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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Oumayma Kahouli Mariem Hafsa Hiba Hellara Imed Eddine Bennour Najoua Essoukri Ben Amara Olfa Kanoun Department of Computer Science National Engineering School of Sousse University of Sousse Sousse Tunisia Laboratory of Advanced Technology and Intelligent Systems National Engineering School of Sousse Laboratory of Measurement and Sensor Technology Technische Universität Chemnitz Chemnitz Germany Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Center of Sfax University of Sfax Tunisia

Electrical Impedance Tomography (EIT) is a clinical imaging technique that gained a lot of attention because it is a non-invasive and radiation-free method. To obtain an inner image of the domain under study, a specific number of electrodes is attached to the surface of the object, then through a pair of electrodes, a low alternative current is injected. Potentials produced by this injection are measured with the remaining electrodes. Based on these boundary voltages measurements, the inner conductivity can be inferred, thus the image is reconstructed. The focus of this paper is to overcome the major weakness of the EIT image reconstruction technique, which is the low spatial resolution of the reconstructed images caused by the non-linearity of EIT inverse problem. This paper considers this problem, an optimization problem that is solved using the Particle Swarm Optimization (PSO) meta-heuristic. A variant of the standard PSO is proposed and validated, first on a circular mesh composed of 686 triangles then on a lung mesh composed of 2707 triangles.

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A Stackelberg Game Approach for Signal Temporal Logic Control Synthesis with Uncontrollable Agents

arXiv

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arXiv 2025年

作者： Cui, Bohan Yu, Xinyi Giua, Alessandro Yin, Xiang Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China Thomas Lord Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Electrical and Electronic Engineering University of Cagliari Cagliari09123 Italy

In this paper, we investigate the control synthesis problem for Signal Temporal Logic (STL) specifications in the presence of uncontrollable agents. Existing works mainly address this problem in a robust control setting by assuming the uncontrollable agents are adversarial and accounting for the worst-case scenario. While this approach ensures safety, it can be overly conservative in scenarios where uncontrollable agents have their own objectives that are not entirely opposed to the system’s goals. Motivated by this limitation, we propose a new framework for STL control synthesis within the Stackelberg game setting. Specifically, we assume that the system controller, acting as the leader, first commits to a plan, after which the uncontrollable agents, acting as followers, take a best response based on the committed plan and their own objectives. Our goal is to synthesize a control sequence for the leader such that, for any rational followers producing a best response, the leader’s STL task is guaranteed to be satisfied. We present an effective solution to this problem by transforming it into a single-stage optimization problem and leveraging counterexample guided synthesis techniques. We demonstrate that the proposed approach is sound and identify conditions under which it is optimal. Simulation results are also provided to illustrate the effectiveness of the proposed framework. © 2025, CC BY.

关键词： Control system synthesis

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MetaFruit Meets Foundation Models: Leveraging a Comprehensive Multi-Fruit Dataset for Advancing Agricultural Foundation Models

arXiv

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arXiv 2024年

作者： Li, Jiajia Lammers, Kyle Yin, Xunyuan Yin, Xiang He, Long Lu, Renfu Li, Zhaojian Department of Electrical and Computer Engineering Michigan State University East LansingMI United States School of Chemical and Biomedical Engineering Nanyang Technological University Singapore Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Department of Agricultural and Biological Engineering Pennsylvania State University United States United States Department of Agriculture Agricultural Research Service East LansingMI United States Department of Mechanical Engineering Michigan State University East LansingMI United States

