV optical communication with good secrecy is also suitable for dynamic *** UAV tracker positions the UAV model by returning the coordinates and calculating the time delay,and then controls the spotlight to target the *** order to facilitate the deployment of deep learning models on hardware devices,the lighter and more efficient model is selected after *** trained model can achieve 99.25%accuracy on the test *** dynamic target detection can reach 20 frames per second(FPS)on a computer with an MX520 graphics processing unit(GPU)and 6 GB of random access memory(RAM).Dynamic target detection on a Jetson Nano can reach 5.4 FPS.

关键词： unmanned aerial vehicles deep learning light tracking target detection unmanned aerial vehicles location unmanned aerial vehicles tracking

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Multi-Resource Allocation for On-Device Distributed Federated Learning systems

Multi-Resource Allocation for On-Device Distributed Federate...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Yulan Gao Ziqiang Ye Han Yu Zehui Xiong Yue Xiao Dusit Niyato The National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China The School of Computer Science and Engineering Nanyang Technological University Singapore Pillar of Information Systems Technology and Design Singapore University of Technology and Design (SUTD) Singapore

ISBN: (纸本)9781665435413

This work poses a distributed multi-resource allocation scheme for minimizing the weighted sum of latency and energy consumption in the on-device distributed federated learning (FL) system. Each mobile device in the system engages the model training process within the specified area and allocates its computation and communication resources for deriving and uploading parameters, respectively, to minimize the objective of system subject to the computation/communication budget and a target latency requirement. In particular, mobile devices are connect via wireless TCP/IP architectures. Exploiting the optimization problem structure, the problem can be decomposed to two convex sub-problems. Drawing on the Lagrangian dual and harmony search techniques, we characterize the global optimal solution by the closed-form solutions to all sub-problems, which give qualitative insights to multi-resource tradeoff. Numerical simulations are used to validate the analysis and assess the performance of the proposed algorithm.

关键词： Wireless communication Training Machine learning algorithms Federated learning Computational modeling Simulation Search methods

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Free Adversarial Training with Layerwise Heuristic Learning 11th

Free Adversarial Training with Layerwise Heuristic Learning

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11th International Conference on Image and Graphics, ICIG 2021

作者： Zhang, Haitao Shi, Yucheng Dong, Benyu Han, Yahong Li, Yuanzhang Kuang, Xiaohui College of Intelligence and Computing and Tianjin Key Lab of Machine Learning Tianjin University Tianjin China Beijing Institute of Technology Beijing China National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9783030873578

Due to the existence of adversarial attacks, various applications that employ deep neural networks (DNNs) have been under threat. Adversarial training enhances robustness of DNN-based systems by augmenting training data with adversarial samples. Projected gradient descent adversarial training (PGD AT), one of the promising defense methods, can resist strong attacks. We propose "free" adversarial training with layerwise heuristic learning (LHFAT) to remedy these problems. To reduce heavy computation cost, we couple model parameter updating with projected gradient descent (PGD) adversarial example updating while retraining the same mini-batch of data, where we "free" and unburden extra updates. Learning rate reflects weight updating speed. Weight gradient indicates weight updating efficiency. If weights are frequently updated towards opposite directions in one training epoch, then there are redundant updates. For higher level of weight updating efficiency, we design a new learning scheme, layerwise heuristic learning, which accelerates training convergence by restraining redundant weight updating and boosting efficient weight updating of layers according to weight gradient information. We demonstrate that LHFAT yields better defense performance on CIFAR-10 with approximately 8% GPU training time of PGD AT and LHFAT is also validated on ImageNet. We have released the code for our proposed method LHFAT at https://***/anonymous530/LHFAT. © 2021, Springer Nature Switzerland AG.

关键词： Deep neural networks

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TICNet: Three-Branch Real-Time Semantic Segmentation Network with Intensive Compensation of Railway Track Scenes

TICNet: Three-Branch Real-Time Semantic Segmentation Network...

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Machine Learning and Computer Application (ICMLCA), International Conference on

作者： Yiwen Bai Lu Yang Lei Zhang Yajing Song School of Transportation Science and Engineering Beihang University Beijing China Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China Traffic Control Technology Co. Ltd Beijing China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

With the rapid development of railway traffic system, real-time semantic segmentation plays a crucial role in railway track scene monitoring. However, most of the existing methods use lightweight convolution to reduce the computational complexity, which results in reduced accuracy. To solve this problem, this paper proposes a real-time semantic segmentation network called TICNet, which is specifically used for accurate segmentation of railway track scenes. TICNet uses a novel three-branch structure designed for efficient feature extraction and accurate segmentation. Results on the RailSem19 dataset show that TICNet has a segmentation accuracy of 62.36% mIoU with an inference speed of 81.2 FPS, which is significantly better than many existing methods.

