• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.189-196
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• 2004

This paper describes what an operational change detection tool requires and the software which was designed and developed according to the requirements. The top requirement for the application of the software to operational change detection was identified: minimization of false detections, missing detections and operational cost. In order to meet such a requirement, the software was designed with the concept that the ultimate decision and isolation of changes must be performed manually by visual interpretation and all automatic algorithms and/or visualization techniques must be defined as support functions. In addition, the modular structure of the proposed software enables the addition of a new support function with the minimum development cost and minimum change of the operational environment.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.235-245
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• 2011

Early criticality prediction models that determine whether a design entity is fault-prone or not are becoming more and more important as software development projects are getting larger. Effective predictions can reduce the system development cost and improve software quality by identifying trouble-spots at early phases and proper allocation of effort and resources. Many prediction models have been proposed using statistical and machine learning methods. This paper builds a prediction model using Support Vector Machine(SVM) which is one of the most popular modern classification methods and compares its prediction performance with a well-known prediction model, BackPropagation neural network Model(BPM). SVM is known to generalize well even in high dimensional spaces under small training data conditions. In prediction performance evaluation experiments, dimensionality reduction techniques for data set are not used because the dimension of input data is too small. Experimental results show that the prediction performance of SVM model is slightly better than that of BPM and polynomial kernel function achieves better performance than other SVM kernel functions.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.875-886
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• 2016

In this study, we investigate an influence of the China government's software support policy on the revenue of software export. In the analysis in the areas of technology development, manpower development, quality control and marketing reinforcement from 2008 to 2014, it has been found that the amounts of the policy influence and annual revenue of software export increase simultaneously, proving that the China government's support policy has a close relationship with the software export revenue. However, the annual ratio of the software export revenue to the gross software production revenue has decreased over the period, which indicates that the growth of software industry in China has been mainly driven by domestic market.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.437-444
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• 2004

In this study, an optimum support design problem is considered to minimize displacement of stacked plates under self weight condition. During the displacement analysis, several kinds of contact arise between the plates themselves and support bar. These can be easily considered if commercial analysis software, which provides capability to solve the contact problem, is used. It is found, however, that the computing time is extraordinarily long due possibly to the generality of the software and also to the ignorance of the control parameters used in the software. In this paper, the contact condition is imposed directly by the authors, while the software is used only to solve the ordinary displacement analysis problem. In this way, the computing time is decreased remarkably by more than 30 times, while yielding the same accurate results. Optimization is conducted based on this efficient analysis method to find minimum number of supporting bars using the response surface algorithm.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.729-736
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• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. Until recent days, the model using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software cost using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying genetic algorithm. The proposed GA-SVR model outperform some recent results reported in the literature.

• Journal of Information Technology Services
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• v.11 no.4
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• pp.171-180
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• 2012

Since software and hardware integration has became a strategic tool for companies to innovate their products, an information system that can comprehensively manage software and hardware integrated product development is critical for the current product development. This paper proposed a product data model that can support modules of related software and hardware parts in Product Data Management(PDM) integrated with Software Configuration Management(SCM). The model allows engineers to define software and hardware product structure independently, and support the integration module that can summon related software and hardware parts to build a comprehensive module for collaboration. Through the integration module, engineers can identify and examine the effectiveness of their design alternatives to other related parts form different disciplines. The product data model was implemented as a prototype PDM system and tested with an example robotics product.

• Korean Management Science Review
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• v.30 no.2
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• pp.11-30
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• 2013

Small and medium-sized enterprises (SMEs) constitute an important part of current industrial economies. Information technologies can be useful strategic weapons for SMEs by enhancing their competitiveness. Categorized as one kind of cloud computing, SaaS is a computing resource and software sharing model which can be accessed via the Internet. Based on virtualization technology, SaaS is expected to improve the efficiency and quality of the IT service level in SMEs. This study attempts to identify the determinants of SaaS adoption intention among Korean SMEs. Through the lens of the theory of planned behavior, this study adopts technological, organizational, environmental factors to explore the determinants of cloud computing adoption intention. The research population is the SMEs that have been funded by the Korean government. Partial least square method was used for empirical analysis of 190 samples collected through on-line survey. The results show that the positive attitude is influenced by business process improvements. Vender support and top management support are positively associated with subjective norm. Vendor support, top management support can relieve perceived behavior control factors. Government support directly influences adoption intention of cloud computing. These findings can provide useful strategy for both SMEs and vendors of SaaS.

• Nuclear Engineering and Technology
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• v.38 no.3
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• pp.259-276
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• 2006

As the use of digital systems becomes more prevalent, adequate techniques for software specification and analysis have become increasingly important in nuclear power plant (NPP) safety-critical systems. Additionally, the importance of software verification and validation (V&V) based on adequate specification has received greater emphasis in view of improving software quality. For thorough V&V of safety-critical systems, V&V should be performed throughout the software lifecycle. However, systematic V&V is difficult as it involves many manual-oriented tasks. Tool support is needed in order to more conveniently perform software V&V. In response, we developed four kinds of computer aided software engineering (CASE) tools to support system specification for a formal-based analysis according to the software lifecycle. In this work, we achieved optimized integration of each tool. The toolset, NuSEE, is an integrated environment for software specification and V&V for PLC based safety-critical systems. In accordance with the software lifecycle, NuSEE consists of NuSISRT for the concept phase, NuSRS for the requirements phase, NuSDS for the design phase and NuSCM for configuration management. It is believed that after further development our integrated environment will be a unique and promising software specification and analysis toolset that will support the entire software lifecycle for the development of PLC based NPP safety-critical systems.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1499-1510
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• 2016

This study is the result of a fuzzy-AHP-based evaluation of the support policy for the export of Chinese software, for which nine Class 1 evaluation indexes were established. Following a survey of 10 Chinese software experts, fuzzy AHP was used to assess and evaluate the absolute and relative importance of each index. The evaluation revealed that the support policy had relatively positive effects. More specifically, the analysis showed that several indices - technology development, HR development, marketing reinforcement, fund support, platform establishment, and product support - carried relatively significant importance. Quality management and tax deductions, on the other hand, showed no importance, while the importance of international certification was relatively small. In light of these discoveries, there is a need to train experts, increase software quality, and reconsider software brands.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.53-58
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• 2018

The Republic of Korea (ROK) has been putting much effort to deal with diabetes which is being increasingly found in all age groups due to inadequate diet. Diabetes is closely related to one's eating habits and lifestyle that often cause hyperglycemia so that it is essential for the diabetic patients to change them to improve or control the major symptoms of diabetes. This study introduces a software engineering solution to support these patients. The software designed for the solution lets the patients to easily recognize their sugar levels and current treatment schemes and then advises a more effective approach along with the essential information through the embedded push service. The major goal of this study is to support diabetes patients by providing a convenient but effective means to prevent or improve diabetic symptoms by patients themselves who will in turn change their lifestyles in a positive manner.