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A Perspective on Rhythmic Gymnastics Performance Analysis Powered by Intelligent Fabric

Advanced Fiber Materials 2023年第1期5卷 1-11页

作者： Dan Zhu Zhenyu Zhang Min Chen Pan Li Yuanzhuo Xiang Jingyu Ouyang Zhiheng Huang Xiaojuan Liu Fuhong Wang Maiping Yang Hongtao Zeng Ping Hong Lei Wei Chong Hou Guangming Tao School of Martial Arts and Performance Capital University of Physical Education and SportsBeijing 100191China Wuhan National Laboratory for Optoelectronics and School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China School of Sports Medicine and Mealth Chengdu Sport UniversityChengdu 610000China School of Physical Education Chaohu UniversityHefei 238000China School of Physical Education Huazhong University of Science and TechnologyWuhan 430074China Beijing Sport University Beijing 100091China School of Electronic and Electrical Engineering and School of Materials Science and Engineering Nanyang University of TechnologySingapore 639798Singapore School of Optics and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China

Performance analysis is an important tool for gymnasts and coaches to assess the techniques,strengths,and weaknesses of rhythmic gymnasts during *** have an accurate insight about the motion and postures can help the optimization of their performance and offer personalized ***,there are three primary limitations of traditional perfor-mance analysis systems applied in rhythmic gymnastics:(1)Inability to quantify anthropometric data in an imperceptible way,(2)labor-intensive nature of data labeling and analysis,and(3)lack of monitoring of all-round and multi-dimensional perspectives of the ***,an advanced performance analysis system for rhythmic gymnastics is proposed in this paper,powered by intelligent *** system uses intelligent fabric to detect the physiological and anthropometric data of the *** a variety of data are collected,the analysis component is implemented by artificial intelligence techniques resulting in behavior recognition,decision-making,and other functions assisting performance improvement.A feasible solution to implementing the analysis component is the use of the hyperdimensional computing *** addition,four typical applications are presented to improve training *** by intelligent fabric,the proposed advanced performance analysis system exhibits the potential to promote innovative technologies for improving training and competi-tive performance,prolonging athletic careers,as well as reducing sports injuries.

关键词： Rhythmic gymnastics Intelligent fabric Augmented reality Artificial intelligence

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A Review on the Application of Radiomics and Deep Learning for Disease Identification in Musculoskeletal Radiography 5

A Review on the Application of Radiomics and Deep Learning f...

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5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Das, Shyamali Rama Devi, C. Nayagam, M. Gomathy Suganthi, D. Thachamkode, Fidha Senthil, K. Manoj Cmr Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India St.Joseph's College of Engineering Electrical and Electronics Engineering India Ramco Institute of Technology Department of Computer Science and Engineering Rajapalayam India Saveetha College of Liberal Arts and Sciences Saveetha Institute of Medical and Technical Sciences Department of Computer Science Chennai602105 India Kmct Dental College Department of Oral Medicine and Radiology Kerala Kozhikode673602 India Kongu Engineering College Electronics and Communication Engineering Erode638 060 India

ISBN: (纸本)9798350321425

Musculoskeletal disorders cause most disability worldwide. Musculoskeletal (MSK) issues are diagnosed, predicted, and treated utilizing imaging methods, magnetic resonance imaging (MRI), and ultrasound, and their precise interpretation by specialized radiologists. Radiological scanning aids metabolic health, aging, and diabetes assessment. Proposed research shows how machine learning, specifically deep learning, may be used to analyze MRI data quickly and reliably, addressing a crucial clinical need in MSK radiology. As primary care radiography services grow, so does interest in how AI, and especially deep learning, might help radiologists and primary care physicians make accurate diagnoses and enhance patient treatment. Chronic pain impairs mobility, dexterity, and function. Diagnosis requires bone X-rays. Deep learning algorithms are increasingly used in musculoskeletal radiology, with promising outcomes. The proposed method uses a calibrated ensemble of deep learners to musculoskeletal radiograph recognition. In the suggested model uses three deep neural networks, which are commonly utilized in deep learning-based solutions for this problem domain. Publicly available dataset to demonstrates the suggested strategy outperforms three individual models and a standard ensemble learner. This study strongly supports the use of a calibrated ensemble approach for identifying abnormalities in musculoskeletal X-rays, where the greatest radiologist accuracy is between 0.95 and 0.98 in Cohen's kappa statistic. © 2023 IEEE.

