• Journal of the Korean Data and Information Science Society
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• 제24권6호
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• pp.1543-1550
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• 2013

In this paper, we study Bayesian estimation for the finite population proportion in binary data under selection bias. We use a Bayesian nonignorable selection model to accommodate the selection mechanism. We compare four possible estimators of the finite population proportions based on data analysis as well as Monte Carlo simulation. It turns out that nonignorable selection model might be useful for weekly biased samples.

• 대한치과기공학회지
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• 제29권1호
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• pp.35-48
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• 2007

The purpose of this study was to evaluate shade selection using conventional visual assessment in vivo natural teeth and porcelain-fused-to-metal (PFM) crown. Maxillary central incisors, lateral incisors and canines of one hundred twenty four college women were used as vivo natural teeth. Fifty one PFM crown for maxillary central incisor fabricated by dental laboratory were used as experimental materials. Using Vitapan Classical Shade Guides, shade selection of natural teeth was measured by each college woman and shade selection of PFM crown was measured by three ceramists with more than ten years career. Both natural teeth and PFM crown shade selection were measured through Shade Eye-Ex. From the shade selection comparing, following results were obtained. The results were as follows: 1. The shade matching identification of natural teeth between the shade selection using Vitapan Classical Shade Guides and the shade selection using Shade Eye-Ex was 27.4% in maxillary central incisor, 13.7% in lateral incisor and 18.5% in canine. 2. Among the shade selection of PFM crown by three ceramists, the shade evaluation of three ceramists were same only in ten cases. In twenty case, those of two ceramists were same. 3. The shade matching identification of PFM crown between the shade selection using Vitapan Classical Shade Guides and the shade selection using Shade Eye-Ex was 38.6% in average. These results suggest that the shade selection using conventional visual assessment should be dealt with care in clinic and need a credible method for shade matching color.

• 반도체디스플레이기술학회지
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• 제14권2호
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• pp.9-16
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• 2015

In this paper, selection criterions on selection diversity are researched. The diversity is applied to the multiple antenna system based on wireless access in vehicular environment (WAVE) standard for rapid varying channel. Least squares (LS) based decision feedback equalizer (DFE) are used for channel equalization. Received signal is regenerated by means of the decision feedback path. In the selection diversity, the regenerated signal as well as the received signal is selected according to selection criterion. The decision feedback algorithm can follow the fast speed of WAVE fading channel. To control the tracking speed of the time-varying channel, simple low pass filter is used. Finally, the estimated channel value recovers the distorted payloads. Signal power before automatic gain control (AGC) in analog stage can be used as a selection criterion. In the digital stage, signal power after AGC, noise power after AGC, signal to noise ratio after AGC and cross-correlation method can be used as selection criterions. According to the simulation results, the performance of the selection diversity is improved in comparison with that of the combining diversity for the WAVE fading channel.

• Communications for Statistical Applications and Methods
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• 제29권6호
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• pp.629-640
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• 2022

Variable selection is one of the most crucial tasks in supervised learning, such as regression and classification. The best subset selection is straightforward and optimal but not practically applicable unless the number of predictors is small. In this article, we propose directly solving the best subset selection via the genetic algorithm (GA), a popular stochastic optimization algorithm based on the principle of Darwinian evolution. To further improve the variable selection performance, we propose to run multiple GA to solve the best subset selection and then synthesize the results, which we call ensemble GA (EGA). The EGA significantly improves variable selection performance. In addition, the proposed method is essentially the best subset selection and hence applicable to a variety of models with different selection criteria. We compare the proposed EGA to existing variable selection methods under various models, including linear regression, Poisson regression, and Cox regression for survival data. Both simulation and real data analysis demonstrate the promising performance of the proposed method.

• 한국통신학회논문지
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• 제35권7B호
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• pp.1009-1017
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• 2010

Offering of different attractive opportunities by different wireless technologies trends the convergence of heterogeneous networks for the future wireless communication system. To make a seamless handover among the heterogeneous networks, the optimization of the power consumption, and optimal selection of interface are the challenging issues. The access of multi interfaces simultaneously reduces the handover latency and data loss in heterogeneous handover. The mobile node (MN) maintains one interface connection while other interface is used for handover process. However, it causes much battery power consumption. In this paper we propose an efficient interface selection scheme including interface selection algorithms, interface selection procedures considering battery power consumption and user mobility with other existing parameters for overlaying networks. We also propose a priority based network selection scheme according to the service types. MN‘s battery power level, provision of QoS/QoE and our proposed priority parameters are considered as more important parameters for our interface selection algorithm. The performances of the proposed scheme are verified using numerical analysis.

• 복식문화연구
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• 제15권5호
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• pp.888-901
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• 2007

The purpose of this study was to examine the differences in clothing selection criteria and store selection criteria between each consumer groups by the preference for fast fashion. The data was collected from a questionnaire conducted on 317 female adults. The results were as follows. First, the factor analysis used to identify clothing selection criteria involved the following four factors: fashion, quality/practicality, status symbol, and economics. The consumer group preferring fast-fashion regarded fashion and economics as important factors and the non-preferring group regarded status symbol factor more. Second, five factors(atmosphere, product service/salesperson, shopping convenience, promotion/facilities) of store selection criteria were constructed by factor analysis, The consumer group preferring fast-fashion regarded atmosphere and product as important factors and the non-preferring group considered service/salesperson and promotion/facilities factors more. Third, the consumers who were of low age, low education, low income and unmarried preferred fast fashion brand.

• 복식
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• 제50권5호
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• pp.77-90
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• 2000

The purpose of this study is to disclose the dimension of job characteristic, working place situation. and clothes selection, which are variable on clothes selection, to research the relation of job characteristic, working place situation, and clothes selection and to disclose the feature of consumers by each group in accordance with job characteristic. The follows are summary of this study result : The concept structure of job characteristic is composed by four types. Working place situation related with clothes selection are consisted of five types. Professional women selected clothes in accordance with nine feature. Job characteristic is related with working palace situation and influences on clothes selection. The persons influenced by activity state regarded personality as important when select clothes. The persons influenced by duty state regarded harmony and control as important, instead of, they ignored conformity. People select occupation according to individual feature, so the feature of consumers, working place environment, working place situation are different in accordance with job characteristic, as a result we can find differences in clothes selection suitable for working palace and purchasing.

• 한국멀티미디어학회논문지
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• 제14권12호
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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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• 제13권7호
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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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• 제20권3호
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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.