Fault estimation observer design for discrete‐time systems in finite‐frequency domain

This paper proposes a framework of fault estimation observer design in finite‐frequency domain for discrete‐time systems. First, under the multiconstrained idea, a full‐order fault estimation observer in finite‐frequency domain is designed to achieve fault estimation by using the generalized Kalman–Yakubovich–Popov lemma to reduce conservatism generated by the entire frequency domain. Then, a reduced‐order fault estimation observer is constructed, which results in a new fault estimator to realize fault estimation using current output information. Furthermore, by introducing slack variables, improved results on full‐order fault estimation observer and reduced‐order fault estimation observer design with finite‐frequency specifications are obtained such that different Lyapunov matrices can be separately designed for each constraint. Simulation results are presented to illustrate the advantages of the theoretic results obtained. Copyright © 2014 John Wiley & Sons, Ltd.     

Effective composite image detection method based on feature inconsistency of image components

This paper proposes an effective composite image detection method that uses the feature inconsistency of image components of the composite image to detect tampered regions. The composite image is first divided into image components. Next, the variance of the noise remaining after de-noising in each image component is calculated and used as a feature. Finally, tampered regions are detected using this feature based on a tampering detection rule. Experimental results show that the proposed method has good composite image detection performance.     

Utilizing linguistically enhanced keystroke dynamics to predict typist cognition and demographics

Entering information on a computer keyboard is a ubiquitous mode of expression and communication. We investigate whether typing behavior is connected to two factors: the cognitive demands of a given task and the demographic features of the typist. We utilize features based on keystroke dynamics, stylometry, and “language production”, which are novel hybrid features that capture the dynamics of a typists linguistic choices. Our study takes advantage of a large data set (~350 subjects) made up of relatively short samples (~450 characters) of free text. Experiments show that these features can recognize the cognitive demands of task that an unseen typist is engaged in, and can classify his or her demographics with better than chance accuracy. We correctly distinguish High vs. Low cognitively demanding tasks with accuracy up to 72.39%. Detection of non-native speakers of English is achieved with F₁=0.462 over a baseline of 0.166, while detection of female typists reaches F₁=0.524 over a baseline of 0.442. Recognition of left-handed typists achieves F₁=0.223 over a baseline of 0.100. Further analyses reveal that novel relationships exist between language production as manifested through typing behavior, and both cognitive and demographic factors.     

基于内容分析的网络新闻中社会网络自动抽取

本文针对网络新闻报道,提出了一种基于文本内容分析的社会网络自动抽取方法。此方法在对输入文章进行分词标注、共指消解等预处理之后,通过名词合并及主动词识别,得到存在关系的命名实体之间的关系指向和关系描述,最后通过有向图把存在关系的命名实体进行连接,形成由命名实体、实体间关系指向、实体间关系描述构成的关系网络。试验结果表明该方法对新闻中的命名实体关系抽取比较有效。     

Optimistic Byzantine fault tolerance

The primary concern of traditional Byzantine fault tolerance is to ensure strong replica consistency by executing incoming requests sequentially according to a total order. Speculative execution at both clients and server replicas has been proposed as a way of reducing the end-to-end latency. In this article, we introduce optimistic Byzantine fault tolerance. Optimistic Byzantine fault tolerance aims to achieve higher throughput and lower end-to-end latency by using a weaker replica consistency model. Instead of ensuring strong safety as in traditional Byzantine fault tolerance, nonfaulty replicas are brought to a consistent state periodically and on-demand in optimistic Byzantine fault tolerance. Not all applications are suitable for optimistic Byzantine fault tolerance. We identify three types of applications, namely, realtime collaborative editing, event stream processing, and services constructed with conflict-free replicated data types, as good candidates for applying optimistic Byzantine fault tolerance. Furthermore, we provide a design guideline on how to achieve eventual consistency and how to recover from conflicts at different replicas. In optimistic Byzantine fault tolerance, a replica executes a request immediately without first establishing a total order of the message, and Byzantine agreement is used only to establish a common state synchronization point and the set of individual states needed to resolve conflicts. The recovery mechanism ensures both replica consistency and the validity of the system by identifying and removing the operations introduced by faulty clients and server replicas.     

基于超熵产生的河型稳定判别式

基于非平衡态热力学理论中的超熵产生研究河型的稳定性,对河型是否有可能转化做出定量判别分析。选择河流系统的广义力和广义流,构造出河流的超熵产生以及超能耗率,根据超能耗率推导出河型稳定判别式。应用该判别式分析了黄河下游5个河段3种不同河型的稳定性,计算结果表明这5个河段的河型是稳定的,近期没有发生河型转化的可能性,与实际情况相符。利用该河型稳定判别式,不仅可判别河型的稳定性,还可以预测河流调整方向,为河流整治工程提供科学依据。     

新疆汉水泉地区地下水环境背景值计算

以新疆汉水泉地区为研究区,依据其水文地质条件,将其划分为两个相对独立的水文地质单元——库木苏洼地和汉水泉洼地,采集该地区39组地下水水样,研究该地区的地下水环境背景值。采用格鲁布斯检验法剔除采集样本中的异常数据,库木苏洼地剔除异常指标1个,汉水泉洼地剔除异常指标13个。采用夏皮洛—威尔克检验法判断地下水化学组分含量频数分布类型,结果表明:库木苏洼地和汉水泉洼地以正态分布和对数正态分布居多,偏态分布较少。通过对整个汉水泉地区地下水组分含量的分析,得出汉水泉地区地下水环境的背景值,分析结果表明:研究区微量元素的检出率不高,表示其受污染程度较低。     

活动断裂对新建集镇选址规划的影响——以乌东德水电站库区移民集镇选址为例

活动断裂附近地质条件复杂,在其附近进行新城镇选址时必须明确活动断裂对场地和建筑可能带来的不利影响。以金沙江乌东德水电站库区移民集镇选址为例,依照规范要求,综合地质调查、物探、勘探等手段,查明了元谋活动断裂的分布及特征;对其可能产生的震害类型及程度进行了分析;结合地质条件对规划场地工程建设的适宜性进行了分区;明确了活动断裂对场地和建筑物的影响,为合理设防、规避震害奠定了基础。可为类似新建城镇选址规划提供借鉴。      

Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis

 Envelope analysis is an effective method for characterizing impulsive vibrations in wired condition monitoring (CM) systems. This paper depicts the implementation of envelope analysis on a wireless sensor node for obtaining a more convenient and reliable CM system. To maintain CM performances under the constraints of resources available in the cost effective Zigbee based wireless sensor network (WSN), a low cost cortex-M4F microcontroller is employed as the core processor to implement the envelope analysis algorithm on the sensor node. The on-chip 12 bit analog-to-digital converter (ADC) working at 10 kHz sampling rate is adopted to acquire vibration signals measured by a wide frequency band piezoelectric accelerometer. The data processing flow inside the processor is optimized to satisfy the large memory usage in implementing fast Fourier transform (FFT) and Hilbert transform (HT). Thus, the envelope spectrum can be computed from a data frame of 2048 points to achieve a frequency resolution acceptable for identifying the characteristic frequencies of different bearing faults. Experimental evaluation results show that the embedded envelope analysis algorithm can successfully diagnose the simulated bearing faults and the data transmission throughput can be reduced by at least 95% per frame compared with that of the raw data, allowing a large number of sensor nodes to be deployed in the network for real time monitoring.