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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Ueda, Rena Doi, Hirokazu Furui, Akira Shimatani, Koji Hayashi, Hideaki Tsuji, Toshio Hiroshima University Graduate School of Advanced Science and Engineering 1-4-1 Kagamiyama Hiroshima Higashi-Hiroshima739-8527 Japan Nagaoka University of Technology Department of Information and Management Systems Engineering 1603-1 Kamitomioka Niigata Nagaoka940-2188 Japan Nagasaki University Graduate School of Biomedical Sciences 1-12-4 Sakamoto Nagasaki Nagasaki852-8523 Japan Prefectural University of Hiroshima Faculty of Health and Welfare 1-1 Gakuen-machi Hiroshima Mihara723-0053 Japan Osaka University Institute for Datability Science 2-8 Yamadaoka Osaka Suita565-0871 Japan

ISBN: (纸本)9798331531614

Anomalies in motor function and social communication skills constitute early signs of autism spectrum disorder (ASD). In recent years, researchers have paid attention to the possibility of the quantitatively evaluating infants' social communication skills based on their eye movement. In this paper, we attempt to evaluate ASD risk using infants' eye movement data by examining the relationship between eye movement patterns at 4, 10, and 18 months of age and ASD risk as assessed by caregivers using a checklist at 18 months of age. A total of 18 eye movement indices were calculated from eye movement data measured by an optical eye tracker. The results revealed an association between ASD risk and eye movement indices. The indices included those related to a preference for social information at 4 months of age, those related to visual exploration of images at 10 months of age, and those indices related to both preference and visual exploration at 18 months of age. These results indicate that eye movement analysis may potentially serve as a means for early screening of ASD risk. © 2025 IEEE.

关键词： Risk assessment

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Sustainable management of iron ore extraction processes using methods of borehole hydro technology

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International Journal of Mining and Mineral engineering 2025年第1期16卷 92-112页

作者： Kosenko, Andrii Khomenko, Oleh Kononenko, Maksym Polyanska, Alla Buketov, Valentyn Dychkovskyi, Roman Polański, Jaroslaw Howaniec, Natalia Smolinski, Adam Department of Rock Mass Condition Control Poliakov Institute of Geotechnical Mechanics National Academy of Sciences of Ukraine Symphyropilska Str. 15 DniproUA-490005 Ukraine Department of Mining Engineering and Education Dnipro University of Technology Yavornytskoho Ave. 19 DniproUA-49005 Ukraine Department of Transport Systems and Energy-Mechanical Complexes Dnipro University of Technology Yavornytskoho Ave. 19 DniproUA-49005 Ukraine Faculty of Management AGH University of Science and Technology al. Mickiewicza 30 Krakow30059 Poland Institute of the Center of Renewable Energy and Energy Efficiency Universidad Nacional de San Agustin de Arequipa San Agustin Street 107 ArequipaPE-04000 Peru Faculty of Science and Technology Institute of Chemistry University of Silesia Szkolna 9 Katowice40-006 Poland Department of Energy Saving and Air Protection Central Mining Institute Plac Gwarkow 1 Katowice40-166 Poland

The development of rich iron ore deposits in the Kryvyi Rih Basin is carried out by underground methods at considerable depths. This mining method is characterised by high labour, capital and operating costs. In the paper, the experimental research on the establishment of rational parameters of borehole hydrotechnology for the sustainable management of iron ore extraction processes of martite ore deposits at considerable depths. Based on the experimental studies, mathematical expressions have been derived to calculate the rational parameters for borehole disintegration of martite ore masses using rotating water jets. Dependencies between the structural and morphological characteristics and the fracturing of martite ores, as well as the parameters of influence of water control, were identified. It was found that the use of borehole hydrotechnology ensures selective exposure of ore-forming minerals. As a result, the ore quality is improved and the silica mass fraction is reduced, which enables the production of the highest quality iron ore raw materials – superconcentrates. In addition, this technology is a combined ore preparation process that includes beneficiation, grinding, and classification of destruction products based on their particle size composition during their washing. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Iron ores

