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2024 China Automation Congress, CAC 2024

作者： Yang, Chengqian Du, Ziyi Lin, Lixiong Xu, Guangtong Huang, Bomin School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China Department of Precision Instrument Tsinghua University Beijing China School of Ocean Information Engineering Jimei University Xiamen China Huzhou Institute Zhejiang University Huzhou China College of Computer Engineering Jimei University Xiamen China

ISBN: (纸本)9798350368604

This paper studies a class of perimeter defense problems for large-scale multi-robot systems. A perimeter defense strategy is designed via relative time calculations and maximum matching methods. The strategy is simple, effective, and easy to implement for large-scale perimeter defense problems. Some simulations are made to verify the effectiveness of the strategy. © 2024 IEEE.

关键词： Nanorobots

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Optimal denial-of-service attack scheduling for remote state estimation via sequential observations 43

Optimal denial-of-service attack scheduling for remote state...

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43rd Chinese control Conference, CCC 2024

作者： Yang, Xinxin Ni, Yuqing Chen, Xiaomeng Chen, Shan Liu, Fei Jiangnan University The Key Laboratory of Advanced Process Control for Light Industry Ministry of Education School of Internet of Things Engineering Wuxi214122 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong999077 Hong Kong

ISBN: (纸本)9789887581581

This study investigates the optimal allocation problem of attack energy in multi-system remote state estimation for Cyber-Physical Systems (CPSs). We consider a scenario where there are M independent systems, each equipped with a remote sensor monitoring system. The local estimates from these systems are sent to a remote estimator through a packet loss channel. The objective of the attacker is to degrade the communication channel between the sensors and the remote estimator. Due to capacity limitations, the attacker is restricted to attacking at most one out of M channels. We incorporate interference from other sensors or interference sources into the communication model based on the SINR (Signal-to-Interference-plus-Noise Ratio) model. It should be noted that the same attack power can lead to different packet loss rates in different network environments. From the attacker's perspective, the goal is to find the optimal attack strategy that maximizes the average estimation error of the remote estimator. Given the uncertainties of wireless network environments, we employ the sequentially-observed Markov decision process (SOMDP) framework to solve the problem. By observing the wireless channels, we gather additional information and incorporate it into the decision-making policy, resulting in better performance than using a standard Markov decision process (MDP). The simulation results support our theoretical findings. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Markov processes

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Mask R-CNN Based Real Time near Drowning Person Detection System in Swimming Pools

Mask R-CNN Based Real Time near Drowning Person Detection Sy...

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2022 Mohammad Ali Jinnah University International Conference on Computing, MAJICC 2022

作者： Hayat, Muhammad Aftab Yang, Goutian Iqbal, Atif School of Control & Computer Engineering North China Electric Power University Beijing China The University of Lahore Department of Electrical Engineering Lahore Pakistan

ISBN: (数字)9781665475198

ISBN: (纸本)9781665475198

To find the drowning person in time in swimming pool to reduce the drowning person mortality rate. We used the Mask R-CNN algorithm, and optimizing the convolution backbone of the traditional Mask R-CNN algorithm by adding features of cascaded with pyramid model to design a swimmer drowning detection system. Through real-time recognition of the posture of swimmers in the swimming pool, it can determine the drowning person and alert in time. The system's proposed algorithm has been put to the test on multiple real-world video sequences taken in swimming pools, and the findings show that it is very accurate and capable of monitoring people in real time. The experimental results show that the detection speed of the system is 6 FPS, while the detection rate is 94.1 %, while the false detection rate is 5.9%. The effect is good, which satisfying the anticipated requirements. © 2022 IEEE.

关键词： Swimming pools

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Gigahertz Optical Digital-to-Analog Multiplier

Gigahertz Optical Digital-to-Analog Multiplier

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2023 International Russian Automation Conference, RusAutoCon 2023

作者： Kamenskiy, Vladislav Sokolov, Sergey Kurinenko, Marianna Rostov State Transport University «automation and Remote Control in Railway Transport» Department Rostov-on-Don Russia Moscow Technical University of Communications and Informatics Department of Informatics and Computer Engineering Rostov-on-Don Russia

ISBN: (纸本)9798350345551

The article analyzes modern computing devices that perform multiplication operations. The main classes of multipliers built on the basis of both electronic and optical elements are considered. The main disadvantage of these devices, which negatively affects their performance, is the inability to carry out parallel calculations with them. In turn, this disadvantage is due to the fact that multiplication of the multi-bit binary number in general is carried out by calculating the partial products of the bits of the multipliers and their addition with the inevitable implementation of a corresponding, usually very large, number of transfers. The presence of a large number of transfers fundamentally does not allow solving the problem of increasing the speed of calculations. The developed optical binary digital-to-analog multiplier is devoid of this drawback. This optical digital-to-analog multiplier is implemented on the basis of optical splitters, optical couplers and optical banners with a well-developed technology for their manufacture today, which provides a minimum delay time of the optical signal (in the picosecond range). The functional diagram of the proposed optical digital-to-analog multiplier is shown and the principle of its operation is described. The possibility of increasing the speed of this optical digital-to-analog multiplier to the potential for optical information processing circuits is shown. © 2023 IEEE.