关键词： Magnetic resonance imaging

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SilverCycling: Exploring the Impact of Bike-Based Locomotion on Spatial Orientation for Older Adults in VR

arXiv

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arXiv 2024年

作者： Chen, Qiongyan Wu, Zhiqing Liu, Yucheng Han, Lei Li, Zisu Kan, Ge Lin Fan, Mingming Computational Media and Arts Thrust The Hong Kong University of Science and Technology Guangzhou China The Hong Kong University of Science and Technology China Urban Governance and Design Thrust The Hong Kong University of Science and Technology Guangzhou China Computational Media and Arts The Hong Kong University of Science and Technology Guangzhou China Integrative Systems and Design & Computer Science and Engineering The Hong Kong University of Science and Technology China

Spatial orientation is essential for people to effectively navigate and interact with the environment in everyday life. With age-related cognitive decline, providing VR locomotion techniques with better spatial orientation performance for older adults becomes important. Such advancements not only make VR more accessible to older adults but also enable them to reap the potential health benefits of VR technology. Natural motion-based locomotion has been shown its effective in enhancing younger users’ performance in VR navigation tasks that require spatial orientation. However, there is a lack of understanding regarding the impact of natural motion-based locomotion on spatial orientation for older adults in VR. To address this gap, we selected the SilverCycling system, a VR bike-based locomotion technique that we developed, as a representative of natural motion-based locomotion, guided by findings from our pilot study. We conducted a user study with 16 older adults to compare SilverCycling with the joystick-based controller. The findings suggest SilverCycling potential to significantly enhance spatial orientation in the open-road urban environment for older adults, offering a better user experience. Based on our findings, we identify key factors influencing spatial orientation and propose design recommendations to make VR locomotion more accessible and user-friendly for older adults. Copyright © 2024, The Authors. All rights reserved.

关键词： Bicycles

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Application of Normal Form Theory to Power Systems: A Proof of Concept of a Novel Structure-Preserving Approach

Application of Normal Form Theory to Power Systems: A Proof ...

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IEEE General Meeting Power& Energy Society

作者： Bin Wang Xavier Kestelyn Erfan Kharazian Aurélien Grolet Department of Electrical and Computer Engineering University of Texas at San Antonio San Antonio TX Laboratory of Electrical Engineering of Lille (L2EP) Arts et Metiers Institute of Technology (ENSAM) Lille France Laboratory of Physical and Numerical Systems (LISPEN) Arts et Metiers Institute of Technology (ENSAM) Lille France

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Differential algebraic equations (DAE) of power systems, classically obtained by aggregating all component equations and network equations, are a standard input of transient stability simulation software. To add a parametric approach to the provided transient stability simulation, the linear modal analysis is a commonly adopted approach because it provides insights about system dynamics, such as eigenvalues and eigenvectors, that can be used for control design. When the power system is more heavily loaded, the linear modal analysis becomes less accurate in terms of capturing system dynamic behaviors when subjected to large disturbances. Normal form analysis, based on a higher-order Taylor expansion of the system model, has been proved to capture the major nonlinear effects occurring in the system. Unfortunately, the normal form method is currently only applicable to ordinary differential equations (ODE) and imposes a recast of the DAE system onto an ODE system, which is feasible only under restrictive assumptions and is usually time-consuming. In this paper, we propose a novel method in order to directly apply the normal form theory to power system DAE without the need to recast DAE into an ODE form. A single-machine-infinite-bus (SMIB) system is adopted to show the feasibility and accuracy of the proposed method.