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Maximum Power Point Tracking Using Cross-Correlation Algorithm for Pv System

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SSRN 2022年

作者： Abulanwar, Sayed Shahin, Ahmed Gad, Hesham H. Rizk, Mohammad E.M. Hu, Weihao Electrical Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Computer and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Engineering Horus University Egypt

This paper suggests an online, rapid, dynamic, and pragmatic cross-correlation (CC) technique to eﬀectively realize maximum power point tracking (MPPT) of the photovoltaic (PV) array. The PV voltage and current are extracted, averaged, and rate of change of the power and terminal voltage dynamics are integrally cross-correlated to regulate the duty ratio of the converter. According to this approach, the maximum power point (MPP) is defned in terms of the polarity of the CC coefcient (rcc). If the CC coefcient is positive, the operating point is at left of the MPP, while a negative CC coefcient indicates that the operating point is located at right of the MPP, otherwise the MPP is attained zero CC coefcient with lower steady-state ﬂuctuations. In this regard, a tracking optimization can be realized with confned drift either under gradual or step solar irradiance changes. The proposed CC technique quickly converges to the MPP without identifcation of PV array parameters. Besides, the proposed CC tracking algorithm tracks MPP with wide-range small step-size iterations since the search area is restricted to the vicinity of the MPP rather than the entire PV curve. Moreover, the proposed technique is featured by robustness against system parameters and load variations with simple hardware implementation as compared to several existing techniques. The eﬀectiveness of the proposed technique is thoroughly explored via time-domain, experimental, and hardware-in-loop investigations and meanwhile compared to the two most popular techniques: P&O INC methods, for both gradual and step irradiance changes and also shadow eﬀects. © 2022, The Authors. All rights reserved.

关键词： Time domain analysis

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Discriminative Analysis of Autistic Tendencies at 18 Months of Age Using Eye Gaze Characteristics in 4-, 10-, and 18-month-old Infants

Discriminative Analysis of Autistic Tendencies at 18 Months ...

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IEEE/SICE International Symposium on System Integration

作者： Rena Ueda Hirokazu Doi Akira Furui Koji Shimatani Hideaki Hayashi Toshio Tsuji Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Japan Department of Information and Management Systems Engineering Nagaoka University of Technology Niigata Japan Graduate School of Biomedical Sciences Nagasaki University Nagasaki Japan Faculty of Health and Welfare Prefectural University of Hiroshima Hiroshima Japan Institute for Datability Science Osaka University Osaka Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Anomalies in motor function and social communication skills constitute early signs of autism spectrum disorder (ASD). In recent years, researchers have paid attention to the possibility of the quantitatively evaluating infants’ social communication skills based on their eye movement. In this paper, we attempt to evaluate ASD risk using infants’ eye movement data by examining the relationship between eye movement patterns at 4, 10, and 18 months of age and ASD risk as assessed by caregivers using a checklist at 18 months of age. A total of 18 eye movement indices were calculated from eye movement data measured by an optical eye tracker. The results revealed an association between ASD risk and eye movement indices. The indices included those related to a preference for social information at 4 months of age, those related to visual exploration of images at 10 months of age, and those indices related to both preference and visual exploration at 18 months of age. These results indicate that eye movement analysis may potentially serve as a means for early screening of ASD risk.

关键词： Visualization Accuracy Tracking Input variables System integration Variable speed drives Optical variables measurement Feature extraction Optical imaging Motors

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A Modified Dempster Shafer Approach to Classification in Surgical Skill Assessment

A Modified Dempster Shafer Approach to Classification in Sur...

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Iranian Conference on Electrical engineering (ICEE)

作者： Arash Iranfar Mohammad Soleymannejad Behzad Moshiri Hamid D. Taghirad School of Electrical and Computer Engineering University College of Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is.

