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Aerial-ground collaborative routing with time constraints

Chinese Journal of Aeronautics 2023年第2期36卷 270-283页

作者： Jiahao XING Lichen SU Wenjing HONG Lu TONG Renli LYU Wenbo DU School of Electronics and Information Engineering Beihang UniversityBeijing 100091China School of Future Aerospace Technology/Shen Yuan Honors College Beihang UniversityBejing 100091China School of Automation Science and Electrical Engineering Beihang UniversityBejing 100091China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Shenzhen 518055China Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Research Institute of Frontier Science Beihang UniversityBeijing 100083China CAAC Key Laboratory of General Aviation Operation Civil Aviation Management Institute of ChinaBeijing 100102China

The advancement of autonomous technology makes electric-powered drones an excellent choice for flexible logistics services at the last mile delivery *** reach a balance between green transportation and competitive edge,the collaborative routing of drones in the air and trucks on the ground is increasingly invested in the next generation of delivery,where it is particularly reasonable to consider customer time windows and time-dependent travel times as two typical time-related factors in daily *** this paper,we propose the Vehicle Routing Problem with Drones under Time constraints(VRPD-T)and focus on the time constraints involved in realistic scenarios during the delivery.A mixed-integer linear programming model has been developed to minimize the total delivery completion ***,to overcome the limitations of standard solvers in handling large-scale complex issues,a space-time hybrid heuristic-based algorithm has been developed to effectively identify a high-quality *** numerical results produced from randomly generated instances demonstrate the effectiveness of the proposed algorithm.

关键词： Aerial-ground collaborative delivery Mixed-integer programming Space-time hybrid heuristic algorithm Vehicle routing problem with drones Time-dependent travel times

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Path Following of a Tractor-Trailer System via Dynamic Extension in Forward and Backward Motion 12

Path Following of a Tractor-Trailer System via Dynamic Exten...

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12th RSI International Conference on Robotics and Mechatronics, ICRoM 2024

作者： Olyai, Mohammad Alipour, Khalil Tarvirdizadeh, Bahram Sorouri, Majid Ghamari, Mohammad Laboratory Department of Mechatronics Eng. Tehran Iran Maynooth University Department of Electronic Engineering Co. Kildare Maynooth Ireland Science and Research Branch Islamic Azad University Department of Computer and Mechatronics Engineering Tehran Iran California Polytechnic State University Electrical Engineering Department San Luis ObispoCA93407 United States

ISBN: (纸本)9798331529734

Tractor-trailer wheeled robots (TTWRs) have gained significant attention across various industries and control studies due to their complex dynamics and non-minimum phase behavior, which pose substantial control challenges. This study investigates the control of a differentially-driven tractor to follow a specified path under pure rolling conditions in both forward and backward motion. Notably, it has been established that using static feedback linearization (SFL) leads to instability during backward motion. In contrast, this research uses dynamic feedback linearization (DFL), also known as dynamic extension, for controlling the tractor-trailer system in both directions for the first time. Our findings demonstrate that the internal dynamics of the system remain stable in both forward and backward motions, enabling successful adherence to the desired path. © 2024 IEEE.

关键词： Tractors (truck)

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Design of Distributed Nonlinear Observers Without Using Global Inputs

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IEEE Transactions on Automatic Control 2025年

作者： Cao, Ganghui Wang, Jinzhi Polycarpou, Marios M. Peking University State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Beijing100871 China University of Cyprus KIOS Research and Innovation Center of Excellence and the Department of Electrical and Computer Engineering Nicosia1678 Cyprus

This paper investigates the design of distributed observers for a class of nonlinear systems. The designed distributed observers reside in a network of sensor nodes. The communication links in the network enable each sensor node to estimate all states of the nonlinear system, even though each one can only collect a small portion of the system's outputs. However, all inputs of the system are still needed at each node to carry out a correct state estimation. For this problem, the paper further proposes a distributed nonlinear observer without using global inputs, in which each sensor node only needs partial input information of the nonlinear system. © 1963-2012 IEEE.

关键词： Nonlinear simulations

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Exploring Image Generation for UAV Change Detection

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1061-1072页

作者： Xuan Li Haibin Duan Yonglin Tian Fei-Yue Wang Peng Cheng Laboratory Shenzhen 518000China IEEE State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083 Department of Automation University of Science and Technology of ChinaHefei 230027 State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense TechnologyChangsha 410073China

Change detection(CD)is becoming indispensable for unmanned aerial vehicles(UAVs),especially in the domain of water landing,rescue and ***,even the most advanced models require large amounts of data for model training and ***,sufficient labeled images with different imaging conditions are *** by computer graphics,we present a cloning method to simulate inland-water scene and collect an auto-labeled simulated *** simulated dataset consists of six challenges to test the effects of dynamic background,weather,and noise on change detection ***,we propose an image translation framework that translates simulated images to synthetic *** framework uses shared parameters(encoder and generator)and 22×22 receptive fields(discriminator)to generate realistic synthetic images as model training *** experimental results indicate that:1)different imaging challenges affect the performance of change detection models;2)compared with simulated images,synthetic images can effectively improve the accuracy of supervised models.

