关键词： Fault detection   Transmission lines   Power system waveforms   FPGA and syntactic pattern recognition  

摘要： In this paper, an efficient hardware relay is presented that is implemented based on syntactic pattern recognition techniques. The proposed system is capable of detecting faults existing at power system waveforms in s, after reading each peak of the examined signal, aiming to reduce or even to totally prevent safety problems and economic losses. In order syntactic pattern recognition methods to be utilized as a recognition tool of waveforms at transmission lines, the tasks of selecting appropriate primitive patterns, determining the linguistic representation and forming a suitable grammar, should be developed. In this study, attribute grammars have been selected to model the examined signals due to their power to describe syntactic and semantic knowledge. The hardware implementation of the suggested relay, that stands on Earley's parsing algorithm, is developed using Verilog hardware description language, downloaded on a Virtex 7 XILINX FPGA board and evaluated through real waveforms and data received from IPTO. The obtained results have shown that the presented system could be an efficient alternative tool in the field of transmission lines' fault detection.

关键词： Pattern-triggered immunity   Pattern-recognition receptor   Receptor-like kinase   Type III secretion system   Type III effector  

摘要： Innate immune signaling of plants is initiated by pattern recognition receptors (PRRs) at the plasma membrane. Upon pathogen attack, PRRs recognize pathogen-associated molecular patterns (PAMPs) via ectodomain and lead to signaling cascade via cytoplasmic kinase domain. PAMP-triggered immunity (PTI) activates basal defense responses sufficient to confer broad-spectrum disease resistance by inhibiting pathogen entry and growth. On the other hand, one of the major virulence factors in plant-pathogenic bacteria is type III secretion system, which can deliver effector proteins into the host cell and modulate host cellular processes. Most type III effectors are implicated in PTI suppression, and PRRs have been identified as targets of multiple type III effectors. Mutants defective in T3SS lack pathogenicity in many bacterial species, revealing that T3SS-mediated PTI suppression is critical for host colonization and subsequent disease development. This review summarizes molecular basis of bacterial pathogen perception by plant PRRs and also interaction between PRRs and type III effectors during early stages of plant-pathogen interaction.

关键词： Intelligent building   Image processing   Satellite imagery   Building contours   Edge detection  

摘要： With the continuous development of urbanization, urban population, economy and other factors have a close impact on the geometry and distribution of urban buildings. Obtaining information of urban buildings from aerial images or satellite images quickly and accurately is not only conducive to updating geospatial data, but also of great significance for effective monitoring of new thematic information such as new buildings. Moreover, in recent years, the research and improvement of building recognition and contour extraction algorithms based on satellite images or aerial images are helpful to the recognition and classification of urban buildings. It is of great significance to the acquisition of GIS data, the understanding of images, large-scale mapping and many other applications of remote sensing data. With the development of artificial intelligence and computer technology, the image processing of intelligent building environment based on pattern recognition technology has become an important research direction in the field of intelligent building image recognition. Based on the concept, principle and technology analysis of pattern recognition technology, this paper studies the application of pattern recognition technology in the image processing of intelligent building environment. In this paper, based on image processing of intelligent building as the basic theoretical platform, with the pattern recognition technology as the basic research means, three problems of image processing, image extraction and image recognition in image processing of building intelligent environment are studied respectively, and corresponding reasonable solutions are put forward. (C) 2019 Published by Elsevier Inc.

关键词： Geological boundary   Pattern recognition   Well-log   Wavelet transform   Fractal parameter   Optimal wavelet function   ANOVA   Tukey multiple comparison  

摘要： The knowledge of geological strata sequences and their exact boundaries depths is of a great importance in the characterization of oil and gas reservoirs. The aim of automated well-to-well correlation approaches is to facilitate and accelerate the procedure of geological boundary detection. In this study, we implement an automatic well-to-well correlation approach based on pattern extraction from well-logs. The well-log patterns are recognized by calculating several statistical and fractal parameters. As a fractal parameter, we select the wavelet standard deviation exponent, calculated by the discrete wavelet transform. Furthermore, to select the proper wavelet function, as the heart of wavelet transform, the energy to Shannon entropy ratio criterion is implemented. The statistical pattern recognition parameters of this study include average value, maximum to minimum ratio, coefficient of variation, and the trend angle of well-log data (i.e., Gamma ray log) in a window around the geological boundary. Moreover, the analysis of variance (ANOVA) tool and the Tukey multiple comparison method are implemented to evaluate the effectiveness of each parameter (i.e., fractal or statistical parameters) during the determination of boundary depths. The gamma ray logs from three wells of an oil field are used as a dataset for the evaluation of our algorithm. The outputs of our methodology are also compared with the new detrended fluctuation analysis (DFA) method, which show promising outcomes over it. The results show that the average value of the signal, among the analyzed parameters, is the most effective parameter;however, implementing the combination of all fractal and statistical parameters can improve the accuracy of the geological boundary detection.

