• Journal of Animal Science and Technology
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• v.65 no.6
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• pp.1180-1193
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• 2023

Most carcass and meat quality traits are moderate to highly heritable, indicating that they can be improved through selection. Genetic evaluation for these types of traits is performed using performance data obtained from commercial and progeny testing evaluation. The performance data from commercial farms are available in large volume, however, some drawbacks have been observed. The drawback of the commercial data is mainly due to sorting of animals based on live weight prior to slaughter, and this could lead to bias in the genetic evaluation of later measured traits such as carcass traits. The current study has two components to address the drawback of the commercial data. The first component of the study aimed to estimate genetic parameters for carcass and meat quality traits in Korean Hanwoo cattle using a large sample size of industry-based carcass performance records (n = 469,002). The second component of the study aimed to describe the impact of sorting animals into different contemporary groups based on an early measured trait and then examine the effect on the genetic evaluation of subsequently measured traits. To demonstrate our objectives, we used real performance data to estimate genetic parameters and simulated data was used to assess the bias in genetic evaluation. The results of our first study showed that commercial data obtained from slaughterhouses is a potential source of carcass performance data and useful for genetic evaluation of carcass traits to improve beef cattle performance. However, we observed some harvesting effect which leads to bias in genetic evaluation of carcass traits. This is mainly due to the selection of animal based on their body weight before arrival to slaughterhouse. Overall, the non-random allocation of animals into a contemporary group leads to a biased estimated breeding value in genetic evaluation, the severity of which increases when the evaluation traits are highly correlated.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.5
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• pp.285-294
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• 2024

Seismic fragility curves present the conditional probability of damage to target structures due to external seismic load and are widely used in various ways. When constructing such a seismic fragility curve, it is essential to consider various types and numbers of ground motions. In general, the earthquake occurrence characteristics of an area where the target structure of the seismic fragility curve exists are analyzed, and based on this, appropriate ground motions are selected to derive the seismic fragility curve. If the number of selected ground motions is large, the diversity of ground motions is considered, but a large amount of computational time is required. Conversely, if the number of ground motions is too small, the diversity of ground motions cannot be considered, which may distort the seismic fragility curve. Therefore, this study analyzed the relationship between the number of ground motions considered when deriving the seismic fragility curve and the parameters of the seismic fragility curve. Using two example structures, numerical analysis was performed by selecting a random number of ground motions from a total of two hundred, and a seismic fragility curve was derived based on the results. Analysis of the relationship of the parameter of the seismic fragility curve and the number of selected ground motions was performed. As the number of ground motions considered increases, uncertainty in ground motion selection decreases, and when deriving seismic fragility curves considering the same number of ground motions, uncertainty increases relatively as the degree of freedom of the target structure increases. However, considering a relatively large number of ground motions, uncertainty appeared insignificant regardless of increased degrees of freedom. Finally, it is possible that the increase in the number of ground motions could lower the epistemic uncertainty and thus improve the reliability of the results.

• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.349-356
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• 2010

