• 방사성폐기물학회지
• /
• 제20권4호
• /
• pp.533-540
• /
• 2022

Because of the massive development of nuclear power plants in China in recent years, China is facing the challenge of radioactive waste disposal. China has established complete regulatory requirements for radioactive waste disposal, but it also has encountered problems and challenges in low-level radioactive waste disposal in terms of management, selection of disposal facility sites, and implementation of a site selection plan. Three low-level radioactive waste disposal facilities that have been operated in China are described, and their activity limits, locations, and capacities are also outlined. The connotations of "regional" and "centralized" disposal policies are discussed in light of the characteristics of the radioactive waste. The characteristics and advantages of the regional and centralized disposal policies are compared. It is concluded that the regional disposal policy adopted in 1992 can no longer meet the current disposal needs, and China should adopt a combination of the two disposal policies to solve the problem of radioactive waste disposal.

• Genomics & Informatics
• /
• 제4권1호
• /
• pp.45-47
• /
• 2006

D2GSNP is a web-based server for the selection of single nucleotide polymorph isms (SNPs) within genes related to human diseases. The D2GSNP is based on a relational database created by downloading and parsing OMIM, GAD, and dbSNP, and merging it with positional information of UCSC Golden Path. Totally our server provides 5,142 and 1,932 non-redundant disease genes from OMIM and GAD, respectively. With the D2GSNP web interface, users can select SNPs within genes responding to certain diseases and get their flanking sequences for further genotyping experiments such as association studies.

• 대한약학회:학술대회논문집
• /
• 대한약학회 2001년도 Proceedings of the Pharmaceutical Society of Korea
• /
• pp.169.1-169.1
• /
• 2001

• Food Science and Biotechnology
• /
• 제15권4호
• /
• pp.485-493
• /
• 2006

Lactococcus species are noninvasive and nonpathogenic microorganisms that are widely used in industrial food fermentation and as well-known probiotics. They have been modified by traditional methods and genetic engineering to produce useful food-grade materials. The application of genetically modified lactococci in the food industry requires their genetic elements to be safe and stable from integration with endogenous food microorganisms. In addition, selection for antibiotic-resistance genes should be avoided. Several expression and secretion signals have been developed for the production and secretion of useful proteins in lactococci. Food-grade systems composed of genetic elements from lactic acid bacteria have been developed. Recent developments in this area have focused on food-grade selection markers, stabilization, and integration strategies, as well as approaches for controlled gene expression and secretion of foreign proteins. This paper reviews the expression and secretion signals available in lactococci and the development of food-grade markers, food-grade cloning vectors, and integrative food-grade systems.

• Communications for Statistical Applications and Methods
• /
• 제22권1호
• /
• pp.55-67
• /
• 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.

• 응용통계연구
• /
• 제25권3호
• /
• pp.471-483
• /
• 2012

One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

• 제어로봇시스템학회논문지
• /
• 제3권5호
• /
• pp.490-496
• /
• 1997

This paper describes a new process-plan selection method using a modified Fuzzy Quantification Theory(FQT). The problem of process-plan selection can be characterized by multiple attributes and used subjective, uncertain information. Fuzzy Quantification Theory is used for handling such information because it is a useful tool when human judgment or evaluation is quantified via linguistic variables, and the proposed method is concerned with the selection of a process plan by derivation of the values of categories for each attribute. In this paper, a modified Fuzzy Quantification Theory(FQT) is described and the procedure of this approach is explained and examples illustrated.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1995년도 하계학술대회 논문집 B
• /
• pp.1006-1010
• /
• 1995

This paper describes Sexual Reproduction Genetic Algorithm(SRGA) for function optimization. In SRGA, each individual utilize a diploid chromosome structure. Sex cells(gametes) are produced through artificial meiosis in which crossover and mutation occur. The proposed method has two selection operators, one, individual selection which selects the individual to fertilize, and the other, gamete selection which makes zygote for offspring production. We consider the effects of multi-selection and diploidy on search performance. SRGA improves local and global search(exploitation and exploration) and show optimum tracking performance in nonstationary environments. Gray coding is incorporated to transforming the search space and Genic uniform distribution method is proposed to alleviate the problem of premature convergence.

• 산업경영시스템학회지
• /
• 제38권2호
• /
• pp.82-90
• /
• 2015

Location selection of distribution centers is a crucial task for logistics operators and key decision makers of an organization. This is a multi-criteria decision making (MCDM) process which includes both quantitative and qualitative criteria. In order to propose an optimized location selection model, this research suggests a hierarchical group of evaluation criteria : 5 major criteria with 15 sub-criteria. The MCDM approach presented in this research, by integrating Grey Relational Analysis (GRA) with Analytic Hierarchy Process (AHP), tends to rectify the overall quality and uncertainty of the values of evaluation criteria. An example of a location selection case in Korea is illustrated in this study to show the effectiveness of this method.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제6권4호
• /
• pp.277-281
• /
• 2006

Cyber counseling, one of the most compatible type of consultation for the information society, enables people to reveal their mental agonies and private problems anonymously, since it does not require face-to-face interview between a counsellor and a client. However, there are few cyber counseling centers which provide high quality and trustworthy service, although the number of cyber counseling center has highly increased. Therefore, this paper is intended to enable an appropriate consultation for each client by analyzing client propensity using Bayesian variable selection. Bayesian variable selection is superior to stepwise regression analysis method in finding out a regression model. Stepwise regression analysis method, which has been generally used to analyze individual propensity in linear regression model, is not efficient since it is hard to select a proper model for its own defects. In this paper, based on the case database of current cyber counseling centers in the web, we will analyze clients' propensities using Bayesian variable selection to enable individually target counseling and to activate cyber counseling programs.