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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Feihang Qiu Jing Guo Huineng Diao Xu Zhang School of Mechatronic Engineering and Automation Foshan University Foshan China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

Unmanned Aerial Vehicle enabled (UAV-enabled) wireless powered Wireless Sensor Networks (WSN) provide an effective way to deploy massive and passive sensors for environmental monitoring in harsh environments. This study focuses on maximizing the total energy received by all Sensor Nodes (SNs) through the optimization of the UAV trajectory. An energy-aware smoothing trajectory method is proposed by considering the dynamic energy requirements of SNs. First, the optimization problem (P1) is formulated according to the mathematical model. Second, the B-spline method is introduced to turn the smoothing problem into a solvable problem (P2). Finally, problem (P2) is solved under the constraints to obtain the trajectory solution. Simulation results indicate the proposed method can adjust the overall trajectory according to the SNs demands. Meanwhile, according to the wake-up distance and energy-aware, the trajectory of some nodes can be locally adjusted without affecting other trajectory segments.

关键词： Wireless communication Wireless sensor networks Smoothing methods Simulation Autonomous aerial vehicles Mathematical models Trajectory

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Anomaly Detection for Stochastic Networked Cyber-Physical systems: A Statistical Approach

Anomaly Detection for Stochastic Networked Cyber-Physical Sy...

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International Conference on control and Automation (ICCA)

作者： Yamin Yan Minyue Fu Maria M. Seron School of Electrical and Electronic Engineering Nanyang Technological University Singapore Shenzhen Key Laboratory of Control Theory and Intelligent Systems and Centre for Control Science and Technology School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Engineering The University of Newcastle Callaghan NSW Australia

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In this paper, we investigate the anomaly detection problem within stochastic networked cyber-physical systems. We introduce an anomaly detection scheme centered on estimator design employing a statistical approach. Specifically, we extend the statistical method recently developed for single systems to networked control scenarios. Additionally, we analyse the detection of several representative anomalies through this statistical approach. We then apply our anomaly detection strategy to a power network system exposed to such anomalies. Our findings demonstrate that the proposed design effectively detects these anomalies, which simpler methods relying solely on residual assessment with a threshold fail to identify.

关键词： Analytical models Automation Statistical analysis Stochastic processes Cyber-physical systems control systems Anomaly detection

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An Improved RT-DETR-Based Object Detection Algorithm for Gm-APD LiDAR

An Improved RT-DETR-Based Object Detection Algorithm for Gm-...

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Academic International Symposium on Optoelectronics and Microelectronics technology (AISOMT)

作者： Qianxin Wang Jianfeng Sun Peng Jiang Xin Zhou Yuanxue Ding Guanlin Chen National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin Heilongjiang China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou Henan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798331542283

ISBN: (纸本)9798331542290

Gm-APD LiDAR has a high sensitivity response characteristic, enabling imaging for detecting targets at extended distances, and finds broad utility. However, the highly sensitive response characteristic also makes Gm-APD LiDAR vulnerable to noise, resulting in poor imaging quality and challenging the application of target detection algorithms to this type of LiDAR. Therefore, this paper proposes a long-range vehicle detection model DRT-DETR for Gm-APD LiDAR. DRT-DETR is based on RT-DETR and employs a dual-channel feature extraction backbone, which combines with the lightweight FasterNet Block to capture semantic features from distance and intensity images effectively. It also incorporates mixed attention modules to selectively combine and enhance key features from both types of images. Attention-based Intrascale Feature Interaction employs cascaded group attention as a replacement for multi-head attention in order to minimize computational redundancy. Finally, Dysample is used instead of nearest neighbor upsampling in the cross-scale feature fusion to align features better and minimize distortion. The improved model boosts detection accuracy by 3.8% over RT-DETR and outperforms other common object detection models on the dataset, demonstrating its effectiveness.

关键词： Laser radar Sensitivity Computational modeling Vehicle detection Semantics Redundancy Imaging Object detection Feature extraction Distortion

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3D bioprinting of a dermal scaffold for full-thickness skin tissue regeneration

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Bio-Design and Manufacturing 2025年第1期8卷 68-84,I0039-I0041页

作者： Lu Han Zixian Liu Meng Li Zhizhong Shen Jianming Wang Shengbo Sang Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China General Hospital of TISCO Taiyuan 030809China

Dermal substitutes have provided a template for the regeneration and reconstruction of the ***,the healed skin tissue often exhibits abnormal morphology and functionality,including scarring and *** this study,a composite bioink composed of methacrylated gelatin(GelMA)and chitosan oligosaccharide(COS)was proposed for printing a dermal scaffold using digital light processing(DLP)*** GelMA/COS bioink exhibited suitable porosity,swelling,degradation rate,and mechanical *** inclusion of COS demonstrated antibacterial effects against both Gram positive and Gram-negative bacteria,while simultaneously fostering the proliferation of human dermal fibroblasts(HDFs).Additionally,the application of COS could effectively reduce the expression levels of fibrosis-related genes,such as collagen I,collagen III,and fibronectin *** three-dimensionally printed cell-laden dermal scaffold exhibited excellent shape fidelity and high cellular viability,facilitating the extension of HDFs along the scaffold and the simultaneous secretion of extracellular matrix ***,the HDF-laden dermal scaffold transplanted into full-thickness skin defect sites in nude mice was shown to accelerate wound closure,reduce inflammation,and improve wound ***,the DLP-printed dermal scaffold provides an appealing approach for effectively treating full-thickness skin defects in clinical settings.

