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Ultra-conformable liquid metal particle monolayer on air/water interface for substrate-free E-tattoo

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npj Flexible Electronics 2023年第1期7卷 244-252页

作者： Fali Li Wenjuan Lei Yuwei Wang xingjian lu Shengbin Li Feng Xu Zidong He Jinyun Liu Huali Yang Yuanzhao Wu Jie Shang Yiwei Liu Run-Wei Li CAS Key Laboratory of Magnetic Materials and Devices Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo 315201P.R.China Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo 315201P.R.China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences100049 BeijingP.R.China

Gallium-based liquid metal has gained significant attention in conformal flexible electronics due to its high electrical conductivity,intrinsic deformability,and ***,the fabrication of large-area and highly uniform conformal liquid metal films remains *** self-assembly has emerged as a promising method,but traditional approaches face difficulties in assembling liquid metal ***,we realized the multi-size universal self-assembly(MUS)for liquid metal particles with various diameters(100 cm^(2))and high floating yield(50–90%).Moreover,the films can be conformally transferred onto complex surfaces such as human skin,allowing for the fabrication of substrate-free flexible *** eliminates interference from traditional substrate mechanical responses,making the liquid metal e-tattoo more user-friendly.

关键词： liquid floating conformal

Target tracking method based on the fusion of structured SVM and KCF algorithm

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Target tracking method based on the fusion of structured SVM...

A systematic framework of constructing surrogate model for slider track peeling strength prediction

第32届中国控制与决策会议

作者： Lei Huan Ma Jingqi lu xingjian Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology

Aiming at the drift problem of traditional KCF(kernelized correlation filter) target tracking algorithm caused by scale change and fast movement,a tracking method based on the fusion of structured SVM(support vector machine)and KCF algorithm is *** with the location and scale information of the tracking target,a structured SVM classification and prediction model is established to replace the ridge regression filtering method in KCF,train the samples collected by cyclic matrix,and solve the problem of not detailed *** addition,a search strategy optimization method based on tracking target motion features is proposed to reduce unnecessary search time in dense sampling,further improve the search efficiency and classifier accuracy of traditional KCF algorithm in dense sampling,improve its calculation efficiency and target tracking performance in complex *** can solve the problem that the target cannot be accurately tracked due to the drift caused by the change of target scale and fast *** show that the algorithm can locate the target area more accurately when the target scale changes and fast *** with the traditional KCF tracking algorithm,it has better performance and stronger robustness.

关键词： target tracking KCF structured SVM scale change drift

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Science China Technological Sciences 2024年第10期67卷 3261-3274页

作者： DONG xingjian CHEN Qian LIU WenBo WANG Dong PENG ZhiKe MENG Guang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University KEIPER Seating Mechanisms Co. Ltd. Department of Industrial Engineering and Management Shanghai Jiao Tong University

Peeling strength can comprehensively reflect slider track safety and is crucial in car seat safety assessments. Current methods for determining slider peeling strength are primarily physical testing and numerical simulation. However, these methods encounter the potential challenges of high costs and overlong time consumption which have not been adequately addressed. Therefore, the efficient and low-cost surrogate model emerges as a promising solution. Nevertheless, currently used surrogate models suffer from inefficiencies and complexity in data sampling, lack of robustness in local model predictions, and isolation between data sampling and model prediction. To overcome these challenges, this paper aims to set up a systematic framework for slider track peeling strength prediction, including sensitivity analysis, dataset sampling, and model prediction. Specifically, the interpretable linear regression is performed to identify the sensitivity of various geometric variables to peeling strength. Based on the variable sensitivity, a distance metric is constructed to measure the disparity of different variable groups. Then, the sparsity-targeted sampling(STS) is proposed to formulate a representative dataset. Finally, the sequentially selected local weighted linear regression(SLWLR) is designed to achieve accurate track peeling strength prediction. Additionally, a quantitative cost assessment of the supplementary dataset is proposed by utilizing the minimum adjacent sample distance as a mediator. Experimental results validate the efficacy of sequential selection and the weighting mechanism in enhancing localization ***, the proposed SLWLR method surpasses similar approaches and other common surrogate methods in terms of prediction performance and data quantity requirements, achieving an average absolute error of 3.3 kN in the simulated test dataset.

关键词： slider track peeling strength surrogate model sensitivity analysis data sampling local weighted linear regression

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Deep Neural Networks for Semantic Segmentation of lung Nodules

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Deep Neural Networks for Semantic Segmentation of Lung Nodul...

