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Classifier performance comparison on American sign language gesture recognition

AIP Conference Proceedings 2024年第1期3069卷

作者： Asep Nugroho Latif Rozaqi Yukhi Mustaqim Kusuma Sya'ban Sharfiden Hassen Yusuf Rio Prasetyo Lukodono Research Center for Smart Mechatronics National Research and Innovation Agency (BRIN) Kawasan Sains dan Teknologi (KST) Samaun Samadikun Jalan Sangkuriang Bandung 40135 Indonesia School of Electrical and Computer Engineering Dire Dawa Institute of Technology Dire Dawa 1487 Ethiopia School of Industrial Management National Taiwan University of Science and Technology No. 43 Section 4 Keelung Rd Da'an District Taipei City 10607 Taiwan

Non-verbal communication usually uses for human computer interactions. One of non-verbal communication uses sign language such as hand gestures. To understand the command through hand gestures, the machine should recognize every movement so it needs classifier algorithms. Common classifiers algorithms such as k-nearest neighbor, decision tree, and support vector machine are used to recognize American sign language gestures. This study provides comparison performance among three common classifiers. Based on performance assessment, the support vector machine has the best accuracy and precision performance compared to two other algorithms. It can achieve 81.11% accuracy and 83.54% precision. In another hand, the k-nearest neighbor gives 74.44% accuracy and 74.40% precision while decision trees deliver 74.44% accuracy and 75.30%. Overall algorithms that are assessed giving accuracy below 90%. The features extraction that is based only on the time domain is not enough to spot distinction especially for signal that has a quite similar pattern, although it is a different class. In order to achieve more than 90% accuracy deep convolution neural network could be proposed as a future works.

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On the normalisation and mapping of influence lines

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Mechanical Systems and Signal Processing 2025年 237卷

作者： Alan J. Ferguson David Hester Farhad Huseynov Chul-Woo Kim James Brownjohn Roger Woods Lawrence A. Bull School of Natural and Built Environment Queen’s University Belfast Belfast BT9 5AG UK Department of Engineering University of Cambridge Cambridge CB3 0FA UK Department of Civil and Earth Resources Engineering Kyoto University Kyoto 615-8540 Japan Vibration Engineering Section University of Exeter Exeter EX5 2FN UK School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast BT9 5AG UK School of Mathematics and Statistics University of Glasgow Glasgow G12 8SQ UK

Bridges are vital components of transportation infrastructure, necessitating effective management of structural conditions to ensure safety and cost-effectiveness. Structural health monitoring (SHM) systems, utilising sensor data, offer a promising approach to tracking structural condition changes. By exploiting the increasing availability of structural information as a result of this activity, population-based SHM (PBSHM) aims to enhance approaches for practically managing structures by utilising the similarities between structures within a population to permit knowledge transfer between different population members. Influence lines have proven insightful for bridge condition assessment but are typically limited to individual structures and often rely on pre-damage baselines, which are unavailable for structures not instrumented and tested before damage or deterioration occurs, a common scenario on older structures and even newer ones. To address these limitations, we propose a population-based bridge condition assessment methodology that utilises normalised influence lines, where the resulting non-dimensional functions permit comparisons across different bridges, alleviating the requirement for repeated load testing. The originality of this approach lies in the fact that normalised influence lines are independent of specific material and geometry properties, which enables the creation of transformed influence lines (via simple parametric maps) for comparing varying sensor locations and structural responses across bridges. For SHM researchers and practitioners alike, the significance of this approach lies in its potential to address a gap in current influence line work by systematically facilitating transfer learning between structures, thus providing the potential to unearth patterns that individual analyses may miss. Our method is validated using experimental case studies at both laboratory scale, with known damage states, and full scale, demonstrating its effect

关键词： Bridge influence lines Bridge condition assessment Bridge structural health monitoring Population-based structural health monitoring Domain adaptation Transfer learning

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Multiscale modeling algorithm for core images

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Physical Review E 2020年第5期101卷 053303-053303页

作者： Zhengji Li Xiaohai He Qizhi Teng Honggang Chen College of Electronics and Information Engineering Sichuan University Chengdu 610065 China College of Computer Science and Technology Jincheng College of Sichuan University Chengdu 610065 China Key Laboratory of Wireless Power Transmission of Ministry of Education No. 24 South Section 1 1st Ring Road Chengdu Sichuan 610065 People's Republic of China

