• 대한간호학회지
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• 제46권5호
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• pp.744-752
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• 2016

Purpose: This study was done to investigate factors influencing successful aging in middle-aged women. Methods: A convenience sample of 103 middle-aged women was selected from the community. Data were collected using a structured questionnaire and analyzed using descriptive statistics, two-sample t-test, one-way ANOVA, Kruskal Wallis test, Pearson correlations, Spearman correlations and multiple regression analysis with the SPSS/WIN 22.0 program. Results: Results of regression analysis showed that significant factors influencing successful aging were post-traumatic growth and social support. This regression model explained 48% of the variance in successful aging. Conclusion: Findings show that the concept 'post-traumatic growth' is an important factor influencing successful aging in middle-aged women. In addition, social support from friends/co-workers had greater influence on successful aging than social support from family. Thus, we need to consider the positive impact of post-traumatic growth and increase the chances of social participation in a successful aging program for middle-aged women.

• 한국자동차공학회논문집
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• 제18권3호
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• pp.104-109
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• 2010

The fatality of pedestrian accounts for about 21.2% of all fatality at 2007 year in Korea. In car to pedestrian accident it is very important to inspect the throw distance of pedestrian after collision for exact reconstructing of the accident. The variables that influence on the throw distance of pedestrian can be classified into the factors of vehicle and pedestrian, and road condition. It was simulated by PC-CRASH, a kinetic analysis program for a traffic accident in sedan type vehicle and SPSS program was used for regression analysis. From the results, the throw distance of pedestrian increased with the increasing of vehicle velocity, and decreased with the increasing of impact offset. Also it decreased with the increasing of velocity of pedestrian at accident, and throw distance at the road condition of wet was longer than that at dry condition. Finally, the regression model of sedan type vehicle on the throw distance of pedestrian was as follows; $$dist_i=2.39-0.11offset_i+0.59speed_i-545height_i-0.25walk_i+2.78wet_i+{\epsilon}_i$$.

• 한국콘텐츠학회논문지
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• 제18권6호
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• pp.414-423
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• 2018

본 연구는 간호대학생의 그릿에 영향을 미치는 요인을 규명하기 위한 서술적 조사연구이다. 본 연구의 대상자는 Y시에 소재하고 있는 일개 대학의 간호대학생을 대상으로 하였으며, 146부를 최종 분석에 사용하였다. 수집된 자료는 IBM SPSS Statistics 20.0 프로그램을 사용하여 기술통계, t-test, ANOVA, Scheffe, Pearson's correlation coefficient, multiple regression을 통해 분석하였다. 연구결과 그릿은 학업스트레스, 학업적 자기효능감, 전공만족도에 유의한 상관관계가 있는 것으로 나타났다. 다중회귀분석결과 그릿에 영향을 미치는 요인은 전공만족도, 학업적 자기효능감, 학업스트레스, 학점이었으며 이들의 설명력은 22.5%였다. 본 연구결과를 바탕으로 간호대학생의 그릿을 높일 수 있는 중재 프로그램 개발이 필요할 것으로 생각된다.

• 산업경영시스템학회지
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• 제38권2호
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• pp.17-30
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• 2015

Technology-oriented national R&D programs produce intellectual property as their final result. Patents, as typical industrial intellectual property, are therefore considered an important factor when evaluating the outcome of R&D programs. Among the main components of patent evaluation, in particular, the patent right quality is a key component constituting patent value, together with marketability and usability. Current approaches for patent right quality evaluation rely mostly on intrinsic knowledge of patent attorneys, and the recent rapid increase of national R&D patents is making expert-based evaluation costly and time-consuming. Therefore, this study defines a hierarchy of patent right quality and then proposes how to quantify the evaluation process of patent right quality by combining text mining and regression analysis. This study will contribute to understanding of the systemic view of the patent right quality evaluation, as well as be an efficient aid for evaluating patents in R&D program assessment processes.

• International Journal of Internet, Broadcasting and Communication
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• 제11권2호
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• pp.1-10
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• 2019

Research classification of software modules was done to validate the approaches proposed for addressing limitations in existing classification approaches. The objective of this study was to replicate the experiments of a recently published research study and re-evaluate its results. The reason to repeat the experiment(s) and re-evaluate the results was to verify the approach to identify the faulty and non-faulty modules applied in the original study for the prioritization of test cases. As a methodology, we conducted this study to re-evaluate the results of the study. The results showed that binary logistic regression analysis remains helpful for researchers for predictions, as it provides an overall prediction of accuracy in percentage. Our study shows a prediction accuracy of 92.9% for the PureMVC Java open source program, while the original study showed an 82% prediction accuracy for the same Java program classes. It is believed by the authors that future research can refine the criteria used to classify classes of web systems written in various programming languages based on the results of this study.