Low-frequency bandgap and vibration suppression mechanism of a novel square hierarchical honeycomb metamaterial

第40届中国控制会议

作者： Liangsheng Wu Chentong Li Jingqi Ma xingjian lu Huan Lei Institute of Intelligent Manufacturing GDAS

Segmentation of lung nodule from computed tomography(CT) images is of great importance for lung nodule *** order to improve the segmentation accuracy of lung nodules,a lot of research work has been *** two main challenges in segmentation of lung nodules are lung nodules have the similar characteristics as surrounding tissues and lung nodules are extremely unbalanced with the *** this study,we investigated the performance of U-Net to segment the lung nodules in CT *** imaging pre-process methods,image resizing and intensity normalization,are applied to alleviate the problem of small nodules in lung and improve the quality of training *** addition,to increase the diversity and variation of training data,we propose a fusion over-sampling method to augment the *** dice coefficient loss function was also introduced to solve the problem of imbalance distribution of positive and negative *** on the luNA 16 dataset demonstrate that this method can improve the performance of lung nodules segmentation network,which is better than the state-of-the-art methods in the aspect of lung nodules segmentation.

关键词： deep learning U-Net lung nodule segmentation

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Applied Mathematics and Mechanics(English Edition) 2024年第10期45卷 1841-1856页

作者： xingjian DONG Shuo WANG Anshuai WANG Liang WANG Zhaozhan ZHANG Yuanhao TIE Qingyu LIN Yongtao SUN State Key Laboratory of Mechanical Systems and Vibration Shanghai Jiao Tong University Department of Mechanics Tianjin University Tianjin Key Laboratory of Nonlinear Dynamics and Control Tianjin University School of Mechanical and Automotive Engineering Guangxi University of Science and Technology

The suppression of low-frequency vibration and noise has always been an important issue in a wide range of engineering applications. To address this concern,a novel square hierarchical honeycomb metamaterial capable of reducing low-frequency noise has been developed. By combining Bloch's theorem with the finite element method,the band structure is calculated. Numerical results indicate that this metamaterial can produce multiple low-frequency bandgaps within 500 Hz, with a bandgap ratio exceeding50%. The first bandgap spans from 169.57 Hz to 216.42 Hz. To reveal the formation mechanism of the bandgap, a vibrational mode analysis is performed. Numerical analysis demonstrates that the bandgap is attributed to the suppression of elastic wave propagation by the vibrations of the structure's two protruding corners and overall expansion vibrations. Additionally, detailed parametric analyses are conducted to investigate the effect of θ, i.e., the angle between the protruding corner of the structure and the horizontal direction, on the band structures and the total effective bandgap width. It is found that reducing θ is conducive to obtaining lower frequency bandgaps. The propagation characteristics of elastic waves in the structure are explored by the group velocity, phase velocity, and wave propagation direction. Finally, the transmission characteristics of a finite periodic structure are investigated experimentally. The results indicate significant acceleration amplitude attenuation within the bandgap range, confirming the structure's excellent low-frequency vibration suppression capability.

关键词： 70J50 low-frequency bandgap metamaterial O321 vibration suppression wave propagation

Development of Spectral Features for Monitoring Rice Bacterial Leaf Blight Disease Using Broad-Band Remote Sensing Systems

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Phyton-International Journal of Experimental Botany 2024年第4期93卷 745-762页

作者： Jingcheng Zhang xingjian Zhou Dong Shen Qimeng Yu Lin Yuan Yingying Dong College of Artificial Intelligence Hangzhou Dianzi UniversityHangzhou310018China School of Information Engineering Zhejiang University of Water Resources and Electric PowerHangzhou310018China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing100094China

As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae ***), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result ofthe disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remotesensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutionsoffer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapiddispersal under suitable conditions, making it difficult to track the disease at a regional scale with a single sensorin practice. Therefore, it is necessary to identify or construct features that are effective across different sensors formonitoring RBLB. To achieve this goal, the spectral response of RBLB was first analyzed based on the canopyhyperspectral data. Using the relative spectral response (RSR) functions of four representative satellite or UAVsensors (i.e., Sentinel-2, GF-6, Planet, and Rededge-M) and the hyperspectral data, the corresponding broad-bandspectral data was simulated. According to a thorough band combination and sensitivity analysis, two novel spectralindices for monitoring RBLB that can be effective across multiple sensors (i.e., RBBRI and RBBDI) weredeveloped. An optimal feature set that includes the two novel indices and a classical vegetation index was *** capability of such a feature set in monitoring RBLB was assessed via FLDA and SVM algorithms. The resultdemonstrated that both constructed novel indices exhibited high sensitivity to the disease across multiple ***, the feature set yielded an overall accuracy above 90% for all sensors, which indicates its cross-sensorgenerality in monitoring RBLB. The outcome of this research permits disease monitoring with different remotesensing data over a large scale.

