• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.43-69
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• 2005

This study provides empirical evidence that the stochastic beta model based on Bayesian analysis outperforms the existing conditional beta model and GARCH model in terms of the estimation accuracy and the explanatory power in the cross-section of stock returns in Korea. Betas estimated by the stochastic beta model explain $30{\sim}50%$ of the cross-sectional variation in stock-returns, whereas other time-varying beta models account for less than 3%. Such a difference in explanatory power across models turns out to come from the fact that the stochastic beta model absorbs the variation due to the market anomalies such as size, BE/ME, and idiosyncratic volatility. These results support the rational asset pricing model in that market anomalies are closely related to the variation of expected returns generated by time-varying betas.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8
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• pp.1077-1083
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• 2019

Objective: Sow longevity is important for efficient and profitable pig farming. Recently, there has been an increasing interest in social genetic effect (SGE) of pigs on stress-tolerance and behavior. The present study aimed to estimate genetic correlations among average daily gain (ADG), stayability (STAY), and number of piglets born alive at the first parity (NBA1) in Korean Yorkshire pigs, using a model including SGE. Methods: The phenotypic records of ADG and reproductive traits of 33,120 and 11,654 pigs, respectively, were evaluated. The variances and (co) variances of the studied traits were estimated by a multi-trait animal model applying the Bayesian with linear-threshold models using Gibbs sampling. Results: The direct and SGEs on ADG had a significantly negative (-0.30) and neutral (0.04) genetic relationship with STAY, respectively. In addition, the genetic correlation between the social effects on ADG and NBA1 tended to be positive (0.27), unlike the direct effects (-0.04). The genetic correlation of the total effect on ADG with that of STAY was negative (-0.23) but non-significant, owing to the social effect. Conclusion: These results suggested that total genetic effect on growth in the SGE model might reduce the negative effect on sow longevity because of the growth potential of pigs. We recommend including social effects as selection criteria in breeding programs to obtain satisfactory genetic changes in both growth and longevity.

• Journal of Animal Science and Technology
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• v.50 no.1
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• pp.33-44
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• 2008

The purpose of this study was to estimate the genetic parameters and trend of Landrace and Yorkshire pigs, which were raised on private farms from 1999 to 2005 and tested for their reproductive performance by the Korea Animal Improvement Association. Prior to analysis, records without pedigree or having value with larger than±3×standard deviation for the Total number of born were excluded. The effects of breed and environmental factors were estimated with least square method(Harvey, 1979), and estimation of breeding values and genetic parameters were performed on the data of 1’st litter only with GIBBSF90(Misztal, 2001) which was programmed according to Gibbs Sampling method based on Bayesian Inference by Gianola and Fernando(1986), Jensen(1994) and others. Gibbs sampling was performed 50,000 times for each parameter, and the first 5000 samples were regarded as those in burn-in period and thus, excluded for post hoc analysis. Total number of born and total number of accident were statistically significant(p<0.01) for the breed, farrowing year, farrowing season and parity effects, and the number born alive at birth was statistically significantp<(0.01) for the breed, farrowing year, farrowing season and parity effects. No particular trend was observed in the genetic and phenotypic improvement of the total number of born and number born alive at birth before 2001, when the piglet registration system started, but the tendencies of increasing for the total number of born and number born alive and decreasing for the total number of accident were observed since 2001. Somewhat higher heritability estimates of our study seems to be attributed to the situations that first parity records with poor farrowing performances were used in the analyses and it was impossible to obtain accurate reproductive performance due to the absence of criteria for record keeping at the level of individual farms.

• Korean Journal of Environmental Agriculture
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• v.39 no.1
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• pp.36-43
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• 2020

BACKGROUND: Wicheon watershed has the largest irrigation area among the mid-watershed of Nakdong river. However, no investigation of irrigation water quality has been conducted on the Wicheon watershed, which evaluates the effects on the soil quality and crop cultivation. Therefore, this study aims to provide various assessments of water quality of Wicheon watershed as the scientific basic data for efficient agricultural activities. METHODS AND RESULTS: Water sampling was performed in five locations of the first tributaries of Wicheon. Wicheon watershed showed clean water quality with very low organic matters and safe water quality from metals at all points of investigation. It was estimated that the natural chemical components of Wicheon watershed were originated from water-rock interaction in Gibbs diagram. All samples were concentrated in the type of Ca-HCO₃-Cl in the Piper diagram. The quality of irrigation water was evaluated with sodium adsorption ratio (SAR), residual sodium carbonate (RSC), permeability index (PI), and percent sodium (%Na). The values of these water quality indices were in the range of 0.37-0.67, -2.11--0.24, 41.13-84.52% and 11.28-21.84%, respectively, and were classified as good grades at all sites. CONCLUSION: The water quality of Wicheon watershed was very low in salt, indicating good irrigation water suitable for growing agricultural products. We hope that the results of this study will be used as the basic data for the cultivation of agricultural products and promotion of their excellence.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.281-291
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• 2020

