Uncertainty,belief, and probability1

We introduce a new probabilistic approach to dealing with uncertainty, based on the observation that probability theory does not require that every event be assigned a probability. For a nonmeasurable event (one to which we do not assign a probability), we can talk about only the inner measure and outer measure of the event. In addition to removing the requirement that every event be assigned a probability, our approach circumvents other criticisms of probability-based approaches to uncertainty. For example, the measure of belief in an event turns out to be represented by an interval (defined by the inner and outer measures), rather than by a single number. Further, this approach allows us to assign a belief (inner measure) to an event E without committing to a belief about its negation -E (since the inner measure of an event plus the inner measure of its negation is not necessarily one). Interestingly enough, inner measures induced by probability measures turn out to correspond in a precise sense to Dempster-Shafer belief functions. Hence, in addition to providing promising new conceptual tools for dealing with uncertainty, our approach shows that a key part of the important Dempster-Shafer theory of evidence is firmly rooted in classical probability theory. Cet article présente une nouvelle approche probabiliste en ce qui concerne le traitement de l'incertitude; celle-ci est basée sur l'observation que la théorie des probabilityés n'exige pas qu'une probabilityé soit assignée à chaque événement. Dans le cas d'un événement non mesurable (un événement pour lequel on n'assigne aucune probabilityé), nous ne pouvons discuter que de la mesure intérieure et de la mesure extérieure de l'évenément. En plus d'éliminer la nécessité d'assigner une probabilityéà l'événement, cette nouvelle approche apporte une réponse aux autres critiques des approches à l'incertitude basées sur des probabilityés. Par exemple, la mesure de croyance dans un événement est représentée par un intervalle (défini par la mesure intérieure et extérieure) plutǒt que par un nombre unique. De plus, cette approche nous permet d'assigner une croyance (mesure intérieure) à un événement E sans se compromettre vers une croyance à propos de sa négation -E (puisque la mesure intérieure d'un événement et la mesure intérieure de sa négation ne sont pas nécessairement une seule et unique mesure). II est intéressant de noter que les mesures intérieures qui résultent des mesures de probabilityé correspondent d'une manière précise aux fonctions de croyance de Dempster-Shafer. En plus de constituer un nouvel outil conceptuel prometteur dans le traitement de l'incertitude, cette approche démontre qu'une partie importante de la théorie de l'évidence de Dempster-Shafer est fermement ancrée dans la theorie classique des probabilityés.     

The Buck Stops Where?

SUMMARY

University students-whether adult, distance learner, or traditional age-need access to university services and quick accurate answers to their questions beyond traditional “business” hours. Students' busy schedules and changing life patterns dictate that university services meet their needs. At DePaul University in Chicago, student focus groups repeatedly pointed to the need for one central place to get an answer or solve a problem. DePaul Central was created as an information and referral service to satisfy that student need, at the same capitalizing on the value of the librarian skill set.     

基于C#的网络教学网站的设计与研究

远程教育和校园的信息化建设成为网络应用一个新的热点。网络考试作为远程教育和校园信息化建设的一部分,有着其独特的需求和作用。该文就网络考试系统的总体结构与功能以及实现技术进行了逐一的论述。     

A comment on “Using locally estimated geodesic distance to optimize neighborhood graph for isometric data embedding”

A geodesic distance-based approach to build the neighborhood graph for isometric embedding is proposed to deal with the highly twisted and folded manifold by Wen et al. [Using locally estimated geodesic distance to optimize neighborhood graph for isometric data embedding, Pattern Recognition 41 (2008) 2226-2236]. This comment is to identify the error in their example and the ineffectiveness of their algorithm.     

Commentary on Krishnaswamy et al. - Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate

Remote sensing is a powerful tool for characterizing, estimating or modelling species diversity. Differences in environmental properties of different habitats should lead to differences of spectral responses, which can be detected by satellite imagery. Hence, spectral distance may be related to species diversity. Based on previous studies, Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] used spectral distance to estimate species diversity. Since a noisy scatterplot of species versus spectral diversity is expected, the commonly used Ordinary Least Square regression may fail to detect trends which occur across other quantiles than the mean.Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] proposed a quantile-quantile plot method as an alternative to conventional regression based approaches which are inappropriate for dependent pair-wise dissimilarity or similarity data. By this commentary I demonstrate the utility of a quantile regression technique to complement the Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] graphical approach in terms of a predictive model.     

Learning a color distance metric for region-based image segmentation

In this paper we describe an experiment where we studied empirically the application of a learned distance metric to be used as discrimination function for an established color image segmentation algorithm. For this purpose we chose the Mumford–Shah energy functional and the Mahalanobis distance metric. The objective was to test our approach in an objective and quantifiable way on this specific algorithm employing this particular distance model, without making generalization claims. The empirical validation of the results was performed in two experiments: one applying the resulting segmentation method on a subset of the Berkeley Image Database, an exemplar image set possessing ground-truths and validating the results against the ground-truths using two well-known inter-cluster validation methods, namely, the Rand and BGM indexes, and another experiment using images of the same context divided into training and testing set, where the distance metric is learned from the training set and then applied to segment all the images. The obtained results suggest that the use of the specified learned distance metric provides better and more robust segmentations, even if no other modification of the segmentation algorithm is performed.     

宽频介电谱仪热激励去极化电流功能研究

利用宽频介电谱仪拓展热激励去极化电流模块测量介质材料的TSDC操作简单实用,它不仅容易把材料中的各种不同活化能或弛豫时间的荷电粒子区分开,并且能从TSDC谱中直接得出被测材料的介电性能以及相关微观参数,这为研究材料内部机理提供了一条捷径。     

浅析金鸡拦河闸重建工程的环境保护与防治控制

论述了泉州市金鸡拦河闸重建工程的意义,分析了重建工程对河道上下游水生态环境的影响,提出了环境保护与污染防治措施。     

点到平面距离公式的一种新证法

该文根据球面上一点切平面的方程和平移变换,对空间任一点P(x0,y0,z0),分P点为坐标原点和P点不是坐标原点两种情形,给出了到平面π:Ax By Cz D=0的距离公式d=|Ax0 By0 Cz0 D|/√A2 B2 C2 的一种新证法.     

说话人识别中LPCCEP倒谱分量的相对重要性

文中研究表明,反映说话人特征信息的特征参数矢量的各个分量通常具有不同的分布,对正确识别说话人身份的有效性是有差别的。文中通过增减分量的方法对LPCCEP的各维分量进行分析,得到一个关于LPCCEP参数各维分量的平均贡献序列,将此序列运用于WDMVQ有助于系统识别率的提高。