磁盘阵列环境下的取证目标系统重构

封存原始硬盘与业务系统服务的连续性是计算机取证中面临的一对矛盾。在独立硬盘环境中,问题的解决并不困难,但在磁盘阵列(RAID)环境下,目前还缺乏有效的解决办法。为此,为RAID环境下的取证目标系统的重构提出一套解决方案,并设计实现其中关键任务的处理软件。实验表明,该方法可适用于不同RAID等级、不同操作系统下的系统重构,使得用户感受不到重构得到的系统与原系统有任何差异。与数据同步方法相比,该方法可以有效地减少重构的时间开销,且不会破坏原始证据硬盘上的数据。     

角蛋白基药物载体的发展及应用探讨

从毛发中提取角蛋白，开发具有独特功能的角蛋白基药物载体材料，提高药物的活性和生物利用率，既能够增加毛发的利用价值，又能够实现节能减排，符合可持续发展战略要求。对毛发中提取角蛋白进行二硫键重建、自由基聚合、多糖改性和烷基化等改性处理，赋予角蛋白基药物载体优异地功能特性，进一步拓宽其作为角蛋白基药物载体的应用范围。角蛋白基药物载体可被加工成纳米粒子、纤维支架、水凝胶等各种形式用于药物的递送。作为一种高硫含量且具有良好细胞相容性的结构蛋白，角蛋白基药物载体在组织工程、再生医学等领域扮演着重要的角色。     

相空间重构在语音情感识别中的研究

为了更为全面地表征语音情感状态,弥补线性情感特征参数在刻画不同情感类型上的不足,将相空间重构理论引入语音情感识别中来,通过分析不同情感状态下的混沌特征,提取Kolmogorov熵和关联维作为新的情感特征参数,并结合传统语音特征使用支持向量机（SVM）进行语音情感识别。实验结果表明,通过引入混沌参数,与传统物理特征进行识别的方案相比,准确率有了一定的提高,为语音情感的识别提供了一个新的研究途径。     

动态信号分析系统自动化校准方法研究

实现动态信号分析系统的自动化校准,需要分析处理的数据量极大,消耗计算机系统资源大且处理时间长。采用Lab View设计了一套自动化校准软件,可以有效缩短数据处理长度,提高处理速度。该软件分为数据采集模块和数据分析模块,被检动态信号分析系统连续采集标准信号源所发的信号,将采集数据保存为文本文件或电子表格文件,通过LAN将其载入数据分析模块。数据分析模块查找各校准点的初始有效索引,提取有效的校准数据段,然后采用逐段分析方法处理数据。将实验测试结果与采用常规方法的测试结果对比,该方法可以正确计算其频谱幅值线性误差、频谱幅值示值误差和幅频特性等参数,且需要的时间缩短为常规方法的40%,实现了动态信号分析系统的自动化校准。     

艾立许混捏机在炭阳极生产中的应用

在预焙阳极生产中，卧式连续混捏机曾经大量应用，使用效果良好。目前艾立许混捏机以其简化机械设计、降低维修及操作成本等许多独特的优点，在铝电解炭阳极生产中也得到大量应用。通过对原有卧式混捏机设备增加艾立许冷却系统，可以使两种设备得到最佳组合，可提高阳极质量，取得良好效益。     

Order-k α-hulls and α-shapes

We introduce order-k α-hulls and α-shapes – generalizations of α-hulls and α-shapes. Being also a generalization of k-hull (known in statistics as “k-depth contour”), order-k α-hull provides a link between shape reconstruction and statistical depth. As a generalization of α-hull, order-k α-hull gives a robust shape estimation by ignoring locally up to k outliers in a point set. Order-k α-shape produces an “inner” shape of the set, with the amount of “digging” into the points controlled by k. As a generalization of k-hull, order-k α-hull is capable of determining “deep” points amidst samples from a multimodal distribution: it correctly identifies points which lie outside clusters of samples.The order-k α-hulls and α-shapes are related to order-k Voronoi diagrams in the same way in which α-hulls and α-shapes are related to Voronoi diagrams. This implies that order-k α-hull and α-shape can be readily built from order-k Voronoi diagram, and that the number of different order-k α-shapes for all possible values of α is proportional to the complexity of order-k Voronoi diagram.     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

A distributed solution to the network reconstruction problem

It has been recently shown in Ren et al. (2010) that by collecting noise-contaminated time series generated by a coupled-oscillator system at each node of a network, it is possible to robustly reconstruct its topology, i.e. determine the graph Laplacian. Restricting ourselves to linear consensus dynamics over undirected communication networks, in this paper we introduce a new dynamic average consensus least-squares algorithm to locally estimate these time series at each node, thus making the reconstruction process fully distributed and more easily applicable in the real world. We also propose a novel efficient method for separating the off-diagonal entries of the reconstructed Laplacian, and examine several concepts related to the trace of the dynamic correlation matrix of the coupled single integrators, which is a distinctive element of our network reconstruction method. The theory is illustrated with examples from computer, power and transportation systems.     

基于灰度形态重构的颗粒图像分割方法

提出了一种基于距离变换、形态重构和分水岭算法的图像分割算法。将一幅图像通过距离变换得到距离灰度图,与形态重构算法结合,得到颗粒图像的标识点图,用标识点图对距离灰度图进行分割,再用分水岭变换对分割后的距离灰度图进行变换。试验表明,该算法能有效合理地解决粘连或者重叠颗粒等物体的分割。