Fruit harvesting poses a significant labor and financial burden for the industry, highlighting the critical need for advancements in robotic harvesting solutions. Machine vision-based fruit detection has been recognized as a crucial component for robust identification of fruits to guide robotic manipulation. Despite considerable progress in leveraging deep learning and machine learning techniques for fruit detection, a common shortfall is the inability to swiftly extend the developed models across different orchards and/or various fruit species. Additionally, the limited availability of pertinent data further compounds these challenges. In this work, we introduce MetaFruit, the largest publicly available multi-class fruit dataset, comprising 4,248 images and 248,015 manually labeled instances across diverse U.S. orchards. Furthermore, this study proposes an innovative open-set fruit detection system leveraging advanced Vision Foundation Models (VFMs) for fruit detection that can adeptly identify a wide array of fruit types under varying orchard conditions. This system not only demonstrates remarkable adaptability in learning from minimal data through few-shot learning but also shows the ability to interpret human instructions for subtle detection tasks. The performance of the developed foundation model is comprehensively evaluated using several metrics, which outperforms the existing state-of-the-art algorithms in both our MetaFruit dataset and other open-sourced fruit datasets, thereby setting a new benchmark in the field of agricultural technology and robotic harvesting. The MetaFruit dataset (https://***/datasets/jiajiali/metafruit) and detection framework (https://***/JiajiaLi04/FMFruit) are open-sourced to foster future research in vision-based fruit harvesting, marking a significant stride toward addressing the urgent needs of the agricultural sector. © 2024, CC BY-NC-SA.

关键词： Fruits

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UHVDC Islanded Operation system Ultralow-Frequency Oscillation and Its Countermeasures

IEEE Canadian Journal of Electrical and Computer Engineering

引用

IEEE Canadian Journal of Electrical and computer engineering 2021年第2期44卷 110-117页

作者： Li, Wei Gole, Aniruddha M. Kaffashan, Iman Xiao, Xiangning The Department of Electrical and Computer Engineering University of Manitoba ManitobaMBR3T 5V6 Canada The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China

There exists serious frequency instability in the UHVDC islanded operation system consisting of a large capacity UHVDC and its corresponding power source with hydraulic power generators. Ultralowfrequency oscillation (ULFO) is one of the frequency instable problems, which will happen because of the inconsistent frequency control features between UHVDC and hydraulic power generators. Through the frequency-domain analysis, there exists a frequency band with negative damping in the hydraulic turbine control system, and UHVDC is negative damping for frequency deviation with constant power control mode. There are four negative damping contributing factors as hydrowater starting time constant, hydrogenerator governor forward gain, islanded system total inertia, and UHVDC power. These four factors are analyzed in this article in the frequency domain. Based on the detailed ULFO damping analysis, effective frequency control strategies for UHVDC islanded system are proposed in this article by withdrawing a part of primary frequency control functions of generators or coordinating the frequency controls between hydraulic generator governors and UHVDC frequency limitation controller (FLC). Through the proposed frequency strategies, islanded system frequency is mainly controlled by UHVDC FLC, which can successfully suppress the ULFO. Validation simulations are performed on the RTDS platform, and the simulation results prove the proposed strategies. © 2021 IEEE.

关键词： Frequency domain analysis

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Resonantly enhanced second-and third-harmonic generation in dielectric nonlinear metasurfaces

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Opto-Electronic Advances 2024年第5期7卷 5-19页

作者： Ji Tong Wang Pavel Tonkaev Kirill Koshelev Fangxing Lai Sergey Kruk Qinghai Song Yuri Kivshar Nicolae C.Panoiu Department of Electronic and Electrical Engineering University College LondonLondon WC1E 7JEUnited Kingdom Nonlinear Physics Center Research School of PhysicsAustralian National UniversityCanberra ACT 2601Australia Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of TechnologyShenzhen 518055China Wuzhen Laboratory EGO Wuzhen Digital Economy Industrial ParkNo.925 Daole RoadTongxiangChina

