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IEEE Conference on Decision and control

作者： Ruslan Seifullaev André M. H. Teixeira Anders Ahlén Department of Information Technology Division of Systems and Control Uppsala University Sweden Department of Electrical Engineering Division of Signals and Systems Uppsala University Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We address the problem of event-triggered networked control of nonlinear systems under simultaneous deception and Denial-of-Service (DoS) attacks. By DoS attacks, we refer to disruptions in the communication channel that prevent sensor measurements from reaching the controller. When the system undergoes a deception attack, the controller receives a modified output, deviating from the sensor’s original measurement. We implement the input delay approach and the Lyapunov-Krasovskii technique to obtain sufficient conditions, expressed in terms of linear matrix inequalities (LMIs), that characterize the duration of the DoS interruptions under which input-to-state stability (ISS) of the closed-loop system is preserved. Furthermore, we explore scenarios involving simultaneous attacks, where the DoS is modeled as a stochastic Bernoulli process. The closed-loop system is then considered as a stochastic impulsive system. In a similar manner, we derive conditions to ensure mean-square ISS for this case. A numerical example illustrates the efficiency of the results.

关键词： Event detection Stochastic processes Denial-of-service attack Stability analysis Linear matrix inequalities Delays Trajectory Closed loop systems Nonlinear systems Numerical stability

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KN-LIO: Geometric Kinematics and Neural Field Coupled LiDAR-Inertial Odometry

arXiv

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arXiv 2025年

作者： Wang, Zhong Ren, Lele Wen, Yue Wang, Hesheng The Department of Automation School of Electronics Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China The School of Information and Control Engineering China University of Mining and Technology Xuzhou221008 China

Recent advancements in LiDAR-Inertial Odometry (LIO) have boosted a large amount of applications. However, traditional LIO systems tend to focus more on localization rather than mapping, with maps consisting mostly of sparse geometric elements, which is not ideal for downstream tasks. Recent emerging neural field technology has great potential in dense mapping, but pure LiDAR mapping is difficult to work on high-dynamic vehicles. To mitigate this challenge, we present a new solution that tightly couples geometric kinematics with neural fields to enhance simultaneous state estimation and dense mapping capabilities. We propose both semi-coupled and tightly coupled Kinematic-Neural LIO (KN-LIO) systems that leverage online SDF decoding and iterated error-state Kalman filtering to fuse laser and inertial data. Our KN-LIO minimizes information loss and improves accuracy in state estimation, while also accommodating asynchronous multi-LiDAR inputs. Evaluations on diverse high-dynamic datasets demonstrate that our KN-LIO achieves performance on par with or superior to existing state-of-the-art solutions in pose estimation and offers improved dense mapping accuracy over pure LiDAR-based methods. The relevant code and datasets will be made available at https://**. Copyright © 2025, The Authors. All rights reserved.

关键词： Mapping

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Modeling the Correlation of Human Vertebral Body Volumes*

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IFAC-PapersOnLine 2023年第2期56卷 9030-9035页

作者： Bálint Szabó Ákos Szlávecz Sándor Bazsó Péter Somogyi Katalin Kovács Árpád Viola Balázs István Benyó Budapest University of Technology and Economics Faculty of Electrical Engineering and Information Technology Department of Control Engineering and Information Technology Budapest Hungary. Department of Informatics Széchenyi István University Győr Hungary Péterfy Sándor Street Hospital Department of Neurosurgery Budapest Hungary

Anatomical parameters of the human body strongly correlate with each other. Modelling these dependencies enables the creation of a realistic anatomical human body model that can be parameterized. Such a model can be used for several diagnostic processes to identify abnormalities or even give guidance in surgical interventions. This paper proposes a probabilistic model describing the dependencies between the vertebral body volumes of humans from the Caucasian human race. As demonstrated, the proposed model can accurately describe the relationship between the vertebral body volumes and is used for the prediction of an unknown vertebral volume based on a known one. The probabilistic model is created by using the CT segmentation of 37 patients.

关键词： Biomedical engineering Statistical Modelling Human Body Modelling Spinal Chord Segmentation Probabilistic Model

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Dynamic Event-Triggered Consensus on Matrix-Weighted Networks: Leadless Case 42

Dynamic Event-Triggered Consensus on Matrix-Weighted Network...