关键词： Accuracy Convolution Semantic segmentation Semantics Focusing Machine learning Feature extraction Real-time systems Computational complexity Monitoring

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Broadband Wide-Angle Linear-to-Circular Polarization Converter Based on Metal Strips Loaded Metasurface

Broadband Wide-Angle Linear-to-Circular Polarization Convert...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Jingwen Wang Shasha Deng Weidong Chen Zhongxiang Zhang Chang Chen School of Information Science and Technology University of Science and Technology of China Hefei China Key Laboratory of simulation and design for Electronic information system Hefei Normal University Hefei China

A transmissive broadband wide-angle linear-to-circular polarization converter based on metal strips loaded metasurface is proposed in this paper. The converter is composed of three metallic layers separated by dielectric substrates and the metal strips printed on each layer keep orthogonal to each other. To further investigate the operating mechanism of the design, equivalent circuit models are presented. Moreover, the converter is verified to be effective in polarization conversion through the full-wave simulation. With the insertion loss less than 2 dB and 3 dB, the simulation 3-dB axial ratio (AR) bandwidth keeps 67% and 76%, respectively. Furthermore, at an increased incident angle of 40°, the device can still maintain an AR bandwidth over 47% at 2 dB insertion loss, which manifests the validity and rationality of the converter design.

关键词： Strips Computational modeling Metals Insertion loss Bandwidth Metasurfaces Broadband communication

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A Band Stop Decoupling Structure for Circularly Polarized Antennas With Different Intervals

A Band Stop Decoupling Structure for Circularly Polarized An...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yuhang Ding Shasha Deng Weidong Chen Zhongxiang Zhang Chang Chen School of Information Science and Technology University of Science and Technology of China Hefei China Key Laboratory of simulation and design for Electronic information system Hefei Normal University Hefei China

In this paper, a novel band stop decoupling structure (BSDS) for circularly polarized microstrip antenna array with different intervals to realize mutual coupling reduction is proposed. The BSDS is composed of complementary split-rings resonator (CSRRs) and split-rings resonator (SRRs), where the CSRRs block TM waves by electric resonance and the SRRs block TE waves by magnetic resonance, respectively. The proposed design is verified by the simulation and the results indicate that the isolation enhancement more than 35 dB can be obtained at the center frequency of 3.4 GHz when the center spacing is 0.37 $\lambda$0. Futhermore, when the center spacing reduces to 0.26 $\lambda$0, the mutual coupling remains below 25 dB. Besides, the BSDS can improve the radiation pattern offset without affecting the gain and the backward radiation of antennas.

关键词： Mutual coupling Microstrip antenna arrays Surface waves Simulation Magnetic resonance Microstrip antennas Scattering parameters

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design of an Online Operational Task Reliability Analysis system in Nuclear Power Plant

Design of an Online Operational Task Reliability Analysis Sy...

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system Reliability and Safety Engineering (SRSE), International Conference on

作者： Wei Li Ming Yang Zhengxi He Zhao Gao Yan Xiong Zhongyue Zhang Dehang Jiang Jipu Wang Fundamental Science on Nuclear Safety and Simulation Technology Laboratory College of Nuclear Science and Technology Harbin Engineering University Harbin China Nuclear Reactor System Design Technology Key Laboratory China Nuclear Power Research and Design Institute Chendu China Institute for Advanced Study in Nuclear Energy & Safety College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen China

Human factors play an important role in human- computer interaction systems such as nuclear power plants (NPPs). Especially for the human-computer interaction process in unknown scenarios, incorrect personnel actions will affect the operation of equipment and systems, and finally the achievement of safety goals of NPPs. This paper presents a design of an online operational task reliability analysis (OOTRA) system which provides early warnings to operations in a timely manner by monitoring the states of plant systems and equipment, and operator actions. For any wrong action of operators, the OOTRA system can online evaluate the impact of the wrong action on the operational task and the goals of NPPs.

