• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.291-295
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• 2005

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.34-40
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• 2000

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.565-566
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• 2018

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2017.05a
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• pp.217-218
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• 2017

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.191-196
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• 2009

In this paper, we proposed a feature selection method using Binary Particle Swarm Optimization(BPSO) and Mutual information. This proposed method consists of the feature selection part for selecting candidate feature subset by mutual information and the optimal feature selection part for choosing optimal feature subset by BPSO in the candidate feature subsets. In the candidate feature selection part, we computed the mutual information of all features, respectively and selected a candidate feature subset by the ranking of mutual information. In the optimal feature selection part, optimal feature subset can be found by BPSO in the candidate feature subset. In the BPSO process, we used multi-object function to optimize both accuracy of classifier and selected feature subset size. DNA expression dataset are used for estimating the performance of the proposed method. Experimental results show that this method can achieve better performance for pattern recognition problems than conventional ones.

• Journal of the Korea Institute of Building Construction
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• v.16 no.4
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• pp.331-339
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• 2016

According to high-rise, complexation, and enlargement of buildings, various construction methods are being developed, and the significance of construction method selection about main work types has emerged as a major interest. However, it has been pointed out that hand-on workers cannot consider project characteristics carefully, and they lack an objective standard or reference for main construction method selection. Hence, the selection is being made depending on hand-on workers' experience and intuition. To solve this problem, various studies have proceeded for construction method selection of main work types using Artificial Intelligence like Fuzzy, AHP and Case-based reasoning. It is difficult to apply many different kinds of construction method selection to every main work type with consideration for characteristics of work types and condition of a construction site when selecting construction method in the field. Accordingly, this study proposed the decision-making model which can apply to fields easily. Using matrix analysis and liner transformation, this study verified consistency of study models applied in the process of soil retaining selection with a case study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.560-569
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• 2005

This paper proposes an algorithm for transmit antenna selection in a multi-input multi-output(MIMO) spatial multiplexing system with per antenna rate control(PARC) and an ordered successive interference cancellation (OSIC) receiver. The active antenna subset is determined at the receiver and conveyed to the transmitter using feedback information on transmission rate per antenna. We propose a serial decision procedure consisting of a successive process that tests whether antenna selection gain exists when the antenna with the lowest pre-processing signal to interference and noise ratio(SINR) is discarded at each stage. Furthermore, we show that 'reverse detection ordering', whereby the signal with the lowest SINR is decoded at each stage of successive decoding, widens the disparities among fractions of the whole capacity allocated to each individual antenna and thus maximizes a gain of antenna selection. Numerical results show that the proposed reverse detection ordering based serial antenna selection approaches the closed-loop MIMO capacity and that it induces a negligible capacity loss compared with the heuristic selection strategy even with considerably reduced complexity.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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• pp.71-86
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• 2009

The healthcare environment today is changing rapidly with factors of healthcare consumers in selecting medical institutions also altering at a fast pace under the circumstances. In this study, the theory of consumption values established by Sheth in 1991 is adopted in order to examine particular value affecting consumer selection of healthcare institutions. For the purpose of this study, healthcare consumers were surveyed using questionnaires developed based on the five values of Sheth supplemented by value of effort to acquire hospital information and value in health. Consequently, 24 consumption values affecting selection process were confirmed through discriminant analysis. As a result of regression analysis on factors affecting consumer selection of healthcare institution, effort to acquire hospital information and age among demographic characteristics of respondents are determined important predictors for consumer selection of general hospitals over clinics or small-sized hospitals. Further, service, reputation scale of healthcare institution among functional values and importance of health and effort to acquire hospital information among value in health are identified as significant predictors for consumer selection of large-sized general hospitals over clinic or small-sized hospitals. This study suggests not only vital implications for marketing strategy of healthcare institutions, but also methods to promote positive image for healthcare providers. In addition, this study closely examines the cause of the leaning phenomenon of healthcare comsumers toward large-sized general hospitals.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.203-213
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• 2021

This study involves descriptive research designed to understand the level of major satisfaction, the motivation for major selection, and major commitment of undergraduate nursing students, as well as the factors influencing major commitment and the mediating role of major selection motives. Data collection was conducted with 228 people enrolled in nursing colleges located in Daegu and North Gyeongsang Province, and proceeded from November 7th to November 16th, 2020. The collected data was analyzed with the SPSS/WIN 22.0 program. The analysis found that the level of major satisfaction was high and that the motivation for major selection and the major commitment were strong. Major satisfaction and motivation for major selection were predicted as factors influencing major commitment. Major satisfaction and major commitment were partially mediated by the motive for major selection, and specifically, they were partially mediated by personal motives. These results provide basic information to improve the undergraduate nursing students' major commitment, and suggests the importance of the process in which nursing is selected as a major.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.111-116
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• 2005

This paper considers the problem of optimally choosing the sub-process means of a mixture production process where two important ingredients are mixed. The quantity of each ingredient is controlled through each corresponding sub-process. The values of the sub-process mean directly affect the defective rate, production, scrap and reprocessing costs for the mixture production process. After inspecting every incoming item, each conforming item is sold in a regular market for a fixed price and any nonconforming item is scraped. A model is constructed on the basis of the selling price, production, inspection, and scrap and reprocessing costs. The goal is to determine the optimum sub-process mean values based on maximizing expected profit function relating selling price and cost components. A method of finding the optimum sub-process means is presented when the quantities of the two ingredients are assumed to be normally distributed with known variances. A numerical example is given and numerical studies are performed.