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7,465 results on '"Liu, Shuo"'

276. Fitbeat: COVID-19 Estimation based on Wristband Heart Rate

Author

Liu, Shuo, Han, Jing, Puyal, Estela Laporta, Kontaxis, Spyridon, Sun, Shaoxiong, Locatelli, Patrick, Dineley, Judith, Pokorny, Florian B., Costa, Gloria Dalla, Leocan, Letizia, Guerrero, Ana Isabel, Nos, Carlos, Zabalza, Ana, Sørensen, Per Soelberg, Buron, Mathias, Magyari, Melinda, Ranjan, Yatharth, Rashid, Zulqarnain, Conde, Pauline, Stewart, Callum, Folarin, Amos A, Dobson, Richard JB, Bailón, Raquel, Vairavan, Srinivasan, Cummins, Nicholas, Narayan, Vaibhav A, Hotopf, Matthew, Comi, Giancarlo, and Schuller, Björn

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning
Abstract

This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilises data from the ongoing EU IMI RADAR-CNS research project that is investigating the feasibility of wearable devices and smart phones to monitor individuals with multiple sclerosis (MS), depression or epilepsy. Aspart of the project protocol, heart-rate data was collected from participants using a Fitbit wristband. The presence of COVID-19 in the cohort in this work was either confirmed through a positive swab test, or inferred through the self-reporting of a combination of symptoms including fever, respiratory symptoms, loss of smell or taste, tiredness and gastrointestinal symptoms. Experimental results indicate that our proposed contrastive convolutional auto-encoder (contrastive CAE), i. e., a combined architecture of an auto-encoder and contrastive loss, outperforms a conventional convolutional neural network (CNN), as well as a convolutional auto-encoder (CAE) without using contrastive loss. Our final contrastive CAE achieves 95.3% unweighted average recall, 86.4% precision, anF1 measure of 88.2%, a sensitivity of 100% and a specificity of 90.6% on a testset of 19 participants with MS who reported symptoms of COVID-19. Each of these participants was paired with a participant with MS with no COVID-19 symptoms., Comment: 34pages, 4figures

Published
2021

277. Peripheral blood leucocyte telomere length is associated with progression of interstitial lung disease in systemic sclerosis

Author

Liu, Shuo, Chung, Melody P, Ley, Brett, French, Sarah, Elicker, Brett M, Fiorentino, David F, Chung, Lorinda S, Boin, Francesco, and Wolters, Paul J

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Lung, Scleroderma, Rare Diseases, Clinical Research, Autoimmune Disease, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Respiratory, Humans, Idiopathic Pulmonary Fibrosis, Lung Diseases, Interstitial, Retrospective Studies, Scleroderma, Systemic, Telomere, systemic disease and lungs, interstitial fibrosis, rare lung diseases, connective tissue disease associated lung disease, Respiratory System, Cardiovascular medicine and haematology, Clinical sciences
Abstract

BackgroundPeripheral blood leucocyte telomere length (PBL-TL) is associated with outcomes in patients with idiopathic pulmonary fibrosis. Whether PBL-TL is associated with progression of systemic sclerosis-associated interstitial lung disease (SSc-ILD) is unknown.MethodsA retrospective observational cohort study was performed using prospectively collected data from 213 patients with SSc followed at the University of California San Francisco (UCSF) Scleroderma Center. PBL-TL was measured by quantitative PCR of DNA isolated from peripheral blood. Associations between PBL-TL and pulmonary function test trends in patients with SSc-ILD were assessed by longitudinal analysis using Generalised Linear Mixed Models. Findings were validated in a cohort of 61 patients with SSc-ILD enrolled in the Stanford University Scleroderma Center database.ResultsPatients with UCSF SSc with ILD were found to have shorter PBL-TL compared with those without ILD (6554±671 base pairs (bp) vs 6782±698 bp, p=0.01). Shorter PBL-TL was associated with the presence of ILD (adjusted OR 2.1 per 1000 bp TL decrease, 95% CI [1.25 to 3.70], p=0.006). PBL-TL was shorter in patients with SSc-ILD lacking SSc-specific autoantibodies compared with seropositive subjects (6237±647 bp vs 6651±653 bp, p=0.004). Shorter PBL-TL was associated with increased risk for lung function deterioration with an average of 67 mL greater loss in per year for every 1000 bp decrease in PBL-TL in the combined SSc-ILD cohorts (longitudinal analysis, adjusted model: 95% CI -104 mL to -33 mL, p

Published
2021

278. Approximate Byzantine Fault-Tolerance in Distributed Optimization

Author

Liu, Shuo, Gupta, Nirupam, and Vaidya, Nitin H.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

