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contrastive consistency and Attentive complementarity for Deep Multi-View Subspace Clustering

2012 International conference on computer technology and science(ICCTS 2012)

作者： Guohai Yang Shunhua Tan Miao Chen and Yizhi wang National school of Defense technology school of information engineering southwest university of science and technology mianyang china

With the growing number of Internet user nodes on the Internet,resources have tended to reveal a marginal *** this case,if it continues to rely on traditional client/server （C/S） model of resource access architecture,the servers will meet challenges about costing huge investment of ***,using peer to peer （P2P） model and technology of NAT traversal can share resources between edge nodes,thus network bandwidth will be used more efficiently,and visualization of NAT subnet hidden nodes will be *** paper is about development of campus network resource sharing system and its reliable test,which is based on the Visual C++ and the MySQL database platform.

关键词： Peer network Marginalization Resource integration Udp punching Time synchronization

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computers, Materials & continua 2024年第4期79卷 143-160页

作者： Jiao wang Bin Wu Hongying zhang school of information engineering Southwest University of Science and TechnologyMianyang621010China

Deep multi-view subspace clustering (DMVSC) based on self-expression has attracted increasing attention dueto its outstanding performance and nonlinear application. However, most existing methods neglect that viewprivatemeaningless information or noise may interfere with the learning of self-expression, which may lead to thedegeneration of clustering performance. In this paper, we propose a novel framework of contrastive consistencyand Attentive complementarity (CCAC) for DMVsSC. CCAC aligns all the self-expressions of multiple viewsand fuses them based on their discrimination, so that it can effectively explore consistent and complementaryinformation for achieving precise clustering. Specifically, the view-specific self-expression is learned by a selfexpressionlayer embedded into the auto-encoder network for each view. To guarantee consistency across views andreduce the effect of view-private information or noise, we align all the view-specific self-expressions by contrastivelearning. The aligned self-expressions are assigned adaptive weights by channel attention mechanism according totheir discrimination. Then they are fused by convolution kernel to obtain consensus self-expression withmaximumcomplementarity ofmultiple views. Extensive experimental results on four benchmark datasets and one large-scaledataset of the CCAC method outperformother state-of-the-artmethods, demonstrating its clustering effectiveness.

关键词： Deep multi-view subspace clustering contrastive learning adaptive fusion self-expression learning

A hybrid data driven framework considering feature extraction for battery state of health estimation and remaining useful life prediction

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Green Energy and Intelligent Transportation 2024年第2期3卷 50-59页

作者： Yuan Chen Wenxian Duan Yigang he Shunli wang Carlos Fernandez school of Artificial Intelligence Anhui UniversityHefei 230009China State Key Laboratory of Automotive Simulation and control Jilin UniversityChangchun 130022China school of Electrical engineering and Automation Wuhan UniversityWuhan 430000China school of information engineering Southwest University of Science and TechnologyMianyang 621010China school of Pharmacy and Life sciences Robert Gordon UniversityAberdeenAB10-7GJUK

Battery life prediction is of great significance to the safe operation,and reduces the maintenance *** paper proposes a hybrid framework considering feature extraction to achieve more accurate and stable life prediction performance of the *** feature extraction,eight features are obtained to fed into the life prediction *** hybrid framework combines variational mode decomposition,the multi-kernel support vector regression model and the improved sparrow search algorithm to solve the problem of data backward,uneven distribution of high-dimensional feature space and the local escape ability,*** parameters of the estimation model are obtained by introducing the elite chaotic opposition-learning strategy and adaptive weights to optimize the sparrow search *** algorithm can improve the local escape ability and convergence performance and find the global *** comparison is conducted by dataset from National Aeronautics and Space Administration which shows that the proposed framework has a more accurate and stable prediction *** with other algorithms,the SOH estimation accuracy of the proposed algorithm is improved by 0.16%–1.67%.With the advance of the start point,the RUL prediction accuracy of the proposed algorithm does not change much.

关键词： State of heath Improved sparrow search algorithm Remaining useful life Variational mode decomposition Multi-kernel support vector regression Feature extraction

A review of data-driven whole-life state of health prediction for lithium-ion batteries:Data preprocessing,aging characteristics,algorithms,and future challenges

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Journal of Energy Chemistry 2024年第10期97卷 630-649,I0013页

作者： Yanxin Xie Shunli wang Gexiang zhang Paul Takyi-Aninakwa Carlos Fernandez Frede Blaabjerg school of information engineering Southwest University of Science and TechnologyMianyang 621010SichuanChina college of Electric Power Inner Mongolia University of TechnologyHohhot 010080Inner MongoliaChina school of Pharmacy and Life sciences Robert Gordon UniversityAberdeen AB10-7GJUK Department of Energy technology Aalborg UniversityPontoppidanstraede 1119220 Aalborg EastDenmark

