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Face Anti-Spoofing with Unknown Attacks:A Comprehensive Feature Extraction and Representation Perspective

Journal of Computer Science & Technology 2024年第4期39卷 827-840页

作者： li-min li Bin-Wu Wang Xu Wang Peng-Kun Wang Yu-Dong Zhang Yang Wang School of Software Engineering University of Science and Technology of ChinaHefei 230000China School of Data Science University of Science and Technology of ChinaHefei 23000China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215000China

Face anti-spoofing aims at detecting whether the input is a real photo of a user(living)or a fake(spoofing)*** new types of attacks keep emerging,the detection of unknown attacks,known as Zero-Shot Face Anti-Spoofing(ZSFA),has become increasingly important in both academia and *** ZSFA methods mainly focus on extracting discriminative features between spoofing and living ***,the nature of the spoofing faces is to trick anti-spoofing systems by mimicking the livings,therefore the deceptive features between the known attacks and the livings,which have been ignored by existing ZSFA methods,are essential to comprehensively represent the ***,existing ZSFA models are incapable of learning the complete representations of living faces and thus fall short of effectively detecting newly emerged *** tackle this problem,we propose an innovative method that effectively captures both the deceptive and discriminative features distinguishing between genuine and spoofing *** method consists of two main components:a two-against-all training strategy and a semantic *** two-against-all training strategy is employed to separate deceptive and discriminative *** address the subsequent invalidation issue of categorical functions and the dominance disequilibrium issue among different dimensions of features after importing deceptive features,we introduce a modified semantic *** autoencoder is designed to map all extracted features to a semantic space,thereby achieving a balance in the dominance of each feature *** combine our method with the feature extraction model ResNet50,and experimental results show that the trained ResNet50 model simultaneously achieves a feasible detection of unknown attacks and comparably accurate detection of known *** results confirm the superiority and effectiveness of our proposed method in identifying the living with the interference of both known

关键词： face anti-spoofing spoof detection zero-shot learning convolutional neural network deep learning

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竞塑“故乡”——1930年代国共两党围绕“民族故乡”的形象塑造与话语竞争

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中华民族共同体研究 2024年第3期 24-44,170,171页

作者：李立敏清华大学人文学院历史系

围绕民族故乡的话语生产是现代国家与民族认同塑造的重要一环,既有研究对1930年代起国共双方以“民族故乡在西北”为中心的论争却少有分析。面对空前国难,国民政府通过设置“民族扫墓节”等方式,率先将边界相对模糊的“西北”叙述为“... 详细信息

围绕民族故乡的话语生产是现代国家与民族认同塑造的重要一环,既有研究对1930年代起国共双方以“民族故乡在西北”为中心的论争却少有分析。面对空前国难,国民政府通过设置“民族扫墓节”等方式,率先将边界相对模糊的“西北”叙述为“民族故乡”,将“黄帝陵”明确为界定“故乡”的象征符号。可当中国共产党开始政策转型并加入关于“民族故乡”的论争后,“故乡”的重心渐趋位移。在诸多中外人士的日记、游记及相关文章中,“红色中国”渐与“民族故乡”重叠至一处。这一变化的出现,是中国共产党主动吸收、改造民族话语资源的结果,与其在全民族抗战中的具体实践相辅相成,亦与地理区位、政治实践与历史资源密切相关。由之切入,亦能更好认识中华民族共同体意识的普遍性与民族主义作为意识形态的两面性。

关键词：民族故乡西北抗日战争代表权之争中华民族共同体意识

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红外特征提取与关联分析的设备故障预警方法

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激光与红外 2024年第8期54卷 1277-1285页

作者：杨磊王国丽朱丽晓李云红李丽敏苏雪平王梅国家能源集团新疆吉林台水电开发有限公司新疆伊犁835000 西安工程大学电子信息学院陕西西安710048

水电站电气设备的安全稳定运行至关重要。为了实现设备故障的自动预警,通过红外特征提取并进行灰色关联分析,提出建立主成分分析(PCA)和基于密度的聚类算法(DBSCAN)的设备故障预警模型。首先,通过数据预处理补全缺失数据,剔除异常数据... 详细信息

水电站电气设备的安全稳定运行至关重要。为了实现设备故障的自动预警,通过红外特征提取并进行灰色关联分析,提出建立主成分分析(PCA)和基于密度的聚类算法(DBSCAN)的设备故障预警模型。首先,通过数据预处理补全缺失数据,剔除异常数据后进行主成分分析降维并提取新的主成分特征。其次,将新的主成分采用DBSCAN算法构建特征样本集,建立灰色关联模型,计算灰色关联系数,然后,通过灰色关联系数的变化程度突变点进行故障预警。实验结果表明,所提方法能有效提取红外特征,并在设备异常状态下实现设备故障预警,故障预警准确率达到97.88%。