This study used Gauss-Poisson jump diffusion process on standard assets to estimate the statutory reserves of Variable Annuity (VA) guarantees specified in Korean bylaw of insurance supervision and calculated guarantee fees and risks based on the model to see the effect of considering the jumps. Financial assets, except KOSPI 200, have fat-tailed return distributions, which is an indirect evidence of discontinuous jumps. In the case of a domestic stock index and foreign stock indexes(Korean Won), guarantee fees and risks decrease when jumps are considered in models of underlying assets. This is explained by decreases in standard deviations after the jump diffusion is considered. On the other hand, in the case of domestic bond indexes and a foreign bond index(Korean Won), guarantee fees and risks tend to increase when jumps are considered. Results from a foreign stock index(US Dollar) and a foreign bond index(US Dollar) were opposite to those from the same kinds of Korean Won indexes. We conclude that VA guarantee fees and risks may be under or over estimated when jumps are not considered in models of underlying assets.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1674-1678
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• 2017

Objective: The aim of the study was to evaluate genetic correlations between the behavioural profile and performance in laying hens as an indirect answer to the question whether the observed behavioural responses are associated with increased levels of stress in these birds. Methods: The assessment of birds' temperament was carried out using the novel objects test. The behavioural test was conducted in two successive generations comprising 9,483 Rhode Island White (RIW) birds (approx. 4,700 individuals per generation) and 4,326 Rhode Island Red (RIR) birds (approx. 2,100 individuals per generation). Based on the recorded responses, the birds were divided into two groups: a fearful profile (1,418 RIW hens and 580 RIR hens) and a brave/curious profile (8,065 RIW hens and 3,746 RIR hens). The birds were subjected to standard assessment of their performance traits, including SM, age at sexual maturity; ST, shell thickness; SG, egg specific gravity; EW, mean egg weight; IP, initial egg production; and HC, number of hatched chicks. The pedigree was three generations deep (including two behaviourrecorded generations). Estimation of the (co)variance components was performed with the Gibbs sampling method, which accounts for the discrete character of the behavioural profile denotation. Results: The analyses revealed negative correlations between the performance traits of the laying hens and the behavioural profile defined as fearful. In the group of fearful RIW birds, delayed sexual maturation (0.22) as well as a decrease in the initial egg production (-0.30), egg weight (-0.54), egg specific gravity (-0.331), shell thickness (-0.11), and the number of hatched chicks (-0.24) could be expected. These correlations were less pronounced in the RIR breed, in which the fearful birds exhibited a decline in hatchability (-0.37), egg specific gravity (-0.11), and the number of hatched chicks (-0.18). There were no correlations in the case of the other traits or they were positive but exhibited a substantial standard error, as for the egg weight. Conclusion: To sum up the results obtained, it can be noted that behavioural responses indicating fearfulness, i.e. escape, avoidance, and approach-avoidance may reflect negative emotions experienced by birds. The negative correlations with performance in the group of fearful hens may indirectly indicate a high level of stress in these birds, especially in the white-feathered birds, where stronger performance-fearfulness correlations were found. Fearful birds should be eliminated from breeding by inclusion of the behavioural profile in the selection criterion in the case of laying hens.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.489-495
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• 2020

The amount of data is increasing through various IT devices in a hyper-connected society where the 4th revolution is progressing, and new value can be created by analyzing that data. This paper was collected total 1,526 articles from 2017 to 2019 in central magazines, economic magazines, regional associations, and major broadcasting companies with the keyword "(East Coast Tourism or East Coast Travel) and Gangwon-do" through Bigkinds. It was performed the topic modeling using LDA algorithm implemented in the R language to analyze the collected 1,526 articles. It was extracted keywords for each year from 2017 to 2019, and classified and compared keywords with high frequency for each year. It was setted the optimal number of topics to 8 using Log Likelihood and Perplexity, and then inferred 8 topics using the Gibbs Sampling method. The inferred topics were Gangneung and Beach, Goseong and Mt.Geumgang, KTX and Donghae-Bukbu line, weekend sea tour, Sokcho and Unification Observatory, Yangyang and Surfing, experience tour, and transportation network infra. The changes of articles on East coast tourism was was analyzed using the proportion of the inferred eight topics. As the result, the proportion of Unification Observatory and Mt. Geumgang showed no significant change, the proportion of KTX and experience tour increased, and the proportion of other topics decreased in 2018 compared to 2017. In 2019, the proportion of KTX and experience tour decreased, but the proportion of other topics showed no significant change.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.43-56
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• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.