Lithium-ion batteries are the preferred green energy storage method and are equipped with intelligent battery management systems(BMSs)that efficiently manage the *** not only ensures the safety performance of the batteries but also significantly improves their efficiency and reduces their damage *** their whole life cycle,lithium-ion batteries undergo aging and performance degradation due to diverse external environments and irregular degradation of internal *** degradation is reflected in the state of health(SOH)***,this review offers the first comprehensive analysis of battery SOH estimation strategies across the entire lifecycle over the past five years,highlighting common research focuses rooted in data-driven *** delves into various dimensions such as dataset integration and preprocessing,health feature parameter extraction,and the construction of SOH estimation *** approaches unearth hidden insights within data,addressing the inherent tension between computational complexity and estimation *** enha nce support for in-vehicle implementation,cloud computing,and the echelon technologies of battery recycling,remanufacturing,and reuse,as well as to offer insights into these technologies,a segmented management approach will be introduced in the *** will encompass source domain data processing,multi-feature factor reconfiguration,hybrid drive modeling,parameter correction mechanisms,and fulltime health *** on the best SOH estimation outcomes,health strategies tailored to different stages can be devised in the future,leading to the establishment of a comprehensive SOH assessment *** will mitigate cross-domain distribution disparities and facilitate adaptation to a broader array of dynamic operation *** article reviews the current research landscape from four perspectives and discusses the challenges that lie *** and practitioners can gain

关键词： Lithium-ion batteries Whole life cycle Aging mechanism Data-driven approach State of health Battery management system

Dynamic risk assessment of gas pipeline operation process by fusing visual and olfactory monitoring

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Journal of Safety science and Resilience 2024年第2期5卷 156-166页

作者： Denglong Ma Weigao Mao Guangsen zhang Chaoyi Liu Yi Han Xiaoming zhang Hansheng wang Kang Cen Wan Lu Denghui Li Hanyue zhang school of Mechanical engineering Xi'an Jiaotong UniversityXi'an 710049China Hanzhong Natural Gas Investinent development co.ltd Hanzhong723011China Shaanxi Special Equipment Inspection and Testing Institute Xi'an710038China school of Civil engineering and Architecture Southwest Petroleum UniversityChengdu610500China sichuan Tianxin Gas co.ltd. Mianyang62100China Petro china southwest Oil and Gas Field company Gas Branch Chengdu610500China

With the rapid increase in urban gas consumption,the frequency of maintenance and repair of gas pipelines has escalated,leading to a rise in safety accidents during these *** traditional manual supervision model presents challenges such as inaccurate monitoring results,incomplete risk factor analysis,and a lack of quantitative risk *** research focuses on developing a dynamic risk assessment technology for gas emergency repair operations by integrating the monitoring outcomes of artificial olfactory for gas leakage information and video object recognition for visual safety factor monitoring *** quantitatively evaluate the risk of the operation process,a three-dimensional risk assessment model combining gas leakage with riskcorrelated sensitivity was established as well as a separate three-dimensional risk assessment model integrating visual risk factors with predictable risk ***,a visual risk quantification expression mode based on the risk matrix-radar map method was ***,a risk quantification model based on the fusion of visual and olfactory results was *** verification results of simulation scenarios based on field data indicate that the visual-olfactory fusion risk assessment method can more accurately reflect the dynamic risk level of the operation process compared to simple visual safety factor *** outcomes of this research can contribute to the identification of safety status and early warning of risks related to personnel,equipment,and environmental factors in emergency repair ***,these results can be extended to other operational scenarios,such as oil and gas production stations and long-distance pipeline operations.

关键词： Gas pipelinemaintenance Dynamicriskassessment Visual-olfactoryfusion Risk matrix Risk quantification model

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组合GPS静态定位的一种算法

信息与电子工程 2009年第4期7卷 253-256,277页

作者：邓旭辉王俊波西南科技大学信息工程学院四川绵阳621000

单站GPS定位由于数据受体系结构及观测条件的影响,测量结果精度低且不稳定。用多个手持GPS设备构成组合GPS静态定位系统,通过固联结构对随机误差进行校正,并充分利用测量数据的方差信息构成权矩阵,得到加权最小二乘解。仿真实验表明新... 详细信息

单站GPS定位由于数据受体系结构及观测条件的影响,测量结果精度低且不稳定。用多个手持GPS设备构成组合GPS静态定位系统,通过固联结构对随机误差进行校正,并充分利用测量数据的方差信息构成权矩阵,得到加权最小二乘解。仿真实验表明新方法可将定位精度快速稳定地提高到3m左右。

关键词：固联系统统计信息几何信息加权最小二乘估计

Optimized online filter stack spectrometer for ultrashort X-ray pulses

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Nuclear science and Techniques 2024年第5期35卷 85-98页

