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.     

The effects of widowhood on physical and mental health, health behaviors, and health outcomes: The Women's Health Initiative.

This study examined whether widowhood was associated with physical and mental health, health behaviors, and health outcomes using a cross-sectional (N=72,247) and prospective (N=55,724) design in women aged 50-79 years participating in the Women's Health Initiative observational study (85.4% White). At baseline, married women reported better physical and mental health and generally better health behaviors than widowed women. Whereas women who remained married over the 3-year period showed stability in mental health, recent widows experienced marked impairments and longer term widows showed stability or slight improvements. Both groups of widows reported more unintentional weight loss over the 3-year period. Changes in physical health and health behaviors were inconsistent, with generally small effect sizes. Findings underscore the resilience of older women and their capacity to reestablish connections, but point to the need for services that strengthen social support among women who have difficulty during this transition. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Toughening mechanism for a rubber-toughened epoxy resin with rubber/matrix interfacial modification

For a rubber-toughened piperidine-DGEBA epoxy resin, the interface between the rubber particle and the epoxy resin matrix was modified by an epoxide end-capped carboxyl terminated butadiene and acrylonitrile random copolymer (CTBN). The end-capping epoxides used were a rigid diglycidyl ether of bisphenol-A (Epon 828), a short-chain flexible diglycidyl ether of propylene glycol (DER 736), and a long-chain flexible diglycidyl ether of propylene glycol (DER 732). The microstructures and the fracture behaviour of these rubber-modified epoxy resins were studied by transmission electron microscopy and scanning electron microscopy. Their thermal and mechanical properties were also investigated. In the rubber-modified epoxy resins, if the added CTBNs were end-capped by a flexible diglycidyl ether of propylene glycol (DER 732 or DER 736) before curing, the interfacial zone of the undeformed rubber particle, the degree of cavitation of the cavitated rubber particle on the fracture surface and the fracture energy of the toughened epoxy resin were all significantly increased. The toughening mechanism based on cavitation and localized shear yielding was considered and a mechanism for the interaction between cavitation and localized shear yielding that accounts for all the observed characteristics is proposed.     

Moderators of nonverbal indicators of deception: A meta-analytic synthesis.

In many legal proceedings, fact finders scrutinize the demeanor of a defendant or witness, particularly his or her nonverbal behavior, for indicators of deception. This meta-analysis investigated directly observable nonverbal correlates of deception as a function of different moderator variables. Although lay people and professionals alike assume that many nonverbal behaviors are displayed more frequently while lying, of 11 different behaviors observable in the head and body area, only 3 were reliably associated with deception. Nodding, foot and leg movements, and hand movements were negatively related to deception in the overall analyses weighted by sample size. Most people assume that nonverbal behaviors increase while lying; however, these behaviors decreased, whereas others showed no change. There was no evidence that people avoid eye contact while lying, although around the world, gaze aversion is deemed the most important signal of deception. Most effect sizes were found to be heterogeneous. Analyses of moderator variables revealed that many of the observed relationships varied as a function of content, motivation, preparation, sanctioning of the lie, experimental design, and operationalization. Existing theories cannot readily account for the heterogeneity in findings. Thus, practitioners are cautioned against using these indicators in assessing the truthfulness of oral reports. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dialogue as the interplay of otherness and shared humanity.

Presents a reply by B. Fowers and B. Davidov to Islam's comments (see record 2007-14606-019) regarding their article (see record 2006-11202-002). Islam noted that virtues are often presented as universally valid character strengths, yet formulations of virtues are always embedded in a particular cultural context, a point we took pains to make in our article. We focus our response on Islam's important suggestion that this tension between universal human characteristics and the particulars of cultural context is indissoluble. Whereas he suggested this tension leads to contradiction and paradox, we see it as a fertile dialectic. The virtue of openness to the other is also subject to the same tension of abstract formulation and particular application. Although we formulated this virtue in a very general way, any instantiation of it would be shaped by the particulars of the cultural context and the situation in which it is exercised. We introduced the concept of dialogue because it is constituted not only by differences between individuals or groups but even more fundamentally by the dialectical relationship between those differences in cultural particularities and the universal human capacities for reason, curiosity, and social engagement, among others. Dialogue acknowledges the indissoluble otherness one finds in those culturally different from oneself, and yet real interchange can only occur because participants in dialogue exercise the cognitive flexibility characteristic of human beings and recognize a shared humanity with the other. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.     

A site selection model for high technology manufacturing firms in the United States

This article offers a quantitative model for site selection by high technology manufacturing firms. In the past, site selection studies have usually been qualitative in nature, and very subjective. This is an attempt to introduce a more objective quantitative approach. The site selection factors most important to high technology manufacturing firms were identified, ranked and weighted based on a US Joint Economic Committe survey of such firms. The eight most important factors were: the availability of technical and professional workers, labor costs, tax climate, academic institutions, cost of living, transportation for people, and access to markets. Demographic data on these factors were collected and analyzed for 32 developing high technology areas in the United States. By using the quantitative model, a score was developed for each area, allowing them to be ranked as R & D manufacturing environments. This model should prove a useful tool for both regional planners and high-tech companies seeking to relocate.     

A neural network model for fault detection in conjunction with a programmable logic controller

This paper discusses the feasibility of using neural networks as a tool in the fault detection process. A neural network is integrated with a state language programmable logic controller, an important device in an automatic control system. Time series data related to time spent in a state is gathered and used as input into a neural network, for the purpose of identifying when a fault has occurred. A feedforward neural network is used to identify which (if any) of three types of faults may have occurred. Experimental results related to sensitivity and accuracy measures are presented. A brief review of related applications and research is also presented.     

Frontiers in research on cystic fibrosis: understanding its molecular and chemical basis and relationship to the pathogenesis of the disease

In recent years a new family of transport proteins called ABC transporters has emerged. One member of this novel family, called CFTR (cystic fibrosis transmembrane conductance regulator), has received special attention because of its association with the disease cystic fibrosis (CF). This is an inherited disorder affecting about 1 in 2000 Caucasians by impairing epithelial ion transport, particularly that of chloride. Death may occur in severe cases because of chronic lung infections, especially by Pseudomonas aeruginosa, which cause a slow decline in pulmonary function. The prospects of ameliorating the symptoms of CF and even curing the disease were greatly heightened in 1989 following the cloning of the CFTR gene and the discovery that the mutation (deltaF508), which causes most cases of CF, is localized within a putative ATP binding/ATP hydrolysis domain. The purpose of this introductory review in this minireview series is to summarize what we and others have learned during the past eight years about the structure and function of the first nucleotide binding domain (NBF1 or NBD1) of the CFTR protein and the effect thereon of disease-causing mutations. The relationship of these new findings to the pathogenesis of CF is also discussed.