• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.175-178
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• 2002

A number of controlled selection methods, which have some advantages for practical surveys in considering controls beyond stratification, have developed throughout the last half-century. With respect to the optimization of sampling plan, it is obvious that we may use optimal controlled selection in preference to satisfactory controlled selection. However, there are currently certain restrictions on the employment of optimal controlled selection. We present further research to improve an algorithm for optimal controlled selection and to develop standard software.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1544-1548
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• 2011

A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.7
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• pp.883-887
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• 2000

One way of evaluating the effectiveness of a dairy breeding program is to measure response to selection. This may be direct or indirect. The objectives of this study were to estimate expected progress for direct selection on milk, fat and protein yields; to estimate the expected correlated responses on indirect selection for milk, fat and protein yields in Zimbabwean Holstein cattle and to establish the effect of selection intensity on responses. The Animal Model contained fixed effects of herd, year of calving, calving month, dry period, milking frequency and additive effects pertaining to cows, sires and dams. AIREML software package was used to analyse the data. The genetic and phenotypic parameters obtained in this study were used to compute direct and correlated responses to selection. Because of the higher heritabilities in first parity, genetic progress was found to be greater when selection was practised on first parity cows as compared to later lactations. It is therefore recommended that older cows in the herd be replaced with improved heifers so as to enhance genetic progress.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.3
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• pp.453-460
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• 2007

An overview of developments important in the future of animal breeding is discussed. Examples from the application of quantitative genetic principles to selection in chickens and mice are given. Lessons to be learned from these species are that selection for production traits in livestock must also consider selection for reproduction and other fitness-related traits and inbreeding should be minimized. Short-term selection benefits of best linear unbiased predictor methodology must be weighed against long-term risks of increased rate of inbreeding. Different options have been developed to minimize inbreeding rates while maximizing selection response. Development of molecular genetic methods to search for quantitative trait loci provides the opportunity for incorporating marker-assisted selection and introgression as new tools for increasing efficiency of genetic improvement. Theoretical and computer simulation studies indicate that these methods hold great promise once genotyping costs are reduced to make the technology economically feasible. Cloning and transgenesis are not likely to contribute significantly to genetic improvement of livestock production in the near future.

• The International Journal of Costume Culture
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• v.5 no.1
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• pp.26-33
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• 2002

Re purposes of this study were to determine consumers' selection criteria of fashion shopping area and to examine the effects of clothing consumption value and fashion leadership on the selection criteria of fashion shopping area. In addition, the third purpose was to clarify the relation beかeon the above variables and shopping intent. The data were collected from 198 females in their twenties using questionnaire. The results could be summarized as follows. First, the selection criteria of fashion shopping area were composed of 5 factors: scale & variety of shopping area, convenience of location, entertainment, physical service, and atmosphere. Second, the fashion leadership and clothing consumption value except functional and social values had an effect on the selection criteria fashion shopping area. Particularly, the attractiveness-sought value best explained the selection criteria. Third, the fashion leadership and selection criteria fashion shopping area had an effect on the shopping intent. The effect clothing consumption value was not significant.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.1-14
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• 2020

Antenna selection is a method to enhance the performance of spatial multiplexing multiple-input multiple-output (MIMO) systems, which can achieve the diversity order of the full MIMO systems. Although various selection criteria have been studied in the literature, they should be adjusted to the detection operation implemented at the receiver. In this paper, antenna selection methods that optimize the post-processing signal-to-noise ratio (SNR) and eigenvalue are considered for the lattice reduction (LR)-based receiver. To develop a complexity-efficient antenna selection algorithm, the incremental selection strategy is adopted. Moreover, for improvement of performance, an additional iterative selection method is presented in combination with an incremental strategy.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.652-662
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• 2023

Identifying highly discriminating genes is a critical step in tumor recognition tasks based on microarray gene expression profile data and machine learning. Gene selection based on tree models has been the subject of several studies. However, these methods are based on a single-tree model, often not robust to ultra-highdimensional microarray datasets, resulting in the loss of useful information and unsatisfactory classification accuracy. Motivated by the limitations of single-tree-based gene selection, in this study, ensemble gene selection methods based on multiple-tree models were studied to improve the classification performance of tumor identification. Specifically, we selected the three most representative tree models: ID3, random forest, and gradient boosting decision tree. Each tree model selects top-n genes from the microarray dataset based on its intrinsic mechanism. Subsequently, three ensemble gene selection methods were investigated, namely multipletree model intersection, multiple-tree module union, and multiple-tree module cross-union, were investigated. Experimental results on five benchmark public microarray gene expression datasets proved that the multiple tree module union is significantly superior to gene selection based on a single tree model and other competitive gene selection methods in classification accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6B
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• pp.358-366
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• 2007

Recently, FCC(Federal Communications Commission) has considered for that unlicensed device leases licensed devices' channel to overcome shortage of communication channels. Therefore, IEEE 802.22 WRAN(Wireless Regional Area Networks) working group progresses CR (Cognitive Radio) technique that is able to sense and adopt void channels that are not being occupied by the licensed devices. Channel selection is of the utmost importance because it can affect the whole system performance in CR network. Thus, we propose a policy-based dynamic channel selection architecture for cognitive radio network to achieve an efficient communication. We propose three kinds of method for channel selection; the first one is weighted channel selection, the second one is sequential channel selection, and the last one is combined channel selection. We can obtain the optimum channel list and allocates channels dynamically using the proposed protocol.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.56
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• pp.3-27
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• 2012

The purpose of this thesis is to develop a relational model which can explain consumer selection for exporting goods and analyze the effect of corporate image on the relations between country image and consumer selection under global trade environment. The specific objectives are as follows: 1) to suggest a concept of consumer selection and measurement criteria, 2) to analyze correlations among country image, corporate image and consumer selection and 3) to find out the effect of corporate image on the relations between country image and consumer selection. The SPSS program for window and LISREL program were used to analyze the data for this study. The statistical method used in this study was the covariance structure analysis estimating parameters by maximum likelihood method. Path coefficients were tested for t-tests with a statistical significance level of .05. The conclusions of this study are as follows. First, significant correlations were observed among all sub-variables proposed in this study. In addition, significant correlations were detected among country image, consumer selection and corporate image. Second, a hypothetical model proposed in this study was mostly appropriate. Country image had a positive direct effect on consumer selection and corporate image with statistical significance. In addition, it has an indirect impact on consumer selection with statistical significance with corporate image as an intervening variable. Third, corporate image had a significant moderation effect in country image-consumer selection relations. As corporate image levels increased, the effect of country image on consumer selection increased as well. In other words, it has been confirmed that if corporate image levels are high, country image could end up with consumer selection.

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