关键词： Accuracy System dynamics Modal analysis Power system stability Mathematical models Stability analysis Software Transient analysis Thermal stability Standards

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Multi-Objective Grey Wolf Optimization Algorithm for Solving Real-World BLDC Motor Design Problem

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computers, Materials & Continua 2022年第2期70卷 2435-2452页

作者： M.Premkumar Pradeep Jangir B.Santhosh Kumar Mohammad A.Alqudah Kottakkaran Sooppy Nisar Department of Electrical and Electronics Engineering GMR Institute of TechnologyRajam532127Andhra PradeshIndia Rajasthan Rajya Vidyut Prasaran Nigam Sikar332025RajasthanIndia Department of Computer Science and Engineering GMR Institute of TechnologyRajam532127Andhra PradeshIndia German Jordanian University Amman11180Jordan Department of Mathematics College of Arts and SciencesPrince Sattam Bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia

The first step in the design phase of the Brushless Direct Current(BLDC)motor is the formulation of the mathematical framework and is often used due to its analytical ***,the BLDC motor design problem is considered to be an optimization *** this paper,the analytical model of the BLDC motor is presented,and it is considered to be a basis for emphasizing the optimization *** analytical model used for the experimentation has 78 non-linear equations,two objective functions,five design variables,and six non-linear constraints,so the BLDC motor design problem is considered as highly non-linear in electromagnetic ***-objective optimization becomes the forefront of the current research to obtain the global best solution using metaheuristic *** bio-inspired multi-objective grey wolf optimizer(MOGWO)is presented in this paper,and it is formulated based on Pareto optimality,dominance,and archiving *** performance of theMOGWO is verified on standard multi-objective unconstraint benchmark functions and applied to the BLDC motor design *** results proved that the proposedMOGWO algorithm could handle nonlinear constraints in electromagnetic optimization *** performance comparison in terms of Generational Distance,inversion GD,Hypervolume-matrix,scattered-matrix,and coverage metrics proves that the MOGWO algorithm can provide the best solution compared to other selected *** source code of this paper is backed up with extra online support at https://***/mysite and https://***/matlabcentral/fileexchange/75259-multiobjective-non-sorted-grey-wolf-mogwo-nsgwo.

关键词： BLDC motor electromagnetics metaheuristic multi-objective grey wolf optimizer

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Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer

arXiv

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arXiv 2023年

作者： Zhang, Jianwei Jayasuriya, Suren Berisha, Visar School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85281 United States School of Arts Media and Engineering School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85281 United States College of Health Solutions School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85281 United States

A good supervised embedding for a specific machine learning task is only sensitive to changes in the label of interest and is invariant to other confounding factors. We leverage the concept of repeatability from measurement theory to describe this property and propose to use the intra-class correlation coefficient (ICC) to evaluate the repeatability of embeddings. We then propose a novel regularizer, the ICC regularizer, as a complementary component for contrastive losses to guide deep neural networks to produce embeddings with higher repeatability. We use simulated data to explain why the ICC regularizer works better on minimizing the intra-class variance than the contrastive loss alone. We implement the ICC regularizer and apply it to three speech tasks: speaker verification, voice style conversion, and a clinical application for detecting dysphonic voice. The experimental results demonstrate that adding an ICC regularizer can improve the repeatability of learned embeddings compared to only using the contrastive loss;further, these embeddings lead to improved performance in these downstream tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

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Evaluating Interactive Concept Maps Produced from E-Portfolios

Evaluating Interactive Concept Maps Produced from E-Portfoli...

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IEEE International Symposium on Multimedia

作者： Alexander Gantikow Andreas Isking Wolfgang Müller Paul Libbrecht Sandra Rebholz Media Education and Visualization University of Education Weingarten Weingarten Germany IT & Technology IU International University of Applied Science Erfurt Germany Electrical Engineering Media and Computer Science Ostbayerische Technische Hochschule Amberg-Weiden Amberg-Weiden Germany

ISBN: (数字)9798331511111

ISBN: (纸本)9798331511128

Natural Language Processing opens new ways to analyze digital works. We are interested in the assessment of e-portfolios which are digital learning logs. Through analysis techniques such as the recognition of topics of a paragraph it is is possible to visualize the topic coverage and content depth. Such visualizations can be useful in the e-portfolio creation and review processes. We have applied these technologies to develop interactive concept maps for exam-relevant e-portfolios and have used them in a real-life setting at university. The experiment has shown that the interactive concept maps have motivated the students and that they have the potential to be useful in the writing process if they are well integrated into the workflow.