关键词： Rice bacterial leaf blight analysis of spectral response multispectral data simulation vegetation indices cross-sensor disease monitoring

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光栅投影测量系统中的相位误差校正算法

光学学报 2014年第7期34卷 123-128页

作者：吴蜀予杨宜民钟震宇卢杏坚广东工业大学自动化学院广东广州510001 广东省自动化研究所广东广州510070

依据光栅图像的相位单调增长特性,提出了一种基于最小二乘法的单调光顺算法进行光栅相位误差校正。详细分析了光栅图像的相位单调特性和相位误差,以光栅图像相位的单调性为约束条件,改进了传统的最小二乘拟合方法,对绝对相位图进行相位... 详细信息

依据光栅图像的相位单调增长特性,提出了一种基于最小二乘法的单调光顺算法进行光栅相位误差校正。详细分析了光栅图像的相位单调特性和相位误差,以光栅图像相位的单调性为约束条件,改进了传统的最小二乘拟合方法,对绝对相位图进行相位误差校正。实验结果表明,该方法降低了投影仪伽马非线性造成的相位误差,误差减少60%以上,校正后的绝对相位具有光滑性良好的优点。

关键词：测量最小二乘法单调光顺算法

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基于深度学习的图异常检测技术综述

计算机研究与发展 2021年第7期58卷 1436-1455页

作者：陈波冯李靖东卢兴见沙朝锋王晓玲张吉华东师范大学计算机科学与技术学院上海200062 复旦大学计算机科学技术学院上海200433 之江实验室杭州310000

图异常检测旨在大图或海量图数据库中寻找“陌生”或“不寻常”模式,具有广泛的应用场景.深度学习可以从数据中学习隐含的规律,在提取数据中潜在复杂模式方面表现出优越的性能.近年来随着基于深度神经网络的图表示学习取得显著进展,如... 详细信息

图异常检测旨在大图或海量图数据库中寻找“陌生”或“不寻常”模式,具有广泛的应用场景.深度学习可以从数据中学习隐含的规律,在提取数据中潜在复杂模式方面表现出优越的性能.近年来随着基于深度神经网络的图表示学习取得显著进展,如何利用深度学习方法进行图异常检测引起了学术界和产业界的广泛关注.尽管最近一系列研究从图的角度对异常检测技术进行了调研,但是缺少对深度学习技术下的图异常检测技术的关注.首先给出了静态图和动态图上各类常见的异常定义,然后调研了基于深度神经网络的图表示学习方法,接着从静态图和动态图的角度出发,梳理了基于深度学习的图异常检测的研究现状,并总结了图异常检测的应用场景和相关数据集,最后讨论了图异常检测技术目前面临的挑战和未来的研究方向.

关键词：异常检测深度学习图网络图表示学习图神经网络

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基于VR火灾逃生游戏的应急行为评估系统

系统仿真学报 2017年第11期29卷 2796-2803,2810页

作者：何高奇郁明强蒋正清卢兴见华东理工大学计算机科学与工程系上海200237 华东师范大学地理信息科学教育部重点实验室上海200241 华东理工大学艺术设计与传媒学院上海200237 上海交通大学智慧城市协同创新中心上海200240

在突发事件场景中,个体的行为和心理具有较强的复杂性和动态性,是真实感群体行为模拟所面临的一大挑战。将虚拟现实和游戏技术相结合,设计了虚拟现实火灾逃生游戏VRFEG(Virtual Reality Fire Escape Game),并对用户的应急行为进行有效... 详细信息

在突发事件场景中,个体的行为和心理具有较强的复杂性和动态性,是真实感群体行为模拟所面临的一大挑战。将虚拟现实和游戏技术相结合,设计了虚拟现实火灾逃生游戏VRFEG(Virtual Reality Fire Escape Game),并对用户的应急行为进行有效的评估分析。VRFEG主要由交互式情节设计、架构设计、数据采集和行为分析等四个模块组成。实验表明,VRFEG系统具有直观、易用等特点,能让人们在感受游戏刺激的同时学习到一些应急逃生的技能,也为获取人们在突发状况下的部分行为数据提供了一个有效和有趣的通道。

关键词：虚拟现实游戏行为评估应急演练游戏行为记录器 unity3d