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2,765 results on '"Gu, Yue"'

63. Progressive Learning for Stabilizing Label Selection in Speech Separation with Mapping-based Method

Author

Gao, Chenyang, Gu, Yue, and Marsic, Ivan

Subjects
Computer Science - Sound, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Speech separation has been studied in time domain because of lower latency and higher performance compared to time-frequency domain. The masking-based method has been mostly used in time domain, and the other common method (mapping-based) has been inadequately studied. We investigate the use of the mapping-based method in the time domain and show that it can perform better on a large training set than the masking-based method. We also investigate the frequent label-switching problem in permutation invariant training (PIT), which results in suboptimal training because the labels selected by PIT differ across training epochs. Our experiment results showed that PIT works well in a shallow separation model, and the label switching occurs for a deeper model. We inferred that layer decoupling may be the reason for the frequent label switching. Therefore, we propose a training strategy based on progressive learning. This approach significantly reduced inconsistent label assignment without added computational complexity or training corpus. By combining this training strategy with the mapping-based method, we significantly improved the separation performance compared to the baseline., Comment: Submitted to Interspeech 2022

Published
2021

64. Three-dimensional transistor arrays for intra- and inter-cellular recording

Author

Gu, Yue, Wang, Chunfeng, Kim, Namheon, Zhang, Jingxin, Wang, Tsui Min, Stowe, Jennifer, Nasiri, Rohollah, Li, Jinfeng, Zhang, Daibo, Yang, Albert, Hsu, Leo Huan-Hsuan, Dai, Xiaochuan, Mu, Jing, Liu, Zheyuan, Lin, Muyang, Li, Weixin, Wang, Chonghe, Gong, Hua, Chen, Yimu, Lei, Yusheng, Hu, Hongjie, Li, Yang, Zhang, Lin, Huang, Zhenlong, Zhang, Xingcai, Ahadian, Samad, Banik, Pooja, Zhang, Liangfang, Jiang, Xiaocheng, Burke, Peter J, Khademhosseini, Ali, McCulloch, Andrew D, and Xu, Sheng

Subjects
Cardiovascular, Bioengineering, Underpinning research, 1.1 Normal biological development and functioning, Action Potentials, Cell Communication, Electrophysiological Phenomena, Myocytes, Cardiac, Nanoscience & Nanotechnology
Abstract

Electrical impulse generation and its conduction within cells or cellular networks are the cornerstone of electrophysiology. However, the advancement of the field is limited by sensing accuracy and the scalability of current recording technologies. Here we describe a scalable platform that enables accurate recording of transmembrane potentials in electrogenic cells. The platform employs a three-dimensional high-performance field-effect transistor array for minimally invasive cellular interfacing that produces faithful recordings, as validated by the gold standard patch clamp. Leveraging the high spatial and temporal resolutions of the field-effect transistors, we measured the intracellular signal conduction velocity of a cardiomyocyte to be 0.182 m s-1, which is about five times the intercellular velocity. We also demonstrate intracellular recordings in cardiac muscle tissue constructs and reveal the signal conduction paths. This platform could provide new capabilities in probing the electrical behaviours of single cells and cellular networks, which carries broad implications for understanding cellular physiology, pathology and cell-cell interactions.

Published
2022

65. Pressure-enhanced ferromagnetism in layered CrSiTe3 flakes

Author

Zhang, Cheng, Gu, Yue, Wang, Le, Huang, Lianglong, Fu, Ying, Liu, Cai, Wang, Shanmin, Mei, Jia-Wei, Zou, Xiaolong, and Dai, Jun-Feng

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

The research on van der Waals (vdW) layered ferromagnets have promoted the development of nanoscale spintronics and applications. However, low-temperature ferromagnetic properties of these materials greatly hinder their applications. Here, we report pressure-enhanced ferromagnetic behaviours in layered CrSiTe3 flakes revealed by high-pressure magnetic circular dichroism (MCD) measurement. At ambient pressure, CrSiTe3 undergoes a paramagnetic-to-ferromagnetic phase transition at 32.8 K, with a negligible hysteresis loop, indicating a soft ferromagnetic behaviour. Under 4.6 GPa pressure, the soft ferromagnet changes into hard one, signalled by a rectangular hysteretic loop with remnant magnetization at zero field. Interestingly, with further increasing pressure, the coercive field (H_c) dramatically increases from 0.02 T at 4.6 GPa to 0.17 T at 7.8 GPa, and the Curie temperature (T_c^h: the temperature for closing the hysteresis loop) also increases from ~36 K at 4.6 GPa to ~138 K at 7.8 GPa. The influences of pressure on exchange interactions are further investigated by density functional theory calculations, which reveal that the in-plane nearest-neighbor exchange interaction and magneto-crystalline anisotropy increase simultaneously as pressure increases, leading to increased H_c and T_c^h in experiments. The effective interaction between magnetic couplings and external pressure offers new opportunities for both searching room-temperature layered ferromagnets and designing pressure-sensitive magnetic functional devices.

