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2,999 results on '"Lin, Ke"'

59. Alterations of pathogen transmission patterns and attenuated immune stimulation might be the cause of increased adult respiratory infections cases in 2023, results from a multi-center study in mainland China

Author

Ai, Jingwen, Wang, Hongyu, Zhang, Haocheng, Song, Jieyu, Zhang, Yi, Lin, Ke, Qu, Lihong, Zhang, Yanliang, Zhang, Shiliang, Xiang, Qiyun, Geng, Jiawei, Jin, Guangxia, Song, Wei, Zhang, Liaoyun, Hu, Xiaoli, Liu, Hongyan, Yuan, Guanmin, Jiang, Ning, Zhou, Yang, Xu, Yuanyuan, Ying, Jun, Wu, Jiqin, Xing, Yajiao, Fang, Kai, Yan, Hui, Chen, Feiying, Xu, Tailin, Wang, Sen, Qian, Zhaohui, and Zhang, Wenhong

Published
2024
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75. Discovering giant magnetoelasticity in soft matter for electronic textiles.

Author

Chen, Guorui, Zhao, Xun, Andalib, Sahar, Xu, Jing, Zhou, Yihao, Tat, Trinny, Lin, Ke, and Chen, Jun

Subjects
Bioengineering, Affordable and Clean Energy
Abstract

We discovered a giant magnetoelasticity in soft matter with up to 5-fold enhancement of magnetomechanical coupling factors compared to that of rigid metal alloys without an externally applied magnetic field. A wavy chain analytical model based on the magnetic dipole-dipole interaction and demagnetizing field was established, fitting well to the experimental observation. To explore its potentials in electronic textiles, we coupled it with magnetic induction to invent a textile magnetoelastic generator (MEG), a new working mechanism for biomechanical energy conversion, featuring an intrinsic waterproofness, an ultralow internal impedance of approximately 20 Ω, and a high short-circuit current density of 1.37 mA/cm2, which is about four orders of magnitude higher than that of other textile generator counterparts. Meanwhile, assisted by machine learning, the textile MEG could continuously monitor the respiratory activities on heavily perspiring skin without any encapsulation, allowing a timely diagnosis of the respiration abnormalities in a self-powered manner. We foresee that this discovery can be extended to wide-range soft-matter systems, emerging as a compelling approach to develop electronic textiles for energy, sensing, and therapeutic applications.

Published
2021

78. A portable triboelectric spirometer for wireless pulmonary function monitoring

Author

Xu, Qinghao, Fang, Yunsheng, Jing, Qingshen, Hu, Ning, Lin, Ke, Pan, Yifan, Xu, Lin, Gao, Haiqi, Yuan, Ming, Chu, Liang, Ma, Yanwen, Xie, Yannan, Chen, Jun, and Wang, Lianhui

Subjects
Engineering, Nanotechnology, Biomedical Engineering, Rare Diseases, Bioengineering, Clinical Research, Lung, Rehabilitation, Respiratory, Good Health and Well Being, Biosensing Techniques, COVID-19, Humans, SARS-CoV-2, Spirometry, Vital Capacity, Self-powered sensors, Triboelectric nanogenerators, Spirometers, Pulmonary function tests, Analytical Chemistry, Bioinformatics, Analytical chemistry, Biomedical engineering
Abstract

Coronavirus disease 2019 (COVID-19) as a severe acute respiratory syndrome infection has spread rapidly across the world since its emergence in 2019 and drastically altered our way of life. Patients who have recovered from COVID-19 may still face persisting respiratory damage from the virus, necessitating long-term supervision after discharge to closely assess pulmonary function during rehabilitation. Therefore, developing portable spirometers for pulmonary function tests is of great significance for convenient home-based monitoring during recovery. Here, we propose a wireless, portable pulmonary function monitor for rehabilitation care after COVID-19. It is composed of a breath-to-electrical (BTE) sensor, a signal processing circuit, and a Bluetooth communication unit. The BTE sensor, with a compact size and light weight of 2.5 cm3 and 1.8 g respectively, is capable of converting respiratory biomechanical motions into considerable electrical signals. The output signal stability is greater than 93% under 35%-81% humidity, which allows for ideal expiration airflow sensing. Through a wireless communication circuit system, the signals can be received by a mobile terminal and processed into important physiological parameters, such as forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC). The FEV1/FVC ratio is then calculated to further evaluate pulmonary function of testers. Through these measurement methods, the acquired pulmonary function parameters are shown to exhibit high accuracy (>97%) in comparison to a commercial spirometer. The practical design of the self-powered flow spirometer presents a low-cost and convenient method for pulmonary function monitoring during rehabilitation from COVID-19.

