• Asian-Australasian Journal of Animal Sciences
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• v.23 no.6
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• pp.814-824
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• 2010

The objective of this research was to assess the effect of experience, education, record keeping, labor, and decision making on monthly milk yield per farm (MYF), monthly milk yield per cow (MYC), monthly milk revenue per farm (MRF), and monthly revenue per cow (MRC) of dairy farms supported by a private organization in Central Thailand. The dataset contained 34,082 monthly milk yield and revenue records collected from January 2004 to December 2008 on 497 farms, and information on individual farmer experience and education, record keeping, and decision making obtained with a questionnaire. Farmer experience categories were i) no experience, ii) one year, iii) two to five years, iv) six to ten years, v) eleven to fifteen years, vi) sixteen to twenty years, and vii) more than twenty years. Farmer education categories were i) no education or primary school, ii) high school, and iii) bachelor or higher degree. Record keeping categories were: i) no records and ii) kept records. Labor categories were: i) family, ii) hired people, and iii) family and hired people. Decision making categories were: i) decisions made by farmers themselves, ii) decisions made with help from government officials, and iii) decisions made with help from organization staff. The mixed linear model contained the fixed effects of year-season, farm location-farm size subclass, experience, education, record keeping, labor, and decision making on sire selection, and the random effects of farm and residual. Results showed that longer experience increased (p<0.05) monthly milk yield (MYF and MYC) and revenue (MRF and MRC). Farms that hired people produced the highest (p<0.05) monthly milk yield (MYF and MYC) and revenue (MRF and MRC), followed by farms that used family, and the lowest values were for farms that used both family and hired people. Better educated farmers produced more MYC and MRC (p<0.05) than lower educated farmers. Farms that kept records had higher MYF and MRF (p<0.05) than those without records. Although differences among farms were non-significant, farms that received help from the organization staff had higher monthly milk yield (MYF and MYC) and revenue (MRF and MRC) than those that decided by themselves or with help from government officials. These findings suggested that dairy farmers needed systematic training and continuous support to improve farm milk production and revenues in a sustainable manner.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.3
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• pp.320-327
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• 2017

Objective: The objective of this research was to estimate genetic correlations between number of piglets born alive in the first parity (NBA1), litter birth weight in the first parity (LTBW1), number of piglets weaned in the first parity (NPW1), litter weaning weight in the first parity (LTWW1), number of piglets born alive from second to last parity (NBA2+), litter birth weight from second to last parity (LTBW2+), number of piglets weaned from second to last parity (NPW2+) and litter weaning weight from second to last parity (LTWW2+), and to identify the percentages of animals (the top 10%, 25%, and 50%) for first parity and sums of second and later parity traits. Methods: The 9,830 records consisted of 2,124 Landrace (L), 724 Yorkshire (Y), 2,650 LY, and 4,332 YL that had their first farrowing between July 1989 and December 2013. The 8-trait animal model included the fixed effects of first farrowing year-season, additive genetic group, heterosis of the sow and the litter, age at first farrowing, and days to weaning (NPW1, LTWW1, NPW2+, and LTWW2+). Random effects were animal and residual. Results: Heritability estimates ranged from $0.08{\pm}0.02$ (NBA1 and NPW1) to $0.29{\pm}0.02$ (NPW2+). Genetic correlations between reproduction traits in the first parity and from second to last parity ranged from $0.17{\pm}0.08$ (LTBW1 and LTBW2+) to $0.67{\pm}0.06$ (LTWW1 and LTWW2+). Phenotypic correlations between reproduction traits in the first parity and from second to last parity were close to zero. Rank correlations between LTWW1 and LTWW2+ estimated breeding value tended to be higher than for other pairs of traits across all replacement percentages. Conclusion: These rank correlations indicated that selecting boars and sows using genetic predictions for first parity reproduction traits would help improve reproduction traits in the second and later parities as well as lifetime productivity in this swine population.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.513-522
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• 2002

