• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.4 s.163
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• pp.615-623
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• 2007

This study aimed to construct an effective decision-making model on selection of cloth stores using AHP technique. The proposed AHP structure consists of three levels. The highest level includes the cloth stores alternative which are department store, specialty store, and a clothes store. The second level consists of the key performance measurements for evaluating the optimal selection of cloth stores, such as location, facilities, product, service, and promotion. The lowest level consists of items which affects the performance measurements in the upper level. The items are convenience location, courteous service, decor/ambience, availability of parking, etc. The data for this research were collected from questionnaires of 132 in Busan. Data were analyzed by frequency and AHP. As the result of this study, 'product' was decided as a most important item in department store, while 'location' was decided as a most important item in specialty store and a clothes store. And 'variety goods' evaluated as that of first priority in the totality evaluation items in department store, but 'convenience location' evaluated as that of first priority in the totality evaluation items specialty store and a clothes store.

• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.287-299
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• 2022

In radiation epidemiology, the excess relative risk (ERR) model is used to determine the dose-response relationship. In general, the dose-response relationship for the ERR model is assumed to be linear, linear-quadratic, linear-threshold, quadratic, and so on. However, since none of these functions dominate other functions for expressing the dose-response relationship, a Bayesian semiparametric method using splines has recently been proposed. Thus, we improve the Bayesian semiparametric method for the selection of the tuning parameters for splines as the number and location of knots using a Bayesian knot selection method. Equally spaced knots cannot capture the characteristic of radiation exposed dose distribution which is highly skewed in general. Therefore, we propose a nonparametric Bayesian knot selection method based on a Dirichlet process mixture model. Inference of the spline coefficients after obtaining the number and location of knots is performed in the Bayesian framework. We apply this approach to the life span study cohort data from the radiation effects research foundation in Japan, and the results illustrate that the proposed method provides competitive curve estimates for the dose-response curve and relatively stable credible intervals for the curve.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.2
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• pp.29-40
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• 2022

The study investigated the challenges of recruitment and selection process of librarians in federal university libraries in South-South, Nigeria. The study adopted a descriptive survey. The population of the study consists of 108 librarians. 95 copies of the questionnaire were filled and returned. The questionnaire was used in collecting data. The overall reliability of the instrument yielded 0.95 with the use of Cronbach Alpha Coefficient. Standard deviation and mean was used to generate the data that was gathered. The rating scale of 4 points was subjected to an estimation procedure using SPSS version 17.0. A mean score of 2.5 and above on any item was accepted. The findings revealed that the librarians identified the challenges to include ethnicity influence; favouritisms; recruitment based on godfatherism; dwindling budgetary allocation. The librarians also identified some of the strategies to include performance at interview as benchmark; equity and fairness as benchmark; recruitment should be done according to relevant discipline; and having channels for reporting cases of corruption during recruitment. Based on the above findings the study recommended among others that recruitment and selection of qualified librarians should be done according to the laid down procedures.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.190-195
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• 2004

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.549-553
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• 2002

This paper develops knowledge-based multiple fuzzy rules for researcher-selection by automatic ranking process. Inference rules for researcher-selection are created, then the multiple fuzzy rule system with max-min inference is applied. The way to handle for selection standards according to a certain criteria in dynamic manner, is also suggested in a simulation model. The model offers automatic, fair, and trust decision for researcher-selection processing.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.491-499
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• 2011

In this paper, we offer a new strategic portfolio model for national IT R&D project selection in Korea. A risk and return (R-R) portfolio model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R portfolio model to solve the non-strategy and subjectivity problems of the existing national R&D project selection model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technical level reports (TLR) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic portfolio project and balancing the allocation of resources effectively and objectively.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.231-235
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• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• Journal of the Korean Society for Library and Information Science
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• v.29
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• pp.173-204
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• 1995

The purpose of this study is to promote understanding of the book selection theory by researching dialectically of its development process centering on the BSTv(value theory) and BSTd(demand theory). The results of this study are summarized as follows 1. In the period of enlightenment and education, the book selection theory of public libraries was the thesis state of BSTv(d). 2. Antithesis state of BSTv(d), that is, BSTd was raised to real central theory of book selection in the early 20th century. 3. In the 1930-40's, BSTv and BSTd were transformed into balance state or coexistence relations(BSTb $[v(d){\cdot}d(v)$]. 4. After World War II, BSTn(library needs theory) and BSTo(library objective theory) were evoked, and opposed to the existing selection theories. Now, they are developing into BSTbl$[n(d)\cdot\;o(v)\;or\;n(d){\cdot}v(o)]$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.158-164
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• 2007

Supply Chain Management (SCM) system is a critical investment that can affect the competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper presents the characteristic factors of SCM system and a Fuzzy AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. This study focuses on quantitative factors, applying the fuzzy concept to various evaluative factors. The proposed model can systematically construct the objectives of SCM system selection to achieve the business goals. A empirical example demonstrates the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.