Published
2021

82. Evaluation of subgrid scale models in turbulent large eddy simulations of pumpjet propulsor

Author

Lin Ke, Jinming Ye, and Wei He

Subjects
Pumpjet propulsor, Large eddy simulation, Subgrid scale model, Unsteady load, Turbulent fluctuating scale, Ocean engineering, TC1501-1800, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

To assess the effectiveness of subgrid scale (SGS) models on the prediction results of unsteady loads and turbulent fluctuation of pumpjet propulsors equipped with both front and rear stators, a pumpjet propulsor computational model with attached parts at the model scale is developed using a fully structured mesh, and large eddy simulations are conducted. The computational results of the different SGS models are compared based on five aspects: open water characteristics, turbulence parameters, incoming turbulence spectrum, vortex structure, and fluctuating pressure. Their results are also compared with the experimental values, and the correlation between the internal flow characteristics of the pumpjet propulsor and the turbulent fluctuation is analyzed. According to the results, as regards the prediction of the open water performance of the pumpjet propulsor containing both front and rear stators, the overall trend obtained by the three subgrid models is similar, and the error between the values predicted by the SL model and the experimental ones is the smallest. At the same mesh level, the turbulent fluctuating scale obtained by the SL model is larger than that obtained by the WALE and DSL models, and the turbulent time scale obtained by the DSL model has the smallest fluctuation in the circumferential direction. Among the three SGS models, the turbulent fluctuating scale of the SL model is larger than those of the WALE and DSL models. The SL model exhibits the largest energy dissipation among the three SGS models, followed by the DSL model, while that of the WALE model is the smallest. In the WALE model, the leakage vortex at the top of the blade is the longest, followed by the DSL model, while it is the shortest in the SL model. In the WALE and DSL models, the fluctuating load fluctuates more in the transition region from the middle section to the trailing edge of the blade.

Published
2024
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83. Optimally Combining Classifiers for Semi-Supervised Learning

Author

Wang, Zhiguo, Yang, Liusha, Yin, Feng, Lin, Ke, Shi, Qingjiang, and Luo, Zhi-Quan

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

This paper considers semi-supervised learning for tabular data. It is widely known that Xgboost based on tree model works well on the heterogeneous features while transductive support vector machine can exploit the low density separation assumption. However, little work has been done to combine them together for the end-to-end semi-supervised learning. In this paper, we find these two methods have complementary properties and larger diversity, which motivates us to propose a new semi-supervised learning method that is able to adaptively combine the strengths of Xgboost and transductive support vector machine. Instead of the majority vote rule, an optimization problem in terms of ensemble weight is established, which helps to obtain more accurate pseudo labels for unlabeled data. The experimental results on the UCI data sets and real commercial data set demonstrate the superior classification performance of our method over the five state-of-the-art algorithms improving test accuracy by about $3\%-4\%$. The partial code can be found at https://github.com/hav-cam-mit/CTO.

Published
2020

84. Multi-modal Feature Fusion with Feature Attention for VATEX Captioning Challenge 2020

Author

Lin, Ke, Gan, Zhuoxin, and Wang, Liwei

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

This report describes our model for VATEX Captioning Challenge 2020. First, to gather information from multiple domains, we extract motion, appearance, semantic and audio features. Then we design a feature attention module to attend on different feature when decoding. We apply two types of decoders, top-down and X-LAN and ensemble these models to get the final result. The proposed method outperforms official baseline with a significant gap. We achieve 76.0 CIDEr and 50.0 CIDEr on English and Chinese private test set. We rank 2nd on both English and Chinese private test leaderboard.