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Damping Linearization of Ankle Prosthesis Based on Electro-Hydrostatic Actuation

Damping Linearization of Ankle Prosthesis Based on Electro-H...

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2022 CSAA/IET International Conference on Aircraft Utility systems, AUS 2022

作者： Dong, Dengpeng Wang, Xingjian Tian, Xinyu Wang, Shaoping Wei, Yi Gavrilov, Alexander I. School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang University Beijing100191 China Bauman Moscow State Technical University Department of Automatic Control Systems Moscow105005 Russia

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

The research object of this paper is the ankle prosthesis system based on electro-hydrostatic actuation. In the passive state, the prosthesis uses PWM wave to drive a high speed ON/OFF valve (HOV), making it equivalent to a proportional valve with a certain opening size to adjust the damping of the system and achieve a compliant control. However, due to the mechanical delay characteristics of the HOV, there are obvious nonlinear regions in the low duty cycle and high duty cycle regions, which affect the control performance of the system. This paper will discuss this problem. Using the control strategies in PWM-PFM to widen the linear region of the prosthetic system damping control, improve the system's ability to adjust the damping, and facilitate the prosthesis to better achieve active compliance control. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Linearization

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Prescribed-Time Tracking control for Robotic systems with Uncertain Dynamics

Prescribed-Time Tracking Control for Robotic Systems with Un...

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Data Driven control and Learning systems (DDCLS)

作者： Hang Yang Yingbo Huang Jing Na Qiang Chen Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming China Data-Driven Intelligent Systems Laboratory College of Information Engineering Zhejiang University of Technology Hangzhou China

This paper presents a prescribed-time tracking control scheme for robotic systems with unknown dynamics. One salient feature is that the robotic systems can achieve prescribed-time stability with the prescribed transient performance, which is different with the traditional work that achieves uniformly ultimately bounded (UUB) and/or asymptotic stability. To realize this purpose, the prescribed performance dynamics (PPD) instead of the traditional prescribed performance function (PPF) is suggested, by which both the transient and steady-state tracking performance can be guaranteed within a specified region in-priori. To avoid using the function approximators (i.e., neural networks (NNs), fuzzy logic systems (FLSs)), an approximation-free-based prescribed-time controller is established with the inertial matrix of robotic systems and the finite-time function merely, which can not only address the system unknown uncertainties but also regulate the control error to zero in a prescribed-time. Furthermore, the Lyapunov-based theoretical analysis is conducted to prove the prescribed-time stability of the closed-loop system. Finally, comparative numerical simulation results are provided to demonstrate the effectiveness of the proposed method.

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Sustainability and Predictive Accuracy Evaluation of Gel and Embroidered Electrodes for ECG Monitoring

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SSRN 2024年

作者： Othman, Ghada Ben Kumar, Atal Anil Hassine, Faten Ben Copot, Dana Sidhom, Lilia Kamavuako, Ernest N. Trabelsi, Mohamed Ionescu, Clara Mihaela Chihi, Inès Ghent University Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Zwijnaarde9052 Belgium Department Of Engineering Faculty of Science Technology and Medicine University of Luxembourg Kirchberg Luxembourg Faculty of Sciences of Tunis Tunis Tunisia National Engineering School of Bizerte Carthage University Tunis LAPER- Faculty of Sciences of Tunis El Manar University Tunis Tunisia Technical University of Cluj-Napoca Department of Automation Memorandumului no. 28 Cluj-Napoca400114 Romania Department of Informatics King’s College London London United Kingdom Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait City Kuwait

