• 지역사회간호학회지
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• 제30권2호
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• pp.174-182
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• 2019

Purpose: The purpose of this study is to find out how much influence nursing students' environmental consciousness and knowledge of medical waste have on their attitudes toward medical waste. Methods: The subjects were 211 nursing students recruited from 2 universities. Data were collected with a structured self-report questionnaire comprising measures of environmental consciousness, and knowledge of and attitude toward medical waste. Data analysis was conducted with the SPSS/WIN 25.0 program. Results: A total of 211 copies of the questionnaire were used for the final analysis, except for 9 untrusted responses out of 220 that included missing values. Those subjects' environmental consciousness who received environmental education in middle and high schools was higher (t=3.15, p=.002). The higher their grades, the better their knowledge of medical waste (F=3.40, p=.035). Those subjects' knowledge of medical waste who received medical waste education was relatively high (t=3.14, p=.002). Those subjects with clinical practice experience had more sensitive attitudes toward medical waste (t=2.06, p=.041). Those subjects' attitudes toward Medical waste who received medical waste education at the universities were relatively high (t=2.04, p=.043). The subjects' environmental consciousness was positively correlated with their attitudes toward medical waste (r=.44, p<.001). The most influential factor in their attitudes toward medical waste is their environmental attitudes and medical waste education. Conclusion: The higher the nursing students' environmental consciousness, the higher their attitudes toward medical waste. It is necessary to provide environment and medical waste education for nursing students in order to strengthen their environmental consciousness and attitude toward medical waste.

• 한국콘텐츠학회논문지
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• 제21권2호
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• pp.343-350
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• 2021

본 논문에서는 학업중단 청소년의 우울, 자아존중감, 부모애착, 또래애착 간의 관계를 규명하고, 우울과 자아존중감에 대한 부모애착, 또래애착의 매개효과를 검증하는 데 목적이 있다. 본 연구에서는 학업중단 청소년 패널조사 5차년도(2017) 데이터를 활용하여 결측치를 제외한 학업중단 청소년 315명의 자료를 최종 분석하였다. 자료는 SPSS WIN v21.0을 활용하여 기술통계, 상관관계 분석, 매개 회귀분석을 실시하였다. 본 연구의 주요결과는 다음과 같다. 학업중단 청소년의 우울과 자아존중감 간의 관계에서 부모애착, 또래애착은 매개효과가 있는 것으로 나타났다. 즉, 부모애착, 또래애착은 우울과 자아존중감에 대해서 정적으로 매개됨이 확인되었다. 본 연구결과에 근거하여 부모애착, 또래애착을 향상시켜 자아존중감을 높일 수 있는 실천 및 정책적 제언을 제시하였다.

• 융합정보논문지
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• 제11권6호
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• pp.49-54
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• 2021

최근 스마트 헬스케어 기술의 발전에 따라 일상적인 질환에 대한 관심이 증가하고 있다. 이에 따라 헬스케어 데이터를 통해 예측 모델로 질병을 분석하거나 예측하는 연구들이 증가하고 있다. 그러나 헬스케어 데이터에는 양성 데이터와 음성 데이터의 불균형이 존재한다. 이는 특정 질환을 가진 환자에 비하여 상대적으로 환자가 아닌 사람이 많아 데이터 수집에 어려움이 있어 발생하는 현상이다. 데이터 불균형은 질병 예측 및 탐지 시 진행하는 모델의 성능에 영향을 끼치기 때문에 이를 제거할 필요가 있다. 따라서 본 연구에서는 오버샘플링과 결측값 대치를 통해서 데이터 불균형을 해소한다. AutoML을 기반으로 여러 모델의 성능을 파악하고 모델 중 상위 3개의 모델을 앙상블한다.