关键词： Visualization Reviews Navigation Text categorization Natural language processing Usability Interviews

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Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

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computers, Materials & Continua 2023年第5期75卷 3239-3255页

作者： Majdy M.Eltahir Adil Yousif Fadwa Alrowais Mohamed K.Nour Radwa Marzouk Hatim Dafaalla Asma Abbas Hassan Elnour Amira Sayed A.Aziz Manar Ahmed Hamza Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Arts and Science Najran UniversitySharourahSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Applied SciencesKing Khalid UniversityMuhayil63772Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event *** is especially applicable in the case of elderly or disabled people who live self-reliantly in their *** sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during *** is one of the most important problems confronted by older people and people with movement *** previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled ***,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor ***,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s *** this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)*** presented IWODL-FDDP model aims to identify the fall events to assist disabled *** presented IWODLFDDP model applies an image filtering approach to pre-process the ***,the EfficientNet-B0 model is utilized to generate valuable feature vector ***,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall ***,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the *** experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.

关键词： Fall detection disabled people deep learning improved whale optimization assisted living

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Computation of an Emptiable Minimal Siphon in a Subclass of Petri Nets Using Mixed-Integer Programming

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 219-226页

作者： Shouguang Wang Wenli Duo Xin Guo Xiaoning Jiang Dan You Kamel Barkaoui MengChu Zhou the School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China the Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China the Department of Computer Science Conservatoire National des Arts et MétiersParis 75141France the Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems Macao University of Science and TechnologyMacao 999078China

Deadlock resolution strategies based on siphon control are widely *** computational efficiency largely depends on siphon ***-integer programming(MIP)can be utilized for the computation of an emptiable siphon in a Petri net(PN).Based on it,deadlock resolution strategies can be designed without requiring complete siphon enumeration that has exponential *** to this reason,various MIP methods are proposed for various subclasses of *** work proposes an innovative MIP method to compute an emptiable minimal siphon(EMS)for a subclass of PNs named S^(4)*** particular,many particular structural characteristics of EMS in S4 PR are formalized as constraints,which greatly reduces the solution *** results show that the proposed MIP method has higher computational ***,the proposed method allows one to determine the liveness of an ordinary S^(4)PR.

关键词： Automated manufacturing systems deadlocks discrete event system mixed-integer programming(MIP) Petri nets(PN) siphons

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Design and Development of an IoT Based Smart Vaccine Carrier and Real-Time Monitoring System

Design and Development of an IoT Based Smart Vaccine Carrier...

引用

Sustainable Technologies for Industry 4.0 (STI), International Conference on

作者： Raisa T. Hasanat Nafees Mansoor Nabeel Mohammed Mohammad S. Rahman Sifat Momen Mirza Rasheduzzaman EA Technology Capenhurst United Kingdom Dept. of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh Dept. of Electrical and Computer Engineering North South University Dhaka Bangladesh Dept. of Computer Science and Engineering United International University Dhaka Bangladesh Dept. of Electrical and Electronic Engineering BRAC University Dhaka Bangladesh

ISBN: (数字)9798331531973

ISBN: (纸本)9798331531980

Vaccination stands as the most reliable defense against a spectrum of life-threatening diseases. However, the eq-uitable distribution of vaccines in developing and least-developed nations face formidable challenges due to the absence of efficient and transparent cold chain management systems. This article introduces a real-time data-centric monitoring system designed to track the distribution and transportation of vaccines. Additionally, this research presents an energy-efficient vaccine carrier based on thermoelectric cooling, boasting minimal power consumption requirements. This innovative carrier ensures the safe transportation of vaccines even to the most remote regions. Moreover, the proposed system regulates the temperature and humidity of individual carriers by continuously monitoring sensor data. Furthermore, the system includes real-time tracking and reporting features. Anticipated outcomes include a significant increase in vaccination coverage in remote areas and enhanced transparency in the distribution process.

关键词： Temperature sensors Temperature distribution Power demand Cold chain Transportation Humidity Real-time systems Vaccines Reliability Monitoring

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