• Journal of the Korean Operations Research and Management Science Society
• /
• v.19 no.2
• /
• pp.1-19
• /
• 1994

A generalized network problem is a special class of linear programming problem whose coefficient matrix contains at most two nonzero elements per column. A generalized network problem with 0-1 flow restrictions is called an integer generalized network(IGN) problem. In this paper, we presented a branch and bound algorithm for the IGN that uses network relaxation. To improve the procedure, we develop various strategies, each of which employs different node selection criterion and/or branching variable selection criterion. We test these solution strategies and compare their efficiencies with LINDO on 70 randomly generated problems.

• Proceedings of the Korean Statistical Society Conference
• /
• 2003.05a
• /
• pp.151-156
• /
• 2003

Variable selection algorithm for principal component analysis using penalized likelihood method is proposed. We will adopt a probabilistic principal component idea to utilize likelihood function for the problem and use HARD penalty function to force coefficients of any irrelevant variables for each component to zero. Consistency and sparsity of coefficient estimates will be provided with results of small simulated and illustrative real examples.

• Communications for Statistical Applications and Methods
• /
• v.5 no.1
• /
• pp.25-33
• /
• 1998

We review a multivariate version of Kendall's tau based on direction vectors of observations. And with this statistic we propose an analog of the forward variable selection method which selects a set of independent variables for further studies to build the eventual predicting model. This method does not assume the distributions of observations and the linear model and it is strong to the outliers with high asymptotic efficiencies relative to the parametric Pearson's correlation coefficient.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.38 no.5
• /
• pp.636-643
• /
• 2009

This research was to find out what impacts do selection attributes of Jeju local folklore food by Jeju tourists provide on their behaviors. Multiple regression analysis was carried out using statistics package of SPSS+/WIN 12.0 to find out impacts of selection attribute factors of Jeju local folklore food on customers' satisfaction, re-visit, and intention by word of mouth. As the results, for factors with statistically meaningful impacts at the level of meaningfulness (p<0.05); level of satisfaction showed regression coefficient of 0.476 and t value of 5.198 in essential factors; auxiliary factors showed regression coefficient of 0.232 and t value of 2.808; and sensual (five senses) factors showed regression coefficient of 0.165 and t-value of 2.013. Also, for re-visit, essential factors showed impacts with regression coefficient of 0.413 and t-value of 3.540; factors of menu composition showed regression coefficient of 0.228 and t-value of 3.118; and auxiliary factors showed regression coefficient of 0.218 and t-value of 2.643. In positive word of mouth factors, auxiliary factors showed impacts with regression coefficient of 0.273 and t-value of 2.555; sensual (five senses) factors showed regression coefficient of 0.264 and t-value of 2.238; essential factor showed regression coefficient of 0.237 and t-value of 2.230 and factors of menu composition showed regression coefficient of 0.161 and t-value of 2.167. Therefore, in customer behaviors (customer satisfaction, re-visit, and positive word of mouth) regarding Jeju local folklore food by tourists who visited Jeju, local folklore and cultures did not impact on customer behaviors; also, it can suggested this thesis is meaningful as a study proving that the best marketing is focus on essential substances of food as indicated in existing researches.

• Asian-Australasian Journal of Animal Sciences
• /
• v.21 no.11
• /
• pp.1559-1571
• /
• 2008

A rule was developed to constrain the annual rate of inbreeding to a predefined value in a population with different lifetimes between sires and dams, and to maximize the selection response over generations. This rule considers that the animals in a population should be divided into sex-age classes based on the theory of gene flow, and restricts the increase of average inbreeding coefficient for new offspring by limiting the increase of the mean additive genetic relationship for parents selected. The optimization problem of this rule was formulated as a quadratic programming problem. Inputs for the rule were the BLUP estimated breeding values, the additive genetic relationship matrix of all animals, and the long-term contributions of sex-age classes. Outputs were optimal number and contributions of selected animals. In addition, this rule was combined with the optimization of emphasis given to QTL, and further increased the genetic gain over the planning horizon. Stochastic simulations of closed nucleus schemes for pigs were used to investigate the potential advantages obtained from this rule by combining the standard QTL selection, optimal QTL selection and conventional BLUP selection. Results showed that the predefined rates of inbreeding were actually achieved by this rule in three selection strategies. The rule obtained up to 9.23% extra genetic gain over truncation selection at the same rates of inbreeding. The combination of the extended rule and the optimization of emphasis given to QTL allowed substantial increases in selection response at a fixed annual rate of inbreeding, and solved substantially the conflict between short-term and long-term selection response in QTL-assisted selection schemes.

