推算定位算法在拦截策略中的研究与应用

机器人足球比赛中,研究有效的拦截对方球员的进攻和防守是一项关键的战术,以往开发的拦截策略中存在"漏拦"和"错拦"等现象,造成拦截成功率很低.将推算定位(Dead Reckoning,DR)算法用到拦截策略的研究中,有效估算出对方球员和球的下一步动向,实施有效拦截,提高了比赛过程中拦截判断的精度.对DR算法中的阈值的确定进行了分析和改进,提出一种判据函数,有效地解决动态门选取的问题;针对算法执行和网络的延时给予了延时补偿,提高系统的实时性,使拦截能够快速准确地实现.利用DR算法推算出赛场球和球员的运动趋势,指导赛场策略的生成并和队员的动作与位置的部署.实验数据表明,方法具有很强的优越性.     

基于类内均值的双投影2DPCA人脸识别方法

在人脸识别问题中,如何提取具有鲁棒性的人脸特征和降低特征维数是两个关键。根据二维主成分分析方法直接利用二维图像来构建方差矩阵的优点,引入了类内均值的思想,首先计算每类训练样本的类内平均脸,并用它对各类样本进行规范化处理,有效扩大了类间样本的差别,缩小了类内样本的差别,进行协方差矩阵的计算并提取最优投影特征向量进行人脸图像的特征提取,通过在水平和垂直两个方向上顺序执行两次提取和投影的操作,极大压缩了特征的维数,克服了传统二维主成分算法的不足。在人脸库ORL和Yale的试验对比结果表明,方法对光照与表情变化有较好的鲁棒性,能实现较高的识别率,因此在实际中具有一定的应用意义。     

基于LSA和pLSA的多文档自动文摘

本文提出一种基于LSA和pLSA的多文档自动文摘策略。首先,将多个文档切分成自然段,以自然段作为聚类单位。采用了新的特征提取方法构建词-自然段矩阵,利用LSA对词-自然段矩阵进行奇异值分解,使得向量空间模型中的高维表示变成在潜在语义空间中的低维表示。然后,采用pLSA将数据转换成概率统计模型来计算。在文摘生成的过程中采用基于质心的文摘句挑选办法得到文摘并输出。实验表明,本文提出的方法有效地提高了生成文摘的质量。     

大气湍流图像像素偏差机理分析

对大气湍流导致图像畸变和像素偏差的因素进行了深入分析,对大气湍流状态下激光发射远距离光束的光束漂移均方值进行仿真,分析光束漂移均方值曲线,为后续对图像畸变、像素偏差校正及克服湍流影响提供有效的理论依据。     

传统艺术价值之体现——试析凡高的绘画艺术

早期现代主义艺术是在对传统艺术的叛离,革新的基础上发展起来的,没有传统的积淀,创新和叛离就没有办法真正实现,所以在这个时期的艺术家就面临着如何看待传统的艺术价值,如何依照自己的艺术观念进行取舍,如何继承传统的问题。凡高是西方早期现代主义艺术中的代表画家,在他的艺术风格的形成发展过程中,传统对其绘画创作的影响是十分强大而深远的,体现在他各个时期的艺术作品和观念之中。至今仍具有现实意义。     

改进的粒子群算法

针对基本粒子群算法容易陷入局部最优点,进化后期速度慢等缺点,设计了一种新的粒子群算法,将基本粒子群算法粒子行为基于个体极值点转化为个体自身极值与其他某一个个体极值的加权平均值,而全局极值点转化为群体中优秀个体极值的加权平均值。数值仿真实验表明,新算法比PSO具有更好的收敛性,能更快地找到问题的最优解。     

Economic modeling of board test strategies

A long and deep recession, coupled with continuous competitive pressure to reduce costs, is forcing many companies to review their test strategies. Testing costs have become a more significant proportion of the overall manufacturing cost even though manufacturing yields have increased dramatically over the past ten or twelve years. This causes attention to be focused on testing costs as a key source of cost reduction. The increased use of DFT and the integration of design and test are very positive moves towards controlling testing costs but other methods employed can often backfire. The increased use of low priced testers is one such method. The pressure to reduce costs, higher process yields and exhortations that testing adds no value can lead the test engineering manager to take the cheap route. In reality this can often turn out to be an expensive decision. The only way to avoid expensive mistakes is to perform an economic analysis of the alternative courses of action. In most cases this is done, but not always in the right manner or with the necessary amount of detail to make the comparisons meaningful. This article discusses the need for effective cost analysis of test strategies and highlights some of the pitfalls.     

Disciplined autonomy: How business analytics complements customer involvement for digital innovation

The rise of big data and the fluid boundaries of digital products are driving companies to use business analytics (BA) to power their customer involvement. The complementarity view offers unique competence to generate value from BA because capability complementarity is less likely to be replicated or imitated. Unlike prior studies on BA-enabled value realization, our research investigates the interactions of BA and customer involvement capabilities using the complementarity view. We tested our model using data collected from 317 IT companies in China. Our results suggest that BA value realization requires both a top-down mechanism in which BA skills provide global guidance for alignment with a company’s goals and a bottom-up mechanism in which BA culture empowers local autonomy for adaptation to ever-changing needs. Our BA-complemented mechanisms provide research and practice with a way to concurrently use BA and customer involvement capabilities to address the duality of digital innovation. We further suggest that BA skills are necessary but insufficient for digital innovation because BA culture demonstrates a stronger effect in complementing organizations’ existing capabilities than BA skills do.     

Stochastic approximation learning for mixtures of multivariate elliptical distributions

Most of the current approaches to mixture modeling consider mixture components from a few families of probability distributions, in particular from the Gaussian family. The reasons of these preferences can be traced to their training algorithms, typically versions of the Expectation-Maximization (EM) method. The re-estimation equations needed by this method become very complex as the mixture components depart from the simplest cases. Here we propose to use a stochastic approximation method for probabilistic mixture learning. Under this method it is straightforward to train mixtures composed by a wide range of mixture components from different families. Hence, it is a flexible alternative for mixture learning. Experimental results are presented to show the probability density and missing value estimation capabilities of our proposal.     

An improved lossless data hiding scheme based on image VQ-index residual value coding

Copyright protection and information security have become serious problems due to the ever growing amount of digital data over the Internet. Reversible data hiding is a special type of data hiding technique that guarantees not only the secret data but also the cover media can be reconstructed without any distortion. Traditional schemes are based on spatial, discrete cosine transformation (DCT) and discrete wavelet transformation (DWT) domains. Recently, some vector quantization (VQ) based reversible data hiding schemes have been proposed. This paper proposes an improved reversible data hiding scheme based on VQ-index residual value coding. Experimental results show that our scheme outperforms two recently proposed schemes, namely side-match vector quantization (SMVQ)-based data hiding and modified fast correlation vector quantization (MFCVQ)-based data hiding.