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Cybernetics and Innovations (ICCI), International Conference on

作者： Chawanee Sungthong Saksorn Ruangtanusak Pokpong Songmuang Department of Computer Science Faculty of Science and Technology Thammasat University Pathum Thani Thailand Applied Machine Learning Team Bedrock Analytics AI and Robotics Ventures Bangkok Thailand

ISBN: (数字)9798350370096

ISBN: (纸本)9798350370102

This study focuses on the problem in the field of issue ticketing systems, where the need for human involvement in classifying work task in the ticket often results in insufficient classification. Our primary focus is on a problem associated with multi-label classification. A significant challenge in this study is the dependency of our dataset on low resources, which is different from the large datasets usually used in current multi-label text classification studies. Therefore, we propose a pre-training approach for our low-resource dataset. Our methodology applies several embedding techniques, including TF-IDF, Word2Vec, and BERT (WangchanBERTa and PhayaThaiBERT). The classification models, such as Logistic Regression, Support Vector Classifiers, Decision Trees, Neural Networks, and Deep Neural Networks, are experimented in this study to assess their performance in a low-resource environment. According to our experimental results, a combination of PhayaThaiBERT and Deep Neural Networks outperforms conventional methods. The combination yielded an F1 score of 0.769 on the test dataset.

关键词： Logistic regression Technological innovation Text categorization Static VAr compensators Artificial neural networks Predictive models Vectors

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Analytical Method Considering Rotor Misalignment in Yokeless and Segmented Armature Machines 18

Analytical Method Considering Rotor Misalignment in Yokeless...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Yi, Feng Zhang, Chi Qiu, Shuheng Liu, Wei Zhang, Meitong Li, Shupei Ningbo Institute of Materials & Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology Ningbo China Ningbo Institute of Materials & Technology and Engineering Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo China Hebei University of Science & Technology Ningbo Institute of Materials & Technology and Engineering Chinese Academy of Sciences Faculty of Electrical Engineering Ningbo China Ningbo Institute of Materials & Technology and Engineering Chinese Academy of Sciences Ningbo China

ISBN: (纸本)9798350312201

This paper presents a quasi-3D analytical method considering the rotor misalignment for yokeless and segmented armature (YASA) machines. In the proposed method, a detailed subdomain (SD) method dividing the YASA machine into five SDs is utilized to calculate the magnetic field distribution, accounting for the rotor misalignment and slotted effect with limited depth. The entire magnetic field is obtained by applying the interface and boundary conditions. In addition, based on obtained bilateral air-gap flux density, the cogging torque is calculated considering the rotor misalignment. The effectiveness of the proposed method is validated compared with finite element analysis. © 2023 IEEE.

关键词： Permanent magnets

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BLOCK MEDCARE: ADVANCING HEALTHCARE THROUGH BLOCKCHAIN INTEGRATION

arXiv

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arXiv 2024年

作者： Simonoski, Oliver Bogatinoska, Dijana Capeska Faculty of Communication Networks and Security University of Information Science and Technology St. Paul the Apostle Ohrid6000 Macedonia Faculty of Applied IT Machine Intelligence and Robotics University of Information Science and Technology St. Paul the Apostle Ohrid6000 Macedonia

In an era driven by information exchange, transparency and security hold crucial importance, particularly within the healthcare industry, where data integrity and confidentiality are paramount. This paper investigates the integration of blockchain technology in healthcare, focusing on its potential to revolutionize Electronic Health Records (EHR) management and data sharing. By leveraging Ethereum-based blockchain implementations and smart contracts, we propose a novel system that empowers patients to securely store and manage their medical data. Our research addresses critical challenges in implementing blockchain in healthcare, including scalability, user privacy, and regulatory compliance. We propose a solution that combines digital signatures, Role-Based Access Control, and a multi-layered architecture to enhance security and ensure controlled access. The system's key functions, including user registration, data append, and data retrieval, are facilitated through smart contracts, providing a secure and efficient mechanism for managing health information. To validate our approach, we developed a decentralized application (dApp) that demonstrates the practical implementation of our blockchain-based healthcare solution. The dApp incorporates user-friendly interfaces for patients, doctors, and administrators, showcasing the system's potential to streamline healthcare processes while maintaining data security and integrity. Additionally, we conducted a survey to gain insights into the perceived benefits and challenges of blockchain adoption in healthcare. The results indicate strong interest among healthcare professionals and IT experts, while also highlighting concerns about integration costs and technological complexity. Our findings underscore the transformative potential of blockchain technology in healthcare, pointing towards a new era of patient-centric and secure healthcare services. By addressing current limitations and exploring future enhancements, such as