• Management & Information Systems Review
• /
• v.34 no.1
• /
• pp.65-80
• /
• 2015

In previous studies concerning turnover, they argue individual stock's turnover must be identical to market portfolio's turnover under one condition where 2 funds separation theorem holds. In this kind of world, all market participants hold and trade the same portfolio and this should be only market portfolio. If one's trading portfolio's shape is different from market portfolio's, this would mean he or she has an advantage over others in information and this kind of information would be private. In accordance with this theory, we develop a metric which measures how far one's trading portfolio from market's and name it as Stock Selection by Investor(SSI). We apply this measurement to the various types of investor groups classified as individual, institutional and foreign who participate in Korea stock market. To test the validity of measure, we regress price ratio on this measurement using SUR method. As a result, individual investor group shows large number in SSI, but the coefficient in regression is not significant and economically meaningless. In case of institutional investor group, the coefficient proves to be significantly negative. We can infer from this fact that their trading is somehow far from informed trading. Stock selection activity by foreign investor groups proves to be informed trading by showing significantly positive coefficient and the magnitude of coefficient is economically meaningful, especially in sell activity.

• ETRI Journal
• /
• v.30 no.1
• /
• pp.89-100
• /
• 2008

We consider the feature recombination technique in a multiband approach to speaker identification and verification. To overcome the ineffectiveness of conventional feature recombination in broadband noisy environments, we propose a new subband feature recombination which uses subband likelihoods and a subband reliable-feature selection technique with an adaptive noise model. In the decision step of speaker recognition, a few very low unreliable feature likelihood scores can cause a speaker recognition system to make an incorrect decision. To overcome this problem, reliable-feature selection adjusts the likelihood scores of an unreliable feature by comparison with those of an adaptive noise model, which is estimated by the maximum a posteriori adaptation technique using noise features directly obtained from noisy test speech. To evaluate the effectiveness of the proposed methods in noisy environments, we use the TIMIT database and the NTIMIT database, which is the corresponding telephone version of TIMIT database. The proposed subband feature recombination with subband reliable-feature selection achieves better performance than the conventional feature recombination system with reliable-feature selection.

• The Korean Journal of Applied Statistics
• /
• v.17 no.3
• /
• pp.459-473
• /
• 2004

It has well known that an exhaustive search algorithm suggested by Breiman et. a1.(1984) has a trend to select the variable having relatively many possible splits as an splitting rule. We propose an algorithm to overcome this variable selection bias problem and then construct unbiased regression trees based on the algorithm. The proposed algorithm runs two steps of selecting a split variable and determining a split rule for binary split based on the split variable. Simulation studies were performed to compare the proposed algorithm with Breiman et a1.(1984)'s CART(Classification and Regression Tree) in terms of degree of variable selection bias, variable selection power, and MSE(Mean Squared Error). Also, we illustrate the proposed algorithm with real data sets.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.10 no.3
• /
• pp.413-420
• /
• 2018

This paper documents the result of a preliminary analysis on the influence of hull-ice friction coefficient on model resistance and power predictions and their correlation to full-scale measurements. The study is based on previous model-scale/full-scale correlations performed on the National Research Council - Ocean, Coastal, and River Engineering Research Center's (NRC/OCRE-RC) model test data. There are two objectives for the current study: (1) to validate NRC/OCRE-RC's modeling standards in regarding to its practice of specifying a CFC (Correlation Friction Coefficient) of 0.05 for all its ship models; and (2) to develop a correction methodology for its resistance and propulsion predictions when the model is prepared with an ice friction coefficient slightly deviated from the CFC of 0.05. The mean CFC of 0.056 and 0.050 for perfect correlation as computed from the resistance and power analysis, respectively, have justified NRC/OCRE-RC's selection of 0.05 for the CFC of all its models. Furthermore, a procedure for minor friction corrections is developed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.492-497
• /
• 2009

Computer-Generated Hologram (CGH) is made for three dimensional image of a virtual object. Error diffusion method is used for the phase quantization of CGH, and it is known to be effective to the image quality improvement of the reconstructed image. However, the image quality of the reconstructed image from the CGH using error diffusion method depends on the selection of error diffusion coefficient. In this paper, we derived the relational expression to obtain the error diffusion coefficient from the position of the input object and size of the input object for CGH. As a result, the method of this thesis was able to obtain an excellent reconstructed image compared with the case to derive the error diffusion coefficient from only the position of the input image.