This paper considers the problem of Byzantine fault-tolerance in distributed multi-agent optimization. In this problem, each agent has a local cost function, and in the fault-free case, the goal is to design a distributed algorithm that allows all the agents to find a minimum point of all the agents' aggregate cost function. We consider a scenario where some agents might be Byzantine faulty that renders the original goal of computing a minimum point of all the agents' aggregate cost vacuous. A more reasonable objective for an algorithm in this scenario is to allow all the non-faulty agents to compute the minimum point of only the non-faulty agents' aggregate cost. Prior work shows that if there are up to $f$ (out of $n$) Byzantine agents then a minimum point of the non-faulty agents' aggregate cost can be computed exactly if and only if the non-faulty agents' costs satisfy a certain redundancy property called $2f$-redundancy. However, $2f$-redundancy is an ideal property that can be satisfied only in systems free from noise or uncertainties, which can make the goal of exact fault-tolerance unachievable in some applications. Thus, we introduce the notion of $(f,\epsilon)$-resilience, a generalization of exact fault-tolerance wherein the objective is to find an approximate minimum point of the non-faulty aggregate cost, with $\epsilon$ accuracy. This approximate fault-tolerance can be achieved under a weaker condition that is easier to satisfy in practice, compared to $2f$-redundancy. We obtain necessary and sufficient conditions for achieving $(f,\epsilon)$-resilience characterizing the correlation between relaxation in redundancy and approximation in resilience. In case when the agents' cost functions are differentiable, we obtain conditions for $(f,\epsilon)$-resilience of the distributed gradient-descent method when equipped with robust gradient aggregation., Comment: 43 pages, 5 figures, and 1 table. The report is an important extension to prior work https://dl.acm.org/doi/abs/10.1145/3382734.3405748, and arXiv:2003.09675; Added an alternative result with a better analysis

Published
2021

280. Design and Analysis of Co-axial Twin-Propeller Trans-media Vehicle

Author

Du, Chihao, Wang, Tao, Liu, Shuo, Zhou, Shanmin, Cai, Yong, Yu, Zijing, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Huayong, editor, Liu, Honghai, editor, Zou, Jun, editor, Yin, Zhouping, editor, Liu, Lianqing, editor, Yang, Geng, editor, Ouyang, Xiaoping, editor, and Wang, Zhiyong, editor

Published
2023
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281. Violation Detection Method Based on Improved YOLOv5s

Author

Liu, Shuo, Liang, Yu-chen, Ma, Xiao-cheng, Guo, Yun-qi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Jia, Yingmin, editor, Zhang, Weicun, editor, Fu, Yongling, editor, and Wang, Jiqiang, editor

Published
2023
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284. The False Utopia of VR Gaming: The Mind and Body Under VR Video Games

Author

Liu, Shuo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Marcus, Aaron, editor, Rosenzweig, Elizabeth, editor, and Soares, Marcelo M., editor

Published
2023
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285. Exploration on the Fusion of Artificial Intelligence and Blockchain

Author

Qu, Chongxiao, Jin, Lei, Zhang, Yongjin, Fan, Changjun, Chu, Jinqi, Liu, Shuo, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Kadry, Seifedine, editor, Yan, Yingchen, editor, and Xia, Junjie, editor

Published
2023
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287. Research on the Impact of Manufacturing Digital Technology Transfer on Knowledge Flow Based on Multilayer Regression : The Mediating Effect of Digital Innovation Ecosystem

Author

Wu, Jieru, Liu, Shuo, Wang, Yan, Liu, Yu, Li, Kan, Editor-in-Chief, Li, Qingyong, Associate Editor, Fournier-Viger, Philippe, Series Editor, Hong, Wei-Chiang, Series Editor, Liang, Xun, Series Editor, Wang, Long, Series Editor, Xu, Xuesong, Series Editor, Khan, Syed Abdul Rehman, editor, Jhanjhi, Noor Zaman, editor, and Li, Hongbo, editor

Published
2023
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289. Research on the Impact of Manufacturing Digital Innovation Resources on Knowledge Creation Based on SmartPlS: The Mediation Effect of Digital Innovation Ecosystem

Author

Wang, Yan, Liu, Shuo, Liu, Yu, Wu, Jieru, Li, Kan, Editor-in-Chief, Li, Qingyong, Associate Editor, Fournier-Viger, Philippe, Series Editor, Hong, Wei-Chiang, Series Editor, Liang, Xun, Series Editor, Wang, Long, Series Editor, Xu, Xuesong, Series Editor, Khan, Syed Abdul Rehman, editor, Jhanjhi, Noor Zaman, editor, and Li, Hongbo, editor

Published
2023
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294. Long-term exposure to ambient air pollution and risk of leukemia and lymphoma in a pooled European cohort

Author

Taj, Tahir, Chen, Jie, Rodopoulou, Sophia, Strak, Maciej, de Hoogh, Kees, Poulsen, Aslak Harbo, Andersen, Zorana J., Bellander, Tom, Brandt, Jørgen, Zitt, Emanuel, Fecht, Daniela, Forastiere, Francesco, Gulliver, John, Hertel, Ole, Hoffmann, Barbara, Hvidtfeldt, Ulla Arthur, Jørgensen, Jeanette T., Katsouyanni, Klea, Ketzel, Matthias, Lager, Anton, Leander, Karin, Liu, Shuo, Ljungman, Petter, Severi, Gianluca, Besson, Caroline, Magnusson, Patrik K.E., Nagel, Gabriele, Pershagen, Göran, Peters, Annette, Rizzuto, Debora, Samoli, Evangelia, Sørensen, Mette, Stafoggia, Massimo, Tjønneland, Anne, Weinmayr, Gudrun, Wolf, Kathrin, Brunekreef, Bert, Hoek, Gerard, and Raaschou-Nielsen, Ole

Published
2024
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