关键词： Electronic health record

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Block MedCare: Advancing healthcare through blockchain integration with AI and IoT

arXiv

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arXiv 2024年

This research explores the integration of blockchain technology in healthcare, focusing on enhancing the security and efficiency of Electronic Health Record (EHR) management. We propose a novel Ethereum-based system that empowers patients with secure control over their medical data. Our approach addresses key challenges in healthcare blockchain implementation, including scalability, privacy, and regulatory compliance. The system incorporates digital signatures, Role-Based Access Control, and a multi-layered architecture to ensure secure, controlled access. We developed a decentralized application (dApp) with user-friendly interfaces for patients, doctors, and administrators, demonstrating the practical application of our solution. A survey among healthcare professionals and IT experts revealed strong interest in blockchain adoption, while also highlighting concerns about integration costs. The study explores future enhancements, including integration with IoT devices and AI-driven analytics, contributing to the evolution of secure, efficient, and interoperable healthcare systems that leverage cutting-edge technologies for improved patient care. © 2024, CC BY.

关键词： Electronic health record

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RL-Based Guidance in Outpatient Hysteroscopy Training: A Feasibility Study

RL-Based Guidance in Outpatient Hysteroscopy Training: A Fea...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Poliakov, Vladimir Niu, Kenan Poorten, Emmanuel Vander Tsetserukou, Dzmitry Skolkovo Institute of Science and Technology Intelligent Space Robotics Lab Moscow121205 Russia Robot Assisted Surgery Group Faculty of Mechanical Engineering KU Leuven Leuven3001 Belgium

ISBN: (纸本)9781665481090

This work presents an RL-based agent for out-patient hysteroscopy training. Hysteroscopy is a gynecological procedure for examination of the uterine cavity. Recent ad-vancements enabled performing this type of intervention in the outpatient setup without anaesthesia. While being beneficial to the patient, this approach introduces new challenges for clinicians, who should take additional measures to maintain the level of patient comfort and prevent tissue damage. Our prior work has presented a platform for hysteroscopic training with the focus on the passage of the cervical canal. With this work, we aim to extend the functionality of the platform by designing a subsystem that autonomously performs the task of the passage of the cervical canal. This feature can later be used as a virtual instructor to provide educational cues for trainees and assess their performance. The developed algorithm is based on the soft actor critic approach to smooth the learning curve of the agent and ensure uniform exploration of the workspace. The designed algorithm was tested against the performance of five clinicians. Overall, the algorithm demonstrated high efficiency and reliability, succeeding in 98 % of trials and outperforming the expert group in three out of four measured metrics. © 2022 IEEE.

关键词： Hydraulic structures

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Method for improving the accuracy of mobile robot odometry based on machine learning 2

Method for improving the accuracy of mobile robot odometry b...

