• Asia pacific journal of information systems
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• 제29권2호
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• pp.248-267
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• 2019

As merging online and offline channels into one single platform, individuals could easily and frequently switch between online and offline channels. In order for understanding such unique behaviors, this study attempts to explore why and how consumers choose their channels to search and purchase a product. We have drawn on multiple theories that have been used to explain individuals' judgment and decision making (i.e., construal level theory and regula-tory focus theory) in order to develop and tested two-way ANOVA based models of how both regulatory focus (e.g., promotion vs. prevention) and product types (e.g., experience goods vs. searching goods) including the psychological distance cue separately and jointly affect individuals' channel selection behavior (e.g., intention to use single channel vs. intention to use cross-channels). Our results have indicated that consumers with promotion-focus are more likely to use a single channel in experience goods rather than in searching goods when there exists the psychological cue. Based on our findings, the implication for both research and practice are discussed.

• Asian-Australasian Journal of Animal Sciences
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• 제27권12호
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• pp.1678-1683
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• 2014

This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.

• 산경연구논집
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• 제11권10호
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• pp.17-25
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• 2020

Purpose: The purpose of this study is to narrow the target down to college students representing single-person households to identify the main attributes of their choice of Home Meal Replacement(HMR) and to look at the impact on satisfaction and repurchase intentions. Research design, data and methodology: An online survey was conducted for consumers who purchased HMR products at least once and a total of 264 questionnaires were used for demonstration analysis. The collected data have verified for validity and reliability between measurement variables through exploratory factor analysis and reliability analysis. Results: As a result, curiosity, economy, safety, and brand, which are HMR selection attributes that university students' value, have a significant impact on satisfaction, and satisfaction has a significant impact on the intention of repurchase, a variable of behavior. In addition, the adjustment effect of health value pursuit was significant only in safety attributes. Conclusions: This study divided the target group to examine what the HMR selection attributes of single-person college students are, the main consumer of HMR, and how selective attributes affect satisfaction and willingness to repurchase. In the process, we wanted to find out if there was a moderating effect on the health-oriented values in the dietary lifestyle.

• 한국멀티미디어학회논문지
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• 제18권4호
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• pp.533-540
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• 2015

We study relay selection in decode-and-forward (DF)-based relay networks consisting of a source, a destination, an eavesdropper, and multiple relays, where each terminal has a single antenna and operates in a half-duplex mode. In these networks, it is desirable to protect the confidential message from the source to the destination against the eavesdropper with the help of a single selected relay. Specifically, we begin by investigating DF-based networks for the scenario instantaneous signal-to-noise ratios (SNRs) related to the eavesdropper are available. For the scenario, we propose relay selection to maximize the secrecy rate of DF-based networks with and without direct-paths, and we derive the exact secrecy outage probabilities in closed-form.

• 한국가금학회지
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• 제21권2호
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• pp.101-111
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• 1994

From the observations of dietary self-selection by growing pullets, step-up protein or reverse protein and single-stage low protein pullet feeding systems were developed. They offered another pullet feeding concept that appears to control the body weight effectively and to reduce the consumption of feed and nutrients without impairment of subsequent laying performance. It is obvious from the feed and nutrient consumption pattern of layers fed diets for self-selection of energy, protein and calcium that they have a daily cyclic requirement rather than a constant requirement for nutrients. It seems that a practical self-selective feeding system is needed to meet the daily cyclic requirement for nutrients without consuming an excess of energy and protein at certain times of the day as compared to the complete or single diet where layers have to consume extra energy and protein in the afternoon when they have a specific appetite mainly for calcium.

• Asian-Australasian Journal of Animal Sciences
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• 제29권1호
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• pp.36-42
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• 2016

Milk-related traits (milk yield, fat and protein) have been crucial to selection of Holstein. It is essential to find the current selection trends of Holstein. Despite this, uncovering the current trends of selection have been ignored in previous studies. We suggest a new formula to detect the current selection trends based on single nucleotide polymorphisms (SNP). This suggestion is based on the best linear unbiased prediction (BLUP) and the Fisher's fundamental theorem of natural selection both of which are trait-dependent. Fisher's theorem links the additive genetic variance to the selection coefficient. For Holstein milk production traits, we estimated the additive genetic variance using SNP effect from BLUP and selection coefficients based on genetic variance to search highly selective SNPs. Through these processes, we identified significantly selective SNPs. The number of genes containing highly selective SNPs with p-value <0.01 (nearly top 1% SNPs) in all traits and p-value <0.001 (nearly top 0.1%) in any traits was 14. They are phosphodiesterase 4B (PDE4B), serine/threonine kinase 40 (STK40), collagen, type XI, alpha 1 (COL11A1), ephrin-A1 (EFNA1), netrin 4 (NTN4), neuron specific gene family member 1 (NSG1), estrogen receptor 1 (ESR1), neurexin 3 (NRXN3), spectrin, beta, non-erythrocytic 1 (SPTBN1), ADP-ribosylation factor interacting protein 1 (ARFIP1), mutL homolog 1 (MLH1), transmembrane channel-like 7 (TMC7), carboxypeptidase X, member 2 (CPXM2) and ADAM metallopeptidase domain 12 (ADAM12). These genes may be important for future artificial selection trends. Also, we found that the SNP effect predicted from BLUP was the key factor to determine the expected current selection coefficient of SNP. Under Hardy-Weinberg equilibrium of SNP markers in current generation, the selection coefficient is equivalent to $2^*SNP$ effect.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1989년도 춘계학술대회
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• pp.51-54
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• 1989

지난 몇년동안 생체에서의 MR 스펙트로 스코피(Mangetic Resonance Spectroscopy)를 위하여 ISIS, VSE, SPARS, STEAM 등과 같은 여러 체적 선택의 방법이 연구되어 왔다. 그러나 이들 3차윈 체적 선택의 방법은 여러 RF 펄스를 사용하여야 되었으며 상대적으로 오랜시간 동안의 RF여기시간(Radio frequency excitation time) 때문에 T1과 T2 감소효과의 영향을 크게 받았다. 본 논문에서는 3차원의 체적을 선택하기 위하여 단일 RF펄스의 사용을 제안하고 있는데, 이 방법은 원통형 체적을 선택하기 위한 방사형 경사 코일 (a radial gradient coil) 방법과 진동자계 (oscillating selection gradient) 방법을 결합하고 있다. 이렇게 하므로 단일 RF 펄스만을 사용하여 체적 선택 시간을 최소화하여 여러 RF 펄스를 사용할 경우 발생하는 파생적인 에코 신호(echo signal)를 피할 수 있었다. 제안된 방법에 의한 실험적 연구결과로서 펜톰(phantom)에 대하여 선택된 체적에 대한 영상과 스펙트럼 (spectrum)을 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.24-26
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• 2002

The recent emphasis on energy conservation demands an improvement of the efficiency of single-phase induction motors. To take the efficiency operation of the capacitor run single-phase induction motor with auxiliary and main winding, it is very important to select the capacitance value. This paper describes the theoretical analysis method of a single-phase induction motor which is based on the rotating field theory, using the method of symmetrical components. The optimal selection method of capacitance is proposed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.399-402
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• 2000

The reduction of chip area and delay is important purpose of Scheduling in High-Level Synthesis. This paper presents a scheduling approach with component selection. After obtaining a initial schedule taking only single-functional u-nits, the component selection of our approach attempts the reduction of chip area and/or delay by the selection more suitable components in a component library using Simulated Annealing.