Nonlinear dielectric metasurfaces provide a promising approach to control and manipulate frequency conversion optical processes at the nanoscale,thus facilitating both advances in fundamental research and the development of new practical applications in photonics,lasing,and ***,we employ symmetry-broken metasurfaces made of centrosymmetric amorphous silicon for resonantly enhanced second-and third-order nonlinear optical *** the rich physics of optical quasi-bound states in the continuum and guided mode resonances,we comprehensively study through rigorous numerical calculations the relative contribution of surface and bulk effects to second-harmonic generation(SHG)and the bulk contribution to third-harmonic generation(THG) from the ***,we experimentally achieve optical resonances with high quality factors,which greatly boosts light-matter interaction,resulting in about 550 times SHG enhancement and nearly 5000-fold increase of THG.A good agreement between theoretical predictions and experimental measurements is *** gain deeper insights into the physics of the investigated nonlinear optical processes,we further numerically study the relation between nonlinear emission and the structural asymmetry of the metasurface and reveal that the generated harmonic signals arising from linear sharp resonances are highly dependent on the asymmetry of the *** work suggests a fruitful strategy to enhance the harmonic generation and effectively control different orders of harmonics in all-dielectric metasurfaces,enabling the development of efficient active photonic nanodevices.

关键词： second-harmonic generation third-harmonic generation bound state in the continuum guided mode resonance all-dielectric metasurfaces nonlinear optics

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Metafruit Meets Foundation Models: Leveraging a Comprehensive Multi-Fruit Dataset for Advancing Agricultural Foundation Models

SSRN

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SSRN 2024年

Fruit harvesting poses a significant labor and financial burden for the industry, highlighting the critical need for advancements in robotic harvesting solutions. Machine vision-based fruit detection has been recognized as a crucial component for robust identification of fruits to guide robotic manipulation. Despite considerable progress in leveraging deep learning and machine learning techniques for fruit detection, a common shortfall is the inability to swiftly extend the developed models across different orchards and/or various fruit species. Additionally, the limited availability of pertinent data further compounds these challenges. In this work, we introduce MetaFruit, the largest publicly available multi-class fruit dataset, comprising 4,248 images and 248,015 manually labeled instances across diverse U.S. orchards. Furthermore, this study proposes an innovative open-set fruit detection system leveraging advanced Vision Foundation Models (VFMs) for fruit detection that can adeptly identify a wide array of fruit types under varying orchard conditions. This system not only demonstrates remarkable adaptability in learning from minimal data through few-shot learning but also shows the ability to interpret human instructions for subtle detection tasks. The performance of the developed foundation model is comprehensively evaluated using several metrics, which outperforms the existing state-of-the-art algorithms in both our MetaFruit dataset and other open-sourced fruit datasets, thereby setting a new benchmark in the field of agricultural technology and robotic harvesting. The MetaFruit dataset and detection framework are open-sourced to foster future research in vision-based fruit harvesting, marking a significant stride toward addressing the urgent needs of the agricultural sector. © 2024, The Authors. All rights reserved.

关键词： Fruits

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoke Zhu Danyang Li Xiaopan Chen Fumin Qi Fan Zhang Xiao-Yuan Jing School of Computer and Information Engineering Henan University Kaifeng China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng China Department of System Operation National Supercomuting Center in Shenzhen Shenzhen China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China School of Computer Science Wuhan University Wuhan China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Facial image based kinship verification aims to decide whether there exists kinship between the given facial images. In practice, the cross-generation differences will cause adverse effects on kinship verification, which limits the performance. Therefore, how to mine the implied similarity from facial images with large cross-generation divergence is an important problem in kinship verification, which has not yet been well studied. In view of this, we propose a Similarity Mining via Implicit matching pattern LEarning (SMILE) approach for kinship verification. Specifically, SMILE mainly consists of two modules, including a Semi-coupled Multi-pattern Similarity Learning (SMSL) module and a Cross-Generation Feature Normalization (CGFN) module. The SMSL module is designed to learn multiple semi-coupled matching patterns for mining the implicit facial similarity information from different perspectives. The CGFN module aims to reduce the divergence between facial images of parent and child. Extensive experiments demonstrate that the proposed approach outperforms the existing state-of-the-art methods.

