• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.307-329
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• 2022

This study aimed to explore factors which can predict interpersonal tolerance and intolerance. Specifically, the study examined whether tolerance and intolerance would be explained by demographic variables, social desirability, empathy (cognitive empathy and affective empathy), fear of compassion for others, social trust, and zero-sum belief. Participants in the study were 445 adults (218 males and 227 females) who completed an online survey. Data were analyzed by using hierarchical regression analyses to control the effects of demographic variables and social desirability. The results indicated that tolerance was explained by gender, subjective socioeconomic status, social desirability, cognitive empathy, and social trust. In addition, intolerance was predicted by social desirability, fears of compassion for others, and zero-sum belief. It means that the constructs of tolerance and intolerance are distinct, and different factors predict tolerance and intolerance, respectively. Therefore, it would be necessary to develop realistic ways to promote tolerance and to prevent intolerance at the same time in order to achieve co-existence in a multicultural and diverse society.

• Convergence Security Journal
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• v.23 no.1
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• pp.89-95
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• 2023

In order to help reduce the medical expenses of patients with auto insurance accidents, this study predicted the treatment period, which is the most important factor in the medical expenses of patients in their 40s and 50s, and analyzed the factors affecting the treatment period. To this end, a mechine learning model using five algorithms such as Decision Tree was created, and its performance was compared and analyzed between models. There were three algorithms that showed good performance including Decison Tree, Gradient Boost, and XGBoost. In addition, as a result of analyzing the factors affecting the prediction of the treatment period, the type of hospital, the treatment area, age, and gender were found. Through these studies, easy research methods such as the use of AutoML were presented, and we hope that the results of this study will help policies to reduce medical expenses for automobile insurance accidents.

• Clinical and Experimental Pediatrics
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• v.49 no.3
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• pp.298-304
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• 2006

Purpose : We compared the asthma predictive index(API) and the modified asthma predictive index (mAPI) of the Tuscon Children's Respiratory Study Group in Korean children with recurrent wheezing. We investigated the atopic profiles and presence of allergen sensitization of each risk group, and ascertained the significant clinical risk factors. Methods : Two hundred and sixty two children, who visited for recurrent wheezing from 1998 to 2005, were enrolled and divided into groups by API and mAPI. We investigated the history of the patients and their families, atopic profiles, and sensitization to aeroallergen and food allergens. Twenty nine children were followed up to 6 years of age and we evaluated the sensitivity, specificity and positive and negative predictive value of both indices. Results : The high risk group of API were of older age, were more likely to be sensitized to aeroallergen(P=0.001) and food allergen(P=0.034) and had higher levels of total eosinophil count, eosinophil percent, serum ECP, total IgE, and D.p-, D.f-specific IgE. High risk group of mAPI showed higher levels of atopic markers such as egg-, milk-, D.p- and D.f-specific IgE. Even though API did not include allergen sensitization, the high risk group was more significantly sensitized to common allergens than the low risk group. Twenty nine children were followed up until 6 years of age; therefore 15 children were diagnosed as asthma, clinically. The sensitivity, specificity, positive and negative predictive values of mAPI were higher than API. Conclusion : Both high risk groups of API and mAPI had higher levels of atopic markers and were more sensitized to common allergens. These findings suggest that sensitization to aeroallergens and food allergens are more objective markers as asthma predictive indices. In addition, mAPI is a more reliable index in predicting asthma in Korean children with recurrent wheezing than is API. But only 29 patients were followed until the age of 6, so we need to include more children with long term follow up for future study.

• Journal of Korean Academy of Nursing
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• v.32 no.1
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• pp.77-88
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• 2002

The purpose of this study was designed to develope and test the structural model that explains alcohol consumption behaviors among university students in Republic of Korea. The hypothetical model was constructed on the basis of the literature review and Pender's Health promotion model. Data was collected from questionnaires from 512 university students in Republic of Korea, from August to September, 2000. The reliability of instruments was adequate (Cronbach's alpha= .69-.90). Data analysis was done with SAS 6.12 for descriptive statistics and LISREL 8.13 program for covariance structural analysis. The results are as follows; 1. The overall fit of the hypothetical model to the data was moderate. Thus it was modified by male and female models. 2. The revised model has become parsimonious and had a better fit to the empirical data (male: χ2=87.21 p=.00, GFI=.97, AGFI= .94, NFI=.99, NNFI=1.0, CN=619.17, female: χ2=49.29 p=.31, GFI=.45, AGFI= .95, NFI=.99, NNFI=1.0, CN=370.02). 3. Self-efficacy was most significant factor and personality of novelty seeking, reward compensation, alcohol expectancy and drinking attitude have significant effects on male alcohol consumption behavior. 4. Personality of novelty seeking was most significant factor and personality of harm avoidance, friend influence, self-efficacies, alcohol expectancy and drinking attitude have significant effects on female alcohol consumption behavior.

