Increasing the number of psychologists of color: Public policy issues for affirmative diversity.

This article identifies the key issues involved in the debate about affirmative action. The June 2003 Supreme Court decisions allowing consideration of race to ensure that there is a "critical mass" of African American, Latino/Latina, and Native American applicants to higher education are addressed. Social psychologists have identified key myths and provided clarifications about the need for and consequences of strategies used to promote equal opportunity for persons of color and women. A brief history of affirmative action and of the problems it was designed to solve is provided. The accomplishments, benefits, and compelling interest of diversity and affirmative action are described, as well as the concerns and counterpoints. The lack of a substantial applicant pool in psychology hinders progress toward diversity. Alternative strategies for remedying this lack beyond affirmative admissions policies in psychology are briefly discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于进化计算的兴趣建模

为实现对个体的兴趣建模,提出基于进化计算的建模(Evolutionary Computation Based Modeling,ECBM)方法。该方法采用定性和定量相结合的方式对个体的兴趣系统进行建模,首先通过定性分析构建个体的兴趣模型框架,然后通过进化计算(Evolutionary Computation)方法对模型参数自动进化。实验结果表明,ECBM能够通过数据驱动模式优化模型参数,并利用更新信息进化模型,使其不断逼近真实系统。     

中职学校提高《数字电路》课程教学质量的探讨

《数字电路》是中职电类专业的一门专业基础课程。结合目前中职学校教学现状中存在的问题,如何让学生把这门课学好,笔者从精选教材、课堂导入、教学手段、考核评价等方面进行了探讨。指出了只有充分激发起学生的学习兴趣和学习积极性,才是提高教学质量的关键。     

Level of interest sensing in spoken dialog using decision-level fusion of acoustic and lexical evidence

Automatic detection of a user's interest in spoken dialog plays an important role in many applications, such as tutoring systems and customer service systems. In this study, we propose a decision-level fusion approach using acoustic and lexical information to accurately sense a user's interest at the utterance level. Our system consists of three parts: acoustic/prosodic model, lexical model, and a model that combines their decisions for the final output. We use two different regression algorithms to complement each other for the acoustic model. For lexical information, in addition to the bag-of-words model, we propose new features including a level-of-interest value for each word, length information using the number of words, estimated speaking rate, silence in the utterance, and similarity with other utterances. We also investigate the effectiveness of using more automatic speech recognition (ASR) hypotheses (n-best lists) to extract lexical features. The outputs from the acoustic and lexical models are combined at the decision level. Our experiments show that combining acoustic evidence with lexical information improves level-of-interest detection performance, even when lexical features are extracted from ASR output with high word error rate.     

基于随机词汇迭代模型的POI分类检索

从特征选择、局部区域划分和词汇语义相似性计算入手,利用随机词汇迭代模型(random terms iterativemodel,RTIM)进行海量兴趣点(point of interest,POI)文本分类.通过词汇频度、集中度和离散度方法筛选出特征词汇;依据文本与各POI类别间的相似度进行局部区域划分;在每个局部区域内基于词汇在文本中的排列顺序构建词频向量,基于词频向量中词频的随机删除和重构,获取特征映射矩阵;通过特征映射矩阵将文本转为特征向量,并采用SVM分类器进行POI文本分类.实验证明,该方法有效提升了POI文本分类准确性和覆盖率.     

基于Gabor多尺度空间的不变兴趣点检测

针对以往仿射不变兴趣点的特征尺度不能直接断定的问题, 提出一种基于Gabor多尺度空间的不变兴趣点检测算法。该算法主要包括三个步骤：应用Gabor滤波器组与图像卷积建立图像Gabor多尺度空间; 通过极大值准则检测兴趣点并直接断定特征尺度; 采用二阶矩矩阵描述兴趣点局部结构。实验结果表明, 相比较其他Hessian-Affine、MSER等算法, 该算法在图像模糊和JPEG压缩情况下可重复率和可匹配率均取得最好结果, 是一种能有效直接提取特征尺度的兴趣点检测算法。     

基于海量搜索历史数据的用户兴趣模型

针对互联网搜索引擎环境中,基于海量搜索历史数据分析用户兴趣的问题,提出一种改进的用户兴趣模型。该模型根据用户搜索的历史数据,结合向量空间模型（ VSM ）和TF-IDF算法,递归地回溯出用户兴趣权重列表。为解决用户兴趣变化和时间性能的问题,该模型引入时间遗忘机制进行动态更新,并在Hadoop分布式系统架构下利用MapReduce分布式编程模型进行实现。实验结果表明,改进的用户兴趣模型的查准率和召回率都能达到50',具有较好的可行性和可用性。     

结合形态学的结构化车道线快速识别算法

为解决结构化车道线识别算法中存在的约束条件多,计算过于复杂等问题,提出一种基于形态学的车道线快速识别算法. 该算法首先对道路图像进行中值滤波,Sobel算子增强边缘,利用直方图特征分割图像,然后划分感兴趣区域,接着构造具有车道特征的形态学结构元素去提取车道线,最后概率霍夫变换拟合车道线. 实验对比结果表明,针对结构化道路,该算法简单有效,计算量小,具有良好的实时性.     

利率政策对西安房价影响的有效性分析

由于经济发展水平不同,居民购买力水平不同,货币政策调控对不同地区房价的有效性也存在差异,需要根据不同地区的特点进行分析.以西安市房价变化为例,选取2003~2007年的数据,分析利率政策调控对西安房价影响的有效性并进行了实证检验,发现利率政策实施对西安市房地产价格的影响非常有限,2003~2007年的利率政策调控并没有达到预期效果,只是使市场发生了轻微变动.为此,提出了提高利率、提升地方政府公共服务能力等相关的政策建议.