• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.153-163
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• 2009

Unlike the mean-variance approach, the stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum expected return by managing the constraint set and the objective function separately. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.357-366
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• 1999

Let us assume that two different log-linear models are selected by various model selection methods. When these are non-hierarchical it is not easy to choose one of these models. In this paper the well-known Cox's statistic is applied to compare these non-hierarchical log-linear models. Since it is impossible to obtain the analytic solution about the problem we proposed a alternative method by extending Pesaran and pesaran's (1993) simulation approach. We find that the values of proposed test statistic and the estimates are very much stable with some empirical results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.76-80
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• 2003

The procedure of finding operating conditions minimizing qualify loss is proposed with a real industry example. The procedure consists or major two parts - the selection or process variables critical to the response and He determination or operating conditions. The coefficients or ridge regression and the and stores or partial least squares are applied to select important process variables. Functional approach and Non-functional approach are used to find proper operating conditions of important process variables.

• Proceedings of the Korean DIstribution Association Conference
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• 2000.10a
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• pp.183-185
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• 2000

A proactive approach on environmental issues may be one of critical competitive factors for global business in near future. Especially, distribution systems are very related to the various environmental issues, including development of green products and packaging, selection of the transportation vehicles and pallets, design of retail stores and distribution facilities, participation for solving the local environmental problems, and so on. In order to approach the environmental issues on distribution systems, for the first time managers need to understand the strategic framework for green management and then, to find the key success factors of leading companies in this field. Finally, future directions of strategic green management on distribution systems are discussed and shared.

• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.193-197
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• 2004

In this paper, a combination problem of controllers which are the same type of $H_{\infty}$ controllers designed with different weighting functions. This approach can remove the difficulty in the selection of the weighting functions. As a sub-controller, the Youla type of $H_{\infty}$ controller is used. In the $H_{\infty}$ controller, Youla parameterization is used to minimize $H_{\infty}$ norm of mixed sensitivity function by using polynomial approach. Computer simulation results show the robustness improvement and the performance improvement.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1087-1099
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• 2021

MRI has become important for the detection of prostate cancer. MRI-guided biopsy is superior to conventional systematic biopsy in patients suspected with prostate cancer. MRI is also increasingly used for monitoring patients with low-risk prostate cancer during active surveillance. It improves patient selection for active surveillance at diagnosis, although its role during follow-up is unclear. We aim to review existing evidence and propose a practical approach for incorporating MRI into active surveillance protocols.

• Journal of Korean Neurosurgical Society
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• v.59 no.6
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• pp.564-569
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• 2016

Objective : This study used the intradural procedural time to assess the overall technical difficulty involved in surgically clipping an unruptured middle cerebral artery (MCA) aneurysm via a pterional or superciliary approach. The clinical and radiological variables affecting the intradural procedural time were investigated, and the intradural procedural time compared between a superciliary keyhole approach and a pterional approach. Methods : During a 5.5-year period, patients with a single MCA aneurysm were enrolled in this retrospective study. The selection criteria for a superciliary keyhole approach included : 1) maximum diameter of the unruptured MCA aneurysm <15 mm, 2) neck diameter of the MCA aneurysm <10 mm, and 3) aneurysm location involving the sphenoidal or horizontal segment of MCA (M1) segment and MCA bifurcation, excluding aneurysms distal to the MCA genu. Meanwhile, the control comparison group included patients with the same selection criteria as for a superciliary approach, yet who preferred a pterional approach to avoid a postoperative facial wound or due to preoperative skin trouble in the supraorbital area. To determine the variables affecting the intradural procedural time, a multiple regression analysis was performed using such data as the patient age and gender, maximum aneurysm diameter, aneurysm neck diameter, and length of the pre-aneurysm M1 segment. In addition, the intradural procedural times were compared between the superciliary and pterional patient groups, along with the other variables. Results : A total of 160 patients underwent a superciliary (n=124) or pterional (n=36) approach for an unruptured MCA aneurysm. In the multiple regression analysis, an increase in the diameter of the aneurysm neck (p<0.001) was identified as a statistically significant factor increasing the intradural procedural time. A Pearson correlation analysis also showed a positive correlation (r=0.340) between the neck diameter and the intradural procedural time. When comparing the superciliary and pterional groups, no statistically significant between-group difference was found in terms of the intradural procedural time reflecting the technical difficulty (mean${\pm}$standard deviation : $29.8{\pm}13.0min$ versus $27.7{\pm}9.6min$). Conclusion : A superciliary keyhole approach can be a useful alternative to a pterional approach for an unruptured MCA aneurysm with a maximum diameter <15 mm and neck diameter <10 mm, representing no more of a technical challenge. For both surgical approaches, the technical difficulty increases along with the neck diameter of the MCA aneurysm.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.109-123
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• 2004

Corporate financial distress and bankruptcy prediction is one of the major application areas of artificial neural networks (ANNs) in finance and management. ANNs have showed high prediction performance in this area, but sometimes are confronted with inconsistent and unpredictable performance for noisy data. In addition, it may not be possible to train ANN or the training task cannot be effectively carried out without data reduction when the amount of data is so large because training the large data set needs much processing time and additional costs of collecting data. Instance selection is one of popular methods for dimensionality reduction and is directly related to data reduction. Although some researchers have addressed the need for instance selection in instance-based learning algorithms, there is little research on instance selection for ANN. This study proposes a genetic algorithm (GA) approach to instance selection in ANN for bankruptcy prediction. In this study, we use ANN supported by the GA to optimize the connection weights between layers and select relevant instances. It is expected that the globally evolved weights mitigate the well-known limitations of gradient descent algorithm of backpropagation algorithm. In addition, genetically selected instances will shorten the learning time and enhance prediction performance. This study will compare the proposed model with other major data mining techniques. Experimental results show that the GA approach is a promising method for instance selection in ANN.

• The Journal of Korean Academy of Prosthodontics
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• v.42 no.5
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• pp.544-555
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• 2004

Statement of problem: Shade selection has traditionally been accomplished by visual examination, which is particularly relevant to the shade selection of anterior teeth, but the subjective nature of visual analysis can lead to errors in shade matching. Recently shade selection systems have been developed to provide a more objective and scientific approach to understanding and clarifying shade selection. Purpose : The purpose of this study was analysis of various shade analyzing equipment with the goal of providing a more objective shade selection. Materials and method: Visual shade matching system selection(Vita Lumin Vacuum shade guide, Vitapan 3D Master shade guide) and mechanical shade matching method($ShadeEye^{(R)}$-EX Chroma Meter, $Shadescan^{TM}$ System) used for this study. The shade guide tap specimens for 10 extracted maxillary anterior teeth were produced by selecting shades using each shade matching system. The accuracy of the selection of shades for the teeth and fabricated specimens were evaluated by analyzing the calculated shade difference(${\Delta}E^*$), using a spectrophotometer and calculating the output of value $L^*,\;a^*,\;b^*$. Results and conclusion: The results show that the average ${\{Delta}E^*$ value (difference of shade) of the shade tap specimens to the actual specimen decreased in the following order: Vita Lumin Vacuum Shade Guide(VL), $ShadeEye^{(R)}$-EX Chroma Meter(SE) Vitapan 3D Master Shade guide(V3), and $Shadescan^{TM}$ System(55) : and that there are significant statistical differences between the VL and SS (p<0.05). In the analysis of the ${\Delta}E^*$ (difference of shade) value,40% of the VL group was found to be less than 3.3 (limit value of shade tap specimens clinically acceptable), 60% in the V3 group, 50% in the SE group, and 80% in the SS group.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.235-235
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• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.