关键词：红外特征提取 PCA降维 DBSCAN聚类灰色关联分析故障预警

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不同类型油脂高脂膳食对小鼠血脂水平及肠道菌群的影响

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现代预防医学 2024年第8期51卷 1412-1419页

作者：陈睿然陈洁黄佳灵李敏丽郭福川福建医科大学公共卫生学院

目的探究不同类型油脂高脂膳食对小鼠血脂水平及肠道菌群的影响。方法 30只SPF级雄性C57BL/6J小鼠按体重随机分为三组，每组10只，普通对照组(ND)给予对照饲料，棕榈油高脂组(PHFD)和大豆油高脂组(SHFD)分别给予对应高脂饲料，喂养17... 详细信息

目的探究不同类型油脂高脂膳食对小鼠血脂水平及肠道菌群的影响。方法 30只SPF级雄性C57BL/6J小鼠按体重随机分为三组，每组10只，普通对照组(ND)给予对照饲料，棕榈油高脂组(PHFD)和大豆油高脂组(SHFD)分别给予对应高脂饲料，喂养17周后测定血清生化指标，取粪便进行16S rRNA测序。结果与ND相比，PHFD和SHFD小鼠体重显著升高(Plipoprotein cholesterol, LDL-C)水平显著升高(Plidextribacter相对丰度显著升高(P<0.05),PHFD糖代谢相关通路功能显著上升(P<0.05),SHFD脂代谢相关通路功能显著下降(P<0.05)。结论不同类型油脂高脂膳食导致小鼠血脂紊乱，肠道菌群结构显著改变，PHFD糖脂代谢相关菌属相对丰度增加，SHFD脂质代谢相关菌属相对丰度增加，抗氧化相关菌相对丰度降低。

关键词：高脂膳食肠道菌群棕榈油大豆油

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Covariant Prolongation Structure of Konno-Asai-Kakuhata Equation

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Communications in Theoretical Physics 2008年第9期50卷 565-567页

作者： XIE Tao li min-li School of Mathematical Sciences Capital Normal University Beijing 100048 China

Based upon the covariant prolongation structures theory, we construct the sl（2, R）×R（p） prolongation structure for Konno-Asai-Kakuhata equation. By taking two and one-dimensional prolongation spaces, we obtain the inverse scattering equations given by Konno et al. and the corresponding Riccati equation. The Baecklund transformations are also presented.

关键词： integrable equation covariant prolongation structure Baecklund transformation

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Dynamic prediction of landslide displacement using singular spectrum analysis and stack long short-term memory network

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Journal of Mountain Science 2021年第10期18卷 2597-2611页

作者： li li-min Zhang ming-yue WEN Zong-zhou College of Electronics and Information Xi’an Polytechnic UniversityXi’an 710048China

An accurate landslide displacement prediction is an important part of landslide warning system. Aiming at the dynamic characteristics of landslide evolution and the shortcomings of traditional static prediction models, this paper proposes a dynamic prediction model of landslide displacement based on singular spectrum analysis(SSA) and stack long short-term memory(SLSTM) network. The SSA is used to decompose the landslide accumulated displacement time series data into trend term and periodic term displacement subsequences. A cubic polynomial function is used to predict the trend term displacement subsequence, and the SLSTM neural network is used to predict the periodic term displacement subsequence. At the same time, the Bayesian optimization algorithm is used to determine that the SLSTM network input sequence length is 12 and the number of hidden layer nodes is 18. The SLSTM network is updated by adding predicted values to the training set to achieve dynamic displacement prediction. Finally, the accumulated landslide displacement is obtained by superimposing the predicted value of each displacement subsequence. The proposed model was verified on the Xintan landslide in Hubei Province, China. The results show that when predicting the displacement of the periodic term, the SLSTM network has higher prediction accuracy than the support vector machine(SVM) and auto regressive integrated moving average(ARIMA). The mean relative error(MRE) is reduced by 4.099% and 3.548% respectively, while the root mean square error(RMSE) is reduced by 5.830 mm and 3.854 mm respectively. It is concluded that the SLSTM network model can better simulate the dynamic characteristics of landslides.