Computed tomography (CT) images of large core samples acquired by imaging equipment are insufficiently clear and ineffectively describe the tiny pore structure; conversely, images of small core samples are insufficiently globally representative. To alleviate these challenges, the idea of a super-resolution reconstruction algorithm is combined with that of a three-dimensional core reconstruction algorithm, and a multiscale core CT image fusion reconstruction algorithm is proposed. To obtain sufficient image quality with high resolution, a large-scale core image is used to provide global feature information as well as information regarding the basic morphological structure of a large-scale pore and particle. Then the texture pattern and the tiny pore distribution information of a small-scale core image is used to refine the coarse large-scale core image. A blind image quality assessment is utilized to estimate the degradation model of core images at different scales. A multilevel pattern mapping dictionary containing local binary patterns is designed to speed up the pattern matching procedure, and an adaptive weighted reconstruction algorithm is designed to reduce the blockiness. With our method, images of the same core at different scales were successfully fused. The proposed algorithm is extensively tested on microstructures of different rock samples; all cases of the reconstructed results and those of the actual sample were found to be in good agreement with each other. The final reconstructed image contains both large-scale and small-scale information that can provide a better understanding of the core samples and inform the accurate calculation of parameters.

关键词： Classical statistical mechanics Pattern formation Disordered systems Data analysis Multiscale modeling Statistical methods X-ray imaging

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Development of a Method for Compliance Detection in Wearable Sensors

Development of a Method for Compliance Detection in Wearable...

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Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Siavash Esfandiari Fard Tonmoy Ghosh Delwar Hossain Megan A McCrory Graham Thomas Janine Higgins Wenyan Jia Tom Baranowski Matilda Steiner-Asiedu Alex K. Anderson Mingui Sun Gary Frost Benny Lo Edward Sazonov Department of Electrical and Computer Engineering University of Alabama Tuscaloosa AL USA Department of Health Sciences Boston University Boston MA USA Psychiatry and Human Behavior Warren Alpert Medical School of Brown University Providence RI USA Division of Endocrinology Metabolism and Diabetes University of Colorado Anschutz Medical Campus Aurora Colorado USA Department of Neurological Surgery University of Pittsburgh Pittsburgh PA USA Department of Pediatrics USDA/ARS Children's Nutrition Research Center Baylor College of Medicine Houston TX USA Department of Nutrition and Food Science University of Ghana Legon Ghana Department of Nutritional Sciences University of Georgia Athens GA USA Department of Metabolism Section for Nutrition Research Digestion and Reproduction University of Imperial College London London UK Department of Surgery and Cancer Hamlyn Centre Imperial College London London UK

One of the crucial elements in studies relying on wearable sensors for quantification of human activities (like physical activity or food intake) is the assessment of wear time (compliance). In this paper, we propose a novel method based on the Automatic Ingestion Monitor v2 (AIM-2), deployed for measuring nutrient and energy intake. The proposed method was developed using data from a study of 30 participants for two days each (US dataset) and tested with an independent dataset (Ghana dataset) on 10 households (30 Participants, 3 days for each, a total of 90 days). The signals from the accelerometer sensor of the AIM-2 were used to extract features and train the gradient-boosting tree classifier. To reduce the error in the classification of non-compliance in situations where the sensor changes its position with respect to gravity, a two-stage classifier followed by post-processing was introduced. Previously, we developed an offline compliance classifier, and this work aimed to develop a classifier for a cloud-based feedback system. The accuracy and F1-score of the developed two-phase classifier based on K-fold validation for the training and validation dataset were 95.37% and 96.93%, and for the Ghana dataset, were 95.86% and 92.56%, respectively, showing satisfactory performance results. The trained classifier can be deployed to monitor compliance with device wear in realtime applications. Clinical Relevance– Food Intake and physical activity studies can contribute to detecting, controlling, and even improving eating or physical activity-related problems, like obesity, diabetes, and eating planning. To ensure effective monitoring, compliance with the wearing of the device is crucial.

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Segmentation-guided Domain Adaptation and Data Harmonization of Multi-device Retinal Optical Coherence Tomography using Cycle-Consistent Generative Adversarial Networks

arXiv

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arXiv 2022年

作者： Chen, Shuo Ma, Da Lee, Sieun Yu, Timothy T.L. Xu, Gavin Lu, Donghuan Popuri, Karteek Ju, Myeong Jin Sarunic, Marinko V. Beg, Mirza Faisal School of Engineering Science Simon Fraser University BurnabyBC Canada Department of Internal Medicine Section of Gerontology and Geriatric Medicine Wake Forest University School of Medicine Winston-SalemNC United States Center for Biomedical Informatics Wake Forest School of Medicine Winston-SalemNC United States Alzheimer’s Disease Research Center Wake Forest School of Medicine Winston-SalemNC United States Mental Health & Clinical Neuroscience University of Nottingham Nottingham United Kingdom Precision Imaging Beacon University of Nottingham Nottingham United Kingdom Tencent Jarvis Lab. Shenzhen China Department of Computer Science Memorial University of Newfoundland St. John’sNL Canada School of Biomedical Engineering University of British Columbia BC Canada Department of Ophthalmology & Visual Sciences The University of British Columbia VancouverBC Canada Institute of Ophthalmology University College London London United Kingdom Department of Medical Physics and Biomedical Engineering University College London United Kingdom

