• Animal cells and systems
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• v.12 no.2
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• pp.77-83
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• 2008

The canine fearfulness is a behavioral trait known to have a genetic basis. This research analyzed genetic effects of the dopamine D4 receptor polymorphism on this behavior by postulating a mixed model of inheritance. Genotyping for the three different repeat polymorphism found in the third exon of the receptor gene was carried out for the population of the Korean native dogs. Four hundred fifty eight dogs with known pedigree were genotyped, and 264 individuals were tested for their fear responses to an experimenter, in which four different behavioral paradigms were adopted. Since the results assessed by principal factor analysis revealed a major factor explaining 69% of the total phenotypic variance, the subsequent analyses were conducted for this quantity. Analyses of the factor scores by estimating their posterior means indicated that there is a fixed effect exerted by the three different repeat polymorphism found in the D4 receptor as well as sex, in addition to unidentified polygenic effects. The phenotypic contribution of the D4 genotype was roughly estimated to be about 2%, which is a fraction of the total genetic effects responsible for more than 20% of the total phenotypic variance.

• Korean Journal of Cognitive Science
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• v.35 no.2
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• pp.97-112
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• 2024

This study investigated how syllable-level variables such as syllable frequency, syllable (i.e. vowel) type, presence of final consonants (i.e. batchim) and syllable position influence naming of both words and pseudo-words. The results of the linear mixed-effects model analysis showed that, for words, naming time decreased as the frequency of the first syllable increased, and when the first syllable had a final consonant. Additionally, words were named more accurately when they had vertical vowels compared to horizontal vowels. For pseudo-words, naming time decreased and accuracy rate increased as the frequency of the first or the second syllable increased. Furthermore, pseudo-words were named more accurately when they had vertical vowels compared to horizontal vowels. These results suggest that while the frequency of the second syllable had differential effects between words and pseudo-words, the frequency of the first syllable and the syllable type had consistent effects for both words and pseudo-words. The implications of this study were discussed concerning visual word recognition processing.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.8
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• pp.1088-1096
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• 2008

Data from milk performance testing were used to analyze genetic and environmental trends for purebred Tsigai, Improved Valachian and Lacaune sheep. 103,715 (Tsigai), 212,962 (Improved Valachian) and 2,196 (Lacaune) test-day records gathered by the State Breeding Institute of the Slovak Republic entered the analyses. The respective pedigree data comprised 23,724 (Tsigai), 51,401 (Improved Valachian) and 438 (Lacaune) records. The multiple-trait, mixed model methodology was used to predict the breeding values for daily milk yield, fat and protein content and to estimate the fixed and remaining random effects assumed to affect the above mentioned traits, separately for each breed. The breeding values for daily milk yield were adjusted for 150-day standardized lactation length by multiplying with the constant 150, as the breeding goal of the selection scheme in Slovakian sheep is to increase 150-day milk production and constant heritability throughout the whole lactation is assumed. The genetic trends were expressed as changes in averages of breeding values across birth years of animals. For Tsigai and Lacaune breeds, cumulative genetic changes over the analyzed period were 3.8 and 5.1 kg for 150-day milk, 0 and -0.16% for fat content and 0 and -0.12% for protein content. For Improved Valachian breed, either a low (1.6 kg for 150-day milk yield) or zero (fat and protein content) cumulative genetic change was found. The environmental trends were calculated as averages of solutions for flock-test day effect across years and months in which measurements were taken. A distinctive cyclical pattern which reflected short-time variation in milk production traits was found. Possible explanations for this phenomenon are given and discussed.

• Computers and Concrete
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• v.19 no.5
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• pp.579-588
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• 2017

Creep and shrinkage are the main types of volume change with time in concrete. These changes cause deflection, cracking and stresses that affect durability, serviceability, long-term reliability and structural integrity of civil engineering infrastructure. Although laboratory test may be undertaken to determine the deformation properties of concrete, these are time-consuming, often expensive and generally not a practical option. Therefore, relatively simple empirically design code models are relied to predict the creep strain. This paper reviews the accuracy of creep and shrinkage predictions of reinforced concrete (RC) shear walls structures strengthened with carbon fibre reinforced polymer (CFRP) plates, which is characterized by a widthwise varying fibre volume fraction. This review is yielded by three commonly used international "code type" models. The assessed are the: CEB-FIP MC 90 model, ACI 209 model and Bazant & Baweja (B3) model. The time-dependent behavior was investigated to analyze their seismic behavior. In the numerical formulation, the adherents and the adhesives are all modelled as shear wall elements, using the mixed finite element method. Several tests were used to demonstrate the accuracy and effectiveness of the proposed method. Numerical results from the present analysis are presented to illustrate the significance of the time-dependency of the lateral displacements and eigenfrequencies modes.

