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Exploring Deep Learning Methods for Computer Vision Applications across Multiple Sectors:Challenges and Future Trends

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh Rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India Department of Control Systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Mechanical Engineering and University Centre for Research&Development Chandigarh UniversityMohali140413India Department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

Computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

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Qualitative Criterion and Simulation Analysis of Ventilation Efficiency of New High Protection Louver 8th

Qualitative Criterion and Simulation Analysis of Ventilation...

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8th Asia International Symposium on Mechatronics, AISM 2021

作者： Sang, Xian-chen Shao, Wei Chen, Min Yang, Long-fei Jin, Quan NARI Group Corporation/State Grid Electric Power Research Institute Nanjing211106 China NARI-TECH Nanjing Control Systems Ltd. Nanjing211106 China NARI Technology Development Co. Ltd. Nanjing211106 China

ISBN: (纸本)9789811913082

The cabinet of electric power, communication and other industries is required to reach IPx4 protection level, and the high protection louver structure, which has the new special-shaped air ducts, can meet this requirement. In order to analyze the ventilation efficiency of the new louver structure, the simulation analysis experimental models of various louver structures are constructed. According to the common Bernoulli principle, the Bernoulli equation of the simulation model is deduced. And then the parameters are selected for ventilation efficiency analysis. The comparative analysis of ventilation efficiency was carried out, and the qualitative criterion of ventilation efficiency was put forward. The ventilation efficiency of different louver structures is analyzed, using the finite element analysis software. Through the comparative analysis of three different louvers, the effectiveness of the qualitative criterion of ventilation efficiency is verified, and the new high protection louver has excellent comprehensive performance of protection and ventilation. © 2022, Science Press.

关键词： Efficiency

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Polytope Volume Monitoring Problem: Formulation and Solution via Parametric Linear Program Based control Barrier Function

arXiv

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arXiv 2025年

作者： Wu, Shizhen Dong, Jinyang Fang, Xu Sun, Ning Fang, Yongchun Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300353 China The Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China

Motivated by the latest research on feasible space monitoring of multiple control barrier functions (CBFs) as well as polytopic collision avoidance, this paper studies the Polytope Volume Monitoring (PVM) problem, whose goal is to design a control law for inputs of nonlinear systems to prevent the volume of some state-dependent polytope from decreasing to zero. Recent studies have explored the idea of applying Chebyshev ball method in optimization theory to solve the case study of PVM;however, the underlying difficulties caused by nonsmoothness have not been addressed. This paper continues the study on this topic, where our main contribution is to establish the relationship between nonsmooth CBF and parametric optimization theory through directional derivatives for the first time, so as to solve PVM problems more conveniently. In detail, inspired by Chebyshev ball approach, a parametric linear program (PLP) based nonsmooth barrier function candidate is established for PVM, and then, sufficient conditions for it to be a nonsmooth CBF are proposed, based on which a quadratic program (QP) based safety filter with guaranteed feasibility is proposed to address PVM problems. Finally, a numerical simulation example is given to show the efficiency of the proposed safety filter. © 2025, CC BY.

关键词： Chebyshev filters

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Time Synchronization in Industrial Internet of Things: A Survey

Time Synchronization in Industrial Internet of Things: A Sur...

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IEEE Information Technology, Networking, Electronic and Automation control Conference

作者： Ke Zhou Xiaoming Wang Shijie Cui Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Nanning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning China

ISBN: (数字)9798350370805

ISBN: (纸本)9798350370812

Time synchronization is a fundamental strategy for many operations such as data synchronous collection, timely fault tracking, distributed control, and real-time communication in Industrial Internet of Things (IIoT). Over the years, a wide variety of protocols and technologies have been proposed for different application scenarios. The accuracy, security, robustness, low cost, and so on, are the main focus for the design of time synchronization protocol. However, so far, there is no relatively unified standard for time synchronization in IIoT. To clarify the development of time synchronization technology, this paper surveys the latest research for time synchronization in various types of networks including Precision Time Protocol and wireless sensor networks. The future development of time synchronization in IIoT is also investigated.

