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4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Zhang, Zhou Chen, Tianyun Liu, Zhanhao North China Electric Power University School of Control and Computer Engineering Beijing China Yanbian University College of Science Yanji China Wuhan Textiles University School of Electronic and Electrical Engineering Wuhan China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

In fringe projection profilometry, affected by the gamma distortion of the projector, the reconstructed topography of the measured object has a large error compared to the actual situation. In order to eliminate the gamma distortion error, this paper innovatively proposes a mathematical model to solve the wrapping phase with 3(N)+1 images based on the principle of the N-step phase-shift method. The model adds an image modulated by half of the background illumination with gamma distortion to the three-step phase-shifted image. After iteration, the wrapping phase can be solved, and the value of the background illumination and the value of the projector gamma distortion can be obtained. The method effectively avoids the influence of gamma distortion on solving the wrapped phase. It is verified by MATLAB simulation that the method can eliminate gamma distortion. Comparing the phases solved by the simulation standard conditions, the four-step phase-shift method, and the 3(N)+1 method, the results show that the method effectively eliminates the influence of gamma distortion and has high accuracy. © 2022 IEEE.

关键词： Iterative methods

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Measurement-Device-Independent Deterministic Quantum Key Distribution 9

Measurement-Device-Independent Deterministic Quantum Key Dis...

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9th Annual International Conference on Network and Information Systems for computers, ICNISC 2023

作者： Zhang, Ting Liu, Jie Kang, Guodong Jishou University School of Physics and Mechanical and Electrical Engineering Jishou China Jishou University School of Computer Science and Engineering School of Physics and Mechanical and Electrical Engineering Jishou China Hunan Normal University Key Laboratory of Low Dimensional Quantum Structures and Quantum Control Ministry of Education College of Physics and Electronic Science Changsha China

ISBN: (纸本)9798350306682

Improve the secure key rate and the limited communication distance is the main goal in the field of quantum key distribution. Measurement-device-independent quantum key distribution, not only removes all detector side channel attacks, but also doubles the secure transmission distance. However, most of measurement-device -independent quantum key distribution protocols are non-deterministic. In this paper, we propose a measurement-device-independent deterministic quantum key distribution protocol that doubles the secure distance and amends the non-deterministic factor of current measurement-device -independent quantum key distribution. And with imperfect devices model assumption, we derived the formula of the performances for it and find that the limited distance can be extended over 200km with relatively high secure key rate by employing parameters of current technologies. © 2023 IEEE.

关键词： Quantum cryptography

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Research on Arc Fault Simulation Device Based on Closed-loop Feedback control 5

Research on Arc Fault Simulation Device Based on Closed-loop...

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5th IEEE International Conference on Automation, Electronics and Electrical engineering, AUTEEE 2022

作者： Jingjing, Su Zhihong, Xu School of Computer and Control Engineering Minjiang University Fuzhou China Fujian Key Laboratory of New Energy Generation and Power Conversion Fuzhou China College of Electrical Engineering and Automation Fuzhou University Fuzhou China

ISBN: (纸本)9781665471978

An efficient arc fault simulation device is beneficial to the research on the mechanism and detection technology of arc faults. In order to simulate the arc fault caused by insulation aging, an arc fault simulation device based on closed-loop feedback control was developed. The device consists of two high-voltage carbonization circuits and a test circuit, which are used for pretreating cable specimens and testing the effects of carbonization respectively. In order to improve the success rate of cable carbonization channels formation, arc voltage, arc current-zero period and arc current rise rate are taken as the basis for arc fault judgment. Finally, the characteristics of carbonized arc are analyzed by using time domain and frequency domain analysis methods. The results show that the developed cable carbonization device can generate continuous burning arc and reduce the interference of human factors in the experiment process, which lays a foundation for further research on the formation mechanism of fault arc. © 2022 IEEE.

关键词： Carbonization

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Design of Diesel Oxidation Catalyst Temperature control System Based on Fuzzy Adaptive PID

Design of Diesel Oxidation Catalyst Temperature Control Syst...

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2021 International Conference on Robotics Automation and Intelligent control, ICRAIC 2021

作者： Wang, Ning Sun, Yao Hu, Yunfeng Zhao, Jinghua Gong, Xun State Key Laboratory of Automotive Simulation and Control Jilin Changchun China College of Artificial Intelligence Jilin University Jilin Changchun China Department of Control Science and Engineering Jilin University Jilin Changchun China College of Computer Jilin Normal University Jilin Siping China

This paper presents a temperature control framework of Diesel Oxidation Catalyst (DOC) of after-treatment system (ATS) which aims to increase the control precise of DOC temperature under different exhaust flow rates. To start with, a control-oriented DOC temperature model is established. Considering the sensitivity of DOC to different exhaust flow rate, a fuzzy adaptive PID temperature control system framework under the Smith predictor is designed. Finally, the controller is verified in the Matlab/Simulink. The results show that when tracking the desired temperature, the overshoot is reduced and the response speed is faster at different exhaust flow rates compared with the traditional PID control system. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Temperature control

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Branch-Yolo：Efficient Object Detector for Thin Structure Objects Like Pantograph