关键词： Discrete wavelet transform   artificial neural network   motion recognition   vibration  

摘要： This paper presents a wavelet-neural network recognition system for personal fitness assistance and elderly daily activity monitoring applications. This discrete wavelet transform radial basis neural network (DWT-RBNN) analyzes vibration induced by human motions, and identifies motion status automatically. The 3-D vibration signals are measured by integrated accelerometer chip, and then DWT extracts vibration features. Local energy of extracted feature is calculated and used by RBNN. A multi-channel RBNN is designed and used for recognition. The computation burden is reduced because of the DWT pre-processing. From experiment results, RBNN shows successful recognition capability. This paper also presents flow diagram to determine engineering parameters for the present and future product developments.

关键词： Minimax probability machine   Extreme learning machine   Empirical risk   Second-order cone programming   Chebyshev-Cantelli inequality  

摘要： In this work we propose a minimax probability extreme learning machine framework (MPME), which combines the benefits of minimax probability machine (MPM) with extreme learning machine (ELM). For binary classification problems, we illustrate that the proposed MPME can be interpreted geometrically by minimizing the maximum of Mahalanobis distances to the two classes. Then two variants of the MPME are presented based on the l(2)-norm loss and l(1)-norm loss functions (called LSEMPME and LADMPME) respectively. Without making specific assumption on the data distribution, the proposed methods can provide explicit upper-bounds for the generalization error, moreover the LSEMPME and LADMPME minimize empirical risk simultaneously. The decision hyperplanes of the proposed methods pass through the origin in ELM feature space with few decision variables. By using the multivariate Chebyshev-Cantelli inequality, all the proposed problems can be reformulated as second-order cone programming (SOCP) with global solutions. Furthermore, numerical experiments have been carried out on two databases that are drawn from UCI benchmark database and a practical application database. First, the proposed methods are evaluated for a practical application consisting on the analysis of licorice seeds using near-infrared spectral (NIR) data. Experiments in six different spectral regions illustrate that the proposed methods can improve generalization in most cases. Then the proposed methods are evaluated on benchmark datasets. In comparison with traditional methods including MPM, ELM and support vector machine (SVM), experiments show that the proposed methods achieve comparable results in generalization. With few decision variables, the proposed methods are easy to implement for nonlinear classification and to estimate a lower-bound on the prediction accuracy.

关键词： Mandarin   Word order   Case   Topic   Nominative-accusative   Ergative-absolutive  

摘要： The typological classification of Mandarin Chinese as an isolating language lacking inflection brings about a theoretical consideration that word order in Mandarin serves as an interface between syntax and pragmatics. This paper provides from typological perspective a unified framework to examine the role that word order in Mandarin plays in marking case as well as topics. The study finds that Mandarin exhibits a mixed case-marking pattern through word order, namely that nominative-accusative pattern coexists with ergative-absolutive pattern. Both of the two case-marking patterns allow intra-clausal topics and extra-clausal topics, and it is the intra-clausal topics rather than the extra-clausal ones that are associated with case-marking patterns. With respect to the intra-clausal topics, in nominative accusative pattern, topic assignment in unmarked constructions is A/S oriented, whereas in ergative-absolutive pattern, topic assignment in unmarked two/three-argument constructions is post-ba P oriented, and topic assignment in unmarked one-argument constructions is preverbal-S oriented. In light of the two case-marking patterns, context-independent topics in various constructions can be identified, and thus the controversial issue of distinguishing topics from other arguments can be properly addressed. (C) 2019 Elsevier B.V. All rights reserved.

关键词： bortezomib   differential diagnosis   drug-induced liver injury   hepatitis   injury phenotype   reactivation  

摘要： Background Competing causes of liver injury may be difficult to discriminate. Characterization of the typical phenotype of each injury defined by latency, time to improvement and biochemical pattern, could be helpful to identify the most likely of competing causes. Methods Liver injury characteristics of both bortezomib-associated drug-induced liver injury (DILI) and hepatitis B virus (HBV) reactivation associated with bortezomib are derived from PubMed listed publications. Results Bortezomib-associated DILI has very short latency of days and AP is found elevated, while liver injury due to HBV reactivation occurs after several months of bortezomib therapy. Therefore, a patient's liver injury pattern occurring 3 months into bortezomib therapy should be attributed to HBV reactivation. Discussion Identification of liver injury characteristics for competing causes of liver injury can be helpful to identify the most likely cause and improve clinical outcome.

关键词： 模式识别   规则提取   特征选择优化   句法语义互动   属性重要度分析  

摘要： 该文以形式观念分析理论为支撑,以属性结构偏序图为工具,探讨英语情态动词语义排歧中的知识发现,提出进行英语情态动词的知识发现分的五个层次和五个视角。五个层次为:语言学准备层,数据采集层,数据预处理层,形式概念分析层和知识发现层;五个视角为:语义模式识别,语义规则提取,特征选择优化,句法与语义互动关系,属性重要度分析。该文提出的情态动词语义排歧中知识发现框架,既可以其他复杂语义词的知识发现,也可以应用到机器翻译和其他自然语言处理领域。