• Animal Bioscience
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• v.35 no.9
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• pp.1340-1350
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• 2022

Objective: Luxi Black Head sheep (LBH) is the first crossbreed specialized for meat production and was developed by crossbreeding Black Head Dorper sheep (DP) and Small Tailed Han sheep (STH) in the farming areas of northern China. Research on the genomic variations and selection signatures of LBH caused by continuous artificial selection is of great significance for identifying the genetic mechanisms of important traits of sheep and for the continuous breeding of LBH. Methods: We explored the genetic relationships of LBH, DP, and several Mongolian sheep breeds by constructing phylogenetic tree, principal component analysis and linkage disequilibrium analysis. In addition, we analysed 29 whole genomes of sheep. The genome-wide selection signatures have been scanned with four methods: heterozygosity (H_P), fixation index (F_ST), cross-population extended haplotype homozygosity (XP-EHH) and the nucleotide diversity (𝜃_π) ratio. Results: The genetic relationships analysis showed that LBH appeared to be an independent cluster closer to DP. The candidate signatures of positive selection in sheep genome revealed candidate genes for developmental process (HoxA gene cluster, BCL2L11, TSHR), immunity (CXCL6, CXCL1, SKAP2, PTK6, MST1R), growth (PDGFD, FGF18, SRF, SOCS2), and reproduction (BCAS3, TRIM24, ASTL, FNDC3A). Moreover, two signalling pathways closely related to reproduction, the thyroid hormone signalling pathway and the oxytocin signalling pathway, were detected. Conclusion: The selective sweep analysis of LBH genome revealed candidate genes and signalling pathways associated with developmental process, immunity, growth, and reproduction. Our findings provide a valuable resource for sheep breeding and insight into the mechanisms of artificial selection.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.123-135
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• 1997

The solid waste incineration facilities which cause environmental pollution. And those are some kind of loathing facilities for residents who do not want it. This problem could be solved by location feasibility study. The purpose of location feasibility study was to determine one site out of three candidate sites. This study which was done by the law, environmental and economic factor was considered for optimum site selection. Comparative evaluation among the candidate sites was done by ordinal scale and thus the optimum site was selected.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.589-601
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• 2001

Probabilities of overfilling for model selection criteria are derived for several different situations. First, one candidate model with one extra variable is compared to the current model. This is expanded to m candidate models. We show that these comparisons are not independent and discuss ovefitting probabilities. Correlation between two F-tests is derived. Finally, probabilities are computed using the dependent F distributions and F distributions based on order statistics of independent Chi-squares.

• Journal of environmental and Sanitary engineering
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• v.15 no.2
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• pp.85-94
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• 2000

The comparative evaluation is the most effective method for site selection because the selection of waste treatment facility is to determine the optimum site out of limited candidate sites. This study adopted the ordinal scale evaluation, one of methods of comparative evaluation. The ordinal scale evaluation aims to determine the investigating items referring to the character of sites, to determine the importance factors for investigating items, and to determine the optimum site according to the quantitative evaluation. This study has focussed on reflecting the opinion of residents to the maximum extent with a weight on social and economic aspects, considering the state of confrontation against each other between the autonomous government organization and local residents, which is being emerged as a social issue relating to the evaluation rating on each item of site selection of an optimum site. Therefore, rational, and clear validity investigations and proper reduction of both time and expenses in site selection as well through this a study.

• Journal of the Korean Society of Systems Engineering
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• v.9 no.1
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• pp.55-63
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• 2013

Nuclear power plant site selection is a complex process and its successful completion is a critical milestone in the NPP development cycle. Proper siting of NPP will ensure public health and safety, environmental conservation, reduced project failure risks and a smooth NPP development process among other benefits. The objective of this paper is to demonstrate the application of systems engineering to the problem of NPP siting in Kenya. The siting process demonstrated in this paper includes stakeholder need analysis where stakeholders are identified and their needs concerning NPP site are elicited and converted into system functional requirements. A value model is then developed and potential sites iteratively subjected to three types of criteria i.e. exclusionary criteria, avoidance criteria and suitability criteria. This process is used to identify the candidate sites. An additive value model; multiple objectives Decision Analysis (MODA) is then used to calculate candidate solutions values. The site with the highest solution value score is selected. Sensitivity studies using different criterion weight sets (thereby reflecting different viewpoints) can be conducted to assess their effect on the selection of a preferred site and thereby lend additional credibility to the decision process.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.326-330
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• 2008

The study on combining multiple classifiers in the field of pattern recognition has mainly focused on how to combine multiple classifiers, but it has gradually turned to the study on how to select multiple classifiers from a classifier pool recently. Actually, the performance of multiple classifier system depends on the selected classifiers as well as the combination method of classifiers. Therefore, it is necessary to select a classifier set showing good performance, and an approach based on information theory has been tried to select the classifier set. In this paper, a classifier set candidate is made by the selection of classifiers, on the basis of mutual information between classifiers, and the classifier set candidate is compared with the other classifier sets chosen by the different selection methods in experiments.

• Journal of Dairy Science and Biotechnology
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• v.18 no.1
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• pp.47-60
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• 2000

Over decades of work, the probiotic research has grown rapidly with a number of new cultures, which is claimed a variety of benefit. However, many of the specific effects attributed to the ingestion of probiotics remain convoluted and scientifically unsubstantiated. Accordingly, the scientific community faces a greater challenge and must objectively seek cause and effect relationships for many potential and currently investigated probiotic species. Rational selection and design of probiotics remains an important challenge and will require a solid information about the physiology and genetics of candidate strains relevant to their intestinal roles, functional activities, and interaction of with other resident micro flora. As far as beneficial culture of lactic acid bacteria (LAB) is concerned, simple, cost-effective, and exact identification of candidate strains is of foremost importance among others. Until recently, the relatedness of bacterial isolates has been determined sorely by testing for one or several phenotyphic markers, using methods such as serotyping, phage-typing, biotyping, and so forth. However, there are problems in the use of many of these phenotype-based methods. In contrast, some of newer molecular typing methods involving the analysis of DNA offer many advantages over traditional techniques. These DNA-based methods have the greater discriminatory power than that of phenotypic procedures. This review focuses on the importance and the basis of molecular typing methods along with some considerations on de-sign and selection of probiotic culture for human consumption.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.2
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• pp.118-125
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• 1990

An optimal file allocation algorithm which seeks optimal solution of file allocation problem for efficient management and operation of information files in distributed computer system is proposed. Since file allocation time in practical applications that have many computer sites is tool long, the problem size has to be reduced and computation time is improved by using preassignment conditio. A new method which calculate appriasal value for accurrate value for accurrate representation of assigned state is proposed and the selection criteria to candidate nodes for rapid determination of allocation are given. By using selection criteria, file allocation is determined and final appraisal value represent total cost of assigned state.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.164-172
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• 2013

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.109-118
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• 2013

Purpose: Given the several proper models for given mixture components-process variables experimental data, we propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those models. Methods: Given the mixture experimental data with process variables, first we choose the reasonable starting models among the class of admissible product models based on the model selection criteria and then, search for the candidate models that are the subset models of the starting model by the sequential variable selection method or all possible regressions procedure. Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. Results: We propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those good candidate models by adopting the optimization methods developed in multiple responses surface methodology. Conclusion: A strategy is proposed to find the optimal condition in which the performance of the responses is well-behaved under those proper combined models. This strategy to find the optimal condition is illustrated with the example in this paper.