• The Korean Journal of Health Service Management
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• v.6 no.4
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• pp.279-294
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• 2012

The study compared refractive surgery patients' hospital selection factors and satisfaction, through this to see the factors influencing patients' satisfaction, aiming at 235 patients visiting two Eye hospitals. The research results are followed. First, target group's hospital selection factors appeared facilities and environment factor, reliability factor, personal service factor, and accessibility factor in the order. Second, patients' satisfaction appeared reliability factor, facilities and environment factor, and personal factor in the order. Fourth, in the result comparing patients' expectation on hospital selection and satisfaction score, all factors of facilities and environment, personal service, and reliability had high satisfaction score than expectation. Third, in the result of factors influencing refractive surgery patients' satisfaction, in surgery determination period, surgery expenditure, and hospital selection factors among characteristics relating to refractive surgery, facilities and environment, personal service, and reliability appeared as satisfaction influencing factors. In conclusion, the study found that hospital selection factors and satisfaction influencing factors by refractive surgery patients' surgery type are considered to be able to be used to establish marketing strategy in the fields excluded from insurance application, the researches to improve patients' satisfaction in patient-oriented medical market should be continuously proceeded.

• Journal of Information Technology Applications and Management
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• v.19 no.3
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• pp.19-30
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• 2012

Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper is aimed to present a fuzzy decision making approach to deal with the material selection in engineering design problems. A fuzzy multi criteria decision-making model is proposed for solving the material selection problem. The proposed model makes use of fuzzy TOPSIS (Technique for Order reference by Similarity to Ideal Solution) with trapezoidal numbers for evaluating the criteria and ranking the alternatives. And result is compared with fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multi criteria Optimisation and Compromise Solution) which is proposed by Jeya Girubha and Vinodh [2012]. The present paper is aimed to also improve literature of fuzzy decision making for material selection problem.

• Journal of Information Technology Services
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• v.19 no.2
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• pp.93-107
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• 2020

Recently, artificial intelligence (AI) technologies has been widely used in various fields such as finance, and distribution. Accordingly, Korea has also announced its AI R&D strategy for the realization of i-Korea 4.0 in May 2018. However, Korea's AI technology is inferior to major competitors such as the US, Canada, and Japan Therefore, in order to cope with the 4th industrial revolution, it is necessary to allocate AI R&D budgets efficiently through selection and concentration so as to gain competitive advantage under a limited budget. In this study, the importance of each AI technology was evaluated in multi-dimensional way through the questionnaire of expert group using the evaluation index derived from the literature review From the results of this study, we draw the following implication. In order to successfully establish the AI technology development strategies, it is necessary to prioritize the cognitive computing technology that has great market growth potential, ripple effect of technology development, and the urgency of technology development according to the principle of selection and concentration. To this end, it is necessary to find creative ideas, manage assessments, converge multidisciplinary systems and strengthen core competencies. In addition, since AI technology has a large impact on socioeconomic development, it is necessary to comprehensively grasp and manage scientific and technological regulations in order to systematically promote AI technology development.

• Korean Management Science Review
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• v.14 no.2
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• pp.1-17
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• 1997

Many companies in these days have pursued an outsourcing policy to survive in a highly competitive world market. To effectively deal with the outsourcing policy, it is required that the companies have a useful method to rationally evaluate a supplier's performance from a viewpoint of a company's strategy and in a comparative-integrated manner. In this paper, we examined the relative importance of supplier selection criteria for a company's strategy by conducting a survey and proposed "Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)" as one of the plausible techniques to evaluate a supplier's total performance. A hypothetical case study is presented to demonstrate the applicability of the method.

• Journal of Ecology and Environment
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• v.44 no.2
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• pp.106-114
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• 2020

Background: Determining patterns of habitat use is key to understanding of animal ecology. Approximately 1% of bird species use brood parasitism for their breeding strategy, in which they exploit other species' (hosts) parental care by laying eggs in their nests. Brood parasitism may complicate the habitat requirement of brood parasites because they need habitats that support both their host and their own conditions for breeding. Brood parasitism, through changes in reproductive roles of sex or individual, may further diversify habitat use patterns among individuals. However, patterns of habitat use in avian brood parasites have rarely been characterized. In this study, we categorized the habitat preference of a population of brood parasitic lesser cuckoos (Cuculus poliocephalus) breeding on Jeju Island, Korea. By using compositional analyses together with radio-tracking and land cover data, we determined patterns of habitat use and their sexual and diurnal differences. Results: We found that the lesser cuckoo had a relatively large home range and its overall habitat composition (the second-order selection) was similar to those of the study area; open areas such as the field and grassland habitats accounted for 80% of the home range. Nonetheless, their habitat, comprised of 2.54 different habitats per hectare, could be characterized as a mosaic. We also found sexual differences in habitat composition and selection in the core-use area of home ranges (third-order selection). In particular, the forest habitat was preferentially utilized by females, while underutilized by males. However, there was no diurnal change in the pattern of habitat use. Both sexes preferred field habitats at the second-order selection. At the third-order selection, males preferred field habitats followed by grasslands and females preferred grasslands followed by forest habitats. Conclusions: We suggest that the field and grassland habitats represent the two most important areas for the lesser cuckoo on Jeju Island. Nevertheless, this study shows that habitat preference may differ between sexes, likely due to differences in sex roles, sex-based energy demands, and potential sexual conflict.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.4 s.44
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• pp.471-484
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• 1992

