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Machine Learning and Intelligent Systems Engineering (MLISE), International Conference on

作者： Feiyong He Yue Liu Jinfeng Liu Faculty of Applied Sciences Macao Polytechnic University Macao China College of Robotics Guangdong Polytechnic of Science and Technology Zhuhai China

ISBN: (数字)9798350375077

ISBN: (纸本)9798350375084

Crop disease identification is crucial for its role of maintaining crop yield and quality in precision agriculture. Traditional disease detection methods are often inefficient and error-prone. To address this issue, we propose the ECA-ViT model, which combines Efficient Channel Attention (ECA) and Vision Transformers (ViT) to identify crop leaf diseases in cultivation environments. The ECA-ViT model uses adaptive 1D convolution kernels for rapid cross-channel interaction of local disease features in crop images, compensating for the Vision Transformer's lack of global context understanding and optimizing the model. This balanced approach enhances feature learning while maintaining computational efficiency without increasing model complexity. We evaluated the ECA-ViT model using rice leaf disease datasets from real field settings. The results demonstrated that ECA-ViT outperformed existing deep lear-ning methods, achieving an accuracy of 95.41%.

关键词： Productivity Precision agriculture Adaptation models Computer vision Accuracy Computational modeling Crops

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Disturbance Observer-Based Robust Control for Redundant Manipulators Towards Conditional Monitoring

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Procedia Computer science 2024年 250卷 157-163页

作者： Tie-Nan Ma Rui-Dong Xi Wei-Xiang Liang Zhi-Xin Yang Department of Electromechanical Engineering Faculty of Science and Technology University of Macau Taipa Macau SAR 999078 China Shenzhen Key Laboratory of Robotics Perception and Intelligence the Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen 518055 China

Conditional monitoring is crucial for preserving the functionality and longevity of electro-mechanical equipment. The adoption of robots is an effective method for improving the traditional approaches that rely on fixed monitoring sites. Therefore, this work investigates the motion control of a redundant robot manipulator in operational space for the application of conditional monitoring. A simple and efficient kinematic tracking differentiator (KTD) is proposed to convert operational space trajectories into joint space tracking. Redundancy is handled using a null space vector with time delay method. Additionally, a fixed-time terminal sliding mode controller (FxTSMC) is designed with a disturbance observer to improve fast convergence and disturbance rejection ability. Simulation results have been demonstrated to show the effectiveness of the proposed control scheme.

关键词： Redundant robot manipulator Kinematic tracking differentiator Fixed-time terminal sliding mode control

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Decoupling of nanoindentation residual stress field in single-crystalline 4H-SiC via micro-Raman spectroscopy

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Optics Letters 2025年第11期50卷 3513-3516页

作者： Yang, Zhoudong Tian, Jing Wang, Xinyue Chen, Junwei Zuo, Yuanhui Zhang, Rongjun Tang, Hongyu Fan, Xuejun Zhang, Guoqi Fan, Jiajie Shanghai Engineering Technology Research Center for SiC Power Device School of Intelligent Robotics and Advanced Manufacturing Fudan University Shanghai200433 China Research Institute of Fudan University in Ningbo Ningbo315336 China School of Information Science and Technology Fudan University Shanghai200433 China Department of Mechanical Engineering Lamar University PO Box 10028 BeaumontTX77710 United States EEMCS Faculty Delft University of Technology Delft2628 Netherlands

This Letter presents a combined analytical and experimental method to effectively decouple the radial and tangential residual stress fields induced by Berkovich nanoindentation in single-crystalline 4H-SiC using micro-Raman spectroscopy. By integrating the Raman stress characterization model with Yoffe’s expanding cavity model, precise extraction of individual residual stress components around the indentation region is realized. Through the vertical backscattering micro-Raman mapping of the E2 phonon mode, we systematically investigate the residual stress distribution near the indentation. The results highlight significant anisotropy in nanoindentation-induced stress fields, strongly dependent on the crystal orientation of 4H-SiC, predominantly featuring radial tensile stress gradients. This comprehensive theoretical–experimental approach offers a robust optical framework for residual stress characterization in 4H-SiC and provides foundational insights for extending Raman spectroscopy-based stress characterization to other crystalline materials and related device structures. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Raman spectroscopy

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The effect of MeC nanoparticles on the micromechanical and tribological properties of carbon composite coatings

Tribologia

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Tribologia 2021年第4期280卷 157-163页

作者： Zimowski, Slawomir Kot, Marcin Moskalewicz, Tomasz AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics al. A. Mickiewicza 30 Krakow30-059 Poland AGH University of Science and Technology Faculty of Metals Engineering and Industrial Computer Science ul. Czarnowiejska 66 Krakow30-059 Poland