SSRN

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SSRN 2024年

作者： Li, Yaqian Han, Jiaqi Li, Haibin Zhang, Wenming College of Electrical Engineering Yanshan University Hebei Qinhuangdao066000 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Hebei Qinhuangdao066000 China

The pantograph is the key structure in the railway Pantograph-OCS system, acting as the switch for the railway traction power supply system. So it’s crucial to detect the pantograph's lifting and lowing states for production efficiently and safely. However, due to the pantograph’s special slender structure and complex application scenarios, it occupies few pixels and is susceptible to background interference, making accurate real-time detection a challenging task. In this work, we aim to propose a generalized model, designed for detecting, branch-like objects with thin structure and multi-scale size such as pantographs. To this end, we propose the Branch-YOLO based on YOLOv8, which is improved in two stages, feature extraction and feature fusion, to simultaneously enhance perception. First, we introduce BrLayer is consist of BranchConv and EFAC(Extend receptive field attention Convolution), BranchConv can adaptively capture features of thin and tortuous local structures,EFAC is able to assist in expanding the effective receptive field. Subsequently, we propose a feature fusion network (BranchNet) to integrate multilevel semantic information and multi-scale features, which significantly reduces background interference in detecting slender structure objects and enhances the ability to perceive changes in object scale. Besides, we propose the Lightweight Cross-Kernel Convolution layer (LckLayer) and introduce the Feature Decomposition module (FdM) in BranchNet for lightweight design, reducing the computational overhead and enhancing model efficiency. Our proposed Branch-YOLO not only achieves the best performance on the multi-scale pantograph datasets but also attains an outstanding 42.9% AP on the COCO val2017 datasets, with 5.9M parameters and 16.8 GFLOPs. © 2024, The Authors. All rights reserved.

关键词： Religious buildings

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Incomplete Multi-view Clustering via Diffusion Contrastive Generation

arXiv

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arXiv 2025年

作者： Zhang, Yuanyang Lin, Yijie Yan, Weiqing Yao, Li Wan, Xinhang Li, Guangyuan Zhang, Chao Ke, Guanzhou Xu, Jie School of Computer Science and Engineering Southeast University Nanjing210096 China College of Computer Science Sichuan University China School of Computer and Control Engineering Yantai University China Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education China College of Computer National University of Defense Technology China College of Computer Science and Technology Zhejiang University China Department of Control Science and Intelligence Engineering Nanjing University China School of Economics and Management Beijing Jiaotong University China School of Computer Science and Engineering University of Electronic Science and Technology of China China

Incomplete multi-view clustering (IMVC) has garnered increasing attention in recent years due to the common issue of missing data in multi-view datasets. The primary approach to address this challenge involves recovering the missing views before applying conventional multi-view clustering methods. Although imputation-based IMVC methods have achieved significant improvements, they still encounter notable limitations: 1) heavy reliance on paired data for training the data recovery module, which is impractical in real scenarios with high missing data rates;2) the generated data often lacks diversity and discriminability, resulting in suboptimal clustering results. To address these shortcomings, we propose a novel IMVC method called Diffusion Contrastive Generation (DCG). Motivated by the consistency between the diffusion and clustering processes, DCG learns the distribution characteristics to enhance clustering by applying forward diffusion and reverse denoising processes to intra-view data. By performing contrastive learning on a limited set of paired multi-view samples, DCG can align the generated views with the real views, facilitating accurate recovery of views across arbitrary missing view scenarios. Additionally, DCG integrates instance-level and category-level interactive learning to exploit the consistent and complementary information available in multi-view data, achieving robust and end-to-end clustering. Extensive experiments demonstrate that our method outperforms state-of-the-art approaches. Copyright © 2025, The Authors. All rights reserved.

关键词： Contrastive Learning

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Tactile-Based Object Pose Estimation Employing Extended Kalman Filter 8

Tactile-Based Object Pose Estimation Employing Extended Kalm...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Lin, Qiguang Yan, Chaojie Li, Qiang Ling, Yonggen Zheng, Yu Lee, Wangwei Wan, Zhaoliang Huang, Bidan Liu, Xiaofeng College of IoT Engineering Hohai University Jiangsu Key Laboratory of Special Robotic Technology Jiangsu Changzhou213022 China Zhejiang University Institute of Cyber-System and Control State Key Laboratory of Industrial Control and Technology Hangzhou China Bielefeld33619 Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350300178

In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the estimation of the object's pose using an Extended Kalman Filter (EKF) based approach. We defined and derived the state and measurement equations, as well as evaluated the estimation accuracy in grasping tasks. The approach is able to effectively account for the pose transition caused by tactile pushing, and the mapping from the object's pose to the contact position and normal direction as measured by the tactile sensor. The method was evaluated in multiple grasping experiments in simulation scenarios. Results show that the estimation can converge towards the ground truth in a relatively short period of time, with displacement and rotation errors remaining within acceptable levels. This new method has the potential to improve the accuracy and reliability of robotic grasping and manipulation tasks. © 2023 IEEE.