The purpose of this study was 1) to find out Market segmentation possibilities according to consumer's store selection factors by analysis of Consumer's attitude and oriteria of apparel store selection, 2) to provide marketing strategies of segment marker for apparel stores Research problems were as follows. 1) To find out the important factors of consumer's store selection and to segment markets according to their factors. 2) To find out consumer characteristics (demographic variables, clothing life factors, cloth-ing purchase behaviors) according to segment markets. 3) To find out preference store types and preference factors according to segment markets. 4) To provide marketing mix strategy for retail apparel store sales. The subjects selected for the final analysis were 586 female college students, housewives, and workers living in Seoul. A questionnaire was developed in order to measure consumer's selection criteria of apparel store, consumer characteristics and preferred store types and preferential factors. The results of this study were as follows: 1. There were 8 factors of consumer's store selection such that: the high quality, convenience, store atmosphere, economy, dependency commercials, store patronage, the conformity, product assortment. the result of cluster analysis based on these 8 factors of store selection verified that market was able to be segmented as four different market, which were the store loyalty group, the aligned economical group, the assortment pursuing group, the store fame dependent group. 2. There were significant differences among four groups, for 4 variables related to consumer's characteristics such as demographic characteristics (sex, age, job, level of education, the living quarters, marrige or unmarrige), clothing life factors, clothing evaluating criteria, and favorite fashion information sources. 3. There were significant differences among four groups for 2 variable related to store preference such as preference types of store and preference factors of store.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.271-282
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• 2008

Database administrators are demanded to acquire much knowledges and take great efforts for keeping consistent performance in system. Various principles, methods, and tools have been proposed in many studies and commercial products in order to alleviate such burdens on database administrators, and it has resulted to the automation of DBMS which reduces the intervention of database administrator. This paper suggests a resource selection method that estimates the status of the database system based on the workload characteristics and that recommends tuneable resources. Our method tries to simplify selection information on DBMS status using data-mining techniques, enhance the accuracy of the selection model, and recommend tuneable resource. For evaluating the performance of our method, instances are collected in TPC-C and TPC-W workloads, and accuracy are calculated using 10 cross validation method, comparisons are made between our scheme and the method which uses only the classification procedure without any simplification of informations. It is shown that our method has over 90% accuracy and can perform tuneable resource selection.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.35
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• pp.147-178
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• 2007

This study clarified a study of relationship of strategic alliance structure factor, partner selection criteria and performance awareness on the container liners alliance. In order to obtain such objective of study existing literature variables suitable to the container liner were perused and extracted. Research models for research development and three study hypothesis were set out and scope of investigation and samples were chosen. The research hypothesis are followings. H1: The factors of strategic alliance motivation influence the performance awareness. H2: The strategic alliance structure factors influence the performance awareness. H3: The factors of partner selection criteria influence the performance awareness. In the result of the empirical study, the hypothesis 1, hypothesis 2 were supported completely and hypothesis 3 was partially supported.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.878-884
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• 2012

This study presents a portfolio selection strategy focusing on construction corporations by taking into accounts managerial efficiency and growth potential of a company. Data envelopment analysis(DEA) methodology and dividend scoring table are adopted for evaluating the managerial efficiency and growth potential of a company respectively. In order to show the effectiveness of the portfolios selected by the strategies proposed in this study, we constructed 3 portfolios for every 4 years (2007-2010) out of 56 listed construction corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of portfolio evaluation measures.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1177-1186
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• 2017

This paper presents a torque ripple reduction method of direct torque control (DTC) using fuzzy controller with optimal selection strategy of voltage vectors in a five-phase induction motor. The conventional DTC method has some drawbacks. First, switching frequency changes according to the hysteresis bands and motor's speed. Second, the torque ripple is rapidly increased in long control period. In order to solve these problems, some/most papers have proposed torque ripple reduction methods by using the optimal duty ratio of the non-zero voltage vector. However, these methods are complicated in accordance with the parameter. If this drawback is eliminated, the torque ripple can be reduced compared with conventional method. In addition, the DTC can be simply controlled without the use of the parameter. Therefore, the proposed algorithm is changing the voltage vector insertion time by using the designed fuzzy controller. Also, the optimized voltage vector selection method is used in accordance with the torque error. Simulation and experimental results show effectiveness of the proposed control algorithm.