• Journal of Digital Convergence
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• v.10 no.1
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• pp.335-339
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• 2012

Software configuration management is a field of managing sets of large scale software outputs to be the basis of the software products. Configuration management has significantly improved for the past few years, yet new system is still required. Instead of using previous methods or researching about configuration management, professional management of developing project is needed. Therefore, techniques such as storage model for configuration management, management program for change procedure and management of program interface is needed. In this paper, we provide storage for configuration management and implement decision-making system to manage divided program and interface. Thus, we propose a new access method by the configuration management dependency. This paper provides configuration management for developing software to verify and classify using decision-making system for the change and combination of independent components with high dependency.

• Journal of the Korean Society of Clothing and Textiles
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• v.12 no.3 s.28
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• pp.333-342
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• 1988

The purpose of this study was to investigate the relationship between Perception of self anp Clothing Interest, and to determine the difference of Clothing interest and Perception of self by the demographic variables. Perception of self was measured with Perception of self test from Choi's Perceptual Orientation Scale. Appearance, Clothing comfort, Fashion, Psychological dependence, Clothing economics were measured with items from Gurel's Study and Creekmore's for method of measuring clothing variables, items were drawn from preceding measures and, slightly modified. Data were affected from 305 purposively selectee! elderly women over sixty dwelling in Seoul by means of interview and questionnaire. For statistical analyses, frequency distribution, ANOVA, Duncan's multiple Range test, Pearson's Correlation coefficients were used. The results were as follows; 1. The three groups classified, by Perception of self were Positively Correlated to Appearance, Fashion and Psychological dependence. 2. There was partially significant difference between clothing interest and demographic variables. Education and socioeconomic status affected Psychological dependence. Demographic variables not affected Clothing comfort. 3. There was partially significant difference between Perception of self and demographic variables. Age, education, marital status and socioeconomic status affected Perception of Self. 4. There was partially significant relationships among subscales of the Clothing interest. Appearance was positively correlated to clothing comfort, Fashion and Psychological dependence, clothing comfort was positively correlated to Appearance, Psychological dependence. Fashion was positively correlated to Appearance, Clothing comfort and, Psychological dependence.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.443-452
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• 2018

With the explosively increasing intellectual property rights, securing technological competitiveness of companies is more and more important. In particular, since patents include core technologies and element technologies, patent analysis researches are actively conducted to measure the technological value of companies. Various patent analysis studies have been conducted by the International Patent Classification(IPC), which does not include the latest technical classification, and the technical classification accuracy is low. In order to overcome this problem, the Cooperative Patent Classification(CPC), which includes the latest technology classification and detailed technical classification, has been developed. In this paper, we propose a model to analyze the classification of the technologies included in the patent by using the detailed classification system of CPC. It is possible to analyze the inventor's patents in consideration of the relation, importance, and efficiency between the detailed classification schemes of the CPCs to extract the core technology fields and to analyze the details more accurately than the existing IPC-based methods. Also, we perform the comparative evaluation with the existing IPC based patent analysis method and confirm that the proposed model shows better performance in analyzing the inventor's core technology classification.