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Human pose estimation in physiotherapy fitness exercise correction using novel transfer learning approach

PeerJ computer Science 2025年 11卷 e2854-e2854页

作者： Aisha Naseer Ali Raza Hadeeqa Afzal Aseel Smerat Norma Latif Fitriyani Yeonghyeon Gu Muhammad Syafrudin Institute of Information Technology Khwaja Fareed University of Engineering & Information Technology Rahim Yar Khan Pakistan Department of Software Engineering University of Lahore Lahore Pakistan Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Technologies Engineering Mazaya University College Nasiriyah Iraq Faculty of Educational Sciences Al-Ahliyya Amman University Amman Jordan Department of Artificial Intelligence and Data Science Sejong University Seoul South Korea

Objective To introduce and evaluate an efficient neural network approach for human pose estimation and correction during physical therapy exercises using wearable sensor data. Methods We leveraged benchmark data consisting of 276,625 records from wearable inertial and magnetic sensors. A novel method termed Random Forest Long Short-Term Memory (RFL), which integrates long short-term memory and Random Forest neural networks, was implemented for transfer feature engineering. The smartphone sensor data was used to generate new temporal and probabilistic features. These features were then utilized in machine learning methods to classify physical therapy exercises. Rigorous experiments, including k-fold validation and hyperparameter optimization, were conducted to validate the performance of the RFL approach. Results The RFL approach demonstrated superior performance, achieving a remarkable 99% accuracy with the Random Forest method. The rigorous experiments confirmed the efficacy and reliability of the method in classifying physical therapy exercises. Conclusions The proposed RFL method introduces a novel feature generation approach enhancing the accuracy of physical therapy exercise classification and correction. This innovative integration not only improves rehabilitation monitoring but also paves the way for more adaptive and intelligent physiotherapy assistance systems. By leveraging sensor data and advanced machine learning techniques, it has the potential to mitigate risks associated with disabilities and major diseases, thereby offering a feasible alternative to frequent clinic visits for consistent therapist guidance.

关键词： Transfer learning Deep learning Human pose estimation Physiotherapy Fitness Exercise Machine learning

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Cucumber Disease Identification Using Multiple Machine Learning Classifiers with a Pre-Trained VGG16 Model 12

Cucumber Disease Identification Using Multiple Machine Learn...

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12th International Electrical engineering Congress, iEECON 2024

作者： Sutacha, Chalermkiat Yodrot, Teerapon Orachon, Teerapong Orkweha, Khwanjit Ubon Ratchathani Rajabhat University Faculty Of Industrial Technology Department Of Computer Network Engineering Ubon Ratchathani Thailand Rajamangala University Of Technology Rattanakosin Faculty Of Industry And Technology Department Of Electrical Engineering Technology Prachuap Khiri Khan Thailand Kosen Of King Mongkut's Institute Of Technology Ladkrabang Department Of Computer Engineering Bangkok Thailand School Of Telecommunication Engineering Suranaree University Of Technology Nakhon Ratchasima Thailand

ISBN: (纸本)9798350383591

Agriculture is a foundational element of global food security and economic stability, yet it faces the perennial challenge of crop diseases, which can significantly impact yield and quality. Traditional disease detection methods, reliant on manual inspection, are labor-intensive and can lack precision. Addressing this, we propose a hybrid model that combines the strengths of Convolutional Neural Networks (CNNs) and machine learning classifiers for the automated detection of diseases in cucumber plants. Specifically, we employ the VGG16 network, renowned for its feature extraction capabilities, coupled with Support Vector Machine (SVM), Random Forest (RF), Decision Trees (DT), and K-Nearest Neighbors (KNN) classifiers. Our model is trained on a dataset consisting of high-resolution cucumber images, with 80% used for training and 20% for validation. Performance metrics such as accuracy, precision, recall, and F1-score are utilized for evaluation, with a particular emphasis on the F1-score for its balance between precision and recall. The SVM classifier emerges as the most effective, followed by RF, KNN, and DT. The results, analyzed through confusion matrices, validate the SVM's superior performance in accurately classifying the health status of cucumber plants. This study not only enhances disease detection accuracy but also suggests a direction for future agricultural practices, highlighting the potential integration of such models into real-time crop management systems. © 2024 IEEE.