关键词： Extended Kalman filters

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Efficient Hybrid Multi-Population Genetic Algorithm for Multi-UAV Task Assignment in Consumer Electronics Applications

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IEEE Transactions on Consumer Electronics 2025年

作者： Bai, Xiaoshan Jiang, Haoyu Li, Chao Ullah, Inam Dabel, Maryam M. Al Bashir, Ali Kashif Wu, Zongze Sam, Shuzhi Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen University Shenzhen City Joint Laboratory of Autonomous Unmanned Systems and Intelligent Manipulation Shenzhen518060 China Tashkent State University of Economics Department of Artificial Intelligence Tashkent100066 Uzbekistan University of Hafr Al Batin Department of Computer Science and Engineering College of Computer Science and Engineering Saudi Arabia Manchester Metropolitan University Manchester United Kingdom Shenzhen518060 China National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the development of the logistics industry. Consequently, how to deliver consumer electronics to households at minimal cost has become a crucial factor that limits the development of the consumer technology industry. To tackle this problem, this paper studies the task assignment problem for multiple initially dispersed UAVs to deliver products to target locations while minimizing their total operation time. Each UAV can continuously provide delivery services to multiple target locations within its limited loading capacity and operation time. To solve this problem, we propose several hybrid multipopulation genetic algorithms. First, a novel crossover operator for the genetic algorithms is designed, through which a single parent chromosome can generate offspring individually. Second, two mutation mechanisms are performed to increase gene diversity. Third, multiple local search strategies are employed to enhance the populations’ fitness during each iteration of evolution. An improved 2-opt local search strategy is applied to optimize individual chromosomes when their similarity with the current best chromosome falls below a prescribed threshold. Alternatively, local search strategies are utilized for 1-opt, 2h-opt and interchange processes. Combining local search strategies, genetic operators, and the multi-population mechanism leads to several hybrid multi-population genetic algorithms. Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior performance among the designed hybrid genetic algorithms, the minimum marginal cost algorithm (MMA), and the existing popular Co-evolutionary Multi-population Genetic Algorithm (CMGA). In exp

关键词： Genetic algorithms

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CAMInterHand: Cooperative Attention for Multi-View Interactive Hand Pose and Mesh Reconstruction

CAMInterHand: Cooperative Attention for Multi-View Interacti...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Guwen Han Qi Ye Anjun Chen Jiming Chen College of Computer Science and Technology Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China The College of Control Science and Engineeringthe State Key Laboratory of Industrial Control Technology Zhejiang University and the Key Key Lab of CS&AUS of Zhejiang Province

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Interactive hand mesh reconstruction from singleview images poses a significant challenge with the severe occlusion and depth ambiguity inherent in interactive hand gestures. Recent approaches that employ probabilistic models and tokenpruned techniques have shown decent results in multi-view human body reconstruction. Nevertheless, these methods have not fully utilized multi-scale semantic information from multiview images and are not applicable in scenarios involving severe occlusion during dual-hand interactions. Simultaneously, current single-view methods independently reconstruct the left and right hands, which are ineffective in enhancing the interaction between both hands. To address these challenges, we propose CAMInterHand, a cooperative attention-based method for multi-view interactive hand pose and mesh reconstruction. Specifically, CAMInterHand extracts local pyramid features and global vertex features from multi-scale feature maps of multi-view images, enabling the exploration of rich local semantic information and facilitating effective feature alignment. Furthermore, CAMInterHand employs the cooperative attention fusion module to fuse all features from multi-view images, enhancing interactions among vertices of dual hands within global and local contexts. We conduct extensive experiments on the large-scale multi-view dataset InterHand2.6M and CAMInterHand achieves a substantial performance improvement over existing methods for multi-view and single-view interactive hand reconstruction.

关键词： Fuses Semantics Feature extraction Probabilistic logic Data mining Robotics and automation Image reconstruction

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An Electromagnetic Covert Channel based on Neural Network Architecture 27

An Electromagnetic Covert Channel based on Neural Network Ar...

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27th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2021

作者： Gu, Chaojie Chen, Jiale Tan, Rui Jiang, Linshan College of Control Science and Engineering Zhejiang University China School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781665408783

Outsourcing the design of deep neural networks may incur cybersecurity threats from the hostile designers. This paper studies a new covert channel attack that leaks the inference results over the air through a hostile design of the neural network architecture and the computing device's electromagnetic radiation when executing the neural network. Specifically, the hostile neural network consists of a series of binary models that correspond to all classes and are executed sequentially. The execution terminates once any binary model given the input is positive about its responsible class. We describe an approach to generate such binary models by pruning a benign neural network that is trained using the standard method to deal with all the classes. Compared with the benign neural network, the hostile one has similar memory usage and negligible classification accuracy drop, but distinct inference times for the samples of different classes. As a result, the hostile neural network's classification result can be eavesdropped by measuring the duration of the electromagnetic radiation emanated from the computing device. As neural networks are stored and transmitted as data files, this covert channel attack is more stealthy to the anti-malware than other code-based attacks. We implement the described attack on two edge computing devices that execute the hostile neural network on CPU or GPU. Evaluation shows 100% empirical accuracy in eavesdropping the inference results. © 2021 IEEE.

关键词： Electromagnetic wave emission

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