作者： Jia-Xing Wen Ge Ma Ming-Hai Yu Yu-Chi Wu Yong-Hong Yan Shao-Yi wang Huai-Zhong Gao Lu-Shan wang Yu-Gang Zhou Qiang Li Yue Yang Fang Tan Xiao-Hui zhang Jie zhang Wen-Bo Mo Jing-Qin Su Wei-Min Zhou Yu-Qiu Gu Ming Zeng Zong-Qing Zhao science and technology on Plasma Physics Laboratory Laser Fusion Research CenterCAEPMianyang 621900China Department of engineering Physics Tsinghua UniversityBeijing 100084China Key Laboratory of Particle and Radiation Imaging(Tsinghua university) Ministry of EducationBeijing 100084China school of information engineering Southwest University of Science and TechnologyMianyang 621010China

Currently,with the advent of high-repetition-rate laser-plasma experiments,the demand for online diagnosis for the X-ray spectrum is increasing because the laser-plasma-generated X-ray spectrum is very important for characterizing electron dynamics and *** this study,scintillators and silicon PIN(P-type–intrinsic-N-type semiconductor)diodes were used to construct a wideband online filter stack *** X-ray sensor and filter arrangement was optimized using a genetic algorithm to minimize the condition number of the response ***,the unfolding error was significantly reduced based on numerical *** detector responses were quantitatively calibrated by irradiating the scintillator and PIN diode with various nuclides and comparing the measuredγ-ray peaks.A prototype 15-channel spectrometer was developed by integrating an X-ray detector with front-and back-end *** prototype spectrometer could record X-ray pulse signals at a repetition rate of 1 ***,an optimized spectrometer was employed to record the real-time spectra of laser-driven bremsstrahlung *** optimized spectrometer offers a compact solution for spectrum diagnostics of ultrashort X-ray pulses,exhibiting improved accuracy in terms of spectrum measurements and repetition rates,and could be widely used in next-generation high-repetition-rate high-power laser facilities.

关键词： Filter stack spectrometer Laser plasma diagnostics X-ray diagnostics Scintillator PIN diode

改进各向异性导向滤波的明场显微图像清晰化方法

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激光与光电子学进展 2024年第12期61卷 248-257页

作者：黄臣伟蒋和松王学渊徐秋月韩万芬西南科技大学信息工程学院四川绵阳621000

针对光学显微成像系统由于CCD采集、成像对焦精度等不利因素导致成像图像模糊的问题,提出一种改进各向异性导向滤波的反锐化掩模明场显微图像的清晰化方法。首先,通过改进自适应正则项的各向异性导向滤波消除图像噪声,同时强保留边缘细... 详细信息

针对光学显微成像系统由于CCD采集、成像对焦精度等不利因素导致成像图像模糊的问题,提出一种改进各向异性导向滤波的反锐化掩模明场显微图像的清晰化方法。首先,通过改进自适应正则项的各向异性导向滤波消除图像噪声,同时强保留边缘细节信息;其次,利用各向同性的高斯滤波得到强平滑图像结构信息;然后,将细节强保留图像与结构强平滑图像相减,得到掩模图像;最后将输入图像与掩模图像融合,得到清晰的显微图像。该方法减少了传统反锐化掩模算法放大图像噪声导致图像细节特征辨识度降低的现象,在一定程度上降低了图像的模糊感,同时避免了滤波处理结果出现梯度反转和光晕伪影。在Mendeley data公开数据库的利什曼原虫寄生虫数据集实验结果中,所提方法的清晰度评价指标峰值信噪比、均方根误差和平均结构相似度的平均值分别为41.1430、0.000090和0.9905;而在PanNuKe公开数据库实验结果中,所提方法的3个指标平均值分别为28.8541、0.001939和0.9283。主客观的实验结果表明,所提方法能够减少噪声干扰和抑制细节“光晕”问题,同时能够更好地增强边缘细节信息。

关键词：各向异性导向滤波清晰化反锐化掩模显微图像

基于Bi-LSTM模型的恶意JavaScript代码检测方法

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计算机应用与软件 2024年第9期41卷 357-362页

作者：纪育青方艳红谭顺华王学渊西南科技大学信息工程学院四川绵阳621010 西南科技大学特殊环境机器人技术四川省重点实验室四川绵阳621010

传统的静态检测恶意JavaScript代码方法十分依赖于已有的恶意代码特征,无法有效提取混淆恶意代码特征,导致检测混淆恶意JavaScript代码的精确率低。针对该问题提出基于双向长短期记忆网络(Bidirectional Long Short-term Memory, Bi-LS... 详细信息

传统的静态检测恶意JavaScript代码方法十分依赖于已有的恶意代码特征,无法有效提取混淆恶意代码特征,导致检测混淆恶意JavaScript代码的精确率低。针对该问题提出基于双向长短期记忆网络(Bidirectional Long Short-term Memory, Bi-LSTM)的恶意代码检测模型。通过抽象语法树将JavaScript代码转化为句法单元序列,通过Doc2Vec算法将句法单元序列用分布式向量表示,将句向量矩阵送入Bi-LSTM模型进行检测。实验结果表明,该方法对于混淆恶意JavaScript代码具有良好的检测效果且检测效率高,准确率为97.03%,召回率为97.10%。

关键词：恶意JavaScript代码检测 Bi-LSTM 深度学习 Doc2Vec