关键词：

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Energy-Efficient Cell-Free Network Assisted by Hybrid RISs

arXiv

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arXiv 2022年

作者： Lyu, Wanting Xiu, Yue Yang, Songjie Yuen, Chau Zhang, Zhongpei National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu61173 China Pillar Singapore University of Technology and Design Singapore487372 Singapore

In this letter, we investigate a cell-free network aided by hybrid reconfigurable intelligent surfaces (RISs), which consists of a mixture of passive and active elements that are capable of amplifying and reflecting the incident signal. To maximize the energy efficiency (EE) of the system, we formulate a joint transmit beamforming and RIS coefficients optimization problem. To deal with the fractional objective function, Dinkelbach transform, Lagrangian dual reformulation, and quadratic transform are utilized, with a block coordinate descent (BCD) based algorithm proposed to decouple the variables. In addition, successive convex approximation (SCA) method is applied to iteratively to tackle the non-convexity of the sub-problems. Simulation results illustrate the effectiveness and convergence of the proposed algorithm through analyzing the EE and sum rate performance with varying parameter settings. The proposed hybrid RISs schemes can achieve 92% of the sum rate but 188% of EE of active RISs schemes. As compared with passive RISs, 11% gain in sum rate can be achieved with comparable EE. Copyright © 2022, The Authors. All rights reserved.

关键词： Beamforming

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Interdiffusion Behaviors and Mechanical Properties of Zr−Hf system

SSRN

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SSRN 2024年

作者： Jia, Jie Liu, Ying Wang, Renquan Chen, Yuhang Sun, Yongduo He, Yong College of Materials Science and Engineering Sichuan University No.24 South Section 1 Yihuan Road Chengdu610065 China National Key Laboratory of Nuclear Reactor Technology Nuclear Power Institute of China Chengdu610213 China

In this work, Zr-Hf diffusion couples were firstly prepared by Spark Plasma Sintering (SPS) method and the diffusion behavior and mechanical properties of the Zr-Hf system in temperatures range from 1300 to 1600°C were investigated in detail. The microstructure characterization by SEM and TEM reveals that Zr-Hf diffusion zone form some amorphous and nanocrystalline grains in local area. Then the hardness and Young's modulus of the Zr-Hf system in the diffusion zone were tested and the results show that the hardness and Young’s modulus of the alloy system was enhanced by solid solution Hf element, and the maximum hardness and Young's modulus in the diffusion zone reached to 10.74GPa and 203.5GPa, respectively. Finally, based on the profiles of Electron probe microanalysis (EPMA), the interdiffusion coefficient is composition-dependent. The value calculated by Sauer-Freise method is between 10-13 m2/s and 10-11 m2/s, which indicating that SPS diffusion annealing significantly enhances the diffusion rate of the Zr-Hf system. Meanwhile, the interdiffusion coefficient decreases slowly with increasing Hf concentration. The diffusion activation energy Q and the frequency factor D0 of the Zr-Hf binary alloy in this experiment ranges from 182 to 226 kJ/mol and 8.0×10-6 to 4.1×10-5 m2/s, respectively. © 2024, The Authors. All rights reserved.

关键词： Hardness

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Location IoU: A New Evaluation and Loss for Bounding Box Regression in Object Detection

Location IoU: A New Evaluation and Loss for Bounding Box Reg...

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International Joint Conference on Neural Networks (IJCNN)

作者： Lu Yang Kai Zhang Jiaqi Liu Chongke Bi Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China Autobrain (Tianjin) Technology LTD Tianjin China College of Intelligence and Computing Tianjin University Tianjin China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

In the field of object detection bounding box regression, IoU (Intersection over Union) is a commonly used evaluation metric for measuring the overlap between predicted and ground truth bounding boxes. One limitation of IoU, however, is that the gradient goes to zero when there is no intersection between bounding boxes. Recent evaluation metrics have been developed to overcome this problem by incorporating penalty terms and other techniques for improving IoU. Despite these advances, existing methods still suffer to some degree from the problems of small gradients and slow rate of convergence. In this paper, a new evaluation method named LIoU (Location IoU) is proposed to address these issues. It can maximize the shared area of the intersection when used as the loss function and incorporate a variable gradient parameter to fit to datasets of different sizes. The experimental results indicate that we achieve 0.27% and 3.48% accuracy improvements respectively in SSD and YOLOv5 network on the VOC dataset, and 2.23% in the YOLOv5 network on the COCO dataset. The results of this study highlight the effectiveness of LIoU in improving the performance of object detection models.

关键词： YOLO Measurement Location awareness Accuracy Shape Neural networks Benchmark testing

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