关键词： Decision trees

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The eye diagram analysis of restoration scheme in FTTH-PON

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Journal of Applied Sciences 2011年第5期11卷 840-847页

作者： Ab-Rahman, M.S. Azizan, L. Al-Hakim Aziz, S.A.C. Jumari, K. Spectrum Technology Research Division Computer and Network Security Research Group Malaysia Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia

In this study, a technique for automatic restoration scheme for the ease of customers in a passive optical network is proposed. Protection switching against the failure in fiber line is carried out using our restoration scheme. The smart and intelligent system of FTTH is expected to be a key element which provides centralized monitoring, survivability and instantly maintenance of FTTH customer access network. In this study, we implement a cost effective restoration scheme for a novel tree-based for Intermediate Split Structure (ISS) in the drop region section. The protection mechanism for tree based optical switch will have capability to divert the signal onto protection line according to the types of failure condition and location of failures in access network by means of Zig Zag mechanism. This will ensure the data flow continuously due to breakdown occur in the network and instantly repair operation. We employ the dedicated and shared protection in our design. Four faulty conditions are considered in this article and OptiSystem, Inc. software is used to prove the solution feasibility. This study focused on the eye diagram parameter analysis in the FTTH-PON network during the working and failure condition. Four parameters will be concentrated which are BER, eye opening, maximum Q factor and jitter. In the case of failure condition, four restoration schemes are activated to ensure the signal flow continuously without perturbation. © 2011 Asian Network for Scientific Information.

关键词： Passive optical networks

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An Improved Technique for Preliminary Diagnosis of COVID-19 via Cough Audio Analysis 4th

An Improved Technique for Preliminary Diagnosis of COVID-1...

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4th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2021

作者： Pandhi, Tanya Kapoor, Teghdeep Gupta, Bharat Department of Computer Science and Engineering Jaypee Institute of Information Technology Uttar Pradesh Noida201309 India Faculty of Computer Science and Engineering Jaypee Institute of Information Technology Uttar Pradesh Noida201309 India

ISBN: (纸本)9783031070044

Humanity has suffered catastrophically due to the COVID-19 pandemic. One of the most reliable diagnoses of COVID-19 is RT-PCR (Reverse-Transcription Polymer Chain Reaction) testing. This method, however, has its limitations. It is time-consuming and requires scalability. This research work carries out a preliminary prognosis of COVID-19, which is scalable and less time-consuming. The research carried out a competitive analysis of four machine learning models namely, Multilayer Perceptron, Convolutional Neural Networks, Recurrent Neural Networks with Long Short-Term Memory, and VGG-19 with Support Vector Machines. Out of these models, Multilayer Perceptron outperformed with higher specificity of 94.5% and accuracy of 96.8%. The results show that Multilayer Perceptron was able to distinguish between positive and negative COVID-19 coughs by a robust feature embedding technique. © 2022, Springer Nature Switzerland AG.

关键词： Multilayer neural networks

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Multi-objective routing wavelength assignment in WDM network using SPEA2 approach

Multi-objective routing wavelength assignment in WDM network...

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2009 9th International Symposium on Communications and Information technology, ISCIT 2009

作者： Leesutthipornchai, Pakorn Wattanapongsakorn, Naruemon Charnsripinyo, Chalermpol Department of Computer Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi 126 Pracha-Utid Tung-Kru Bangkok 10140 Thailand National Electronics and Computer Technology Center Pathumthani Thailand

ISBN: (纸本)9781424445219

Network design problem is usually complicated. Network designers may have to optimize various design objectives simultaneously. This paper considers a multi-objective network design problem for routing wavelength assignment (RWA) in WDM networks. The design objectives are to maximize the number of accepted communication requests (source-destination pairs) as well as to minimize the number of wavelength channel requirement subject to a limited number of wavelength channels available on each network link and at least 80% of all commodities must be accepted. Both the design objectives are conflicted to each other;maximizing the number of accepted commodities will require a large number of wavelength channels while minimizing the number of wavelength channels will limit the amount of accepted commodities. To solve the problem, we apply a famous multiobjective optimization approach called "SPEA2". The obtained results are compared with those from the Weighted Sum Approach in various weighted cases. The result comparisons show that the SPEA2 is superior in term of providing various sets of feasible solutions as a front in the objective space. ©2009 IEEE.

关键词： Multiobjective optimization

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Emotion Recognition Using Bayesian Learning from a Multi-Label Data Corpus

Emotion Recognition Using Bayesian Learning from a Multi-Lab...

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2022 International Conference on Computing, Networking, Telecommunications and engineering Sciences Applications, CoNTESA 2022

作者： Swathi, Bandi Kumar, Madapuri Rudra Riyaz Belgaum, Mohammad Alansari, Zainab G. Pulla Reddy Engineering College Computer Science and Engineering Kurnool India G Pullaiah College of Engineering and Technology Computer Science and Engineering Kurnool India Multimedia University Faculty of Computing and Informatics Cyberjaya Malaysia University of Malaya Computer System and Information Technology Kuala Lumpur Malaysia Information Technology Muscat Oman

ISBN: (纸本)9798350398014

In the digital era of information systems, emotion detection from audio signals is crucial for forensic services and operator or driver emotion monitoring in large-scale companies' safety and security. Speech is a uniquely human trait used to express and communicate one's point of view to others. Emotion recognition from speech audio signals is obtaining a presenter's emotions from the presenter's audio signal. Machine learning is used to develop emotion recognition systems, a critical research goal in current engineering research. The three main stages in speech emotion recognition are extraction of features, feature engineering, and classification. Even though powerful machine learning-based emotion identification algorithms for speech audio signals exist, the detection rate with maximum specificity and sensitivity is not scalable using most modern methods. A significant research objective is feature optimization for emotion recognition from speech audio signals. This article introduced a unique technique called Supervised Bayes Learning on Digital Features (SBL-DF). To scale its performance, the trials compared the suggested approach's performance to an earlier model depicted against a similar goal. Experiment results indicate that the proposed method for optimizing features could be used on a large scale. The reference classifiers' performance in making accurate detections with few false positives. © 2022 IEEE.