• Journal of Chest Surgery
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• v.36 no.2
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• pp.101-104
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• 2003

Although lung transplantation has been accepted as the most effective treatment for end-stage pulmonary emphysema, it is not only very hard to find a donor but also to obtain a relatively healthy lung. Furthermore, it is more difficult to match the size of the allograft, considering the height, the weight, and the size of the thoracic cage. The single lung transplatations for the end-stage emphysema have been more commonly performed than bilateral lung transplantation due to the shortage of the donors and the long-term survival rate of the single lung transplantations has shown no reasonable difference compared with that of the bilateral lung transplantationh. Recently, the functional criteria based on a comparison of predicted TLCs(Total Lung Capacities) of the donor and recipient according to height, sex and age, have been accepted at a more suitable.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.129-136
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• 2022

This study examines the moderating effect of sociodemographic factors on the relationship between motivation and outcomes of digital device use. The data from 'the 2020 Survey on the Digital Divide' conducted by National Information Society Agency was used for empirical analysis. Significant interaction effects were observed between sociodemographic characteristics and motivation. The results also show that motivation was a primary predictor of the differences in outcomes of digital device use, the third-level digital divide. These findings have implications for closing the third-level digital divide.

• Asia Marketing Journal
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• v.1 no.2
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• pp.19-35
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• 1999

데이터베이스 마케팅 전략을 수립하고 집행함에 있어서 고객에게 접근하기 위한 촉진 매체로써 직접우편(Direct Mail)과 텔레 마케팅 등의 직접반응매체를 주요 수단으로 하는 경우 이를 다이렉트 마케팅이라고 한다. 다른 마케팅 전략들과 마찬가지로 다이렉트 마케팅에서도 마케팅 자원이 효과적으로 사용될 수 있도록 고객 데이터베이스를 세분화하는 작업을 수행한다. 리스펀스 모델링(Response Modeling)은 다이렉트 마케팅분야에서 고객리스트를 세분화하고 각 세그멘트별로 고객의 반응(구매행위)을 예측하는 기법을 말하며 RFM(Recency, Frequency, Monetary), 로지스틱, 신경망은 리스펀스 모델링을 위해서 가장 널리 사용되고 있는 기법이다. 과거에 이들 방법은 고객 데이터베이스 전체에 단독 모델로 적용되어 왔으나 이러한 단독 모델을 고객 데이터베이스에 적용하는 것이 정당화 되려면 고객들이 동일한 방식으로 반응한다는 전제가 필요하다. 그러나 일반적으로 고객의 반응방식에는 상당한 이질성이 존재한다. 예컨대 직업, 나이, 소득, 성별 등이 같다고 해서 같은 구매패턴을 보이지는 않는다는 것이다. 즉 고객A의 구매행위는 회귀선에 의해서 잘 설명되는 반면에 고객B는 신경망이나 RFM으로 잘 설명될 수 있는 경우가 존재하는 것이다. 이러한 구매행위의 이질성을 반영하기 위해서 최근에는 두개 이상의 방법을 결합하여 사용하는 결합 리스펀스 모델링 방법도 시도 되어 왔다. 그러나 결합 리스펀스 모델링에 관한 기존 연구들은 상관관계가 낮은 모델들을 결합함으로써 세분화의 효과를 단독 모델을 사용할 때 보다 개선할 수 있다고는 하였으나 구체적으로 어떤 모델들이 서로 낮은 상관관계를 갖는지는 보여주지 못하였다. 본 논문에서는 RFM 방법을 모델 내에서 사용하는 변수와 이를 이용한 모델링 방법상의 차이로 인하여 다른 두 방법(로지스틱, 신경망)과 매우 낮은 상관관계를 갖는 방법으로 제시하고 RFM과 다른 두 방법간의 낮은 상관관계를 이용하여 결합하는 경우 모델의 예측효과를 상당히 개선할 수 있음을 사례분석을 통해서 보이고자 한다.

• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.367-374
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• 2010

Telomeres at the end of chromosomes consist of tandem repeats of (TTAGGG)n DNA sequence and associated proteins. Telomeres have the essential functions in chromosome stability and genome integrity and are hence related to cell senescence and cancer. This study was carried out to quantify the amount of telomeric DNA and establish age prediction equations by using the quantity of telomeric DNA for cattle. Analysis of the telomere quantity of the lymphocytes was performed at different age, across breeds and between different sexes of cattle. We quantified the amount of telomeric DNA by the Q-FISH technique using the telomeric DNA probe in 460 cattle at age of 1~166 months in Korean Cattle and Holstein breeds. In results, we found that the amount of telomeric DNA decreased gradually with age. The amount of telomeric DNA of Korean Cattle was significantly higher than that of Holstein breed (P<0.01). In addition, the amount of telomeric DNA in male was significantly higher than that in female (P<0.01). Using the relationship between age and the amount of telomeric DNA in cattle, age predicting equations were established as a result of regression analysis. Because sex and breeds influenced telomeric DNA quantity, the age prediction equations were estimated separately in Korean Cattle females and Holstein females. The regression equations were $\hat{Y}$=$38.102X^2$-220.103X + 318.309 (P<0.0001, $R^2$=0.8019) in Korean Cattle females and $\hat{Y}$ = $42.799X^2$ - 199.682X + 242.106 (P<0.0001, $R^2$ = 0.8379) in Holstein females, where the X was quantity of telomeric DNA and Y was predicted age in months. These equations predicted the age of cattle with high significance and accuracy and have high R square values. Thus, it could be possible to scientifically predict the age using the above equations for Korean Cattle and Holstein females.

• Journal of The Korean Ophthalmological Society
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• v.59 no.12
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• pp.1173-1180
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• 2018

Purpose: We evaluated the postoperative accuracy of intraocular lens power prediction for patients undergoing phacotrabeculectomy and identified preoperative factors associated with refractive outcome in those with primary open-angle glaucoma (POAG). Methods: We retrospectively reviewed the medical records of 27 patients who underwent phacotrabeculectomy to treat POAG. We recorded all discrepancies between predicted and actual postoperative refractions. We compared the data to those of an age- and sex-matched control group that underwent uncomplicated cataract surgery during the same time period. Preoperative factors associated with the mean absolute error (MAE) were identified via multivariate regression analyses. Results: The mean refractive error of the 27 eyes that underwent phacotrabeculectomy was comparable to that of the 27 eyes treated via phacoemulsification (+0.02 vs. -0.01 D, p = 0.802). The phacotrabeculectomy group exhibited a significantly higher MAE (0.65 vs. 0.35 D, p = 0.035) and more postoperative astigmatism (-1.07 vs. -0.66 D, p = 0.020) than the phacoemulsification group. The preoperative anterior chamber depth (ACD) and the changes in the postoperative intraocular pressure (IOP) were significantly associated with a greater MAE after phacotrabeculectomy. Conclusions: POAG treatment via combined phacoemulsification/trabeculectomy was associated with greater error in terms of final refraction prediction, and more postoperative astigmatism. As both a shallow preoperative ACD and a greater postoperative change in IOP appear to increase the predictive error, these two factors should be considered when planning phacotrabeculectomy.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.323-338
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• 2024

This study analyzes the Korean professional volleyball league and predict match outcomes using popular machine learning classification methods. Match data from the 2012/2013 to 2022/2023 seasons for both male and female leagues were collected, including match details. Two different data structures were applied to the models: Separating matches results into two teams and performance differentials between the home and away teams. These two data structures were applied to construct a total of four predictive models, encompassing both male and female leagues. As specific variable values used in the models are unavailable before the end of matches, the results of the most recent 3 to 4 matches, up until just before today's match, were preprocessed and utilized as variables. Logistc Regrssion, Decision Tree, Bagging, Random Forest, Xgboost, Adaboost, and Light GBM, were employed for classification, and the model employing Random Forest showed the highest predictive performance. The results indicated that while significant variables varied by gender and data structure, set success rate, blocking points scored, and the number of faults were consistently crucial. Notably, our win-loss prediction model's distinctiveness lies in its ability to provide pre-match forecasts rather than post-event predictions.