This study was conducted to estimate heritabilities, repeatabilities and rank correlation coefficients among breeding values for litter size and sex ratio of Yorkshire and Landrace pigs using various single trait animal models. The analyses were carried out the data comprising 26,390 litters of Yorkshire and 26,173 litters of Landrace collected from the year 1998 to 2008 at a private swine breeding farm located in central part of Korea. Five different analytical models were used for genetic parameter estimation. Model 1 was most simple basic model fitted with year-month contemporary group fixed effect, random additive genetic effect and random residual effect. Model 2 was similar to the model 1 but permanent maternal environmental effect added as random effect, and model 3 was similar with the model 2 but linear and quadratic effects of sow age were added as fixed covariate effect. Model 4 was similar as model 2 except that the parity was added as fixed effect and model 5 was similar to model 3 or model 4 but covariate of sow age was nested within parity effect. The results obtained in this study are summarized as follows: The means and standard error of total number of pigs born per litter (TNB) and number of pigs born alive per litter (NBA) were $11.35{\pm}0.02$ and $10.04{\pm}0.02$ for Yorkshire, $10.97{\pm}0.02$ and $9.98{\pm}0.02$ for Landrace, respectively. The sex ratio (percentage of female per litter) was $45.75{\pm}0.11%$ and $45.75{\pm}0.11%$ for Yorkshire and Landrace, respectively. The heritability estimates of TNB (0.243) and NBA (0.192) from model 1 tended to be higher than those from any other models in both breeds. Differences in heritability and repeatability for TNB were not large among models 3, 4 and 5 and same tendency of negligible differences among estimates by models 3, 4 and 5 were observed for NBA, where heritability and repeatability ranged from 0.096 to 0.099 and from 0.188 to 0.193, respectively, in Yorkshire; and ranged from 0.092 to 0.098 and from 0.193 and 0.196, respectively, in Landrace. The heritability estimates for sex ratio were close to zero which was ranged from 0.002 to 0.003 for TNB and from 0.001 to 0.003 for NBA over the models applied. The rank correlation coefficients of breeding values by model 1 with those from other models (model 2, 3, 4 and 5), and breeding values by model 2 with those from other models (model 1, 3, 4 and 5) were highly positive but lower than the coefficients among breeding values by model 3, model 4 and model 5 which were high of 0.99, approximately, for TNB and NBA of both breeds.

• Journal of Animal Science and Technology
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• v.54 no.1
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• pp.9-14
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• 2012

The purpose of this study was to estimate heritabilities and genetic correlations for reproductive and productive traits and to apply their estimates to selection strategies in a swine population. Reproductive and productive traits considered in this study were number of born alive piglet (NBA), number of weaned piglet (NW), loin eye area (LEA), days to 90 kg (D90KG), back fat thickness (BF), and lean meat content (LEAN). Data were collected from 9,886 litters on 2,447 sows for reproductive traits and 10,181 gilts and boars for productive traits from Jan. 2000 to Dec. 2008 in a swine GGP farm. The statistical model to estimate genetic parameters for considering traits was a multiple traits animal model with including animal and maternal additive effects and litter effects on reproductive traits and animal additive effects on productive traits as random as well as some of fixed effects. For estimating (co) variance components of several random effects, restricted maximum likelihood methodology was used on this assumed model. The estimated heritabilities by animal additive effects and maternal effects were 0.07 and 0.02 for NBA and 0.03 and 0.02 for NW, respectively. Genetic correlation estimate for direct genetic effects between NBA and NW was 0.14. Heritability estimates for direct genetic effects were 0.19, 0.39, 0.36, and 0.43 for LEA, D90KG, BF and LEAN, respectively. The genetic correlation of LEA with LEAN was 0.35. Productive traits were antagonistically correlated with reproductive traits. From these results it is concluded that, if selection is done for strong positive effects of reproductive traits, then this would decline productive performance.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.78-95
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• 2024

For the establishment and comparison of environmental plans across various domains, considering climate change and urban issues, it is crucial to build spatial data at the regional scale classified with consistent criteria. This study mapping the Local Climate Zone (LCZ) of Changwon City, where active climate and environmental research is being conducted, using the protocol suggested by the World Urban Database and Access Portal Tools (WUDAPT). Additionally, to address the fragmentation issue where some grids are classified with different climate characteristics despite being in regions with homogeneous climate traits, a filtering technique was applied, and the LCZ classification characteristics were compared according to the filtering radius. Using satellite images, ground reference data, and the supervised classification machine learning technique Random Forest, classification maps without filtering and with filtering radii of 1, 2, and 3 were produced, and their accuracies were compared. Furthermore, to compare the LCZ classification characteristics according to building types in urban areas, an urban form index used in GIS-based classification methodology was created and compared with the ranges suggested in previous studies. As a result, the overall accuracy was highest when the filtering radius was 1. When comparing the urban form index, the differences between LCZ types were minimal, and most satisfied the ranges of previous studies. However, the study identified a limitation in reflecting the height information of buildings, and it is believed that adding data to complement this would yield results with higher accuracy. The findings of this study can be used as reference material for creating fundamental spatial data for environmental research related to urban climates in South Korea.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.83-87
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• 2012