关键词： Pattern matching Similarity learning

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Intelligent Energy-Efficient and Fair Resource Scheduling for UAV-Assisted Space-Air-Ground Integrated Networks Under Jamming Attacks

Intelligent Energy-Efficient and Fair Resource Scheduling fo...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Shihao Chen Helin Yang Liang Xiao Changyuan Xu Xianzhong Xie Wanting Yang Zehui Xiong Department of Information & Communication Engineering Xiamen University Xiamen China Chongqing Key Laboratory of Computer Network and Communication Technology Chongqing University of Posts and Telecommunications Chongqing China Pillar of Information System Technology & Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

The space-air-ground integrated network (SAGIN) is a crucial technology for sixth-generation (6G) wireless communication networks to achieve seamless coverage and high throughput. In this paper, we propose an unmanned aerial vehicle (UAV)-assisted SAGIN structure, where the UAV is responsible for collecting data from ground users (GUs) and transmitting it to low-earth orbit (LEO) satellites. This paper also formulates a joint energy-efficient and fair resource scheduling optimization problem under jamming attacks and limited energy constraints, where the line-of-sight (LoS) links between the UAV and GUs are susceptible to being jammed. Due to the non-convex problem and dynamic environments, a deep reinforcement learning (DRL)-based twin delayed deep deterministic policy gradient (TD3) is developed to search optimal UAV trajectory to maximize energy efficiency (EE) and fairness against jamming. Simulation results verify that the proposed intelligent resource scheduling algorithm outperforms the baseline algorithms in terms of EE and fairness index in different settings.

关键词： Wireless communication Vehicular and wireless technologies Simulation Autonomous aerial vehicles Space-air-ground integrated networks Energy efficiency Trajectory

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Reinforcement Learning with Unbiased Policy Evaluation and Linear Function Approximation

Reinforcement Learning with Unbiased Policy Evaluation and L...

引用

IEEE Conference on Decision and Control

作者： Anna Winnicki R. Srikant Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois at Urbana-Champaign C3.ai Digital Transformation Institute

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We provide performance guarantees for a variant of simulation-based policy iteration for controlling Markov decision processes that involves the use of stochastic approximation algorithms along with state-of-the-art techniques that are useful for very large MDPs, including lookahead, function approximation, and gradient descent. Specifically, we analyze two algorithms; the first algorithm involves a least squares approach where a new set of weights associated with feature vectors is obtained via least squares minimization at each iteration and the second algorithm is a two-time-scale algorithm taking several steps of gradient descent towards the least squares solution before obtaining the next iterate using a stochastic approximation algorithm.

关键词： Upper bound Process control Reinforcement learning Markov processes Aerospace electronics Approximation algorithms Minimization

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NavG: Risk-Aware Navigation in Crowded Environments Based on Reinforcement Learning with Guidance Points

arXiv

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arXiv 2025年

作者： Zhang, Qianyi Luo, Wentao Liu, Boyi Zhang, Ziyang Wang, Yaoyuan Liu, Jingtai Institute of Robotics and Automatic Information System Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin China Advanced Computing and Storage Lab Huawei 2012 Lab China Department of Electronic and Computer Engineering The Kong Kong University of Science and Technology Hong Kong

Motion planning in navigation systems is highly susceptible to upstream perceptual errors, particularly in human detection and tracking. To mitigate this issue, the concept of guidance points—a novel directional cue within a reinforcement learning-based framework—is introduced. A structured method for identifying guidance points is developed, consisting of obstacle boundary extraction, potential guidance point detection, and redundancy elimination. To integrate guidance points into the navigation pipeline, a perception-to-planning mapping strategy is proposed, unifying guidance points with other perceptual inputs and enabling the RL agent to effectively leverage the complementary relationships among raw laser data, human detection and tracking, and guidance points. Qualitative and quantitative simulations demonstrate that the proposed approach achieves the highest success rate and near-optimal travel times, greatly improving both safety and efficiency. Furthermore, real-world experiments in dynamic corridors and lobbies validate the robot’s ability to confidently navigate around obstacles and robustly avoid pedestrians. © 2025, CC BY.

关键词： Travel time

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