基于人脸卡口数据的行人共现关系图谱构建

随着人脸识别技术的不断进步以及人脸卡口的大范围且密集的部署, 本文针对团伙犯罪案件侦察这一应用场景, 对人脸卡口数据进行深入挖掘, 探究其中行人间的共现关系, 获取所关注的嫌疑人的现实社交网络, 锁定团伙其余人员. 经过实验比对和论证, 本文使用Chinese Whispers聚类算法对行人节点进行识别, 通过Faiss加速邻接边的构建, 加速图的初始化步骤, 解决其聚类效率低下的问题. 在此基础上, 使用共现频次和Apriori算法中的置信度挖掘行人间的共现关系, 构建行人共现关系图谱.     

Asynchronous control for two‐dimensional hidden Markovian jump systems with partly known mode observation conditional probabilities

This study focuses on the asynchronous control problem for two‐dimensional discrete‐time hidden Markovian jump systems where the mode observation conditional probability matrix is partly known. Considering the original system modes are invisible, the observed modes emitted from an observer serve as an alternative for stability analysis and controller design where a mode observation conditional probability matrix is constructed to characterize the emission between system modes and observed modes. Specially, only partly known information of the mode observation conditional probability matrix is accessible. With the introduction of the free‐connection weighting matrices, the asymptotic mean square stability criterion is firstly derived based on Lyapunov method. This introduction provides a further degree of relaxation and less conservatism is therefore achieved. Secondly, we present synthesis conditions for asynchronous state feedback controller design given in terms of a set of interconnected linear matrix inequalities. Moreover, cluster concept based on the partitions of observed modes is adopted which helps to decrease the number of controllers and simplify the design complexity. A numerical example, regarding the cases with and without clustering of the observed modes, is presented to illustrate the effectiveness of the proposed method.     

Arabic sign language intelligent translator

ABSTRACT

Arabic sign language (ArSL) is method of communication between deaf communities in Arab countries; therefore, the development of systemsthat can recognize the gestures provides a means for the Deaf to easily integrate into society. In this research we implemented a computational structurefor an intelligent interpreter that automatically recognizes the isolated dynamic gestures. The proposed system recognizes and translates gesturesperformed with one or both hands. It comprises five subsystems, building dataset, video processing, feature extraction, mapping between ArSL and Arabictext, and text generation. To apply the system, 100-signs of ArSL was used, which was applied on 1500 video files. It's were divided into five classes:alphabet, numbers, "prepositions, pronouns and question words", Arabic life expressions, and "nouns and verbs". The evaluation indicated that thesystem automatically recognizes and translates isolated dynamic ArSL gestures by highly accurate manner. The results showed that the system accuracy is 95.8%.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Structural analysis of assemblages of thin-walled members

A matrix method for the analysis of structural systems composed of thin-walled members is presented. The matrix displacement analysis includes the effects of thin-walled non-uniform torsion theory, cross-section asymmetry, eccentric restraint as well as joint types peculiar to thin-walled members. The method is used for a prediction of the elastic behaviour of a set of representative test frames. The test frames were pitched-roof portals constructed from channel sections bent about their major-axis and supported by eccentric restraints simulating purlins and girts.     

柔性气动连续体机器人关节结构设计与运动学分析

基于气动人工肌肉和缆绳组合驱动,提出了一种三自由柔性气动连续体机器人关节,该关节具有结构紧凑、柔顺性高、控制简单等特点。通过分析该机器人关节结构特性,采用修正的D-H法,建立了其正反解运动学模型,求解了其位置运动学解和速度运动学解,通过仿真验证了关节结构的合理性和运动学方程的正确性。     

A Method for Improving Multivariate Measurement Systems Assessment

Multivariate measurement systems analysis (MSA) is usually performed by designing suitable gauge repeatability and reproducibility (R&R) experiments, ignoring available data generated by the measurement system while used for inspection or process control. This article proposes an approach that, by using the data that are routinely available from the regular operation of the instrument, allows the measurement instrument's current precision to be compared against a benchmark. The proposed method may be appropriately used in an integrated and coordinated manner with the usual multivariate gauge study in the sense that it can be used to assess the stability or a possible deterioration in the precision of the measurement instrument while operational. Therefore, the complementary use of the proposed approach and the traditional multivariate gauge R&R studies can be a useful strategy for improving the overall quality of multivariate measurement systems. Furthermore, because it can be implemented at almost no additional cost, it may be effective in reducing the costs of a multivariate MSA performed with a certain frequency. Copyright © 2014 John Wiley & Sons, Ltd.     

基于RPCA的SAR图像纹理特征去噪

合成孔径雷达(SAR)图像具有丰富的纹理信息,这些纹理信息能反映地物空间结构关系。当前纹理特征被广泛应用于SAR图像分类和SAR图像分割中。受成像因素影响,直接采用从SAR图像中提取的纹理特征效果不够好。为避免传统先滤波再提取纹理特征的方法对纹理、边缘信息造成损失,提出了一种先提取SAR图像纹理特征,再利用Robust PCA方法对纹理特征去噪的新方法,最后采用Kmeans聚类方法检验RPCA处理后的纹理特征表达效果。实验结果表明该方法能将聚类正确率从82%提高到84%。     

Language acceptability of finite automata based on theory of semi‐tensor product of matrices

Using the theories of many‐valued logic and semi‐tensor product of matrices (STP), this paper investigates how to mathematically determine whether or not a regular language is recognized by finite automata (FA). To this end, the dynamic behaviour of FA is first formulated as bilinear dynamic equations, which provides a uniform model for deterministic and non‐deterministic FA. Based on the bilinear model, the recognition power of FA understanding of regular languages is investigated and several algebraic criteria are obtained. With the algebraic criteria, to judge whether a regular sentence is accepted by a FA or not, one only needs to calculate an STP of some vectors, rather than making the sentence run over the machine as traditional manners. Further, the inverse problem of recognition is considered, an algorithm is developed that can mathematically construct all the accepted sentences for a given FA. The algebraic approach of this paper may be a new angle and means to understand and analyse the dynamics of FA.