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.     

An intelligent stock trading system using comprehensive features

The aim of this study is to predict automatic trading decisions in stock markets. Comprehensive features (CF) for predicting future trend are very difficult to generate in a complex environment, especially in stock markets. According to related work, the relevant stock information can help investors formulate objects that may result in better profits. With this in mind, we present a framework of an intelligent stock trading system using comprehensive features (ISTSCF) to predict future stock trading decisions. The ISTSCF consists of stock information extraction, prediction model learning and stock trading decision. We apply three different methods to generate comprehensive features, including sentiment analysis (SA) that provides sensitive market events from stock news articles for sentiment indices (SI), technical analysis (TA) that yields effective trading rules based on trading information on the stock exchange for technical indices (TI), as well as the trend-based segmentation method (TBSM) that raises trading decisions from stock price for trading signals (TS). Experiments on the Taiwan stock market show that the results of employing comprehensive features are significantly better than traditional methods using numeric features alone (without textual sentiment features).     

Web交互模型的形式化验证研究

Web交互模型的形式化验证是对Web事件属性进行校验的十分可信的方法。通过一系列的系统模型建立、系统行为分析以及对于模型中关心属性的相关验证,能够让交互模型在设计阶段就能使形式化模型暴露出其所存在的缺陷,而不至于让缺陷保留到编码阶段或者更后面才能被真正地暴露出来,这样使系统模型的生存能力更加强大,同时避免了因后期缺陷暴露而出现的大代价修复。通过对Web系统的交互应用服务的过程模型化的体系进行研究,通过模型本身具有的属性进行相关正确性的校验,主要通过使用数学推理实现系统逻辑上的服务交互进程,从而进行过程的推演,并对系统服务的正确性进行过程的形式化验证,从而使系统服务模块的属性正确性可以通过逻辑上的演进来发现服务问题的存在,而不再是系统通过编码实现后才发现。对Web交互模型的形式化验证是基于IMWSC模型语义形成的IMWSC模型的验证机制。     

多特征文本蕴涵识别研究

文本蕴涵识别是解决自然语言中存在的同义异形问题的有效途径。虽然国内外学者已经提出了很多文本蕴涵识别模型,但影响文本蕴涵识别的因素错综复杂,识别准确率普遍不高。该文把文本蕴涵识别看作二元分类问题,抽取词汇特征、句法依存关系特征及FrameNet语义知识库特征的多种特征构造特征矩阵,训练SVM分类器,实现文本蕴涵识别。该方法在国际文本蕴涵识别技术评测RTE3的测试集上进行测试,蕴涵正例识别准确率达到了78.1%,高于RTE3评测2-ways的最高结果。     

Low-Power Operational Amplifier for Real-Time Signal Processing System of Micro Air Vehicle

A low-power complementary metal oxide semiconductor(CMOS) operational amplifier (op-amp) for real-time signal processing of micro air vehicle (MAV) is designed in this paper. Traditional folded cascode architecture with positive channel metal oxide semiconductor(PMOS) differential input transistors and sub-threshold technology are applied under the low supply voltage. Simulation results show that this amplifier has significantly low power, while maintaining almost the same gain, bandwidth and other key performances. The power required is only 0.12mW, which is applicable to low-power and low-voltage real-time signal acquisition and processing system.     

电爆炸过程中金属丝电阻变化规律的仿真分析

探讨了电爆炸过程中金属丝相关参数的变化规律,建立了金属丝电阻在气化前的PSpice模型,得到了电容器初始电压由10 kV到20 kV、回路电感由3.9μH到10.8μH、金属丝直径由0.3 mm到1 mm变化时,金属丝电阻变化的仿真结果。对仿真结果分析表明：初始参数影响金属丝上的能量沉积,决定着金属丝的电阻变化过程以及金属丝完全气化所需要的时间。     

电磁领域中复超越方程的遗传算法求解方法

将遗传算法与参数跟踪策略有效结合,跟踪过程中进行搜索域压缩与位移操作,形成了一种功能强大的新算法,可成功应用于电磁领域中各种各样复超越方程的高精度求解问题.在算法实现过程中,使用参数跟踪策略有效地缩小了搜索区域,保证了解的单一性,提高了运算速度;使用动态搜索域提高了解的精度;应用三阶差商公式预估新的搜索中心,使运算速度得以进一步提高.应用本文发展的算法详细求解了终端短路法测量材料的复介电常数时得到的复超越方程和部分填充矩形波导的特征方程,计算结果表明该算法能够轻松地解决复超越方程中的多值问题,解集完备性好,算法鲁棒性强.     

Robust and Low-Complexity Synchronization for Energy Detection UWB Receiver

A simple method using aided sliding rectangular windows for synchronization in e nergy detector (ED) receiver is proposed for impulse-based ultra wideband radio s (IR-UWB) under binary pulse position modulation (PPM), therefore grants an at tractive solution for gaining low complexity while the accompanying performance loss in terms of UWB signal reception is comparatively low. Also, a method is de veloped to suppress noise through accumulation of integrated results before sync hronization point is reached....     

Fast Approaches for Sub-pixel Precision Variable Block Size Motion Estimation

The new features of H.264 video coding standard make the motion estimation module much more time consuming than before.Especially,the motion search is required for each of the 4 modes for inter prediction.In order to reduce the computational complexity,we analyze the statistics of results of motion estimation,such as the continuity of best modes of blocks in successive frames and the chance to give up a sub-partition mode(smaller than 16×16)after integer-pixel motion estimation,from which we suggest to make...     

Research and Application of Broad-Storage Architecture in Digital Television System

A new dual-mode transmission networks(DMTN)based on broad-storage architecture for digital television(DTV)is proposed,in which the primary TV network is superimposed by a complementary framework based on broad-storage TV(BSTV).The necessity of congregating hot TV resources is discussed via analyzing the scale-free properties in DMTN.The self-organized parallel broadcasting technology(SPBT)and the uniform content locator(UCL)are studied to utilize availably transmission channels and to help consumers to comm...