关键词： Change detection computer graphics image translation simulated images synthetic images unmanned aerial vehicles(UAVs)

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Van der Waals integration inch-scale 2D MoSe_(2) layers on Si for highly-sensitive broadband photodetection and imaging

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Nano research 2023年第8期16卷 11422-11429页

作者： Yupiao Wu Shuo-En Wu Jinjin Hei Longhui Zeng Pei Lin Zhifeng Shi Qingming Chen Xinjian Li Xuechao Yu Di Wu School of Physics and Microelectronics and Key Laboratory of Material PhysicsZhengzhou UniversityZhengzhou 450052China Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA School of Microelectronics Science and Technology Sun Yat-Sen UniversityZhuhai 519082China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China

As one of the most promising materials for two-dimensional transition metal chalcogenides(2D TMDs),molybdenum diselenide(MoSe_(2))has great potential in photodetectors due to its excellent properties like tunable bandgap,high carrier mobility,and excellent air *** 2D MoSe_(2)-based photodetectors have been reported to exhibit admired performance,the large-area 2D MoSe_(2)layers are difficult to be achieved via conventional synthesis methods,which severely impedes its future ***,we present the controllable growth of large-area 2D MoSe_(2)layers over 3.5-inch with excellent homogeneity by a simple post-selenization ***,a high-quality n-MoSe_(2)/p-Si van der Waals(vdW)heterojunction device is in-situ fabricated by directly growing 2D n-MoSe_(2)layers on the patterned p-Si substrate,which shows a self-driven broadband photoresponse ranging from ultraviolet to mid-wave infrared with an impressive responsivity of 720.5 mA·W^(−1),a high specific detectivity of 10^(13) Jones,and a fast response time to follow nanosecond pulsed optical *** addition,thanks to the inch-level 2D MoSe_(2)layers,a 4×4 integrated heterojunction device array is achieved,which has demonstrated good uniformity and satisfying imaging *** large-area 2D MoSe_(2)layer and its heterojunction device array have great promise for high-performance photodetection and imaging applications in integrated optoelectronic systems.

关键词： molybdenum diselenide large-area synthesis broadband photodetector integrated device array van der Waals(vdW)heterojunction

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ANIMC: A Soft Approach for Autoweighted Noisy and Incomplete Multiview Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第2期3卷 192-206页

作者： Fang, Xiang Hu, Yuchong Zhou, Pan Wu, Dapeng Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering The School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Multiview clustering has wide real-world applications because it can process data from multiple sources. However, these data often contain missing instances and noises, which are ignored by most multiview clustering methods. Missing instances may make these methods difficult to use directly, and noises will lead to unreliable clustering results. In this article, we propose a novel autoweighted noisy and incomplete multiview clustering (ANIMC) approach via a soft autoweighted strategy and a doubly soft regular regression model. First, by designing adaptive semiregularized nonnegative matrix factorization, the soft autoweighted strategy assigns a proper weight to each view and adds a soft boundary to balance the influence of noises and incompleteness. Second, by proposing θ-norm, the doubly soft regularized regression model adjusts the sparsity of our model by choosing different θ. Compared with previous methods, ANIMC has three unique advantages: 1) it is a soft algorithm to adjust our approach in different scenarios, thereby improving its generalization ability;2) it automatically learns a proper weight for each view, thereby reducing the influence of noises;3) it performs doubly soft regularized regression that aligns the same instances in different views, thereby decreasing the impact of missing instances. Extensive experimental results show its superior advantages over other state-of-the-art works. © 2020 IEEE.

关键词： Clustering algorithms

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PVTSizing: A TuRBO-RL-Based Batch-Sampling Optimization Framework for PVT-Robust Analog Circuit Synthesis 24

PVTSizing: A TuRBO-RL-Based Batch-Sampling Optimization Fram...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Kong, Zichen Tang, Xiyuan Shi, Wei Du, Yiheng Lin, Yibo Wang, Yuan School of Integrated Circuits Peking University China Institute for Artificial Intelligence Peking University China Mpw Center Peking University China Department of Electrical and Computer Engineering The University of Texas Austin United States Yuanpei College Peking University China Beijing Laboratory of Future Integrated Circuit Technology and Science Peking University China Beijing Advanced Innovation Center for Integrated Circuits China

