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.     

Application of Support Vector Machines in Assessing Conceptual Cost Estimates

Total conceptual cost estimates and the assessment of the quality of these estimates are critical in the early stages of a building construction project. In this study, the support vector machine (SVM) model for assessing the quality of conceptual cost estimates is proposed, and the application of SVM in construction areas is investigated. The results show that the SVM model assessed the quality of conceptual cost estimates slightly more accurately than the discriminant analysis model. This shows that using the SVM has potential in construction areas. In addition, the SVM model can assist clients in their evaluation of the quality of the estimated cost and the probability of exceeding the target cost, and in their decision on whether or not it is necessary to seek a more accurate estimate in the early stages of a project.     

A time-domain approach to transmission network equivalents viaProny analysis for electromagnetic transients analysis

This paper presents a method of obtaining transmission network equivalents from the network's response to a pulse excitation signal. The proposed method is based on modal decomposition representation for the large-scale interconnected system. In this framework we use Prony analysis to identify the network function of the system and to decompose the large system into a parallel combination of simple first-order systems. As a result the network function of the transmission network can be identified easily, and a Thevenin-type of discrete-time filter model can be generated. It can reproduce the driving-point impedance characteristic of the network. Furthermore, the proposed model can be implemented into the EMTP in a direct manner. The simulation results with the full system representation and the developed equivalent system showed a good agreement     

Enhanced direct stiffness method for finite element analysis of textile composites

Traditional homogenization techniques are not useful when the microstructural scale of a material is of the same order of magnitude as the structural scale of a component. Such is the case for many textile composites. Since discrete modeling of the microstructure throughout a component is prohibitively expensive, continuum finite elements are needed which account for the microstructure within a single element. This paper describes a simple substructuring technique for formulating these special elements.     

Serum amyloid P component scintigraphy and turnover studies for diagnosis and quantitative monitoring of AA amyloidosis in juvenile rheumatoid arthritis

OBJECTIVE: To evaluate aspects of the natural history of AA amyloidosis complicating juvenile rheumatoid arthritis (JRA), and its response to therapy with chlorambucil. METHODS: Scintigraphy and 7-day turnover studies were performed in JRA patients with histologically proven (n = 35) or clinically suspected (n = 30) AA amyloidosis, following intravenous injection of 123I and 125I-labeled serum amyloid P component (SAP). Prospective monitoring studies were performed over 2-3 years in 20 patients with amyloidosis. All but 2 amyloidosis patients were treated with chlorambucil. RESULTS: Positive scanning results were obtained in all patients in whom imaging was performed within 12 years of positive biopsy findings of amyloid and in 5 patients with clinically suspected amyloidosis. Negative scanning results with normal SAP metabolism, indicating regression of amyloid, were obtained in 4 patients whose amyloidosis had been in full clinical remission for more than 12 years. Prospective monitoring studies in patients whose JRA-associated inflammatory activity was in remission demonstrated regression of amyloid in 8 patients and no substantial changes in 8 others; however, in 4 further patients with active inflammation, there was accumulation of amyloid. There was a very poor correlation between the amount of amyloid present at a particular site and the resultant organ dysfunction. CONCLUSION: Radiolabeled SAP scintigraphy and turnover studies are useful complementary tools in the diagnosis, screening, and quantitative monitoring of type AA amyloidosis in JRA. The amyloid deposits may progress and/or regress at different rates in different anatomic sites over short periods.     

Self-aligned offset gated poly-Si TFTs with a floating sub-gate

We have fabricated a self-aligned offset-gated poly-Si thin film transistor (TFT) by employing a novel photoresist reflow process. The gate structure of the new device is consisted of two unique patterns: A main-gate and a sub-gate. The new fabrication method extends the gate-oxide over the offset region. With the assistance of the sub-gate and reflowed photoresist a self-aligned offset region is successfully obtained due to the offset oxide acting as an implantation mask. The poly-Si TFT with symmetrical offsets is easily fabricated and the new method does not require any additional offset mask step. Compared with the misaligned offset gated poly-Si TFTs, excellent symmetric electrical characteristics are obtained     

Modified atmosphere packaging of a mixed prepared vegetable salad dish

The aim of this study was to design a modified atmosphere package for a mixed vegetable salad consisting of 75 g of cut carrot, 55 g of cut cucumber, 20 g of sliced garlic and 50 g of whole green pepper. Respiration data of all the components were combined with film permeability data to predict package atmospheres and design optimal packages for experimental testing for improved shelf-life of the produce. The optimal package avoided minimum O₂ and maximum CO₂ tolerance limits, and chilling injury temperatures for any component. A pouch form package made of 27 mm low density polyethylene developed a modified atmosphere of 2.0–2.1% O₂ and 5.5–5.7% CO₂, which was beneficial for all components and provided better quality retention than other test packages.     

A neural network-based power system stabilizer using power flowcharacteristics

A neural network-based power system stabilizer (neuro-PSS) is designed for a generator connected to a multi-machine power system utilizing the nonlinear power flow dynamics. The use of power flow dynamics provides a PSS for a wide range of operation with reduced size neural networks. The neuro-PSS consists of two neural networks: neuro-identifier and neuro-controller. The low-frequency oscillation is modeled by the neuro-identifier using the power flow dynamics, then a generalized backpropagation-through-time (GBTT) algorithm is developed to train the neuro-controller. The simulation results show that the neuro-PSS designed in this paper performs well with good damping in a wide operation range compared with the conventional PSS     

A study on the degree of deliberation and meditation of cyber poll respondents for nuclear-related decision making

Public participation is essential in each step of the nuclear-related decision-making process. Recently, the electronic systems using the Internet have become quite popular, and have emerged as a good medium for communicating with the public. In this study, a comprehensive utilization of electronic public participation was used to analyze public opinion on a given nuclear-related decision-making process. The degree of deliberation and meditation of the public participating in an electronic poll survey was evaluated, and the decision-making factors representing the personal characteristics of the poll respondents such as age, income, education, residence, degree of knowledge and concern were carefully incorporated when preparing the poll-survey questionnaire for its evaluation. Fuzzy analysis was used to assess and aggregate the responses to each decision-making factor. As a case study, this procedure was used to analyzing public opinion on the location of a low-level radioactive waste disposal facility on the campus of Seoul National University. The results show that there is a tendency of respondents who are on the negative side of the argument to be more deliberate and meditative in their decision-making process than those on the positive side. Knowledge and residence were found to be important decision-making factors.