Published
2020

85. Exploration-efficient Deep Reinforcement Learning with Demonstration Guidance for Robot Control

Author

Lin, Ke, Gong, Liang, Li, Xudong, Sun, Te, Chen, Binhao, Liu, Chengliang, Zhang, Zhengfeng, Pu, Jian, and Zhang, Junping

Subjects
Computer Science - Robotics
Abstract

Although deep reinforcement learning (DRL) algorithms have made important achievements in many control tasks, they still suffer from the problems of sample inefficiency and unstable training process, which are usually caused by sparse rewards. Recently, some reinforcement learning from demonstration (RLfD) methods have shown to be promising in overcoming these problems. However, they usually require considerable demonstrations. In order to tackle these challenges, on the basis of the SAC algorithm we propose a sample efficient DRL-EG (DRL with efficient guidance) algorithm, in which a discriminator D(s) and a guider G(s) are modeled by a small number of expert demonstrations. The discriminator will determine the appropriate guidance states and the guider will guide agents to better exploration in the training phase. Empirical evaluation results from several continuous control tasks verify the effectiveness and performance improvements of our method over other RL and RLfD counterparts. Experiments results also show that DRL-EG can help the agent to escape from a local optimum.

Published
2020

88. Association of hepatitis B virus DNA levels with efficacy and safety outcomes in patients with hepatitis B virus-associated advanced hepatocellular carcinoma receiving tyrosine kinase inhibitor plus anti-PD-1 antibody: a multicenter propensity-matched study

Author

Chen, Qing-Jing, Lin, Kong-Ying, Lin, Zhi-Wen, Zhang, Bing, Liu, Ming-Qiang, Zhang, Jian-Xi, Huang, Qi-Zhen, Lin, Ke-Can, Zhang, Jin-Yu, Wei, Fu-Qun, You, Peng-Hui, You, Song, Jiang, Ya-Bin, Zhang, Hui, Cheng, Zhi-Qing, Wang, Cong-Ren, and Zeng, Yong-Yi

Published
2023
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98. On boundedness, gradient estimate, blow-up and convergence in a two-species and two-stimuli chemotaxis system with/without loop

Author

Lin, Ke and Xiang, Tian

Subjects
Mathematics - Analysis of PDEs, 35K59, 35B25, 35B44, 35K51
Abstract

In this work, we study dynamic properties of classical solutions to a homogenous Neumann initial-boundary value problem (IBVP) for a two-species and two-stimuli chemotaxis model with/without chemical signalling loop in a 2D bounded and smooth domain. We successfully detect the product of two species masses as a feature to determine boundedness, gradient estimates, blow-up and $W^{j,\infty}(1\leq j\leq 3)$-exponential convergence of classical solutions for the corresponding IBVP. More specifically, we first show generally a smallness on the product of both species masses, thus allowing one species mass to be suitably large, is sufficient to guarantee global boundedness, higher order gradient estimates and $W^{j,\infty}$-convergence with rates of convergence to constant equilibria; and then, in a special case, we detect a straight line of masses on which blow-up occurs for large product of masses. Our findings provide new understandings about the underlying model, and thus, improve and extend greatly the existing knowledge relevant to this model., Comment: 34 pages,To appear in Calc. Var. Partial Differential Equations

Published
2019

99. A Semantics-Assisted Video Captioning Model Trained with Scheduled Sampling

Author

Chen, Haoran, Lin, Ke, Maye, Alexander, Li, Jianming, and Hu, Xiaolin

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computation and Language
Abstract

Given the features of a video, recurrent neural networks can be used to automatically generate a caption for the video. Existing methods for video captioning have at least three limitations. First, semantic information has been widely applied to boost the performance of video captioning models, but existing networks often fail to provide meaningful semantic features. Second, the Teacher Forcing algorithm is often utilized to optimize video captioning models, but during training and inference, different strategies are applied to guide word generation, leading to poor performance. Third, current video captioning models are prone to generate relatively short captions that express video contents inappropriately. Toward resolving these three problems, we suggest three corresponding improvements. First of all, we propose a metric to compare the quality of semantic features, and utilize appropriate features as input for a semantic detection network (SDN) with adequate complexity in order to generate meaningful semantic features for videos. Then, we apply a scheduled sampling strategy that gradually transfers the training phase from a teacher-guided manner toward a more self-teaching manner. Finally, the ordinary logarithm probability loss function is leveraged by sentence length so that the inclination of generating short sentences is alleviated. Our model achieves better results than previous models on the YouTube2Text dataset and is competitive with the previous best model on the MSR-VTT dataset., Comment: 11 pages

Published
2019
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