• 한국인공지능학회지
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• 제9권1호
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• pp.9-14
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• 2021

This paper predicted a model that indicates whether to buy a car based on primary health insurance customer data. Currently, automobiles are being used to land transportation and living, and the scope of use and equipment is expanding. This rapid increase in automobiles has caused automobile insurance to emerge as an essential business target for insurance companies. Therefore, if the car insurance sales are predicted and sold using the information of existing health insurance customers, it can generate continuous profits in the insurance company's operating performance. Therefore, this paper aims to analyze existing customer characteristics and implement a predictive model to activate advertisements for customers interested in such auto insurance. The goal of this study is to maximize the profits of insurance companies by devising communication strategies that can optimize business models and profits for customers. This study was conducted through the Microsoft Azure program, and an automobile insurance purchase prediction model was implemented using Health Insurance Cross-sell Prediction data. The program algorithm uses Two-Class Logistic Regression and Two-Class Boosted Decision Tree at the same time to compare two models and predict and compare the results. According to the results of this study, when the Threshold is 0.3, the AUC is 0.837, and the accuracy is 0.833, which has high accuracy. Therefore, the result was that customers with health insurance could induce a positive reaction to auto insurance purchases.

• Human Ecology Research
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• 제60권2호
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• pp.289-302
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• 2022

This study examined the effect of private educational expenditure on adolescent depression and somatic symptoms. The sample comprised 2,589 first-grade middle-school students who completed the 2018 Korea Children and Youth Panel Survey. Data were analyzed using ANOVA (the generalized linear model), multiple regression, and quantile regression analysis. The principal results were as follows. First, 15.15% of adolescents reported depression symptoms, and 15.57% reported somatic symptoms. Second, levels of depression were significantly different among classes with a different level of private educational expenditure. Third, depression level was significantly negatively associated with private educational expenditure, in that the higher the private educational expenditure, the lower the depression level. Fourth, the effect of private educational expenditure on adolescent depression was significant at the 70~90th quantile regression, suggesting that private educational expenditure was associated with a higher level of depression symptoms. The results indicate that private education was viewed as a consumption commodity rather than a complementary educational practice or investment in human capital. Private education as a commodity might induce the highly developed and costly private education market. In turn, there is an increased financial burden for education at one end of the social-economic continuum and depression caused by relative deprivation at the other end.

• Genomics & Informatics
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• 제19권1호
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

• 재활간호학회지
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• 제2권1호
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• pp.29-44
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• 1999

This study was carried out to obtain basic data required to plan and develop Rehabilitation Day Care Program for the stroke Survivors at home in Korea. The subjects comprised of 118 stroke survivors who discharged from 4 hospitals in Seoul during the past 2 years. The data were collected from August 3, 1998 to September 18, 1998, through interviews with questionnaires about general characteristics, activities of dally living, depression and service need of rehabilitation day care program at the outpatient clinics by trained nursing graduates. Data were analyzed with descriptive analysis, Pearson's correlation analysis, and Stepwise multiple linear regression analysis using SPSS/WIN program. The results obtained are as follows ; 1. The mean score of the general need of rehabilitation day care program of stroke survivors was 2.78(range 1-4). The highest need among the service categories of the rehabilitation day care program was self-care and restorative activities category, and health services referral category, recreation category, psychosocial activities category in order. The needs of each category are as follows ; 1) In the health services referral category, the need for speech therapy was highest, followed by the need for physical therapy and occupational therapy. 2) In the psychosocial activities category, the need for self-help group was highest. 3) In the self-care and restorative activities category, the need for bathing was highest, followed by bowel training, and ambulation training. 4) The need for the recreation category was 2.62. 2. Among the need for the effect related to the utilization of day care program, the need for survivors' physical and psychological well-being was highest and was followed by the need for caregiver's physical and psychological wellbeing. Pearson's correlation analysis revealed following results ; 1. The need for rehabilitation day care program service displayed a correlation with the level of education, ADL, and the level of depression, and a reverse correlation with age. 2. The need for the effect related to the utilization of rehabilitation day program displayed a correlation with the level of education, ADL, and the level of depression. The stepwise multiple linear regression analysis revealed following results : 1. For the need for rehabilitation day care program service, 28.4% of the variance was initially explained by one variable, level of depression. The level of depression plus two variables, survivors' age and ADL, explained 34.2% of the variance in the need for rehabilitation day care program service. 2. For the need for the effect related to the utilization of rehabilitation day care program, 12.4% of the variance was initially explained by one variable, level of depression. The level of depression plus one variable, level of education, explained 20.4% of the variance in the need for the effect related to the utilization of rehabilitation day care program. In conclusion, above characteristics should be considered when we are planning to develop stroke survivors' rehabilitation day care program.

• Journal of Biosystems Engineering
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• 제15권1호
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• pp.23-32
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• 1990

Geometrical characteristics of fruit including perimeter, projected area and length of minor and major axis were calculated by computer programs to be used in fruit sorting by image processing system. The results are summerized as follows. 1. A program calculating perimeter, projected area, and length of minor and major axis by edge detection and chain code was developed. 2. Geometrical characteristics of given figures were calculated to verify the program and the discrepancies from the measured values were about 5%. 3. Regression models for estimating volums of apples were developed and regression coefficients for each variety were found. 4. Abnormal apples could be recognized by comparing the ratio of minor axis to major axis and the standard value was proposed.