Despite standards on electrocardiogram (ECG) monitoring in medical diagnostics, signal acquisition is prone to noisy artefacts and rely greatly on the quality of skin contact and signal transducing interference. Electrodes, serving as indispensable conduits in ECG signal acquisition, act as the crucial interface between the human body and recording instrumentation. The usage of traditional gel electrodes may provoke skin irritation, by contrast, the advent of embroidered electrodes, a contemporary innovation, holds the promise of more comfort monitoring. However, the sustainability quotient and predictive precision of these novel electrodes require more in-depth investigation. This paper endeavors a comprehensive evaluation of both gel and embroidered electrodes concerning ECG signal acquisition. Simultaneously, the study aims to construct a polynomial regression model leveraging advanced machine learning (ML) tools. The inferred model predicts embroidered signals based on experimental data obtained from gel electrodes. The methodology encompasses systematic data collection, preprocessing, insightful analysis, and the application of data-driven techniques. The findings of this study highlight the viability of embroidered electrodes as a compelling alternative, transcending traditional paradigms. Employing ML tools, the developed model achieves predictive accuracy, reflected in robust R2 values extending up to 94.9%. © 2024, The Authors. All rights reserved.

关键词： Electrocardiograms

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Knowledge Graph Completion with Low-Dimensional Gated Hierarchical Hyperbolic Embedding

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SSRN 2024年

作者： Fang, Yan Liu, Xiaodong Lu, Wei Pedrycz, Witold Lang, Qi Yang, Jianhua School of Control Science and Engineering Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian116024 China Department of Electrical and Computer Engineering University of Alberta EdmontonT6R 2V4 AB Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia School of Computer Science and Information Technology Northeast Normal University Changchun130117 China

Knowledge Graph Embedding aims to advance the learning performance of knowledge graphs by deliberating the complexity of hierarchical data structures in a finite-dimensional space. Most traditional Euclidean models struggle to accurately describe and navigate the intricate hierarchical relationships between nodes. The hyperbolic embedding methods, particularly in conjunction with graph neural networks, offer promise in effectively modeling complex hierarchies in a limited-dimensional space. These methods can accommodate more information about nodes under the same conditions but are also more susceptible to interference from complex neighborhood features. This paper introduces HyperGatE, which novelty combines a hyperbolic graph hierarchical neighbor structure based on a gated filter and a hyperbolic isometric rotation model for knowledge graph completion. By analyzing the hierarchical structure of the knowledge base and using a gated mechanism to form multi-layer embedding networks of entity-relational paths, the gated filter selects diverse uneven multi-hop relations within the entity neighborhood and measures them through graph attention networks. Furthermore, the simplified hyperbolic isometric model allows for uncovering hierarchical structures in the data. HyperGatE experimentally surpasses the state-of-the-art Euclidean and hyperbolic space models in high and low dimensions across four well-known data, namely WN18RR, FB15k-237, NELL-995, and Kinship. © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

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Graph-Based Visual-Kinematic Fusion and Monte Carlo Initialization for Fast-Deployable Cable-Driven Robots

Graph-Based Visual-Kinematic Fusion and Monte Carlo Initiali...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： R. Khorrambakht H. Damirchi M.R. Dindarloo A. Saki S.A. Khalilpour Hamid D. Taghirad Stephan Weiss Electrical & Computer Engineering Department Control/Robotics Research Laboratory Tandon School of Engineering New York University Brooklyn NY School of Computer Science University of Adelaide Australia Faculty of Electrical Engineering University of Technology Tehran Iran Department of Smart Systems Technologies University of Klagenfurt Austria

Ease of calibration and high-accuracy task-space state-estimation purely based on onboard sensors is a key requirement for enabling easily deployable cable robots in real-world applications. In this work, we incorporate the onboard camera and kinematic sensors to drive a statistical fusion framework that presents a unified localization and calibration system which requires no initial values for the kinematic parameters. This is achieved by formulating a Monte-Carlo algorithm that initializes a factor-graph representation of the calibration and localization problem. With this, we are able to jointly identify both the kinematic parameters and the visual odometry scale alongside their corresponding uncertainties. We demonstrate the practical applicability of the framework using our state-estimation dataset recorded with the ARAS-CAM suspended cable driven parallel robot, and published as part of this manuscript.

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