关键词： Optical data processing

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Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features 23rd

Estimating Chlorophyll Content from Hyperspectral Data Usin...

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23rd International Conference on Computational Science, ICCS 2023

作者： Ruszczak, Bogdan Wijata, Agata M. Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Opole Poland Faculty of Biomedical Engineering Silesian University of Technology Zabrze Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Gliwice Poland KP Labs Gliwice Poland

ISBN: (纸本)9783031360206

Non-invasive estimation of chlorophyll content in plants plays an important role in precision agriculture. This task may be tackled using hyperspectral imaging that acquires numerous narrow bands of the electromagnetic spectrum, which may reflect subtle features of the plant, and inherently offers spatial scalability. Such imagery is, however, high-dimensional, therefore it is challenging to transfer from the imaging device, store and investigate. We propose a machine learning pipeline for estimating chlorophyll content from hyperspectral data. It benefits from the Savitzky-Golay filtering to smooth the (potentially noisy) spectral curves, and from gradient-based features extracted from such a smoothed signal. The experiments revealed that our approach significantly outperforms the state of the art according to the widely-established estimation quality metrics obtained for four chlorophyll-related parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Efficient Deep Learning Modalities for Object Detection from Infrared Images

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computers, Materials & Continua 2022年第8期72卷 2545-2563页

作者： Naglaa F.Soliman E.A.Alabdulkreem Abeer D.Algarni Ghada M.El Banby Fathi E.Abd El-Samie Ahmed Sedik Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafr el-sheikhEgypt

For military warfare purposes,it is necessary to identify the type of a certain weapon through video stream tracking based on infrared(IR)video *** vision is a visual search trend that is used to identify objects in images or video *** military applications,drones take a main role in surveillance tasks,but they cannot be confident for longtime ***,there is a need for such a system,which provides a continuous surveillance task to support the drone *** a system can be called a Hybrid Surveillance System(HSS).This system is based on a distributed network of wireless sensors for continuous *** addition,it includes one or more drones to make short-time missions,if the sensors detect a suspicious *** paper presents a digital solution to identify certain types of concealed weapons in surveillance applications based on Convolutional Neural Networks(CNNs)and Convolutional Long Short-Term Memory(ConvLSTM).Based on initial results,the importance of video frame enhancement is obvious to improve the visibility of objects in video *** accuracy of the proposed methods reach 99%,which reflects the effectiveness of the presented *** addition,the experimental results prove that the proposed methods provide superior performance compared to traditional ones.

关键词： Deep learning object detection military applications OFDM SPIHT IoT

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Attention-based Vision Knowledge Adaptation for Constrained Continual Learning

Attention-based Vision Knowledge Adaptation for Constrained ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Bicheng Guo Conghao Zhou Haoyu Liu Shibo He Jiming Chen Xuemin Sherman Shen College of Control Science and Engineering Zhejiang University China Department of Electrical and Computer Engineering University of Waterloo Canada

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The demand for continual machine learning in the context of limited computational resources and data availability is critical in the evolving landscape of the connected digital world. Current network applications predominantly rely on deep learning models that require labor/computation-intensive training processes. These models often struggle to effectively adapt to new data while preserving performance on previously acquired knowledge. In this paper, we introduce a lightweight framework for continual knowledge adaptation and learning designed to address these challenges. To prevent disruption of existing services, we propose an attention-based adapter that integrates seamlessly with the existing vision model to encode new incoming data. The weights of the original model are kept fixed during the adaptation process, ensuring the preservation of previously learned knowledge. Furthermore, to enhance learning efficiency and accelerate convergence with new data, we implement a knowledge fusion mechanism that facilitates interaction between existing knowledge and information from new data. Our framework is modular, enabling flexible deployment across distributed devices. The adapter and knowledge fusion module are implemented at each stage with minimal trainable parameters, optimizing resource usage. Extensive experiments and ablation studies validate the effectiveness of the proposed framework.