The purpose of this study was to estimate genetic parameters for productive traits in swine. Productive traits were considered on average daily gain (ADG), body height (BH) and body length (BL). Genetic analysis was consisted of 18,668 heads for productive traits which were based on on-farm performance tested from May, 2007 to Apr, 2011. For estimating genetic parameters on productive traits, single best model was fitted after finding source of variance on fixed and random effects and estimated with a multiple trait animal model by using DF-REML (Derivative-Free Restricted Maximum Likelihood). The estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire 0.22-0.58 for the average daily gain, 0.34-0.41 for the body height and 0.4-0.52 for the body length, respectively. Phenotypic correlations of average daily gain with body height and body length for the four breeds were 0.42-0.48, 0.53-0.58, 0.34-0.46 and 0.47-0.56, respectively. Phenotypic correlations of body height with body length were 0.41, 0.57, 0.52, 0.59, respectively. The estimated genetic correlation coefficients of average daily gain with body height and body length estimated for the four breeds were 0.34-0.47, 0.70-0.75, 0.17-0.38 and 0.50-0.53, respectively. The estimated genetic correlation coefficients of body height with body length were 0.57, 0.69, 0.61 and 0.71, respectively.

• Tuberculosis and Respiratory Diseases
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• v.61 no.4
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• pp.356-365
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• 2006

Background: Corticosteroids are known to be significant prognostic parameters in sepsis. Recently, an absolute and relative insufficiency of the corticosteroids system has often been reported to often develop particularly in severe sepsis. Degree of such an adrenal insufficiency not only has prognostic implications but also can be used to guide corticosteroids replacement therapy. The 24-hour urinary cortisol levels as well as serum cortisol concentrations were measured to assess the clinical significance and their relationship with the other parameters of sepsis, and also evaluated the clinical implications of the relative adrenal insufficiency. Methods: 26 consecutive patients with sepsis were enrolled. The basal random serum cortisol, ACTH, ADH, lactate levels and 24-hour urinary free cortisol amount were measured. The rapid ACTH ($250{\mu}g$) stimulation test was also performed. Results: Basal serum cortisol levels were higher in the non-survivors than in the survivors. The 24-hour urinary free cortisol levels were higher in the patients with severe sepsis than in those without. The serum cortisol levels strongly correlated with the serum ADH and lactate levels. The 24-hour urinary free cortisol levels strongly correlated with the serum cortisol and lactate levels. The fractional changes in the cortisol levels after the rapid ACTH stimulation tests correlated with the serum cortisol, ADH, and lactate levels. Conclusion: Both the serum cortisol and 24-hour urinary cortisol were found to be significant prognostic factors in sepsis, and showed a strong correlation with the other parameters. The relative adrenal insufficiency might also be an important clinical parameter.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.09a
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• pp.119-120
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• 2004