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42nd Chinese control Conference, CCC 2023

作者： Dou, Lintao Wei, Haoyu Huang, Jian Pan, Lulu Shao, Haibin Li, Dewei College of Intelligent Science National University of Defense Technology Changsha410003 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581543

This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks, where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the network. Specifically, a novel distributed dynamic event-triggered coordination strategy is proposed for this category of generalized networks, in which an auxiliary system is employed for each agent to dynamically adjust the triggering threshold, which plays an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Distributed event-triggered control protocols are proposed to guarantee leaderless consensus for multi-agent systems on matrix-weighted networks, respectively. Remarkably, the spectrum of matrix-valued weights is crucial in event-triggered mechanism design for matrix-weighted networks, generalizing those results only applicable for scalar-weighted networks. The proposed approach allows each agent to broadcast and receive information only at its triggering instants. Finally, simulation examples are provided to demonstrate the theoretical results. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Design and Implementation of Telemedicine System Using Light Fidelity and PIC16F877A Microcontroller 14

Design and Implementation of Telemedicine System Using Light...

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14th International Conference on information Science and technology, ICIST 2024

作者： Ezilarasan, M.R. Leung, Man-Fai Dai, Xiangguang Vel Tech Rangarajan Dr. Sagunthala R and D Instituteof Science and Technology Department of Electronics and Communication Engineering Chennai India School of Computing and Information Science Anglia Ruskin University Faculty of Science and Engineering Cambridge United Kingdom Information Processing and Control of Chongqing Municipal Institutions of Higher Education Chongqing Three Gorges University Key Laboratory of Intelligent Chongqing Wanzhou404100 China

ISBN: (纸本)9798350353334

Medical Body Area Networks (MBANs) increasingly utilize wireless communication technologies to enhance the freedom and convenience for patients and caregivers. Currently, radio frequency (RF) is the prevalent medium in healthcare applications;however, the potential for electromagnetic interference with precision medical equipment remains a concern. This study introduces a novel design and implementation of a medical healthcare information system using the newly developed Wireless Visible Light Communication (VLC) technology, also known as Light Fidelity (Li-Fi). Visible Light Emitting Diodes (LEDs), expected to soon surpass traditional incandescent and fluorescent bulbs as the primary light source due to their energy efficiency, facilitate this technology. In this research, patient health is monitored using sensors, with results displayed on an LCD. An LED lightbulb transmits the data as light signals, which are captured by a photo-detector at the receiver's end. This setup not only displays the output on an LCD but also alerts caregivers through an auditory signal, beeping every 15 seconds for respiration and every 30 seconds for heart rate monitoring. Moreover, these lighting fixtures serve dual functions: illumination and wireless data transmission, using the rapid switching capability of LEDs. This prototype VLC-based system offers a promising alternative for data services and monitoring in hospital areas where RF use is restricted. © 2024 IEEE.

关键词： Liquid crystal displays

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Solving PnP Problem Using Improved Sparrow Search Algorithm

Solving PnP Problem Using Improved Sparrow Search Algorithm

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IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Kurihara Riku Kousuke Matsushima Advanced Engineering Course National Institute of Technology Kurume College Kurume Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Kurume Japan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

The Perspective-n-Point (PnP) problem is a fundamental challenge in engineering that plays a crucial role in fields such as computer vision and augmented reality. This problem aims to estimate the position and orientation (pose) of a camera from known 3D points and their corresponding 2D projections on the image plane. With recent technological advancements, application areas such as autonomous vehicles, drones, and robotics are demanding increasingly faster and more accurate camera pose estimation. To address this challenge, we have introduced an improved Sparrow Search Algorithm (SSA) with the capability to dynamically restrict the search area. While the conventional SSA demonstrated excellent optimization capabilities, it faced efficiency issues when searching in high-dimensional spaces, such as those encountered in PnP problems. Our enhancement enables the algorithm to leverage information obtained during the search process to gradually narrow down the search area, thereby more efficiently locating the optimal solution.

关键词： Point cloud compression Accuracy Three-dimensional displays Heuristic algorithms Robot vision systems Pose estimation Signal processing algorithms Search problems Cameras Optimization

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Uncertainty-aware Monocular 3D Object Detection for Safe Driving Assistance

Uncertainty-aware Monocular 3D Object Detection for Safe Dri...

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IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Masahiko Ida Kousuke Matsushima Advanced Engineering Course National Institute of Technology Kurume College Fukuoka Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

Safety is of utmost importance when utilizing mobile vehicles. The introduction of safe driver assistance and automated driving systems will not only solve this problem, but also reduce road accidents and make driving smoother. To achieve these goals, 3D object detection is an essential technology and various methods have been proposed. Among these, monocular 3D object detection is an important technique and it is very difficult to identify the dimensions, direction and position of an object from a monocular image. Previous methods have predicted the dimensions directly from monocular images, resulting in poor accuracy of the dimensions in the depth direction. However, this paper proposes an indirect method for estimating the dimensions in the depth direction by predicting the volume of 3D bounding box. Detection accuracy for distant and partially visible objects is improved by using a loss function that uses uncertainty to account for the variability in predictions that occurs during learning. The proposed method has received an excellent evaluation on KITTI dataset.