Nanocomposite carbon coatings composed of a nanocrystalline phase and an amorphous carbon matrix (a-C or a-C:H) are an important group of coatings for tribological applications, especially if low friction is desired. Strong adhesion between the coating and the substrate as well as the ability to carry load are particularly important in ensuring the durability of the system. In this paper, the impact of a reinforcing phase in the form of hard carbides of chromium, titanium and tungsten (MeC) on the micromechanical and tribological properties of MeC/a-C coatings were analysed. The microhardness and modulus of elasticity using the indentation method and adhesion of these coatings to the substrate in scratch tests were determined. On the basis of tribological tests, the friction coefficient and wear rate of the coatings were determined during nonlubricated sliding contact with an alumina ball. The tested nanocomposite coatings showed very good sliding properties and wear resistance. The nc-WC/a-C and nc-TiC/a-C coatings exhibit the smallest coefficient of friction (below 0.1) and the highest wear resistance. The presence of nanocrystalline carbides in the amorphous carbon matrix limits the propagation of cracks in the coatings and allows the higher load carrying capacity. © 2018 Helsinki University of technology. All rights reserved.

关键词： Wear resistance

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Development of Boxing Glove Type Sensation Device for Exercise Induction and Continuation 11

Development of Boxing Glove Type Sensation Device for Exerci...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Kondo, Yurie Okada, Shima Saito, Moemi Tanaka, Takahide Fumimoto, Kanaru Ritsumeikan University Graduate School of Science and Engineering Shiga Japan Ritsumeikan University Faculty of Science and Engineering Department of Robotics Shiga Japan Corp. Value Link Technology Tokyo Japan

ISBN: (纸本)9781665492324

The COVID-19 pandemic caused by a virus called RARS-CoV-2 spread worldwide. As the result, the number of people who are lack exercise has increased. In addition, there are few systems to evaluate exercise movements and facilitate physical exercise at home. In this study, we developed a boxing glove type sensation device an acceleration sensor was installed in a boxing glove to evaluate the power of a punch, and the device has the function of glitz to the punches by producing sound, vibration, and light according to the type and power of the punching motion. An evaluation experiment was conducted to confirm that this device could induce exercise and promote health by having fun. A comparison was made between a normal boxing glove and the boxing glove type sensation device. As the results, we could confirm that, the number of strong punches with high acceleration and the total number of punches increased in the sensation device. In addition, the heart rate after exercise increased significantly compared to before and after exercise. The results also showed an increase in mood elevation and positive emotions. © 2022 IEEE.

关键词： Viruses

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Terminal Sliding Modes-Based PLLs for Three-Phase Grid-Connected Inverters 49

Terminal Sliding Modes-Based PLLs for Three-Phase Grid-Conne...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Hosseinabadi, Pooyan Alinaghi Kermadi, Mostefa Pota, Hemanshu Mekhilef, Saad Abadi, Ali Soltani Sharif The School of Engineering and Information Technology The University of New South Wales CanberraACT Australia Kuala Lumpur Malaysia The School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia Institute of Automatic Control and Robotics Warsaw University of Technology Faculty of Mechatronics Warsaw Poland

ISBN: (纸本)9798350331820

This paper proposes and experimentally implements new phase-locked loop algorithms using non-adaptive and adaptive terminal sliding modes for the three-phase grid-connected inverters. The proposed algorithms aim to extract the grid voltage phase and frequency and provide them for the inverter controller. The proposed sliding mode-based PLL algorithms provide faster, more robust, and more accurate detection of the grid voltage information compared to the conventional PI-PLL. This leads to better current controller performance and subsequently, improves the quality of the injected currents into the grid. The finite-time stability notion is incorporated with robust sliding modes to ensure a fast convergence rate. An adaptive law is proposed to determine a proper value for the switching gain which leads to a better overall performance of the PLL compared with a non-adaptive one. The Lyapunov stability theory is used to obtain the stability proofs of the closed-loop systems under both designed sliding modes-based PLLs. The proposed PLL algorithms are validated by simulation and experimental results for the three-phase grid-connected inverter under normal and various abnormal grid conditions. © 2023 IEEE.

关键词： Phase locked loops

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Research on Position Accuracy of Autonomous Industrial Vehicles in Polymer Products Factories

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Macromolecular Symposia 2024年第3期413卷 2300216-2300216页

作者： Jugravu, Bogdan Alexandru Lazăr, Marius Vali Savu, Tom Abaza, Bogdan Felician Opran, Constantin Gheorghe Faculty of Industrial Engineering and Robotics Manufacturing Engineering Department National University of Science and Technology Politehnica Bucharest Splaiul Independenței 313 Bucharest060042 Romania

The paper presents a research on estimating the positioning accuracy of autonomous industrial vehicles, using an original sensor fusion combination, in specific polymer production factories environments. Mechanical and electrical subsystems designs are presented, together with the software application and testing results. Conclusions are drawn, serving for future positioning system design. © 2024 Wiley-VCH GmbH.