关键词： Continuing education Training Deep learning Adaptation models Multi-access edge computing Computational modeling Data models Global communication Convergence

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Convergent Approaches to AI Explainability for HEP Muonic Particles Pattern Recognition

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Computing and Software for Big Science 2023年第1期7卷 1-18页

作者： Maglianella, Leandro Nicoletti, Lorenzo Giagu, Stefano Napoli, Christian Scardapane, Simone Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Rome Italy Department of Physics Sapienza University of Rome Rome Italy Institute for Systems Analysis and Computer Science Italian National Research Council Rome Italy Department of Computational Intelligence Electronics and Telecommunications Czestochowa University of Technology Czestochowa Poland Department of Information Engineering Electronics and Telecommunications Sapienza University of Rome Rome Italy

Neural networks are commonly defined as ‘black-box’ models, meaning that the mechanism describing how they give predictions and perform decisions is not immediately clear or even understandable by humans. Therefore, Explainable Artificial Intelligence (xAI) aims at overcoming such limitation by providing explanations to Machine Learning (ML) algorithms and, consequently, making their outcomes reliable for users. However, different xAI methods may provide different explanations, both from a quantitative and a qualitative point of view, and the heterogeneity of approaches makes it difficult for a domain expert to select and interpret their result. In this work, we consider this issue in the context of a high-energy physics (HEP) use-case concerning muonic motion. In particular, we explored an array of xAI methods based on different approaches, and we tested their capabilities in our use-case. As a result, we obtained an array of potentially easy-to-understand and human-readable explanations of models’ predictions, and for each of them we describe strengths and drawbacks in this particular scenario, providing an interesting atlas on the convergent application of multiple xAI algorithms in a realistic context. © 2023, The Author(s).

关键词： Explainable Artificial Intelligence High-energy physics Intrinsically interpretable Decision Trees Saliency maps methods Tracing gradient descent

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Data-Driven Model for Human Tracking and Prediction Using Kalman Filter with Particle Swarm Optimization 3rd

Data-Driven Model for Human Tracking and Prediction Using Ka...

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3rd International Conference on control, Instrumentation and Mechatronics engineering, CIM 2022

作者： Ajasa, Abiodun Afis Nawawi, Sophan Wahyudi Department of Control and Mechatronics Engineering School of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia Department of Electronics and Computer Engineering Faculty of Engineering Lagos State University Epe Campus Lagos Nigeria

ISBN: (纸本)9789811939228

Intelligent monitoring systems have evolved due to technological improvement and innovation in biometric identification technology and protecting lives and property. As a result, intelligent monitoring systems are becoming increasingly prevalent. Consequently, this paper proposes the development of an IoT-based Human Tracking system that incorporates the Kalman Filter (KF) Algorithm. Apart from the deployment of the Kalman Filter, analysis was also done with an optimized Kalman filter with PSO (KF-PSO) using Particle Swarm Optimization. Rather than manually tuning the process noise error, R, and measurement error, Q, which are involved in KF, PSO was also used to adjust the errors to obtain their best values for optimal estimation. As a result, a two-dimensional (2D) Kalman filter is developed. The positions and velocities of the object being tracked (i.e., humans) are estimated in x- and y-directions. The proposed system has been evaluated using ten different human datasets, each consisting of 100 samples. The quality performance of KF and KF-PSO models was also compared using accuracy analysis. In comparison, the KF-PSO model yielded an average Mean-Square error of 17 mm (i.e., 1.7% error), while the conventional KF model gave an average Mean-Square error of 22 mm (i.e., 2.2% error). Hence, the KF-PSO model is a better filter than the conventional KF model because of its higher accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Kalman filters

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Internet of things-based automation design and organizational innovation of manufacturing enterprises

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Materials Today: Proceedings 2022年 56卷 1769-1775页

作者： Babu, T. Roopa, H. Shukla, Arvind Kumar Stalin David, D. Jayadatta, S. Rajesh, A.S. Department of Instrumentation and Control Engineering St. Joseph's College of Engineering Chennai India Department of Information Science and Engineering Bangalore Institute of Technology Bangalore India Department of Computer Application IFTM University Moradabad India Department of CSE IFET College of Engineering Villupuram India Department of Management Studies KLE's IMSR BVB Campus Hubli India Department of Mechanical Engineering JSS S&T University Mysore India

The Internet of Things (IoT) foresaw a transparent network between the real and virtual worlds. IoT offers a promising potential to develop strong market and industrial applications. The export-oriented economy of industrial manufacturers relies on product and service creativity to retain a competitive advantage. The IoT-based applications of innovative manufacturing companies (IOTs), where most companies are involved and engaged in many of the case IoT-based applications, is motivated by computing capacity, networking, cost reduction and electronic components. A common motive is the Internet of Things applications and the improvement of after-sales service activities. The suggested Linear Product Design Regression (LPDR) algorithm classifies business product innovation design based on consumer input to support business development. Businesses, companies and the technology industry: the inhibitors hinder the development of the four IT applications. IoT offers one of the latest innovations in manufacturing to allow us to meet key challenges. The product design and development engineering are engaged in utilizing the Internet of Things (IoT) to create comprehensive policies and policy creation for manufacturing *** support business development. Businesses, companies and the technology industry: the inhibitors hinder the development of the four IT applications. To allow us to meet key challenges and to create comprehensive policies and policy creation for manufacturing companies. © 2021

关键词： Product design

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