• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.91-94
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• 1985

A method optimizing selection of a state weighting matrix is presented. The state weight-ing matrix is chosen so that the closed-loop system responses closely match to the ideal model responses. An algorithm is presented which determines a positive semidefinite state weighting matrix in the linear quadratic optimal control design problem and an numerical example is given to show the effect of the present algorithm.

• Journal of The Korean Association For Science Education
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• v.36 no.3
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• pp.389-397
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• 2016

This study aims to test the efficacy of English-based automated computer scoring models and machine translation to score Korean college students' written responses on natural selection concept items. To this end, I collected 128 pre-service biology teachers' written responses on four-item instrument (total 512 written responses). The machine translation software (i.e., Google Translate) translated both original responses and spell-corrected responses. The presence/absence of five scientific ideas and three $na{\ddot{i}}ve$ ideas in both translated responses were judged by the automated computer scoring models (i.e., EvoGrader). The computer-scored results (4096 predictions) were compared with expert-scored results. The results illustrated that no significant differences in both average scores and statistical results using average scores was found between the computer-scored result and experts-scored result. The Pearson correlation coefficients of composite scores for each student between computer scoring and experts scoring were 0.848 for scientific ideas and 0.776 for $na{\ddot{i}}ve$ ideas. The inter-rater reliability indices (Cohen kappa) between computer scoring and experts scoring for linguistically simple concepts (e.g., variation, competition, and limited resources) were over 0.8. These findings reveal that the English-based automated computer scoring models and machine translation can be a promising method in scoring Korean college students' written responses on natural selection concept items.

• 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.

• Journal of Embryo Transfer
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• v.11 no.1
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• pp.1-6
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• 1996

다배란 수정란이식(MOET)과 체외수정(IVF)기술을 이용한 육종체계에서 예상되는 유전적 개량량을 여러 집단의 크기에서 비교한 결과 체외수정기술이 MOET육종기술보다 특히 개량대상 유전력이 낮을때 훨씬 효율적으로 나타났다. 그러나 유전력이 높아지면 (h$^2$=0.3, 0.5), MOET와 IVF간의 상대적 차이는 미진하게 나타났다. 체외수정을 이용한 육종기술에서 암컷의 선발 강도는 대단히 높일 수 있는 반면 난자의 회수율이 많을수록 상대적으로 수컷에 대한 선발 강도는 낮아진다. 그 이유는 한 가계에서 근친을 피하기 위해 한 마리의 수컷만 선발해야 하므로 수소의 선발강도는 난자의 회수율이 높을수록 상대적으로 낮아진다. 여러 수준의 난자회수율(10, 20, 30, 50, 100)중에서 30일 때 가장 높은 유전적 개량을 나타내었다. (Key word: MOET, IVF,selection responses)

• Culinary science and hospitality research
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• v.23 no.5
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• pp.77-86
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• 2017

The purpose of this study is to investigate the impact of selection attributes of dessert cafes on experience value and revisit intention. A survey was conducted from June 3, 2017 to the June 27th, 2017 with dessert cafe users. Out of 200 responses collected, a total of 157 responses was included for the data analysis. The results from this study are as follows. First, it was found that, the menu features of selective attributes of dessert cafes only affected experience value. However, healthy menu, price, and atmosphere of selective attributes of dessert cafes didn't impact on experience value. Second, experience value of dessert cafes significantly influenced revisit intention. As a result, managers of dessert cafes need to develop an effective marketing strategy to improve the customer experience value so that customers can revisit their dessert cafe and will also develop the unique menu.

• Earthquakes and Structures
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• v.16 no.1
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• pp.29-39
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• 2019

A three-step screening process is presented in this article for selection of consistent earthquake records in which number of suitable ground motions is quickly screened and reduced to a handful number. Records that remain at the end of this screening process considerably reduce the dispersion of structural responses. Then, an effective method is presented for spectral matching and modification of the selected records. Dispersion of structural responses is explored using different statistical measures for each scaling procedure. It is shown that the Uniform Design Method, presented in this study for scaling of earthquake records, results in most cases in the least dispersion measure.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.282-287
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• 2006

This paper presents an original feature selection method for Emotion Recognition which includes many original elements. Feature selection has some merits regarding pattern recognition performance. Thus, we developed a method called thee 'Interactive Feature Selection' and the results (selected features) of the IFS were applied to an emotion recognition system (ERS), which was also implemented in this research. The innovative feature selection method was based on a Reinforcement Learning Algorithm and since it required responses from human users, it was denoted an 'Interactive Feature Selection'. By performing an IFS, we were able to obtain three top features and apply them to the ERS. Comparing those results from a random selection and Sequential Forward Selection (SFS) and Genetic Algorithm Feature Selection (GAFS), we verified that the top three features were better than the randomly selected feature set.

• Journal of Animal Science and Technology
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• v.55 no.6
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• pp.501-508
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• 2013

This study was conducted to determine genetic correlations among carcass traits measured by ultrasound and real carcass measurements and to estimate indirect selection responses for real carcass traits based on ultrasound measurements in Hanwoo cows. To accomplish this, 22,080 ultrasound measurement records from 17,926 cows collected from 2001 to 2012 and 11,907 carcass records obtained from fattened cattle from 2008 to 2012 were used. Genetic parameters were estimated based on eye muscle area (EMA), backfat thickness (BF) and marbling score (MS) measured by ultrasound-scanning of live cows and using the official technique on chilled bovine half-carcasses after slaughtering. Heritability and genetic correlation for carcass traits were estimated using a mixed model equation that consisted of environmental effects as fixed parameters and additive genetic effects and residual effects as random parameters, assuming that traits were different between ultrasound and carcass measurements. This statistical method was applied to the average information restricted maximum likelihood method. The heritability of EMA, BF and MS measured by ultrasound were 0.33, 0.61 and 0.46, respectively, while the heritability estimates of the corresponding traits based on carcass measurements were 0.29, 0.40 and 0.38, respectively and the genetic correlation between ultrasound and carcass traits for EMA, BF and MS were 0.41, 0.78 and 0.67, respectively. The genetic correlation between ultrasound and carcass traits was highly positive. Additionally, the selection response for marbling score was estimated to be 0.42 per generation if the cows were selected based on the ultrasound scan marbling score with an assumed selection intensity of 0.8. Overall, these results indicate that the ultrasound scan technique would be applicable to judging cow selection for genetically improved meat quality.

• Journal of the military operations research society of Korea
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• v.11 no.1
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• pp.47-54
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• 1985

In this paper, for the systematic software evaluation and selection objective, we first discussed the systems software which is distinctly different from applications oriented software in source, concept and use. We suggested the systematic procedures for the effective software evaluation and selection by analyzing categories of commercially available proprietary software, sources of information for software selection, request for information, request for proposal, user surveys as an aid to evaluation and evaluation of responses to the RFP.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.93-107
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• 2002

Random effects generalised linear models are useful for analysing clustered count data in which responses are usually correlated. We propose a Bayesian approach to parameter estimation and variable selection in random effects generalised linear models for count data. A simple Gibbs sampling algorithm for parameter estimation is presented and a simple and efficient variable selection is done by using the Gibbs outputs. An illustrative example is provided.