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2nd International Conference on Algorithms, High Performance Computing and Artificial Intelligence, AHPCAI 2022

作者： Shao, Bingbing Zheng, Tianjiang Li, Qi Chen, Yikun Ningbo University Faculty of Electrical Engineering and Computer Science Zhejiang Ningbo315211 China Key Laboratory of Robotics and Intelligent Equipment Technology of Zhejiang Province Zhejiang Ningbo315201 China

ISBN: (纸本)9798350334784

Omnidirectional mobile robots have the characteristic of moving in any direction with three degrees of freedom in plane XYZ. The positioning accuracy of a mobile robot is not only affected by its manufacturing errors but also may be affected by vibration, load, and other factors, resulting in errors in the process of moving. To reduce the influence of the above factors, this paper presents an error compensation method based on Gaussian process regression (GPR) for omnidirectional mobile robots. The method requires fewer learning parameters and training points, which enables more computational efficiency in the learning process. To verify the effectiveness of the method, a simulation experiment is carried out. The simulation results show that the accuracy of the odometry in the three degrees of freedom of the plane is improved by 89.70%, 88.09%, and 96.32% respectively. © 2022 IEEE.

关键词： Mobile robots

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Versatile Tasks on Integrated Aerial Platforms Using Only Onboard Sensors: Control, Estimation, and Validation

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IEEE Transactions on robotics 2025年 41卷 3518-3538页

作者： Wang, Kaidi Lai, Ganghua Yu, Yushu Du, Jianrui Sun, Jiali Xu, Bin Franchi, Antonio Sun, Fuchun Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beijing Institute of Technology School of Mechanical Engineering Beijing100081 China University of Twente Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science Enschede7500 AE Netherlands Tsinghua University Department of Computer Science and Technology China

Connecting multiple aerial vehicles to a rigid central platform through passive spherical joints holds the potential to construct a fully-actuated aerial platform. The integration of multiple vehicles enhances efficiency in tasks like mapping and object reconnaissance. This paper proposes a control and state estimation framework for the Integrated Aerial Platform (IAP), enabling it to perform versatile tasks like object reconnaissance and physical interactive tasks with only onboard sensors. In the framework, the 6D motion control serves as the low-level controller, while the high-level controller comprises a 6D admittance filter and a perception-aware attitude correction module. The 6D admittance filter, serving as the interaction controller, is adaptable for aerial interaction tasks. The perception-aware attitude correction algorithm is carefully designed by adopting a geometric Model Predictive Controller (MPC). This algorithm, incorporating both offline and online calculations, proves to be well-suited for the intricate dynamics of an IAP. A 6D direct wrench controller is also developed for the IAP. Notably, both the interaction controller and the direct wrench controller operate without reliance on force/torque sensors. Instead, a wrench observer algorithm is devised, considering external disturbances. Additionally, based on the kinematics constraints of the multiple aerials in the platform, a fusion algorithm for multiple Visual-Inertial Odometry (VIO) and kinematics constraints is developed, providing more accurate localization. A prototype of the IAP is constructed, and its capabilities are demonstrated through experiments including perception-aware object reconnaissance, aerial mapping, aerial peg-in-hole task, and 6D contact wrench generation. All experiments are conducted exclusively with onboard sensors. These tasks exemplify the merits of the proposed IAP and validate the effectiveness of the proposed control framework and fusion algorithm. © 2004-2012

关键词： State estimation

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Deep learning for brain age estimation: A systematic review

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Information Fusion 2023年 96卷 130-143页

作者： Tanveer, M. Ganaie, M.A. Beheshti, Iman Goel, Tripti Ahmad, Nehal Lai, Kuan-Ting Huang, Kaizhu Zhang, Yu-Dong Del Ser, Javier Lin, Chin-Teng Department of Mathematics Indian Institute of Technology Indore Simrol Indore453552 India Department of Robotics University of Michigan Ann ArborMI48109 United States Department of Human Anatomy and Cell Science Rady Faculty of Health Sciences Max Rady College of Medicine University of Manitoba WinnipegMB Canada Biomedical Imaging Lab National Institute of Technology Silchar Assam 788010 India Department of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Data Science Research Center Duke Kunshan University China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom Derio48160 Spain Bilbao48013 Spain School of Computer Science Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia

Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern are associated with the accelerated brain aging and brain abnormalities. Hence, efficient and accurate diagnosis techniques are required to elicit accurate brain age estimations. Several contributions have been reported in the past for this purpose, resorting to different data-driven modeling methods. Recently, deep neural networks (also referred to as deep learning) have become prevalent in manifold neuroimaging studies, including brain age estimation. In this review, we offer a comprehensive analysis of the literature related to the adoption of deep learning for brain age estimation with neuroimaging data. We detail and analyze different deep learning architectures used for this application, pausing at research works published to date quantitatively exploring their application. We also examine different brain age estimation frameworks, comparatively exposing their advantages and weaknesses. Finally, the review concludes with an outlook towards future directions that should be followed by prospective studies. The ultimate goal of this paper is to establish a common and informed reference for newcomers and experienced researchers willing to approach brain age estimation by using deep learning models. © 2023 Elsevier B.V.

关键词： Deep neural networks

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Nonlinear Luenberger observer for velocity estimation in active magnetic levitation system

Nonlinear Luenberger observer for velocity estimation in act...

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Rafał Bieszczad Adam Piłat Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Cracow Poland

This article presents the problem of designing a nonlinear observer for an active magnetic suspension system. The design process of the nonlinear Luenberger observer (also known as the Kazantzis-Kravaris-Luenberger observer) is discussed. Particular attention was paid to the main nonlinearity of the system - the electromagnetic force, which was modeled applying the function describing the change in inductance as a function of the distance of the levitating object from the electromagnet surface. Theoretical analyses were confirmed by the results of experimental studies in which the task of moving the sphere between the given positions using current control was carried out. Control tasks were conducted in the real-time regime on an embedded platform. The measured signals and estimated velocity were analyzed in the context of future implementations in control applications.

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A robot-based hybrid lower limb system for Assist-As-Needed rehabilitation of stroke patients: Technical evaluation and clinical feasibility

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Computers in Biology and Medicine 2024年 179卷 108839-108839页

作者： Leerskov, Kasper S. Rikhof, Cindy J.H. Spaich, Erika G. Dosen, Strahinja Prange-Lasonder, Gerdienke B. Prinsen, Erik C. Rietman, Johan S. Struijk, Lotte N.S. Andreasen The Neurorehabilitation Robotics and Engineering Group Center for Rehabilitation Robotics Department of Health Science and Technology Aalborg University Gistrup9260 Denmark Roessingh Research and Development Enschede7522AH Netherlands Faculty of Engineering Technology Department of Biomechanical Engineering University of Twente Enschede7500AE Netherlands Neurorehabilitation Systems Group Department of Health Science and Technology Aalborg University Gistrup9260 Denmark

Background: Although early rehabilitation is important following a stroke, severely affected patients have limited options for intensive rehabilitation as they are often bedridden. To create a system for early rehabilitation of lower extremities in these patients, we combined the robotic manipulator ROBERT® with electromyography (EMG)-triggered functional electrical stimulation (FES) and developed a novel user-driven Assist-As-Needed (AAN) control. The method is based on a state machine able to detect user movement capability, assessed by the presence of an EMG-trigger and the movement velocity, and provide different levels of assistance as required by the patient (no support, FES only, and simultaneous FES and mechanical assistance). Methods: To technically validate the system, we tested 10 able-bodied participants who were instructed to perform specific behaviors to test the system states while conducting knee extension and ankle dorsal flexion exercises. The system was also tested on two stroke patients to establish its clinical feasibility. Results: The technical validation showed that the state machine correctly detected the participants’ behavior and activated the target AAN state in more than 96% of the exercise repetitions. The clinical feasibility test showed that the system successfully recognized the patients’ movement capacity and activated assistive states according to their needs providing the minimal level of support required to exercise successfully. Conclusions: The system was technically validated and preliminarily proved clinically feasible. The present study shows that the novel system can be used to deliver exercises with a high number of repetitions while engaging the participants’ residual capabilities through the AAN strategy. © 2024 The Authors

关键词： robotics

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