Background: Medical images such as Optical Coherence Tomography (OCT) images acquired from different devices may show significantly different intensity profiles. An automatic segmentation model trained on images from one device may perform poorly when applied to images acquired using a different device, resulting in a lack of generalisability. This study aims to address this issue using domain adaptation methods improved by Cycle-Consistent Generative Adversarial Networks(CycleGAN), especially in cases when the ground-truth labels are only available in the source domain. Methods: A two-stage pipeline is proposed to generate segmentation in the target domain. The first stage involves the training of a state-of-the-art segmentation model in the source domain. The second stage aims to adapt the images from the target domain into the source domain. The adapted target domain images are segmented using the model in the first stage. Ablation tests were performed with a different integration of loss functions, and the statistical significance of these models is reported. Both the segmentation performance and the adapted image quality metrics are evaluated. Results: Regarding the segmentation Dice score, the proposed ssppg model achieves a significant improvement of 46.24% compared to no adaptation, and it reaches 87.4% of the upper limit of the segmentation performance. Moreover, the image quality metrics including the FID and KID score indicate that adapted images with better segmentation also have better image qualities. Conclusion: The proposed method demonstrates the effectiveness of segmentation-driven domain adaptation in retinal imaging processing. It reduces the labour cost of manual labelling, incorporates prior anatomic information to regulate and guide the domain adaptation, and provides insights into improving segmentation qualities in image domains without labels. © 2022, CC BY-NC-SA.

关键词： Optical tomography

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Estimation of Mobile Frequency Saturation: Traffic Volume and Frequency Resource Utilization Perspective

Estimation of Mobile Frequency Saturation: Traffic Volume an...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Taeho Kim Seungkeun Park Hyeyeon Kwon Young-Kuk Kim Dept. of Computer Science and Engineering Radio Resource Research Section Electronics and Telecommunications Research Institute(ETRI) Radio Resource Research Section Electronics and Telecommunications Research Institute(ETRI) Daejeon South Korea Dept. of Computer Science and Engineering Chungnam National University Daejeon South Korea

Although 5G service has started, it is predicted that 4G traffic will continue to increase. Thus, in order to provide smooth mobile communication services, continuous research should be conducted to determine the 4G mobile frequency is saturated. Until now, methods have been focused on estimating frequency saturation from the perspective of traffic volume or frequency efficiency. In this paper, we proposed to estimate the frequency saturation based on the relationship between the traffic volume and the RB utilization, unlike the conventional method.

关键词： Frequency estimation Quality of service Mathematical model Market research 5G mobile communication Time series analysis

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Designing a Multimodal Graph System to Support Non-Visual Interpretation of Graphical Information 1

Designing a Multimodal Graph System to Support Non-Visual In...

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1st International Conference computer science and engineering, IC2SE 2019

作者： Setiawan, Deni Priambodo, Bagus Desi Anasanti, Mila Hazidar, Al Hamidy Naf'An, Emil Masril, Mardhiah Handriani, Inge Kudr Nseaf, Asama Pratama Putra, Zico School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4FZ United Kingdom Faculty of Computer Science Universitas Mercu Buana Jakarta11650 Indonesia Section of Genomics of Common Disease Department of Medicine Imperial College London LondonW12 0NN United Kingdom Institute of Visual Informatics Universiti Kebangsaan Malaysia Kuala Lumpur50300 Malaysia Faculty of Computer Science Universitas Putra Indonesia YPTK Padang Indonesia

While researchers have performed numerous studies to understand the human interpretation of visual graphs in reading, comprehending and interpreting displayed data;visually impaired (VI) users still face many challenges that prevent them from fully benefiting from these graphs. Thus, it influences their understanding of data visualization and in turn reduces their role in collaborating with their sighted colleagues in educational and working environments. We intend to develop a mobile application where visually impaired users can work together to build a collaborative graph that supported by data sonification in the mobile environment. The system properties were all tested by the task of identifying line trends in time series, which resulted in an accuracy of more than 80% for notes below 20 points. The usability testing has given result of 6.7 out 10 based on users' perception on the effectivity of the features. © Published under licence by IOP Publishing Ltd.