Current end-to-end congestion control depends only on the information of end points (using three duplicate ACK packets) and generally responds slowly to the network congestion. This mechanism can't avoid TCP global synchronization which TCP congestion window size is fluctuated during congestion occurred and if RTT (Round Trip Time) is increased, three duplicate ACK packets is not a correct congestion signal because congestion maybe already disappeared and the host may send more packets until receive the three duplicate ACK packets. Recently there is increasing interest in solving end-to-end congestion control using active network frameworks to improve the performance of TCP protocols. ACC (Active congestion control) is a variation of TCP-based congestion control with queue management In addition traffic modifications nay begin at the congested router (active router) so that ACC will respond more quickly to congestion than TCP variants. The advantage of this method is that the host uses the information provided by the active routers as well as the end points in order to relieve congestion and improve throughput. In this paper, we model enhanced ACC, provide its algorithm which control the congestion by using information in core networks and communications between active routers, and finally demonstrate enhanced performance by simulation.

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.137-144
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• 2020

Delirium is among the most common mental disorders encountered in patients with a temporary cognitive impairment such as consciousness disorder, attention disorder, and poor speech, particularly among those who are older. Delirium is distressing for patients and families, can interfere with the management of symptoms such as pain, and is associated with increased elderly mortality. The purpose of this paper is to generate useful clinical knowledge that can be used to distinguish the outcomes of patients with delirium in long-term care facilities. For this purpose, we extracted the clinical classification knowledge associated with delirium using a local covering rule acquisition approach with the rough lower approximation region. The clinical applicability of the proposed method was verified using data collected from a prospective cohort study. From the results of this study, we found six useful clinical pieces of evidence that the duration of delirium could more than 12 days. Also, we confirmed eight factors such as BMI, Charlson Comorbidity Index, hospitalization path, nutrition deficiency, infection, sleep disturbance, bed scores, and diaper use are important in distinguishing the outcomes of delirium patients. The classification performance of the proposed method was verified by comparison with three benchmarking models, ANN, SVM with RBF kernel, and Random Forest, using a statistical five-fold cross-validation method. The proposed method showed an improved average performance of 0.6% and 2.7% in both accuracy and AUC criteria when compared with the SVM model with the highest classification performance of the three models respectively.

• Environmental and Resource Economics Review
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• v.14 no.2
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• pp.337-379
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• 2005

This choice experiments study values the non-market benefits of water quality improvements in Paldang Reservoir and Han River, located in Korea. A fractional factorial orthogonal design was used to produce four different choice sets per respondent, before employing choice examples to screen out irrational responses. The panel mixed logit model (with normal distributions for the attributes) fit the data best, indicating that allowing for both heterogeneous preferences across households and correlation between repeated choices may represent actual choice behaviors best of all the estimated models. The significant standard deviations of the random attributes suggest that the taste for each attribute may vary considerably in the population. The annual benefits to the Seoul Metropolitan area for a small (large) enhancement of the clarity of water, a gradual removal of unpleasant waters, and a gradual improvement in biodiversity, were estimated to be some 1.5 trillion (1.7 trillion) Won, 2 trillion Won, and 1.7 trillion Won, respectively, with 1.8~2.6 trillion Won for at least two of them occurring together. The study also discusses potential biases germane to choice experiments studies of this type.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.809-825
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• 2017

The number of TV entertainment shows is increasing. Competition among programs in the entertainment market is intensifying since cable channels air many entertainment TV shows. There is now a need for research on program ratings and the number of episodes. This study presents predictive models for entertainment TV show ratings and number of episodes. We use various data mining techniques such as linear regression, logistic regression, LASSO, random forests, gradient boosting, and support vector machine. The analysis results show that the average program ratings before the first broadcast is affected by broadcasting company, average ratings of the previous season, starting year and number of articles. The average program ratings after the first broadcast is influenced by the rating of the first broadcast, broadcasting company and program type. We also found that the predicted average ratings, starting year, type and broadcasting company are important variables in predicting of the number of episodes.