关键词： 3D printing Dermal scaffold Photo-cross-linking Skin tissue regeneration

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An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers

An Optimal Control Based Trajectory Planning Method for Coop...

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intelligent Robotics and systems (ISoIRS), International Symposium on

作者： Qi Wang Hao Ge Xuting Duan Jianshan Zhou State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology School of Transportation Science and Engineering Beihang University Beijing China State Key Laboratory of Air Traffic Management System and Technology Nanjing Research Institute of Electronic Engineering Nanjing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating system (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution.

关键词：

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Application and Performance Evaluation of Object Detection technology Based on Computer Vision

Application and Performance Evaluation of Object Detection T...

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Asian control Conference

作者： WeiXue Li Hang Zhang Cong Wan JiaWen Shi TingRu Li National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Talent Exchange Center Ministry of Industry and Information Technology P.R.C. Beijing China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In light of the challenges posed by the variability of industrial part shapes, weak texture information, and surface reflections in current industrial vision inspection, traditional methods such as feature descriptors and template matching are inadequate. This paper innovatively proposes a machine learning object detection method, establishes robust stable features for weakly textured industrial parts, and evaluates the performance of the model and feature selection in combination with actual fuel tank cap detection tasks. Firstly, we construct a dataset of fuel tank cap targets and establish a comprehensive and relatively stable feature dataset, including geometric features, texture features, and color features. Secondly, through ablation experiments and comparative experiments, we conduct intelligent per-formance testing on model detection accuracy, parameter selection, and feature contribution. Finally, the evaluation results demon-strate that the support vector machine (SVM) model exhibits the best detection performance after feature selection, with a detection accuracy of 99.0% under the optimal parameter settings validated through experiments.

关键词： Support vector machines Adaptation models Image color analysis Computational modeling Fuel storage Object detection Inspection

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Statistical Feasibility Robust Optimization for Hydrogen-Data Center Microgrid Operation

SSRN

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SSRN 2024年

作者： Duan, Juntao Li, Yuanzheng Li, Yang Liu, Zhiwei Zhao, Yong School of Artificial Intelligence and Automation Key Laboratory on Image Information Processing and Intelligent Control of Ministry of Education Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

The increasing processing demands of information technology (IT) workloads cause the booming of data centers (DCs) in recent years. The servers in the DC emit much heat when processing the IT workloads and thus the DC temperature rises. The power consumption when controlling the DC temperature using the air conditioning (A/C) of the DC is high, which leads to expensive power bills. To reduce the power cost, using renewable energy (RE) to power DC has raised much attention in recent years. However, the intermittency of RE and the uncertainties of outside temperature pose operational challenges. Therefore, in this paper, a data-driven statistical-feasibility-based robust rolling optimization framework for the operation of hydrogen-DC microgrid (H2-DCMG) is proposed to control the DC temperature considering these uncertainties and the intermittency of RE. In the framework, the hydrogen energy storage system (HESS) is introduced to deal with the intermittency of RE, and robust optimization (RO) is adopted to deal with the uncertainty of outside temperature. The statistical feasibility is introduced into the framework to decrease the conservatism of RO, through relaxing the DC temperature constraints without harming normal DC operations. Moreover, we propose the Statistical-Guarantee-based Vertex Link (SGVL) algorithm to construct a polyhedron uncertain set of outside temperatures that can ensure the results of dispatch are economical and satisfy statistical feasibility. The constructed polyhedron uncertain set is linear, which reduces computational complexity in solving. A case study based on the real-world temperature dataset verifies the superiority of the SGVL algorithm on the aspect of the economic cost. It further validates the effectiveness of the proposed robust optimization framework for DC temperature control. © 2024, The Authors. All rights reserved.

关键词： Air conditioning

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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Chinese Journal of Electronics 2023年第3期19卷 451-456页

作者： Bo Li Wenju Liu Lihua Dou School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词： Training Image segmentation Analytical models Parameter estimation Estimation Probability density function Speech processing

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Statistical Feasibility Robust Optimization for Hydrogen-Data Center Microgrid Operation

SSRN

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SSRN 2024年

关键词： Air conditioning

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Review of Research Advances in CFD Techniques for the Simulation of Urban Wind Environments

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Fluid Dynamics & Materials Processing 2022年第2期18卷 449-462页

作者： Pengfei Ju Mingrui Li Jingying Wang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education(Tianjin University of Technology) Tianjin300384China School of Energy and Power Engineering Shandong UniversityJinan250061China Shandong Engineering Laboratory for High-Efficiency Energy Conservation and Energy Storage Technology&Equipment Shandong UniversityJinan250061China

Computational fluid dynamics(CFD)has become the main method for the prediction of the properties of the external wind environment in cities and other urban contexts.A review is presented of the existing literature in terms of boundary conditions,building models,computational domains,computational grids,and turbulence *** specific issues,such as the accuracy/computational cost ratio and the exploitation of existing empirical correlations,are also examined.

关键词： Computational fluid dynamics wind environment pre-processing settings

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