Urban groundwater has a unique hydrologic system because of the complex surface and subsurface infrastructures such as deep foundation of many high buildings, subway systems, and sewers and public water supply systems. It generally has been considered that increased surface impermeability reduces the amount of groundwater recharge. On the other hand, leaks from sewers and public water supply systems may generate the large amounts of recharges. All of these urban facilities also may change the groundwater quality by the recharge of a myriad of contaminants. This study was performed to determine the factors controlling the recharge of deep groundwater in an urban area, based on the hydrogeochemical characteristics. The term ‘contamination’ in this study means any kind of inflow of shallow groundwater regardless of clean or contaminated. For this study, urban groundwater samples were collected from a total of 310 preexisting wells with the depth over 100 m. Random sampling method was used to select the wells for this study. Major cations together with Si, Al, Fe, Pb, Hg and Mn were analyzed by ICP-AES, and Cl, N $O_3$, N $H_4$, F, Br, S $O_4$and P $O_4$ were analyzed by IC. There are two groups of groundwater, based on hydrochemical characteristics. The first group is distributed broadly from Ca-HC $O_3$ type to Ca-C1+N $O_3$ type; the other group is the Na+K-HC $O_3$ type. The latter group is considered to represent the baseline quality of deep groundwater in the study area. Using the major ions data for the Na+K-HC $O_3$ type water, we evaluated the extent of groundwater contamination, assuming that if subtract the baseline composition from acquired data for a specific water, the remaining concentrations may indicate the degree of contamination. The remainder of each solute for each sample was simply averaged. The results showed that both Ca and HC $O_3$ represent the typical solutes which are quite enriched in urban groundwater. In particular, the P$CO_2$ values calculated using PHREEQC (version 2.8) showed a correlation with the concentrations of maior inorganic components (Na, Mg, Ca, N $O_3$, S $O_4$, etc.). The p$CO_2$ values for the first group waters widely ranged between about 10$^{-3.0}$ atm to 10$^{-1.0}$ atm and differed from those of the background water samples belonging to the Na+K-HC $O_3$ type (<10$^{-3.5}$ atm). Considering that the p$CO_2$ of soil water (near 10$^{-1.5}$ atm), this indicates that inflow of shallow water is very significant in deep groundwaters in the study area. Furthermore, the P$CO_2$ values can be used as an effective parameter to estimate the relative recharge of shallow water and thus the contamination susceptibility. The results of our present study suggest that down to considerable depth, urban groundwater in crystalline aquifer may be considerably affected by the recharge of shallow water (and pollutants) from an adjacent area. We also suggest that for such evaluation, careful examination of systematically collected hydrochemical data is requisite as an effective tool, in addition to hydrologic and hydrogeologic interpretation.ion.ion.

• Journal of Embryo Transfer
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• v.32 no.3
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• pp.227-233
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• 2017

Pig has been known to be one of the most feasible animals as a bioreactor to produce pharmaceuticals in milk and as a mediator in xenotransplantation research. Previously, we generated transgenic pigs for both purposes, which were expressing Factor 8, vWF, hTPA, and hEPO in milk, along with expression of MCP at GalT gene locus ($GalT^{-MCP/-MCP}$) as well as expressing MCP at GalT gene loci with CD73 expression ($GalT^{-MCP/+}/CD73$). In this study, we performed comparative analyses of sperm parameters between wild type male (WT) pig and those transgenic males to examine the effects of transgenes integrated into the pigs on motility, morphology, viability, and acrosome integrity of the spermatozoa. Our results showed that the rates of actively motile spermatozoa of WT, Factor 8, vWF, hTPA, hEPO, $GalT^{-MCP/+}/CD73$, and $GalT^{-MCP/-MCP}$ pigs were 85.0%, 83.3%, 82.5%, 83.3%, 82.5%, 77.5%, and 78.7%, respectively. Whereas, the rates of morphologically normal spermatozoa of WT, Factor 8, vWF, hTPA, hEPO, $GalT^{-MCP/+}/CD73$, and $GalT^{-MCP/-MCP}$ pigs were 90.0%, 80.0%, 80.0%, 83.3%, 85.0%, 91.8%, and 80.8%, respectively. In addition, the viability in spermatozoa of WT, Factor 8, vWF, hTPA, hEPO, $GalT^{-MCP/+}/CD73$, and $GalT^{-MCP/-MCP}$ pigs were 93.9%, 82.4%, 89.9%, 83.9%, 87.4%, 92.8%, and 83.6%, respectively. The rates of spermatozoa with normal acrosome integrity in WT, Factor 8, vWF, hTPA, hEPO, $GalT^{-MCP/+}/CD73$, and $GalT^{-MCP/-MCP}$ pigs were 98.1%, 98.6%, 98.6%, 98.7%, 98.1%, 99.5%, and 95.1%, respectively. There were no significant differences in motility, morphology, viability, and acrosome integrity of the spermatozoa among WT, Factor 8, vWF, hTPA, and hEPO, $GalT^{-MCP/+}/CD73$, and $GalT^{-MCP/-MCP}$ pigs. These mean that neither random integration nor targeted integration of the transgene into chromosome of pig effect on characteristics of spermatozoa. Ultimately, the transgenic male pigs subjected in this study could apply to propagate their progenies for production of human therapeutic proteins and advancing the xenotransplantation research.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.