Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners

Fingerprints are the oldest and most widely used biometrics for personal identification. Unfortunately, it is usually possible to deceive automatic fingerprint identification systems by presenting a well-duplicated synthetic or dismembered finger. This paper introduces one method to provide fingerprint vitality authentication in order to solve this problem. Detection of a perspiration pattern over the fingertip skin identifies the vitality of a fingerprint. Mapping the two-dimensional fingerprint images into one-dimensional signals, two ensembles of measures, namely static and dynamic measures, are derived for classification. Static patterns as well as temporal changes in dielectric mosaic structure of the skin, caused by perspiration, demonstrate themselves in these signals. Using these measures, this algorithm quantifies the sweating pattern and makes a final decision about vitality of the fingerprint by a neural network trained by examples.     

Improved direct bonding method of Nd:YVO4 and YVO4 laser crystals

We succeeded in the fabrication of bonded laser crystals composed of a neodymium-doped YVO₄ laser crystal (Nd:YVO₄) and its host crystals YVO₄ by a newly developed dry etching technique using an argon ion beam. The optical distortion caused by the bonded interface of size 5 mm × 6 mm was estimated to be 0.05λ at 633 nm. From the comparison of laser performance pumped by a laser diode, the bonded crystals could increase the laser output power by nearly twice that of the non-bonded crystals with the same degree of polarization of 99.2%. To analyze the mechanism of the enhanced reduction of the thermal load in the bonded crystals, numerical simulations with a finite-element method were also performed.     

A neural network model for fault detection in conjunction with a programmable logic controller

This paper discusses the feasibility of using neural networks as a tool in the fault detection process. A neural network is integrated with a state language programmable logic controller, an important device in an automatic control system. Time series data related to time spent in a state is gathered and used as input into a neural network, for the purpose of identifying when a fault has occurred. A feedforward neural network is used to identify which (if any) of three types of faults may have occurred. Experimental results related to sensitivity and accuracy measures are presented. A brief review of related applications and research is also presented.     

神经网络分类器的快速构造算法

使用ＢＰ算法训练多层网络的速度很慢而且事先难于确定隐节点和隐层的适当数目。本文提出一个有效的算法，先构造决策树，然后将构造的决策树转换为神经网。文中使用一个全局准则函数控制决策树的增长，它较好地匹配了树的复杂性和训练样本量及错分率界。实验结果，本文的算法比用ＢＰ算法训练多层网络要快，而其分类精度不低于用ＢＰ算法训练的多层神经网。     

PMMA／PBA乳胶IPN阻尼材料的研究

用乳液聚合方法合成了一系列的互穿聚合物网络，其中包括：ＰＭＭＡ／ＰＢＡ和Ｐ（ＭＭＡ－ｃｏ－ＰＭＡ）／ＰＢＡ乳胶互穿聚合物网络（ＬＩＰＮ），ＰＭＭＡ／ＰＢＡ乳胶双向互穿聚合物网络（ＬＢＩＰＮ）以及ＰＭＭＡ／ＰＢＡ界面交联互穿聚合物网络（ＩＣＬＩＰＮ）。动态力学谱和拉伸试验结果表明：（１）ＰＭＭＡ／ＰＢＡ互穿聚合物网络的两组分相容性和阻尼性能可通过ＭＭＡ和ＰＭＡ共聚来改善；（２）双向互穿技术是一种行之     

聚苯醚磺酸锂／共聚醚复合物的离子导电性研究

合成了３种不同磺化度的聚苯醚磺酸锂（ＳＰＰＯＬｉ）与Ｐ（ＭＥＯ１６－ＡＭ）／ＳＰＰＯＬｉ复合物。研究了复合物的离子导电性与磺化度，组成比及增塑剂含量的关系。含４０％（ｍａｓｓ）增塑剂的复合物具有单离子导电特征，锂离子迁移数高达０．９７，室温电导率达２×１０－５Ｓ／ｃｍ。     

CFRP强度复合Weibull分布的物理特征分析

本文对ＣＦＲＰ材料疲劳后剩余强度的复合Ｗｅｉｂｕｌｌ分布的物理特征进行了初步分析。指出树脂基复合材料失效（破坏）机理的双重性（基体和纤维失效模型）决定了剩余强度（累积损伤程度）测试结果的分布特征。复合Ｗｅｉｂｕｌｌ分布曲线的特征与分析结果对设计、使用及材料研究都有重要参考意义。     

高分辨裂解气相色谱－质谱研究聚吡咙的热分解

用高分辨裂解气相色谱－质谱考察了不同聚吡咙的热分解，分析了其热分解产物的组成、分布和归属，研究了其环化过程以及该过程对热分解的影响，进而详细阐述了聚吡咙的热分解机理。     

硼／铝复合材料管构件的界面特性EI

主要研究带钛合金连接头硼／铝复合材料管构件中Ｂ－Ａｌ－Ｔｉ间的界面结构与性质。研究表明，在复合工艺条件下，硼－铝界面附近没有检测到任何铝－硼化合物，而钛－铝间形成ＴｉＡｌ有序金属间化合物相。实验证明，硼／铝复合材料与铝合金端环之间采用的固结方法是有效的，且可按照受载类型随意调整斜面搭接长度，达到承受不同载荷的目的。     

实现CDMA最佳多用户检测的神经网络方法

提出并讨论了两种实现码分多址系统中最佳多用户检测的神经网络方法。一种基于离散Ｈｏｐｆｉｅｌｄ神经网络，另一种基于采用反向传播算法的多层感知器神经网络。理论分析和计算机模拟都证实了这两种神经网络方法的可行性，优越性和实用性。前者适用“固定”用户情况；后者既可用于“固定”用户吼适用于移动用户的情况，因而在未来的ＣＤＭＡ个人通信网中有较好的应用前景。