• The Journal of Information Systems
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• v.30 no.2
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• pp.29-56
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• 2021

Purpose Cyber deviance of adolescents has become a serious social problem. With a widespread use of smartphones, incidents of cyber deviance have increased in Korea and both quantitative and qualitative damages such as suicide and depression are increasing. Research has been conducted to understand diverse factors that explain adolescents' delinquency in cyber space. However, most previous studies have focused on a single theory or perspective. Therefore, this study aims to comprehensively analyze motivations of juvenile cyber deviance and to develop a predictive model for delinquent adolescents by integrating four different theories on cyber deviance. Design/methodology/approach By using data from Korean Children & Youth Panel Survey 2010, this study extracts 27 potential factors for cyber deivance based on four background theories including general strain, social learning, social bonding, and routine activity theories. Then this study employs econometric analysis to empirically assess the impact of potential factors and utilizes a machine learning approach to predict the likelihood of cyber deviance by adolescents. Findings This study found that general strain factors as well as social learning factors have positive effects on cyber deviance. Routine activity-related factors such as real-life delinquent behaviors and online activities also positively influence the likelihood of cyber diviance. On the other hand, social bonding factors such as community commitment and attachment to community lessen the likelihood of cyber deviance while social factors related to school activities are found to have positive impacts on cyber deviance. This study also found a predictive model using a deep learning algorithm indicates the highest prediction performance. This study contributes to the prevention of cyber deviance of teenagers in practice by understanding motivations for adolescents' delinquency and predicting potential cyber deviants.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.153-164
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• 2022

In this study, we estimate the quantile-regression framework of the shipping industry for the Capesize used ship, which is a typical raw material transportation from January 2000 to December 2021. This research aims two main contributions. First, we analyze the relationship between the Capesize used ship, which is a typical type in the raw material transportation market, and the freight market, for which mixed empirical analysis results are presented. Second, we present an empirical analysis model that considers the structural transformation proposed in the Hyunsok Kim and Myung-hee Chang(2020a) study in quantile-regression. In structural change investigations, the empirical results confirm that the quantile model is able to overcome the problems caused by non-stationarity in time series analysis. Then, the long-run relationship of the co-integration framework divided into long and short-run effects of exogenous variables, and this is extended to a prediction model subdivided by quantile. The results are the basis for extending the analysis based on the shipping theory to artificial intelligence and machine learning approaches.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1684-1688
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• 2017

Objective: From a review of published information on genetic association studies, a meta-analysis was conducted to determine the influence of the genes ${\kappa}-casein$ (CSN3) and ${\beta}-lactoglobulin$ (LGB) on milk yield traits in Holstein, Jersey, Brown Swiss, and Fleckvieh. Methods: The GLIMMIX procedure was used to analyze milk production and percentage of protein and fat in milk. Models included the main effects and all their possible two-way interactions; not estimable effects and non-significant (p>0.05) two-way interactions were dropped from the models. The three traits analyzed used Poisson distribution and a log link function and were determined with the Interactive Data Analysis of SAS software. Least square means and multiple mean comparisons were obtained and performed for significant main effects and their interactions (p<0.0255). Results: Interaction of breed by gene showed that Holstein and Fleckvieh were the breeds on which CSN3 ($6.01%{\pm}0.19%$ and $5.98%{\pm}0.22%$), and LGB ($6.02%{\pm}0.19%$ and $5.70%{\pm}0.22%$) have the greatest influence. Interaction of breed by genotype nested in the analyzed gene indicated that Holstein and Jersey showed greater influence of the CSN3 AA genotype, $6.04%{\pm}0.22%$ and $5.59%{\pm}0.31%$ than the other genotypes, while LGB AA genotype had the largest influence on the traits analyzed, $6.05%{\pm}0.20%$ and $5.60%{\pm}0.19%$, respectively. Furthermore, interaction of type of statistical model by genotype nested in the analyzed gene indicated that CSN3 and LGB genes had similar behavior, maintaining a difference of more than 7% across analyzed genotypes. These results could indicate that both Holstein and Jersey have had lower substitution allele effect in selection programs that include CSN3 and LGB genes than Brown Swiss and Fleckvieh. Conclusion: Breed determined which genotypes had the greatest association with analyzed traits. The mixed model based in Bayesian or Ridge Regression was the best alternative to analyze CSN3 and LGB gene effects on milk yield and protein and fat percentages.