关键词： Surveys Wireless sensor networks Protocols Accuracy Reviews Robustness Synchronization Security Standards Industrial Internet of Things

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Cloud Edge Collaborative Interaction Technology Based On Compzxutility Boards

Cloud Edge Collaborative Interaction Technology Based On Com...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Yehua Xie Chuanyu Zhang Bo Chang Jianxin Zhou Hongkun Liu Xiaojin Wang NARI Group Corporation/ State Grid Electric Power Research Institute Jiangsu China NARI Technology Development Co. Ltd Jiangsu China NARI-TECH Nanjing Control Systems Ltd Jiangsu China

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

The cloud-edge collaborative interaction technology, leveraging computing power boards, comprises cloud application management services, edge application management clients, and computing power boards. This technology and system serve as a bridge for application and data interaction between cloud and edge systems. The application management service is hosted in the cloud, while the application management client resides on the edge, and the computing power board is integrated into the physical server on the edge. The application management service encompasses modules like application management and edge management. The computing power board facilitates the subscription and deployment of lightweight AI large model applications at the edge. This technology enables the publication, subscription, downloading, and deployment of applications, standardizes application management, facilitates seamless upgrades, enables remote operation and maintenance, and enriches the application ecosystem.

关键词： Biological system modeling Ecosystems Collaboration Software Maintenance Servers Artificial intelligence Information technology Standards Sorting

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Robust control of Interleaved Boost Converter for Open-Cathode PEM Fuel Cell systems

Robust Control of Interleaved Boost Converter for Open-Catho...

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IEEE International Conference on Automatic control and Intelligent systems (I2CACIS)

作者： Jie Ying Tan R.M.T Raja Ismail Institute of Postgraduate Studies Universiti Malaysia Pahang Pekan Pahang Malaysia Robotics Intelligent Systems & Control Engineering (RISC) Research Group Faculty of Electrical & Electronics Universiti Malaysia Pahang Pekan Pahang Malaysia

This paper implements a thermal control and a super-twisting sliding mode (STSM) incorporated with an interleaved boost converter (IBC) for an open-cathode proton exchange membrane fuel cell (OC-PEMFC). The implementation of the thermal control is to regulate the stack temperature and adjust the air stoichiometric during the fuel cell current variation. The STSM controller is designed to ensure the fuel cell system’s robustness by achieving the reference values set. Therefore, simulation results discussed that the thermal control provides the suitable stack temperature to the system and maintains the fan voltage during temperature variations. A PI controller is designed and used as a comparison to the proposed STSM controller. Hence, the proposed STSM demonstrates its effectiveness in tracking down the reference current values for the fuel cell system.

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IoT-based Ambient Parameters Monitoring Device for in-Home Elderly Care 23

IoT-based Ambient Parameters Monitoring Device for in-Home E...

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23rd International Conference on control systems and Computer Science Technologies, CSCS 2021

作者： Elena-Anca, Paraschiv Ovidiu, Bica Cristian, Petrache Ianculescu, Marilena National Institute for Research and Development in Informatics Systems and Applications for Society Department Bucharest Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781665439398

During the last decades, more and more demographic, social and economic changes have influenced the percentage of the ageing population, leading thus to an increasing number of elderly people, correlated with a direct and dramatic influence on the healthcare and social services. Furthermore, the grown longevity of the elderly, the shortage of an appropriate number of caretakers and the raising empowerment of the seniors regarding the self-management of their health status, have led to the stringent necessity of implementing smart environments inside their homes in order to benefit of a prolonged independent, active, healthy and secure life. The Internet of Things (IoT) technology has gained a lot of attention due to its strong potential for supporting these smart environments through devices that can remotely monitor elderly's health and daily activities, without the need to be constantly assisted by a medical specialist. For a comprehensive elderly-targeted remote monitoring able to sustain proactive and preventive measures, the ambient factors should be closely measured and correlated with the physiological and physical vital parameters. RO-SmartAgeing is an undergoing project which aims to create such a smart environment in the home of an elderly person for providing accurate and less-intrusive health and lifestyle monitoring and support services. This paper highlights a component of RO-SmartAgeing project, namely a system that guarantees the collection of ambient-related parameters in order to keep under control the home environment of the patient. Apart from the suggested literature review, as to demonstrate the feasibility of the proposed system, both a proof of concept is used in order to describe the idea and the functionality of the product, and also the conclusions drawn after some preliminary tests have been performed. © 2021 IEEE.