关键词： Training Three-dimensional displays Accuracy Uncertainty Road accidents Object detection Signal processing Safety Object recognition Vehicles

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Detection of Termite Nests in Dams Using Ground Penetrating Radar Based on Deep Learning 20

Detection of Termite Nests in Dams Using Ground Penetrating ...

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20th International Conference on Ground Penetrating Radar, GPR, 2024

作者： Peng, Jiao Xue, Wei Wang, Wenkai Song, Junlei Zhou, Feng Huang, Pengchun Zhang, Zhixuan Zhang, Feng Zhang, Xu Chen, Longjia Sun, Li School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China Dam Safety Monitoring and Termite Control Center of Hubei Provincial Department of Water Resources China Key Laboratory of Termite Control Ministry of Water Resources China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

Termites have always been one of the major hidden dangers to the operational safety of dams. Traditional detection methods such as manual inspection and termite baiting have limitations in terms of efficiency and accuracy. To solve the problems, paper proposes a termite nest detection method based on ground penetrating radar (GPR) and deep learning. First, the simulated GPR data are generated using gprMax software, and the real data are collected using a GPR at several dams. Subsequently, the YOLOv8 deep neural network is employed for termite nest recognition in GPR images. The experimental results show that the proposed model can achieve the mean average precision (mAP) of 0.96 and a detection speed of 53.76 frames per second (FPS). © Published under licence by IOP Publishing Ltd.

关键词： Deep neural networks

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Multi-Lens Visual SLAM with Integrated Moving Object Removal using Unsupervised Models

Multi-Lens Visual SLAM with Integrated Moving Object Removal...

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Robotics, engineering, Science, and technology (RESTCON), International Conference on

作者： Ryoichirou Hara Kousuke Matsushima Advanced Engineering Course National Institute of Technology Kurume College Fukuoka Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

In Advanced Driver-Assistance Systems (ADAS), SLAM (Simultaneous Localization and Mapping) technology is required to accurately estimate the position and orientation of onboard cameras. Compared to LiDAR SLAM, Visual SLAM has the advantage of collecting rich environmental information at a lower cost. However, the accuracy of the estimated pose and map construction is greatly reduced by moving objects in the camera scene. To solve this problem, a multi-camera SLAM has been proposed, which works robustly in dynamic environments by using multiple cameras to acquire more feature points from omnidirectional environmental information. In this paper, we propose a robust SLAM system based on a multi-camera SLAM system combined with object detection and semantic segmentation networks. We then evaluate the robustness of the proposed method by comparing it to SLAM systems that do not remove moving objects. Experimental results showed that the Absolute Trajectory Error and the Relative Position Error performed better than conventional SLAM by masking moving objects. It also showed that more static objects were detected and constructed in the map.

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Reconfigurable and Multiband Graphene THz Antenna Design Optimized Using Machine Learning

Reconfigurable and Multiband Graphene THz Antenna Design Opt...

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2024 International Conference on Advanced Technologies for Communications, ATC 2024

作者： Patel, Shobhit K. Agravat, Dhruvik Nguyen, Tien Dung Nguyen, Thi Thanh Kieu Nguyen, Truong Khang Marwadi University Department of Computer Engineering Gujrat Rajkot360003 India Marwadi University Department of Physics Gujrat Rajkot360003 India Electric Power University Faculty of Control and Automation Ha Noi Viet Nam Binh Thuan College Faculty of Engineering Binh Thuan Viet Nam School of Technology Van Lang University Faculty of Information Technology Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350353983

This study investigates the concept of multiband graphene THz antennas. We investigate the advantages of graphene in THz antenna applications with standard materials. Using a graphene strip, we built a multiband GSSPlp-MIMO antenna in this study that achieves triple operating frequencies of 7.64 THz, 9.57 THz, and 10.90 THz. The reflection response (S11) of -29.2135 dB, which shows excellent signal confinement within the antenna, was greatly improved upon the inclusion of graphene. Superior impedance matching was the trade-off for this, even if the gain decreased slightly (10.41 dB) in comparison to the antenna without graphene (12.30 dB). The parameters are optimized using machine learning, yielding a maximum accuracy (R2) of 0.996622 and a mean square error of 5.3934 ×10-5. This indicates that high-performance terahertz antennas that balance gain and effective signal transmission can be designed using graphene. The antenna's capacity to handle multiple bands makes it ideal for future ultra-broadband wireless communication systems. This results in higher data transfer rates and supports emerging technologies such as 6G and beyond. © 2024 IEEE.

关键词： Data transfer rates

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