关键词： Data visualization

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Automated coding of under-studied medical concept domains: Linking physical activity reports to the international classification of functioning, disability, and health

arXiv

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arXiv 2020年

作者： Newman-Griffis, Denis Fosler-Lussier, Eric Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Epidemiology & Biostatistics Section Rehabilitation Medicine Department National Institutes of Health Clinical Center BethesdaMD United States Department of Computer Science and Engineering Ohio State University ColumbusOH United States

Linking clinical narratives to standardized vocabularies and coding systems is a key component of unlocking the information in medical text for analysis. However, many domains of medical concepts, such as functional outcomes and social determinants of health, lack well-developed terminologies that can support effective coding of medical text. We present a framework for developing natural language processing (NLP) technologies for automated coding of medical information in under-studied domains, and demonstrate its applicability through a case study on physical mobility function. Mobility function is a component of many health measures, from post-acute care and surgical outcomes to chronic frailty and disability, and is represented as one domain of human activity in the International Classification of Functioning, Disability, and Health (ICF). However, mobility and other types of functional activity remain under-studied in the medical informatics literature, and neither the ICF nor commonly-used medical terminologies capture functional status terminology in practice. We investigated two data-driven paradigms, classification and candidate selection, to link narrative observations of mobility status to standardized ICF codes, using a dataset of clinical narratives from physical therapy encounters. Recent advances in language modeling and word embedding were used as features for established machine learning models and a novel deep learning approach, achieving a macroaveraged F-1 score of 84% on linking mobility activity reports to ICF codes. Both classification and candidate selection approaches present distinct strengths for automated coding in under-studied domains, and we highlight that the combination of (i) a small annotated data set;(ii) expert definitions of codes of interest;and (iii) a representative text corpus is sufficient to produce high-performing automated coding systems. This research has implications for continued development of language technologies to

关键词： Natural language processing systems

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Corrigendum to “A decision modeling approach for smart e-tourism data management applications based on spherical fuzzy rough environment” [Applied Soft Computing 143(2023) 110297]

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Applied Soft Computing 2023年 149卷

作者： R.T. Mohammed A.H. Alamoodi O.S. Albahri A.A. Zaidan H.A. AlSattar Uwe Aickelin A.S. Albahri B.B. Zaidan Amelia Ritahani Ismail R.Q. Malik Department of Computing Science Faculty of Science Komar University of Science and Technology (KUST) Sulaymaniyah Iraq Department of Computing and META Technology (FKMT) Universiti Pendidikan Sultan Idris Tanjung Malim 35900 Malaysia Department of Computer Science and Information Technology La Trobe University Melbourne VIC Australia Computer Techniques Engineering Department Mazaya University College Thi-Qar Nassiriya Iraq SP Jain School of Global Management Sydney Australia Department of Business Administration College of Administrative Science The University of Mashreq 10021 Baghdad Iraq School of Computing and Information Systems University of Melbourne 700 Swanston Street Victoria 3010 Australia Iraqi Commission for Computers and Informatics (ICCI) Baghdad Iraq Department of Computer Technology Engineering College of Information Technology Imam Ja'afar Al-Sadiq University Baghdad Iraq Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin 64002 Taiwan Kulliyyah of Information and Communication Technology (KICT) International Islamic University Malaysia Kuala Lumpur Malaysia Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq

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Retraction notice to “New impressive performances for the analytical solutions to the (1+1)-dimensional van der-waals gas system against its numerical solutions” [Res. Phys. 51 (2023) 106667]

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Results in Physics 2025年 72卷

作者： Emad H.M. Zahran Hijaz Ahmad Sameh Askar Dilber Uzun Ozsahin Departments of Basic Science Benha University Faculty of Engineering Shubra Egypt Section of Mathematics International Telematic University Uninettuno Corso Vittorio Emanuele II 39 00186 Roma Italy Near East University Operational Research Center in Healthcare Nicosia PC: 99138 TRNC Mersin 10 Turkey Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Statistics and Operations Research College of Science King Saud University P.O. Box 2455 Riyadh 11451 Saudi Arabia Department of Medical Diagnostic Imaging College of Health Science University of Sharjah Sharjah United Arab Emirates Research Institute for Medical and Health Sciences University of Sharjah Sharjah United Arab Emirates

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