Using classification techniques for informal requirements in the requirements analysis-supporting system

In order to efficiently develop large-scale and complicated software, it is important for system engineers to correctly understand users’ requirements. Most requirements in large-scale projects are collected from various stakeholders located in various regions, and they are generally written in natural language. Therefore, the initial collected requirements must be classified into various topics prior to analysis phases in order to be usable as input in several requirements analysis methods. If this classification process is manually done by analysts, it becomes a time-consuming task. To solve this problem, we propose a new bootstrapping method which can automatically classify requirements sentences into each topic category using only topic words as the representative of the analysts’ views. The proposed method is verified through experiments using two requirements data sets: one written in English and the other in Korean. The significant performances were achieved in the experiments: the 84.28 and 87.91 F1 scores for the English and Korean data sets, respectively. As a result, the proposed method can provide an effective function for an Internet-based requirements analysis-supporting system so as to efficiently gather and analyze requirements from various and distributed stakeholders by using the Internet.     

街面水电站混凝土面板堆石坝主要技术问题探讨

街面水电站拦河坝为混凝土面板堆石坝,在面板止水结构型式、面板防裂措施、上游面的施工方法、趾板开挖处理及趾板灌浆等方面,根据工程实际情况,结合国内外的新技术新工艺进行了探讨。     

一种新的基于直觉模糊集的作战决策算法

针对现有作战决策算法存在的不足,提出了一种新的基于直觉模糊集的作战决策算法.用直觉模糊值表示可行方案指标的不确定信息,综合考虑了方案满足指标的可能性、不满足的可能性和未知的可能性3个方面的因素,给出了直觉模糊决策矩阵的建立方法和可行方案优劣度排序方法.实例及实际应用证明了算法的有效性与可行性.     

中国首创五大新兴智能基础学科的交叉应用与展望

可拓学、灰色系统、界壳论、集对分析和消错学这五大新兴智能基础学科都是我国首创的理论。本文首先简单介绍了五大学科，随后给出了五大学科的关系矩阵并讨论了其交叉应用的发展概况，最后对其交叉所产生的空白领域追行了初步的探讨，然后对其未来发展进行了展望。     

The stiffness matrix in elastically articulated rigid-body systems

Discussed in this paper is the Cartesian stiffness matrix, which recently has received special attention within the robotics research community. Stiffness is a fundamental concept in mechanics; its representation in mechanical systems whose potential energy is describable by a finite set of generalized coordinates takes the form of a square matrix that is known to be, moreover, symmetric and positive-definite or, at least, semi-definite. We attempt to elucidate in this paper the notion of “asymmetric stiffness matrices”. In doing so, we show that to qualify for a stiffness matrix, the matrix should be symmetric and either positive semi-definite or positive-definite. We derive the conditions under which a matrix mapping small-amplitude displacement screws into elastic wrenches fails to be symmetric. From the discussion, it should be apparent that the asymmetric matrix thus derived cannot be, properly speaking, a stiffness matrix. The concept is illustrated with an example.     

On the Consistency of the Normalized Eight-Point Algorithm

A recently proposed argument to explain the improved performance of the eight-point algorithm that results from using normalized data (Chojnacki, W., et al. in IEEE Trans. Pattern Anal. Mach. Intell. 25(9):1172–1177, 2003) relies upon adoption of a certain model for statistical data distribution. Under this model, the cost function that underlies the algorithm operating on the normalized data is statistically more advantageous than the cost function that underpins the algorithm using unnormalized data. Here we extend this explanation by introducing a more refined, structured model for data distribution. Under the extended model, the normalized eight-point algorithm turns out to be approximately consistent in a statistical sense. The proposed extension provides a link between the existing statistical rationalization of the normalized eight-point algorithm and the approach of Mühlich and Mester for enhancing total least squares estimation methods via equilibration. The paper forms part of a wider effort to rationalize and interrelate foundational methods in vision parameter estimation.     

高压加热器技术简介

介绍了东芝高压加热器技术以及技术转让的一些内容 ,以及为能制造出符合东芝技术要求的高压加热器而采取的保证措施     

利用试井资料评价压裂地质效果

依据裂缝井试井解释理论，利用实测试井资料对压裂地质效果进行了深入剖析。通过部分探井措施后增产效果实例研究，把压裂地质效果分为三种类别；并从地质角度出发，详细分析了优选压裂井层的依据。为油气井合理开发和制定增产措施提供参考依据。     

The validity of psychophysiological detection of information with the Guilty Knowledge Test: A meta-analytic review.

The authors performed a meta-analysis based on 169 conditions, gathered from 80 laboratory studies, to estimate the validity of the Guilty Knowledge Test (GKT) with the electrodermal measure. The over-all average effect size was 1.55, but there were considerable variations among studies. In particular, mock-crime studies produced the highest average effect size (2.09). Three additional moderators, were identified: Motivational instructions, deceptive ("no") verbal responses, and the use of at least 5 questions were associated with enhanced validity. Finally, a set of 10 studies that best approximated applications of the GKT under optimal conditions produced an average effect size of 3.12. The authors discuss factors that might limit the generalizability of these results and recommend further research of the GKT in realistic setups. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

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.