• Journal of Distribution Science
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• v.12 no.6
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• pp.67-79
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• 2014

Purpose - This study aims to accomplish three major research goals. First, it strives to change consumers' focus from peripheral routes to a central route of public service advertising related to the good health policy, without problematic effects, by influencing consumers' knowledge or involvement. Second, this study examines the elaboration likelihood model (ELM) and construal level theory (CLT). Specifically, we consider that the central route of ELM might correspond with the focal goal of CLT. Third, this study analyzes ELM through CLT. That is, ELM predicted that low involvement would take the peripheral route, and high involvement would take the central route. Research design, data, and methodology - This study consisted of three experiments. The first experiment had a 2×2 between-subject design. The subjects were university students and the research period was approximately one year. The first independent variable was the involvement of the overweight issue; this variable was measured and split by the median. The second independent variable was the temporal distance (near vs. distant future); this variable was manipulated. The second experiment also had a 2×2 between-subject design. The first variable was the involvement of cervical adenocarcinoma prevention, and was considered already manipulated by sex. Specifically, males had a low involvement of the disease, but females had high involvement. The second independent variable was priming (power vs. submissive). Power priming would induce abstract thinking, but submissive priming would take concrete processing. The third experiment had a 2×2×2 between-subject design. The first variable was cognitive depletion, and was manipulated by memorizing 9-digit numbers. The second and third independent variables were involvement and abstract thinking induction, such as prior experiments. Data were collected through questionnaires, and were analyzed by an SPSS program. Major hypotheses were tested by examining the interaction effects through ANOVA. Results - Major findings are as follows. First, even for low-involved consumers in the overweight category, distant future manipulation induced them to focus not on the peripheral route but on the central route of the public service advertisement. This result does not correspond to the typical ELM prediction. Second, under power priming, low-involved males of the cervical adenocarcinoma category focused on the peripheral route because of the induction to abstract thinking. This result replicated the first experiment, and confirmed the theoretical robustness. Third, high-involved females focused not on the central but on the peripheral route under the mixed condition of cognitive depletion and near future manipulation. Depletion consumed cognitive resources, and the processing mode of consumers changed from systematic to heuristic. Conclusions - ELM needs to be complemented through CLT in context of public service good health advertising. Specifically, the involvement of ELM may impact consumers' thinking mode (abstract vs. concrete), and the interaction effects may influence consumers' focus on advertising (central vs. peripheral route). This study's limitations were bounded subjects, limited stimuli, and somewhat weak external validity.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.969-982
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• 2008

As hydrological models have been progressively developed, they are recognized as appropriate tools to manage water resources. Especially, the need to evaluate the effects of landuse and climate change on hydrological phenomena has been increased, which requires powerful validation methods for the hydrological models to be employed. As measured streamflow data at many locations may not be available, or include significant errors in application of hydrological models, streamflow data simulated by models only might be used to conduct hydrological analysis. In many cases, reducing errors in model simulations requires a powerful model validation method. In this research, we demonstrated a validation methodology of SWAT model using observed flow in two basins with different physical characteristics. First, we selected two basins, Gap-cheon basin and Yongdam basin located in the Guem River Basin, showing different hydrological characteristics. Next, the methodology developed to estimate parameter values for the Gap-cheon basin was applied for estimating those for the Yongdam basin without calibration a priori, and sought for validation of the SWAT. Application result with SWAT for Yongdam basin showed $R_{eff}$ ranging from 0.49 to 0.85, and $R^{2}$ from 0.49 to 0.84. As well, comparison of predicted flow and measured flow in each subbasin showed reasonable agreement. Furthermore, the model reproduced the whole trends of measured total flow and low flow, though peak flows were rather underestimated. The results of this study suggest that SWAT can be applied for predicting effects of future climate and landuse changes on flow variability in river basins. However, additional studies are recommended to further verify the validity of the mixed method in other river basins.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.336-350
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• 2013

This paper proposes a mathematical modeling-based approach for assessing disaster effects and selecting suitable mitigation alternatives to provide humanitarian relief (HR) supplies, shelter, rescue services, and long-term services after a disaster event. Mitigation steps, such as arrangement of shelter and providing HR items (food, water, medicine, etc.) are the immediate requirements after a disaster. Since governments and non-governmental organizations (NGOs) providing humanitarian aid need to know the requirements of relief supplies and resources for collecting relief supplies, organizing and initiating mitigation steps, a quick assessment of the requirements is the precondition for effective disaster management. Based on satellite images from weather forecasting channels, an area/dimension of the disaster-affected zones and the extent of the overall damage may often be obtained. The proposed approach then estimates the requirements for HR supplies, supporting resources, and rescue services using the census and other government data. It then determines reliable transportation routes, optimum collection and distribution centers, alternatives for resource support, rescue services, and long-term help needed for the disaster-affected zones. A numerical example illustrates the applicability of the model in disaster mitigation planning.