关键词： Internet of things

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Model-Free Predictive control for Harmonic Suppression of PMSMs Based on Adaptive Resonant controller

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IEEE Transactions on Energy Conversion 2025年

作者： Li, Teng Sun, Xiaodong Su, Zonghao Zha, Xuhao Dianov, Anton Prakht, Vladimir Demidova, Galina Ma, Jinlin Jiangsu University Automotive Engineering Research Institute Zhenjiang212013 China Wenzhou University Pingyang Institute of Intelligent Manufacturing Wenzhou325035 China Ural Federal University Department of Electrical Engineering Ekaterinburg620062 Russia ITMO University Faculty of Control Systems and Robotics Petersburg197101 Russia Jiangsu University School of Automotive and Traffic Engineering Zhenjiang212013 China

To simultaneously suppress the periodic and aperiodic disturbances experienced by permanent magnet synchronous motors in model predictive control, a model-free predictive current control with adaptive resonance control based on an ultra-local model is proposed. Firstly, the ultra-local models of the speed loop and the current loop are established respectively, and the unmodeled and uncertain unknown part F in the ultra-local model is estimated by using a high-order fast terminal sliding mode observer, and its stability is analyzed. Then, an adaptive resonant controller (ARC) is designed to suppress the periodic disturbance caused by the dead zone effect. The ARC and the model-free control based on the ultra-local model are combined to compensate for their respective shortcomings, achieving the suppression of periodic and aperiodic disturbances in the system. Finally, by comparing with the traditional duty cycle model predictive control and the model-free model predictive control without ARC, the proposed scheme is proved to be robust to periodic and aperiodic disturbances. © 2025 IEEE. All rights reserved.

关键词： Permanent magnets

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Artificial intelligence (AI) use for personal protective equipment training, remediation, and education in health care

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American Journal of Infection control 2025年第6期53卷 678-684页

作者： Preda, Veronica Ong, Zehurn Wijeweera, Chandana Carney, Terence Clay-Williams, Robyn Kankanamge, Denuka Preda, Tamara Kopsidas, Ioannis Wilson, Michael Keith Faculty of Medicine Health and Human Sciences Macquarie University Sydney NSW Australia Emergency Medicine and Rural Practice Bairnsdale Regional Hospital Bairnsdale VIC Australia Surgical XR Innovation and Development Department Sydney NSW Australia Australian Institute of Health Innovation Health Resilence & Systems Research Sydney NSW Australia Department of Surgery University of Notre Dame St Vincent's Clinical School Sydney NSW Australia Centre for Clinical Epidemiology and Infection Control University of Athens Athens Greece

Background: Personal protective equipment (PPE) is a first-line transmission-based precaution for reducing the spread of nosocomial infections between health care workers (HCWs), patients, and staff. The COVID-19 pandemic highlighted a problematic skill gap in effective PPE donning/doffing. Methods: We performed a single-center, mixed-methods, prospective cohort study of 293 HCWs in Sydney, Australia. Participants were assessed using SXR AI-PPE, an artificial intelligence (AI) system that autonomously evaluates donning/doffing of PPE while providing real-time feedback on user technique. Results: Longitudinal results showed improved accuracy rates for correct donning/doffing after each guided session conducted at 3-monthly intervals, with a 100% accuracy rate for correct use of PPE after 2 guided sessions. These improvements were maintained with 3-monthly training sessions. Conclusions: The SXR AI-PPE platform is a comprehensive tool capable of training PPE donning/doffing by HCWs in real time with implications for reducing PPE contamination and risk of nosocomial infections. © 2025 Association for Professionals in Infection control and Epidemiology, Inc.

关键词： Infection prevention Nosocomial infections Personal protective equipment

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Nonlinear Model Predictive control Approximation: Applications to Truck-Trailer control System

Nonlinear Model Predictive Control Approximation: Applicatio...

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International Conference on control, Automation and systems ( ICCAS)

作者： Suyong Park Duc Giap Nguyen Yongsik Jin Jinrak Park Dohee Kim Jeong Soo Eo Kyoungseok Han Department of Automotive Engineering Hanyang University Seoul Republic of Korea Department of Mechanical Engineering Kyungpook National University Daegu Republic of Korea Robotics IT Convergence Research Section Electronics and Telecommunications Research Institute (ETRI) Daegu Republic of Korea Department of Electrified Systems Control Research Lab Hyundai Motor Company Hwaseong Republic of Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

In this work, we demonstrate the effectiveness of nonlinear model predictive control (NMPC) approximation based on deep neural network (DNN). MPC has been widely adopted in autonomous driving control problems to handle multiple objectives and constraints. We first design the implicit NMPC for the forward and backward motions of a truck-trailer (TT) system, which follows the reference path while maintaining safety between the head truck (HT) and the trailer (TR). However, the computational load in implicit MPC makes it a challenge for real-time implementations. To alleviate the computational burden in implicit NMPC online, an NMPC approximation approach based on DNN is adopted in this study to achieve a parametric function approximation. We conduct a comparative study on the proposed approach and a baseline controller for control performance analysis, and the computational load is evaluated on a hardware-in-the-loop (HIL) experimental system.

关键词： Training Tracking Simulation Training data Artificial neural networks Predictive models control systems Real-time systems Safety Predictive control

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