关键词： Industrial research

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Machine learning and deep learning algorithms in detecting COVID-19 utilizing medical images: a comprehensive review

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Iran Journal of Computer science 2024年第3期7卷 699-721页

作者： Nurjahan Mahbub-Or-Rashid, Md. Satu, Md. Shahriare Tammim, Sanjana Ruhani Sunny, Farhana Akter Moni, Mohammad Ali Department of IoT and Robotics Engineering Bangabandhu Sheikh Mujibur Rahman Digital University Kaliakair Bangladesh Department of Computer Science and Engineering Bangladesh University of Business and Technology Mirpur Bangladesh Department of Management Information Systems Noakhali Science and Technology University Noakhali Bangladesh Department of Computer Science and Software Engineering Auburn University Auburn AL United States Department of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh Faculty of Health and Behavioural Sciences School of Health and Rehabilitation Sciences The University of Queensland St Lucia Australia

The public’s health is seriously at risk from the coronavirus pandemic. Millions of people have already died as a result of this devastating illness, which affects countless people daily worldwide. Unfortunately, no specific therapeutic drugs or vaccines are available to cure patients completely. Therefore, early identification of infected individuals and their isolation can help reduce community transmission of COVID-19. Despite being commonly used, the reverse transcription polymerase chain reaction (RT-PCR) test is costly, time-consuming, and requires suitable kits, which are not always readily available. An alternative solution for the traditional RT-PCR test is machine learning and deep learning-based COVID-19 detection that utilizes clinical features of chest X-rays and computed tomography (CT) images. In this study, we conducted a detailed review of more than 100 recently published works to detect COVID-19-infected patients. Thus, different data preprocessing, data augmentation, image enhancement, feature extraction, machine learning, deep learning, Explainable Artificial Intelligence (AI) methods, etc. were explored to understand how these techniques were used to process images for identifying COVID-19. Additionally, we identified the current challenges in this field and suggested further research directions. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Chest X-ray Computed tomography COVID-19 Deep learning Machine learning

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Behavior of Delivery Robot in Human-Robot Collaborative Spaces During Navigation

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Intelligent Automation & Soft Computing 2023年第1期35卷 795-810页

作者： Kiran Jot Singh Divneet Singh Kapoor Mohamed Abouhawwash Jehad F.Al-Amri Shubham Mahajan Amit Kant Pandit Embedded Systems&Robotics Research Group Chandigarh UniversityMohali140413PunjabIndia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Electronics and Communication Shri Mata Vaishno Devi UniversityKatra182320India

Navigation is an essential skill for *** becomes a cumbersome task for the robot in a human-populated environment,and Industry 5.0 is an emerging trend that focuses on the interaction between humans and *** behavior in a social setting is the key to human acceptance while ensuring human comfort and *** the advancement in robotics technology,the true use cases of robots in the tourism and hospitality industry are expanding in *** are very few experimental studies focusing on how people perceive the navigation behavior of a delivery robot.A robotic platform named“PI”has been designed,which incorporates proximity and vision *** robot utilizes a real-time object recognition algorithm based on the You Only Look Once(YOLO)algorithm to detect objects and humans during *** study is aimed towards evaluating human experience,for which we conducted a study among 36 participants to explore the perceived social presence,role,and perception of a delivery robot exhibiting different behavior conditions while navigating in a hotel *** participants’responses were collected and compared for different behavior conditions demonstrated by the robot and results show that humans prefer an assistant role of a robot enabled with audio and visual aids exhibiting social ***,this study can be useful for developers to gain insight into the expected behavior of a delivery robot.

关键词： Human-robot interaction robot navigation robot behavior collaborative spaces industrial IoT industry 5.0

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A Deep Learning Approach with Uncertainty Estimation to Assess Aboveground Biomass Mapping of Tropical Rainforest in Thailand

A Deep Learning Approach with Uncertainty Estimation to Asse...

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2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2024

作者： Sataudom, Nattawach Reangsang, Songphon Navakam, Suwit Manoonpong, Poramate Aobpaet, Anuphao Sunthornhao, Pasuta Yooyen, Natnicha Pongsopon, Mattana Chulinrak, Natthasiree Soontaros, Sasawat Charoensawadpong, Panunya Supavetch, Soravis Varuna Company Limited Bangkok Thailand PTT Public Company Limited Reforestation and Ecology Institute Bangkok Thailand Vidyasirimedhi Institute of Science and Technology Bio-Inspired Robotics and Neural Engineering Rayong Thailand Kasetsart University Faculty of Engineering Department of Civil Engineering Bangkok Thailand Kasetsart University Faculty of Forestry Department of Forest Management Bangkok Thailand

ISBN: (纸本)9798350358582

This study proposes an aboveground biomass (AGB) density model to overcome the limitation of sparse data coverage in Thailand and scale at national level. The model is based on a U-Net convolutional neural network and fuses spaceborne remote sensing data including Sentinel-1, Sentinel-2, and GEDI. Five models were developed using a deep ensemble technique to provide uncertainty estimation, where accuracy was validated using three types of forest inventory data. Tropical rainforests and other forested areas such as perennial crop regions with similar geographical characteristics were evaluated. Results show high uncertainty in the out-of-distribution data areas, with %RRMSE for Pará rubber, mixed deciduous forest, and dry evergreen forest of 17.05, 24.47, and 14.0, respectively. © 2024 IEEE.

关键词： Tropics

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