关键词： Landslide Singular spectrum analysis Stack long short-term memory network Dynamic displacement prediction

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Landslide prediction based on improved principal component analysis and mixed kernel function least squares support vector regression model

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Journal of Mountain Science 2021年第8期18卷 2130-2142页

作者： li li-min CHENG Shao-kang WEN Zong-zhou School of Electronics and Information Xi’an Polytechnic UniversityXi’an710048China School of Automation Northwestern Polytechnical UniversityXi’an710072China

Landslide probability prediction plays an important role in understanding landslide information in advance and taking preventive *** factors can influence the occurrence of landslides,which is easy to have a curse of dimensionality and thus lead to reduce prediction *** the generalization ability of the model will also decline sharply when there are only small *** reduce the dimension of calculation and balance the model’s generalization and learning ability,this study proposed a landslide prediction method based on improved principal component analysis(PCA)and mixed kernel function least squares support vector regression(LSSVR)***,the traditional PCA was introduced with the idea of linear discrimination,and the dimensions of initial influencing factors were reduced from 8 to *** improved PCA can not only weight variables but also extract the original ***,combined with global and local kernel function,the mixed kernel function LSSVR model was framed to improve the generalization *** optimization algorithm(WOA)was used to optimize the ***,Root Mean Square Error(RMSE),the sum of squared errors(SSE),Mean Absolute Error(MAE),Mean Absolute Precentage Error(MAPE),and reliability were employed to verify the performance of the *** with radial basis function(RBF)LSSVR model,Elman neural network model,and fuzzy decision model,the proposed method has a smaller ***,the landslide warning level obtained from the landslide probability can also provide references for relevant decision-making departments in emergency response.

关键词： Landslide probability LSSVR Mixed kernel function Improved PCA Warning level

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Adaptive Iterative Learning Control for Nonlinear Time-delay Systems with Periodic Disturbances Using FSE-neural Network

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International Journal of Automation and computing 2011年第4期8卷 403-410页

作者： Chun-li Zhang Jun-min li Department of Applied Mathematics Xidian University Xi＇an 710071 PRC

An adaptive iterative learning control scheme is presented for a class of strict-feedback nonlinear time-delay systems, with unknown nonlinearly parameterised and time-varying disturbed functions of known periods. Radial basis function neural network and Fourier series expansion （FSE） are combined into a new function approximator to model each suitable disturbed function in systems. The requirement of the traditional iterative learning control algorithm on the nonlinear functions （such as global lipschitz condition） is relaxed. Furthermore, by using appropriate Lyapunov-Krasovskii functionals, all signs in the closed loop system are guaranteed to be semiglobally uniformly ultimately bounded, and the output of the system is proved to converge to the desired trajectory. A simulation example is provided to illustrate the effectiveness of the control scheme.

关键词： Adaptive control iterative learning control (ILC) time-delay systems Fourier series expansion-neural network periodic disturbances.

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Effect of Black Plate on Corrosion Resistance of T5 Tinplate

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Journal of Iron and Steel Research International 2006年第2期13卷 59-64页

作者： HUANG Xing-qiao li Ning JIANG li-min li De-yu Department of Applied Chemistry Harbin Institute of Technology Harbin 150001 Heilongjiang China

The effect of black plate on corrosion resistance of T5 tinplate was studied by glow discharge spectrograph, X-ray diffractometer （XRD）, stress tester, roughness tester and metallographic microscope. The result shows that black plate influences corrosion resistance of T5 tinplate intensely. It also indicates that the increase of content of manganese, phosphorus, silicon and aluminum in black plate would reduce the corrosion resistance of T5 tinplate and the increase of degree of crystal orientation on （200） crystal face, ｜X-Y｜ value （internal stress difference within two orientation）, roughness and exposure degree of iron grain after the same acid wash of black plate would enhance the corrosion resistance of T5 tinplate and the grain number of black plate has small effect on corrosion resistance of T5 tinplate.

关键词： T5 tinplate black plate component crystal orientation internal stress corrosion resistance

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Flow-injection chemiluminescence determination of tryptophan using galangin-potassium permanganate-polyphosphoric acid system

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Chinese Chemical Letters 2008年第2期19卷 203-206页

作者： Hui Chen li li min Zhou Yong Jun Ma College of Chemistry and Chemical Engineering Gansu Key Laboratory of Polymer Materials Northwest Normal University Lanzhou 730070 China

A high sensitive flow-injection chemiluminescence （FI-CL） method for the determination of tryptophan has been developed. The method is based on the chemiluminescence reaction of galangin-potassium permanganate-tryptophan in polyphosphoric acid （PPA） media. Under the optimized conditions, tryptophan was determined in the range 0.05-10 μg/mL with the detection limit （3tr） of 5.0 × 10^-3 μg/mL. The relative standard deviation （RSD） was 1.0% for 11 replicate determinations of 1.0 μg/mL tryptophan. Three synthetic samples were determined selectively with recoveries in the range from 99.6% to 102.0% in the presence of other amino acids.

关键词： Chemiluminescence Flow-injection Galangin Potassium permanganate Tryptophan

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