• Journal of The Korean Society of Grassland and Forage Science
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• v.32 no.2
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• pp.175-184
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• 2012

In the present study, the effects of feeding different forage sources on the growth performance, meat production and meat quality of Hanwoo steers were evaluated using meta-analysis. In total 5 studies that were performed and published in the domestic journals in Korea were employed for the analysis. The results from nutritionally better quality roughage-based steers and rice straw-based steers in each study were assigned as a treatment and a control, respectively, and the mean difference between the treatment and the control was used for the evaluation of effect size. The summary effect was calculated using random effect model. As results, in growth performance, positive effects were found in feed intake, daily weight gain, final body weight and feed efficiency. The significant effect was found only in daily weight gain (p<0.05). In meat production, carcass weight, Longissimus dorsi area, yield index showed positive effect and negative effect was detected in back fat thickness. The significant effect in meat production was found in carcass weight and Longissimus dorsi area (p<0.05). In meat quality, positive effects were represented in marbling score and fat color. Meat color showed little effect. The significance for effects was not observed in the analysis of meat quality. In conclusion, feeding good quality forages to ruminants plays an important role in Korean beef cattle industry and hence further researches are necessary to improve the efficiency of forage utilization in Hanwoo cattle.

• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.1-15
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• 2018

With land-use (cover) and water quality, the distributional characteristics of epilithic diatom communities were studied with 193 samples from estuaries of Korean peninsula between 2015 and 2016. Of total 394 taxa classified, Nitzschia perminuta (19.6%) and N. inconspicua (14.0%) were the 1st and 2nd dominant species. Using a cluster analysis, the epilithic diatom communities of Korean estuaries were divided into four groups (G1-G4). Ecological characteristics of each group were followed: G1 was located in estuaries of the East Sea, and characterized by high forest land-use and high DO and low nutrients; G2 was the eastern part of the South Sea, and characterized by low turbidity and nutrients; G3 was the western part of the South Sea, and characterized by high agriculture, low electric conductivity and low salinity; G4 was the Yellow Sea, and characterized by high nutrients. The environmental factors having significant correlation with diatom distributions were as follows: TN to G1, turbidity to G2, agriculture to G3, and TP to G4. Moreover, the important factors affecting the occurrence of indicator species were forest land-use for Fragilaria construens var. venter in G1, turbidity for Rhoicosphenia abbreviata in G2, urban land- use and total phosphorus (TP) for Bacillaria paradoxa and Hantzschia amphioxys of G3, and TP and turbidity for N. ovalis and Stephanodiscus invistatus of G4. These results collectively indicate that the distribution of epilithic diatom communities in Korean peninsula was largely effected by water quality and land cover/use.

• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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• pp.381-389
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• 2004

Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferiority clinical trial was conducted at 5 institutions in Korea with the random assignment of 248 patients aged 35 to 75 years old with OA of the knee and clinical evidence of OA. Patients were enrolled in this study if they had at least moderate pain in the affected knee joint and a score larger than 35mm as assessed by VAS (Visual Analog Scale). The main exposure variable was treatment (SKI 306X vs. Diclofenac) and other covariates were age, sex, BMI, baseline VAS, center, operation history (Yes/No), NSAIDS (Y/N), acupuncture (Y/N), herbal medicine (Y/N), past history of musculoskeletal disease (Y/N), and previous therapy related with OA (Y/N). The main study outcome was the change of VAS pain scores from baseline to the 2nd and 4th weeks after treatment. Pain scores were obtained as baseline, 2nd and 4th weeks after treatment. We applied GEE approach with empirical covariance matrix and independent(or exchangeable) working correlation matrix to evaluate the relation of several risk factors to the change of VAS pain scores with correlated binary bivariate outcomes. Results : While baseline VAS, age, and acupuncture variables had protective effects for reducing the OA pain, its treatment (Joins/Diclofenac) was not statistically significant through GEE methodology (ITT:aOR=1.37, 95% CI=(0.8200, 2.26), PP:aOR=1.47, 95% CI=(0.73, 2.95)). The goodness-of-fit statistic for GEE (6.55, p=0.68) was computed to assess the adequacy of the fitted final model. Conclusions : Both ANCOVA and GEE methods yielded non statistical significance in the evaluation of non-inferiority of the efficacy between SKI306X and Diclofenac. While VAS outcome for each visit was applied in GEE, only VAS outcome for the fourth visit was applied in ANCOVA. So the GEE methodology is more accurate for the analysis of correlated outcomes.