ISBN: (纸本)9798400706011

With the CMOS technology advancing and the complexity of circuits growing, the demand for analog/mixed-signal design automation tools is increasing quickly. Although some tools have been developed to tackle this challenge, the performance degradation caused by process, voltage, and temperature (PVT) variations has been less considered. This paper presents PVTSizing, an optimization framework for PVT-robust analog circuit synthesis. PVTSizing adopts trust region Bayesian optimization (TuRBO) for high-quality initial datasets and reference points. Multi-task reinforcement learning (RL) is utilized for PVT optimization. Both TuRBO and RL are batch-friendly, allowing parallel sampling of design solutions. Meanwhile, critic-assisted pruning and zoom target metrics are proposed to improve sample efficiency and reduce runtime. In addition, this framework naturally supports sizing over random mismatch. On 4 real-world circuits with TSMC 28/180nm process, PVTSizing achieves 1.9× - 8.8× sample efficiency and 1.6× - 9.8× time efficiency improvements compared to prior sizing tools from both industry and academia. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Reinforcement learning

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Automatic Detection and Characterization of Human Veins Using Infra-Red Image Processing

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Journal of computer and Communications 2024年第9期12卷 141-159页

作者： Jean Ndoumbe Brice Ekobo Akoa Gaelle Patricia Talotsing Frederic Franck Kounga Samuel Kaissassou Bertin Chouanmo Njo Laboratory of Computer Engineering Data Science and Artificial Intelligence Department of Computer & Telecommunications Engineering National Higher Polytechnic School Douala Cameroon Laboratory of Electrical Engineering Mechatronics and Signal Processing Department of Electrical & Telecommunications Engineering National Advanced School of Engineering Yaound Cameroon Mobile Computing and Networking Research Laboratory Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada DigiPlus SARL Bonamoussadi Douala Cameroon

The detection and characterization of human veins using infrared (IR) image processing have gained significant attention due to its potential applications in biometric identification, medical diagnostics, and vein-based authentication systems. This paper presents a low-cost approach for automatic detection and characterization of human veins from IR images. The proposed method uses image processing techniques including segmentation, feature extraction, and, pattern recognition algorithms. Initially, the IR images are preprocessed to enhance vein structures and reduce noise. Subsequently, a CLAHE algorithm is employed to extract vein regions based on their unique IR absorption properties. Features such as vein thickness, orientation, and branching patterns are extracted using mathematical morphology and directional filters. Finally, a classification framework is implemented to categorize veins and distinguish them from surrounding tissues or artifacts. A setup based on Raspberry Pi was used. Experimental results of IR images demonstrate the effectiveness and robustness of the proposed approach in accurately detecting and characterizing human. The developed system shows promising for integration into applications requiring reliable and secure identification based on vein patterns. Our work provides an effective and low-cost solution for nursing staff in low and middle-income countries to perform a safe and accurate venipuncture.

关键词： Vein Detection Blood Radiation Infrared Image CLAHE Algorithm Raspberry Pi

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Wireless control of a D.C. Motor Used for Driving a Conveyor Belt

Wireless control of a D.C. Motor Used for Driving a Conveyor...

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2024 International Conference on Circuit, systems and Communication, ICCSC 2024

作者： Livint, Petru Banu, Ioan-Viorel Culea, George Manale, Bouderbala Majout, Btissam Dusa, Alexandru University 'Vasile Alecsandri' of Bacau Department of Energetics and Science Computer Romania Sidi Mohammed Ben Abdellah University Fez Limas Laboratory Faculty of Sciences Dhar El Mahraz Morocco Sidi Mohammed Ben Abdellah University Fez Laboratory of Engineering Modellingand Systems Analysis Morocco 'Dunarea de Jos' University of Galati Department of Automatic and Electrical Engineering Romania

ISBN: (纸本)9798350365306

This article presents an experimental stand for the remote control of a D.C. motor used to drive a conveyor belt. This is based on two development boards Arduino Uno and two shields NRF24L01. The D. C. motor is supplied from a D.C. voltage source by means of the H type bridge. The emitter circuit sends the control signal generated through a potentiometer to the receptor circuit by means of radio waves at a frequency of 2.4 GHz. The receptor circuit receives the analogue signal emitted by the emitting circuit, transforms it into a PWM (pulse width modulation) signal and uses it for controlling the transistors of the H-bridge. For implementing and validating the remote control system of the D.C. motor two programs have been issued in the programming environment Arduino IDE for the two circuits. emitter and receptor. The remote control system of the D.C. motor has been running in the same way as the direct control of this. The remote control is used in the case of the electric actuation systems made with D.C. motors continuous used in spaces inaccessible to the human operator. © 2024 IEEE.

关键词： Belts

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