分块二维局部保持鉴别分析在人脸识别中的应用

局部保持鉴别分析在人脸识别研究中具有非常重要的地位。在此基础上提出的2DLPDA算法直接在二维空间进行运算,一定程度上提高了性能。但是当样本在光照阴影、遮挡等情况下时,识别率受到很大影响,为此提出一种改进的算法,即分块二维局部保持鉴别分析方法。其将样本分块,以更好地提取样本中的局部近邻特征。这样同一样本的不同分块在选择近邻时,就可能具有来自不同样本的近邻,从而能更好地提取样本的局部特征。最后将局部特征整合为整体作为识别的依据。在AR、YALE及ORL库上验证了算法的有效性。     

Security optimal power flow considering loading margin stability using hybrid FFA–PS assisted with brainstorming rules

This paper presents a new power system planning strategy which combines firefly algorithm (FFA) with pattern search algorithm (PS). The purpose is minimizing total fuel cost, total power loss and reducing total voltage deviation, with the objective of enhancing the loading margin stability and consequently the power system security. A new interactive and simple mechanism, inspired in brainstorming process, is proposed that allows FFA and PS algorithms to explore new regions of the search space. In this study the Static VAR compensator (SVC) is modeled and integrated in an efficient location which is chosen considering the voltage stability index. The proposed algorithm is interactive and tries to optimize a set of control variables at the same time, namely, active power generations, voltage of generators, tap transformers, and the reactive power of shunt compensators to optimize three objective functions such as: fuel cost, total power loss and total voltage deviation. These variables are optimized using a flexible interactive and competitive search mechanism. The proposed planning strategy has been examined and applied to two practical test systems IEEE 14-Bus and IEEE 30-Bus. Simulation results confirm the effectiveness of this hybrid strategy for solving the security optimal power flow.     

Fabrication and characterization of APT specimens from high dose heavy ion irradiated materials

The next generations of advanced energy systems will require materials that can withstand high doses of irradiation at elevated temperatures. Therefore, a methodology has been developed for the fabrication of high-dose ion-irradiated atom probe tomography specimens at a specific dose with the use of a focused ion beam milling system. The method also enables the precise ion dose of the atom probe tomography specimen to be estimated from the local concentration of the implanted ions. The method has been successfully applied to the characterization of the distribution of nanoclusters in a radiation-tolerant 14YWT nanostructured ferritic steel under ion irradiation to doses up to 400 displacements per atom.     

Towards high accuracy calibration of electron backscatter diffraction systems

For precise orientation and strain measurements, advanced Electron Backscatter Diffraction (EBSD) techniques require both accurate calibration and reproducible measurement of the system geometry. In many cases the pattern centre (PC) needs to be determined to sub-pixel accuracy. The mechanical insertion/retraction, through the Scanning Electron Microscope (SEM) chamber wall, of the electron sensitive part of modern EBSD detectors also causes alignment and positioning problems and requires frequent monitoring of the PC. Optical alignment and lens distortion issues within the scintillator, lens and charge-coupled device (CCD) camera combination of an EBSD detector need accurate measurement for each individual EBSD system.This paper highlights and quantifies these issues and demonstrates the determination of the pattern centre using a novel shadow-casting technique with a precision of ∼10 μm or ∼1/3 CCD pixel.     

A metamodeling approach for pattern specification and management

The formal specification of design patterns is central to pattern research and is the foundation of solving various pattern-related problems.In this paper,we propose a metamodeling approach for pattern specification,in which a pattern is modeled as a meta-level class and its participants are meta-level references.Instead of defining a new metamodel,we reuse the Unified Modeling Language(UML)metamodel and incorporate the concepts of Variable and Set into our approach,which are unavailable in the UML but essential for pattern specification.Our approach provides straightforward solutions for pattern-related problems,such as pattern instantiation,evolution,and implementation.By integrating the solutions into a single framework,we can construct a pattern management system,in which patterns can be instantiated,evolved,and implemented in a correct and manageable way.     

基于Snort系统的网络入侵检测模型的研究

网络入侵检测是网络安全领域研究的热点问题,通过应用分组交换检测机制和Markov链,提出基于Snort系统的IDS模型,设计Snort系统规则库和检测引擎。分析结果表明,改进模型和方法可以提高网络入侵检测中海量数据的检测准确率和效率。     

基于主曲线的微阵列数据分类

提出了一种基于主曲线(principal curves)的微阵列数据分类方法(PC)。主曲线是第一主成分的非线性推广,它是数据集合的“骨架”,数据集合是主曲线的“云”。基于主曲线的微阵列数据分类方法,首先利用专门设计的算法在训练数据集上计算出每类样本的主曲线,然后根据测试样本与各类样本主曲线距离的期望方差来确定测试样本所属的类别。实验结果表明,该分类方法在进行小样本微阵列数据分类时性能优于现有的方法。     

基于ROC曲线寻优的支持向量机性能研究

支持向量机在小样本模式识别领域具有优势,但其性能评估及核参数、正则化参数的选择尚未有标准算法.将受试者操作特性曲线(Receiver Operating Characteristic,ROC)引入支持向量机分类性能分析和建模参数优化问题.在核参数及正则化参数所构成的二维空间中,调整模型参数阈值描绘ROC曲线,通过比较不同分类器ROC曲线下面积实现模型的性能分析,研究了基于ROC曲线最佳工作点的模型优化问题.工程实例表明,ROC曲线下面积有效地量化了模型的识别性能,并给出了一定寻优范围内的模型参数最优点,可以在SVM模型参数优化问题中推广应用.     

《GIS软件工程》实验模式研究

GIS软件工程实验是《GIS软件工程》教学过程中的重要环节,分析《GIS软件工程》的特点,结合在教学实验过程中具体的问题,提出基于柔性案例的GIS软件工程实验模式,并从柔性案例的选择、柔点的选择设置方法、实验过程等方面,分别展开描述,对实验实施中的优缺点进行总结。     

KR字符串匹配算法的研究与实现

字符串匹配是判断模式串(短串)是否是文本串(长串)的子串。KR算法是一种随机串匹配算法,详细介绍KR串匹配算法的算法描述及代码实现过程,并对该算法进行测试,讨论该算法的实现效率。