关键词： Genetic algorithms

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Wavelet transformation for dental X-ray radiographs segmentation technique

Wavelet transformation for dental X-ray radiographs segmenta...

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8th International Conference on ICT and Knowledge engineering, ICT and KE 2010

作者： Patanachai, Nakintorn Covavisaruch, Nongluk Sinthanayothin, Chanjira Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok 10330 Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Thailand Science Park Pathumthani 12120 Thailand

ISBN: (纸本)9781424498758

Teeth segmentation of dental X-ray radiographs is the important step in teeth recognition. A segmentation to partition teeth from other areas in dental X-ray images. This paper proposes wavelet transform (WT) to segment dental X-ray images. Wavelet transform are small waves located in different time that analyze according to scale. Indeed, they are obtained using scaling and translation of a scaling function and wavelet function. The result of segmentation is a teeth feature marking each pixel. Such as, edges detection from image segmented. © 2010 IEEE.

关键词： Wavelet transforms

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Multicast Scheduling Algorithm Supporting Spatial Mini-slot Reuse for IEEE 802.16 Mesh Networks

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China Communications 2013年第1期10卷 116-133页

作者： Saleh Yousefi Morteza Maleki Department of Computer Engineering Faculty of Engineering Urmia University University of Applied Science and Technology- Miandoab Branch

Abstract： In this paper, we propose a mecha- nism for multicast data transmission in IEEE 802.16 mesh networks aimed at increasing the throughput by incorporating mini-slot spatial reuse. The proposed mechanism includes two novel algorithms： a source-based multicast tree topology construction algorithm followed by an interference-aware multieast scheduling algorithm. The proposed multicast interfer- ence-aware scheduling algorithm can be ap- plied to both source-based and rendez- vous-based multicast tree topologies. Results of our simulation study show that in compari- son to the mechanism used for the IEEE 802.16＇s standard, the proposed multicast tree generation algorithm reduces the number of consumed mini-slots by 64% on average. Moreover, using the proposed interfer- ence-aware scheduling algorithm decreases the number of required mini-slots by a further 22% on average. Therefore, the proposed mul- ticast scheduling mechanism shows a higher throughput than the previous approaches and it is more scalable with respect to increasing the number of multicast groups as well as in- creasing the number of members inside each multicast group.

关键词： IEEE 802.16 WiMAX Meshmode multicast scheduling interference spatial reuse

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Secure handshake with symptoms-matching: The essential to the success of mhealthcare social network

Secure handshake with symptoms-matching: The essential to th...

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5th International ICST Conference on Body Area Networks, BodyNets 2010

作者： Lu, Rongxing Lin, Xiaodong Liang, Xiaohui Shen, Xuemin Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada Faculty of Business and Information Technology University of Ontario Institute of Technology Canada

ISBN: (纸本)9781936968305

In our aging society, mHealthcare social network (MHSN) built upon wireless body sensor network (WBSN) and mobile communications provides a promising platform for the seniors who have the same symptom to exchange their experiences, give mutual support and inspiration to each other, and help forwarding their health information wirelessly to a related eHealth center. However, there exist many challenging security issues in MHSN such as how to securely identify a senior who has the same symptom, how to prevent others who don't have the symptom from knowing someone's symptom? In this paper, to tackle these challenging security issues, we propose a secure same-symptom-based handshake (SSH) scheme, and apply the provable security technique to demonstrate its security in the random oracle model. In addition, we discuss a promising application - social-based patient health information (PHI) collaborative reporting in MHSN, and conduct extensive simulations to evaluate its efficiency in terms of PHI reporting delay. © 2010 ACM.

关键词： Network security

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Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and Engineering Northeastern UniversityShenyang 110819China Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization *** past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer ***,it is hard to traverse the huge search space within reasonable resource as problem dimension *** evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory *** reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent *** there lacks a thorough review of the state of the art in this specific and important *** paper provides a comprehensive survey of these evolutionary algorithms for *** start with a brief introduction to the research status and the basic concepts of ***,we present surrogate-assisted evolutionary algorithms for HEPs from four main *** also give comparative results of some representative algorithms and application ***,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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