• The Korean Journal of Community Living Science
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• v.16 no.4
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• pp.59-69
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• 2005

This study examined the shop selection standards and preferred shops depending on the clothing attitudes identified by the psychological characteristics of consumers. To this end, this study selected the Korean Chinese college women in Yanbian. The study was conducted against 300 college students from May to June, 2002. Questionnaire was used for studying the subject of the thesis. Each question was rate4 in 5 point scale, where 1 means 'not at all' and 5 means 'definitely'. The data of this study was statistically analyzed using the SAS PC program. The t-test and $X^{2}$ were conducted to identify the evaluation criteria for clothing store and the preferred shops depending on clothing attitude groups and the factor analysis was carried out to analyze the clothing behavior factors. The results of study are summarized as described below. The clothing attitude of college women was classified into four factors: fashionable, brand-oriented, aesthetic and modest. The subjects were divided into two groups with higher average score and that with lower average score by factor, respectively. As a result of study on the evaluation standards of shop selection and preferred shops depending on the clothing attitude, for the evaluation standards of shop selection, three factors, fashionable, brand-oriented and modest factors, showed the significant difference between two groups. There was a significant difference between two groups in fashionable and brand-oriented factor and the preferred shops.

• IE interfaces
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• v.20 no.3
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• pp.376-386
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• 2007

The analytic hierarchy process (AHP), a well-known and useful decision making method, has been applied to R&D project evaluation and selection. The objective of this study is to propose a new model for evaluating and selecting R&D projects of Samsung Electro-Mechanics, the top manufacturer of electronic components in Korea, using the AHP. To show the validity of the new model, we strived to successively compare the final priorities for R&D projects with the priorities obtained by the existing model and the new model respectively.

• Journal of Navigation and Port Research
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• v.33 no.2
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• pp.135-141
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• 2009

The circumstances surrounding world ports have changed rapidly and port competition to attract cargoes has been increasing fiercely. Specifically, deploying large container vessels resulted fewer port visits and strategic alliance among liner shipping companies. Recently, many studies have worked for improving port competitiveness. However, these studies were limited to evaluation of only port competitiveness and few studies suggested strategies for reinforcing port competitiveness. Although implications of these previous studies are practically available to build policies for port, there have been very few academic studies such as identifying port competitiveness and port selection with related attributes for reasonable evaluation and analysis. Therefore, this study aims to classify the existing studies, which dealt with port selection problem, based on basic structure that was suggested by Murphy (1992). Furthermore, the conceptual definition will be carried out by comparison analysis in terms of time of study, type of data and methodology and decision factor of each study.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.25-30
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• 2018

Pattern classification system is often an important component of intelligent systems. In this paper, we present a pattern classification system consisted of the feature selection module, knowledge base construction module and decision module. We introduce a feature impact evaluation selection method based on fuzzy cluster analysis considering computational approach and generalization capability of given data characteristics. A fuzzy neural network, OFUN-NET based on unsupervised learning data mining technique produces knowledge base for representative clusters. 240 blemish pattern images are prepared and applied to the proposed system. Experimental results show the feasibility of the proposed classification system as an automating defect inspection tool.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.265-267
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• 2012

This paper analyzes network selection issues of secondary users (SUs) in Cooperative Cognitive Radio Networks (CRNs) by utilizing Queuing Model. Coordinating with Handover Cost-Based Network selection, this paper also addresses an opportunity for the secondary users (SUs) to enhance QoS as well as economics efficiency. In this paper, network selection of SUs is the optimal association between Overall System Time Minimization Problem evaluation of Secondary Connection (SC) and Handover Cost-Based Network selection. This will be illustrated by simulation results.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.407-416
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• 2023

In order to effectively relieve the traffic pressure of the city, ensure the smooth flow of freight and promote the development of the logistics industry, the selection of appropriate port logistics location is the basis of giving full play to the port logistics function. In order to better realize the selection of port logistics, this paper adopts the entropy weight method to set up a multi-dimensional evaluation index, and constructs the evaluation model of port logistics location. Then through the actual case, from the environmental dimension and economic competition dimension to make choices and analysis. The results show that port d has the largest logistics competitiveness and the highest relative proximity among the three indicators of hinterland city economic activity, hinterland economic structure, and port operation capacity of different port logistics locations, which has absolute advantages. It is hoped that the research results can provide a reference for the multi-dimensional selection of port logistics site selections.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.662-671
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• 2007

Since variety of construction projects with their individual specifications could be handled through different procurement systems, selection of the most appropriate project delivery system is a vital step towards more efficient project execution. The appropriate selection of project delivery system may also ensure more competent management of the project. Its impacts are not only limited to the first stages of the project, as it could also influence pre-construction, construction and operational phases of the project. Among different approaches exerted for this purpose, none has taken uncertainty into account, despite the fact that during first stages of the project most of the selection factors are still uncertain and not clearly defined. This paper, hence, aims to provide a fuzzy insight into the project delivery system selection. Through this approach more tangible model of the evaluation process may be presented. Proposed fuzzy method is indeed a multi criteria decision making model, based on the group of criteria, assigned for the evaluation procedure. A case study is also conducted, based on the opinion of an invented group of the experts.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.25-32
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• 2013

Due to increasing competition of globalization and fast technological improvements the appropriate method for evaluating and selecting IS-personnel is one of the key factors for an organization's success. Personnel selection is a multi-criteria decision-making (MCDM) problem which consists of both qualitative and quantitative metrics. Although many articles have discussed various knowledge and skills IS personnel should possess, no specific model for IS personnel selection and evaluation, to our knowledge, has been published up to now. After reviewing the IS personnel's important characteristics, we propose an approach for categorizing the IS personnel based on their skills, ability, and knowledge during evaluation and selection process. Our proposed approach is derived from a model of neural network algorithm. We have adapted and implemented the fuzzy ART algorithm with Jaccard choice function. The result of an illustrative numerical example is proposed to demonstrate the easiness and effectiveness of our approach.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2008.11a
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• pp.205-211
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• 2008

Recently, selects method of waterproofing where is suitable with method and material physical properties, construction technique, Productive technique and specifications and maintenance techniques evaluation for the same evaluation method is coming to be presented. Respects the application which select system is substantial objectively reflects a weight to evaluation item the research for is necessary. This research the evaluation which in order is effective and the decision-making to be possible about technically countermeasures for a quality security from waterproofing materials, method selection processes, clearly responsible dividing of construction and maintenance techniques. A sets weight of evaluation item for right select system, it stratify the causes which affect in priority based on AHP.

• Journal of Korean Academy of Nursing
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• v.37 no.3
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• pp.414-421
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• 2007

Background: Nursing intervention studies often suffer from a selection bias introduced by failure of random assignment. Evaluation with selection bias could under or over-estimate any intervention's effects. PS matching (PSM) can reduce a selection bias through matching similar Propensity Scores (PS). PS is defined as the conditional probability of being treated given the individual's covariates and it can be reused to balance the covariates of two groups. Purpose: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. Method: An intervention study for patients with some baseline individual characteristic differences between two groups was used for this demonstration. The result of a t-test with PSM was compared with a t-test without matching. Results: The level of HbA1c at 12 months after baseline was different between the two groups in terms of matching or not. Conclusion: This study demonstrated the effects of a quasi-random assignment. Evaluation using PSM can reduce a selection bias impact that affects the result of the nursing intervention. Analyzing nursing research more objectively to reduce selection bias using PSM is needed.