Fast fingerprint identification for large databases

Fingerprint matching has emerged as an effective tool for human recognition due to the uniqueness, universality and invariability of fingerprints. Many different approaches have been proposed in the literature to determine faithfully if two fingerprint images belong to the same person. Among them, minutiae-based matchers highlight as the most relevant techniques because of their discriminative capabilities, providing precise results. However, performing a fingerprint identification over a large database can be an inefficient task due to the lack of scalability and high computing times of fingerprint matching algorithms.In this paper, we propose a distributed framework for fingerprint matching to tackle large databases in a reasonable time. It provides a general scheme for any kind of matcher, so that its precision is preserved and its time of response can be reduced.To test the proposed system, we conduct an extensive study that involves both synthetic and captured fingerprint databases, which have different characteristics, analyzing the performance of three well-known minutiae-based matchers within the designed framework. With the available hardware resources, our distributed model is able to address up to 400 000 fingerprints in approximately half a second. Additional details are provided at http://sci2s.ugr.es/ParallelMatching.     

New results on PWARX model identification based on clustering approach

This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.     

Closed‐Loop Identification for Control of Linear Parameter Varying Systems

This paper deals with system identification for control of linear parameter varying systems. In practical applications, it is often important to be able to identify small plant changes in an incremental manner without shutting down the system and/or disconnecting the controller; unfortunately, closed‐loop system identification is more difficult than open‐loop identification. In this paper we prove that the so‐called Hansen scheme, a technique known from linear time‐invariant systems theory for transforming closed‐loop system identification problems into open‐loop‐like problems, can be extended to accommodate linear parameter varying systems as well. We investigate the identified subsystem's parameter dependency and observe that, under mild assumptions, the identified subsystem is affine in the parameter vector. Various identification methods are compared in direct and Hansen Scheme setups in simulation studies, and the application of the Hansen Scheme is seen to improve the identification performance.     

Fatty acid esterification by reactive distillation: Part 2—kinetics-based design for sulphated zirconia catalysts

In a previous study on the basis of reaction equilibrium, it was demonstrated that the synthesis of fatty acids esters of heavy alcohols by catalytic reactive distillation (RD) is basically feasible. Presently, the analysis is expanded to the kinetics-based design applied to the synthesis of 2-ethylhexyl dodecanoate. Experimental data for a super-acidic sulphated zirconia catalyst are employed. It is shown that this catalyst is highly selective even for the high alcohol/acid ratios as prevail in a RD column. To avoid catalyst deactivation, liquid-liquid segregation into an organic and an aqueous phase must be prevented, and operating temperatures beyond must be chosen. A kinetic model based on liquid activities is proposed, with parameters determined from both kinetic and equilibrium measurements. A typical column design has 13 reactive stages with a catalyst loading of , temperature profile of 400-, and a space velocity of for 99.9% purity product ester. A modified Damköhler number is proposed.     

基于逐层剪枝的中文高频重复模式快速提取算法

为了从大规模语料中快速提取高频重复模式,以递增n-gram模型为基础,使用散列数据结构提取重复串,并提出了一种基于低频字符和层次剪枝的逐层剪枝算法,用于过滤低频垃圾字串,减少I/O读写次数。在此基础上,应用改进的字串排序算法,使字符串排序可在O(n)时间内完成,从而有效提高重复模式的提取效率。实验表明,该算法是一种有效的重复模式提取算法,其I/O读写次数同语料规模呈线性关系,远小于使用首字符进行语料划分的方法,能快速有效地从规模远大于内存容量的文本语料中提取重复模式,特别适合于大规模语料的高频重复模式提取,对以重复模式为基础的新词识别、术语抽取等具有重要的支撑作用。     

最大熵和条件随机场模型相融合的藏文人名识别

藏文人名识别是藏文信息处理领域研究的难点之一,其识别效果直接影响到藏文自动分词的精度和相关应用系统的性能,包括藏汉翻译、藏文信息检索、文本分类等。该文在分析藏文人名构成规律和特点的基础上,提出了一种最大熵和条件随机场相融合的藏文人名识别方法。实验表明,该方法可以获取较好的识别效果,在我们的测试集上F-测度值到达了93.08%。     

指纹识别PDA的设计与实现

PDA是一种轻便、灵巧,具有很强的可移动性的设备,随着指纹技术的发展。其已经在金融保险、门禁、身份识别等领域得到了广泛的应用,详细地分析了指纹识别PDA设计的功能,并且详细地分析了指纹采集、指纹预处理、指纹特征提取、指纹识别等核心技术,设计实现了一个功能强大的指纹识别PDA。     

基于支持向量回归的动力电池参数辨识

根据铅酸蓄电池在放电过程中内部电化学反应导致外部电特性变化的特点,提出一种基于支持向量机原理的电解液密度辨识模型。利用支持向量机理论非线性回归的特性,简化测量电解液密度的过程,在恶劣环境下检测动力电池的电解液密度更显其优越性。预测实验表明,采用改进的交叉验证预测模型具有泛化能力强、稳定性好的特点,并且在小样本的条件下能达到预期的辨识精度。     

基于硬件滤波电路的无刷直流电机转子位置辨识

反电动势过零检测是无刷直流电机无位置传感器控制中转子位置检测的主要方法之一,为消除PWM因素的影响,需要对转子位置检测电路进行滤波处理。本文采用硬件滤波器对反电动势过零检测电路进行滤波,既要考虑深度滤波带来的相移问题又要兼顾消除噪声的影响,分析滤波器的幅频特性和相频特性,根据反电动势过零检测指标要求设计滤波器参数,并用于无刷直流电机转子位置辨识和无位置传感器控制中。仿真结果和实验结果表明,所采用的滤波器及其参数能较好地检测出转子位置,可以明显提高无位置传感器无刷直流电机驱动系统的控制性能。     

使用程序静态分析技术识别Web程序中的用例结构

本文利用程序静态分析技术对Web程序中的用例识别进行了深入研究。对Web页面的用户行为进行了深入分析并建模,从行为模型中提取出描述整个系统中用户行为的事件流图,结合采用现有的从目的成功语句出发、以必经结点为基础的用例识别方法,从各个Web页面中提取的独立控制流图,形成全局控制流图,进行全局用例识别。与以前已有工作相比,本文考虑了Web程序的特点,尤其是前端程序如何实现用户行为,并在前端程序中进行精确的用例识别。本文采用目前使用较为广泛的JSP程序进行了实验,结果表明该方法能够有效识别JSP程序中的用例结构。