Shrinkage-based regularization tests for high-dimensional data with application to gene set analysis

Traditional multivariate tests such as Hotelling’s test or Wilk’s test are designed for classical problems, where the number of observations is much larger than the dimension of the variables. For high-dimensional data, however, this assumption cannot be met any longer. In this article, we consider testing problems in high-dimensional MANOVA where the number of variables exceeds the sample size. To overcome the challenges with high dimensionality, we propose a new approach called a shrinkage-based regularization test, which is suitable for a variety of data structures including the one-sample problem and one-way MANOVA. Our approach uses a ridge regularization to overcome the singularity of the sample covariance matrix and applies a soft-thresholding technique to reduce random noise and improve the testing power. An appealing property of this approach is its ability to select relevant variables that provide evidence against the hypothesis. We compare the performance of our approach with some competing approaches via real microarray data and simulation studies. The results illustrate that the proposed statistics maintains relatively high power in detecting a wide family of alternatives.     

基于Gabor、Fisher脸多特征提取及集成SVM的人脸表情识别*

针对于静态的灰度图像表情库,提出了基于多种脸部表情特征多级分类的表情识别算法。首先在选取的人脸特征点上做局部的Gabor小波变换,为了提高特征提取速度,利用改进的弹性图匹配算法来提取图像中的人脸有效区域,在提取的人脸区域中提取几何特征,并通过Fisher脸法提取统计特征,利用几何特征与建立的相应一级集成SVM来进行初次分类,最后利用Fisher特征与建立的相应二级集成SVM进行最终分类。通过在JAFFE与Cohn-Kanade表情库中实验,证明本文方法同单个特征相比较,具有更高的表情识别率以及更强的鲁棒性     

基于支持向量机的中国地鼠分类特征基因选取

针对中国地鼠基因表达谱数据维数高和样本小的特点,提出一种基于支持向量机(SVM)的分类特征基因选取方法。该方法利用改进的Fisher判别(FDR)基因特征计分准则剔除分类无关基因,提出由空间距离和功能距离组成的新距离作为相似性度量的标准进行冗余基因的剔除,采用SVM作为分类器检验特征基因的分类性能。实验结果表明,该方法有效地剔除了分类无关基因和冗余基因,选取的特征基因满足对中国地鼠正确分类的最小基因数。     

结肠癌基因表达谱的分类检测问题研究

随着大规模基因表达谱技术的发展,基于基因表达谱的癌症诊断方法正在成为临床医学上一种快速有效的诊断方法,但是由于基因表达数据维数过高、样本量小、噪声大,使得正确提取有关癌症的特征基因成为关键。以结肠癌肿瘤的基因表达谱数据为例,提出了结合Fisher权函数、离散傅里叶变换和主成分分析的混合特征基因提取方法,以多元Logistic回归分析和贝叶斯决策作为分类器进行肿瘤分类检测。实验结果表明,该方法对于结肠癌数据集CV识别准确率高达96.80%。     

基因学习算法及其在集合覆盖问题中的应用

在用传统方法解决一些复杂而规模较大的组合优化问题,尤其是NP难题,出现困难时,一些近似算法相继推出。启发式搜索法、模拟退火算法及进化算法等的出现,为解决这些优化问题提供了非常好的手段。近年来,出现了一种概率学习的进化计算模型,如Baluja的PBIL算法与Corno的自私基因算法。概率学习的进化计算模型通过不断地学习每一代的最优个体,最终收敛于最优或较优的解的等位基因概率,其过程描述如下:     

Application of the Self-Organizing Feature Map Algorithm in Facial Image Morphing

A new facial image morphing algorithm based on the Kohonen self-organizing feature map (SOM) algorithm is proposed to generate a smooth 2D transformation that reflects anchor point correspondences. Using only a 2D face image and a small number of anchor points, we show that the proposed morphing algorithm provides a powerful mechanism for processing facial expressions.     

Strategies for Expressing Concise, Helpful Answers

An intelligent help system needs to take into account the user's knowledgewhen formulating answers. This allows the system to provide more conciseanswers, because it can avoid telling users things that they already know.Since these concise answers concentrate exclusively on pertinent newinformation, they are also easier to understand. Information about theuser's knowledge also allows the system to take advantage of the user'sprior knowledge in formulating explanations. The system can provide betteranswers by referring to the user's prior knowledge in the explanation(e.g., through use of similes). This process of refining answers is calledanswer expression.The process of answer expression has been implemented in the UCExpresscomponent of UC (UNIX Consultant), a natural language system that helps theuser solve problems in using the UNIX operating system. UCExpress separatesanswer expression into two phases: pruning and formatting.In the pruning phase, subconcepts of the answer are pruned by being markedas already known by the user (and hence do not need to be generated), ormarked as candidates for generating anaphora or ellipsis (since they arepart of the conversational context). In the formatting phase, UCExpressuses information about the user's prior domain knowledge to select amongspecialized expository formats,such as similes and examples, for expressing information to the user. Theseformats allow UCExpress to present different types of information to theuser in a clear, concise manner. The result of UCExpress' answer expressionprocess is an internal form that a tactical level generator can easily useto produce good English.     

谈高校艺术设计专业的色彩教学改革

如何探索一套适用于艺术设计专业特点的基础教学方法,利用有限的时间,通过有效的训练,为专业设计建立联系,打下基础,一直是艺术设计教育者应该思考和探索的问题。     

软件PLC中梯形图编译的C 实现研究

研究了软件PLC中梯形图的逻辑化表达以及编译为指令表的实现方法,对梯形图元素之间的串并联关系进行了深入探讨,在此基础上给出了基于C 的梯形图逻辑表达模型,实现了梯形图到指令表的转换。该实现在可扩展性以及支持复杂梯形图转换方面具有一定优势。