Published
2021
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72. A photoacoustic patch for three-dimensional imaging of hemoglobin and core temperature

Author

Gao, Xiaoxiang, Chen, Xiangjun, Hu, Hongjie, Wang, Xinyu, Yue, Wentong, Mu, Jing, Lou, Zhiyuan, Zhang, Ruiqi, Shi, Keren, Chen, Xue, Lin, Muyang, Qi, Baiyan, Zhou, Sai, Lu, Chengchangfeng, Gu, Yue, Yang, Xinyi, Ding, Hong, Zhu, Yangzhi, Huang, Hao, Ma, Yuxiang, Li, Mohan, Mishra, Aditya, Wang, Joseph, and Xu, Sheng

Subjects
Nanotechnology, Bioengineering, Humans, Imaging, Three-Dimensional, Temperature, Transducers, Lasers, Hemoglobins
Abstract

Electronic patches, based on various mechanisms, allow continuous and noninvasive monitoring of biomolecules on the skin surface. However, to date, such devices are unable to sense biomolecules in deep tissues, which have a stronger and faster correlation with the human physiological status than those on the skin surface. Here, we demonstrate a photoacoustic patch for three-dimensional (3D) mapping of hemoglobin in deep tissues. This photoacoustic patch integrates an array of ultrasonic transducers and vertical-cavity surface-emitting laser (VCSEL) diodes on a common soft substrate. The high-power VCSEL diodes can generate laser pulses that penetrate >2 cm into biological tissues and activate hemoglobin molecules to generate acoustic waves, which can be collected by the transducers for 3D imaging of the hemoglobin with a high spatial resolution. Additionally, the photoacoustic signal amplitude and temperature have a linear relationship, which allows 3D mapping of core temperatures with high accuracy and fast response. With access to biomolecules in deep tissues, this technology adds unprecedented capabilities to wearable electronics and thus holds significant implications for various applications in both basic research and clinical practice.

Published
2022

73. Optimization Strategy for Residential Heating Based on Model Predictive Control

Author

Jia, Zhiwei, Gu, Yue, Li, Yanxue, 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, Park, Ji Su, editor, Yang, Laurence T., editor, Pan, Yi, editor, and Park, Jong Hyuk, editor

Published
2023
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85. Recurrent Distillation based Crowd Counting

Author

Gu, Yue and Liu, Wenxi

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In recent years, with the progress of deep learning technologies, crowd counting has been rapidly developed. In this work, we propose a simple yet effective crowd counting framework that is able to achieve the state-of-the-art performance on various crowded scenes. In particular, we first introduce a perspective-aware density map generation method that is able to produce ground-truth density maps from point annotations to train crowd counting model to accomplish superior performance than prior density map generation techniques. Besides, leveraging our density map generation method, we propose an iterative distillation algorithm to progressively enhance our model with identical network structures, without significantly sacrificing the dimension of the output density maps. In experiments, we demonstrate that, with our simple convolutional neural network architecture strengthened by our proposed training algorithm, our model is able to outperform or be comparable with the state-of-the-art methods. Furthermore, we also evaluate our density map generation approach and distillation algorithm in ablation studies.

Published
2020

88. Turing Learning : advances and applications

Author

Gu, Yue, Gross, Roderich, and Lawrence, Neil

Abstract

Turing Learning is the family of algorithms where models and discriminators are generated in a competitive setting. This thesis concerns the coevolutionary framework of Turing Learning and investigates the advances for improved model accuracy and the applications in robotic systems. Advances proposed in this thesis are as follows: an interactive approach to enable the discriminator to genuinely influence the data sampling process; a hybrid formulation to combine the benefits of the interactive discriminator in improving model accuracy and the advantages of the passive discriminator for reducing training cost; an exclusiveness reward mechanism to promote candidates with the exclusive performance during the coevolutionary process. Applications presented in this thesis are as follows: an approach for a mobile robotic agent to automatically infer its sensor configuration; an approach for the robot agent to automatically calibrate its sensor reading; a novel approach to infer swarm behaviours from their effects on the environment. The interactive approach has been validated in the inference of sensor configuration and calibration model, leading to the self-modelling/self-discovery process of robotic agents. Results suggest an improved model accuracy with the interactive approach in both cases, compared with the passive approach. The hybrid formulation and the exclusiveness reward mechanism have been demonstrated in the inference of the calibration model. Results show that almost half of the training cost can be reduced without a decrease in model accuracy by applying the hybrid formulation. The novel reward mechanism can accelerate the convergence without a decrease in model accuracy. The indirect way of inferring swarm behaviours requires a small amount of training and reveals novel behavioural controllers for individual robots.

Published
2021

98. Risk assessment of girth welds of high-grade steel pipelines based on fuzzy theory and index method

Author

XIE Qiuju, GUO Yanbao, ZHANG Min, and GU Yue

Subjects
high-grade steel pipelines, girth welds, fault tree, fuzzy evaluation method, index method, risk assessment, Oils, fats, and waxes, TP670-699, Gas industry, TP751-762
Abstract

Among the failure modes of high-grade steel pipelines, cracking or leakage failures of girth welds account for nearly 1/3 in total. Thus, different assessment methods are adopted for various types of indicators, and a risk assessment method based on comprehensive fuzzy theory and index method was proposed. Specifically, the non-quantifiable assessment indicators were obtained by the fault tree method and the maximum membership degree was calculated by combining the fuzzy assessment and the entropy weight method. On this basis, the quantifiable assessment indicators were determined according to the requirements of relevant standards, and their risk values were calculated by the index method. Finally, a risk assessment matrix was established according to the maximum membership degree and risk values obtained with the index method, so as to determine the risk level of girth welds. Herein, risk assessment was performed for the girth welds in a section of Myanmar-China Natural Gas Pipeline with the proposed method. According to the results, the failure risk of girth welds in the pipeline section is mainly determined by the non-quantifiable indicators and the pipeline section is at high risk. Definitely, poor implementation of pipeline maintenance plan, unacceptable qualification of welders, unclear welding procedure specification and other objective factors are the main causes of girth weld failure, and the assessment results are consistent with the field accident reports. Generally, the proposed method supplements and improves the risk assessment system for girth welds of high-grade steel pipelines, and could provide theoretical reference for solving the problem of girth weld failure in high-grade steel pipelines.

Published
2022
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