• 한국빅데이터학회지
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• 제5권2호
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• pp.69-76
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• 2020

이 연구는 2019년도 정부(과학기술정보통신부)의 재원으로 정보통신기술진흥센터의 지원을 받아 수행된 연구이다. 고병원성조류인플루엔자(Highly Pathogenic Avian Influenza, HPAI)는 병원성이 높은 조류인플루엔자 바이러스 감염에 의하여 발생하는 조류의 급성 전염병으로 닭, 오리 등 가금류에서 피해가 심각하게 나타난다. 고병원성 조류인플루엔자(HPAI)는 연중으로 발생하기보다는 겨울철에 집중하여 발생되는 양상을 보이며, 특정 기간에는 아예 발생하지 않는 경우가 있다. 이와 같은 HPAI의 특성으로 인해 충분한 양의 실제 데이터가 축적되지 못하는 문제점이 있다. 본 논문 연구에서는 GAN 네트워크를 활용하여 결측치를 포함하고 있는 실제와 유사한 데이터를 생성하였으며 해당 과정을 소개한다. 본 연구 결과는 HPAI가 발생하지 않은 특정 시기에 대하여 실제와 유사한 시뮬레이션 데이터를 생성하여 위험도를 측정하는데 이용될 수 있다.

• 한국콘텐츠학회논문지
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• 제21권3호
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• pp.676-684
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• 2021

본 연구는 청소년의 우울과 인터넷과의존, 부모양육방식 간의 관계를 규명하고, 청소년 우울과 인터넷과의 존 간의 작용하는 부모양육방식의 매개효과를 검증하는 데 목적이 있다. 본 연구에서는 13차 한국복지패널(KWPS)데이터를 활용하여 청소년 375명의 자료를 분석하였다. 자료는 SPSS WIN v21.0을 활용하여 기술통계, 상관관계분석, 매개 회귀분석을 실시하였다. 본 연구의 주요결과는 다음과 같다. 부모양육태도 중 부모참여는 우울과 인터넷과의존에서 부적인 매개효과를 가졌고, 부모양육태도 중 지도감독의 경우는 매개효과가 없는 것으로 나타났다. 부모양육태도 중 아동학대는 우울과 인터넷과의존에서 정적인 매개효과를 가지는 것으로 나타났다. 본 연구결과에 근거하여 부모참여를 향상시키고 아동학대를 줄일 수 있는 실천 및 정책적 제언을 제시하였다.

• 한국학교보건학회지
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• 제33권3호
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• pp.203-212
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• 2020

Purpose: The purpose of this study was to investigate the relationship between relative handgrip strength (HGS/BMI) and obesity (BMI above 95th percentile) in adolescents. Methods: The subjects of the study were 637 out of 701 adolescents aged 10~18 who participated in the 2018 National Health and Nutrition Survey (KNHANES), excluding those with missing values in body mass index (BMI) and handgrip strength (HGS). The relative handgrip strength (HGS/BMI) value was divided by quartile and composite sample logistic regression analysis was performed to see its relationship with obesity (BMI above 95th percentile). The collected data were analyzed using SPSS 18.0. Results: As a result of analyzing HGS according to gender-specific quartiles, age, height, and weight of male adolescents increased significantly as HGS/BMI increased (p trend<.001). In addition, as HGS/BMI increased, total cholesterol, triglycerides, and HDL cholesterol decreased significantly (p trend<.001). In the case of female adolescents, age and height increased significantly as HGS/BMI increased (p trend<.001). HGS/BMI was lower in the obese group (p=.023), while total cholesterol was higher in the obese group(BMI above 95th percentile) than in the non-obese group. As a result of the composite sample logistic regression analysis, the odds ratio (OR) decreased significantly as the quartile increased in both male and female adolescents. Conclusion: According to these results, a follow-up study is needed to confirm the factors affecting muscle strength of adolescents. In addition, this study intends to be used as basic data to conduct further research and to develop programs that can improve muscle strength and reduce obesity in adolescents.

• 한국콘텐츠학회논문지
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• 제21권2호
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• pp.699-706
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• 2021

본 연구는 만성질환 독거노인의 우울, 음주, 사회적 관계만족도 간의 관계를 규명하고, 우울과 음주에 대한 사회적 관계만족도의 조절효과를 검증하는 데 목적이 있다. 이를 위해 13차 한국복지패널(KWPS) 데이터를 활용하여 결측치를 제외한 만성질환 독거노인 217명의 자료를 최종 분석하였다. 자료는 SPSS WIN v21.0을 활용였다. 본 연구를 위해 기술통계, 상관관계분석, 위계적 회귀분석을 실시하였다. 본 연구의 주요 결과는 다음과 같다. 만성질환 독거노인의 우울과 음주 사이에서 사회적 관계만족도 중 가족관계만족도는 음주를 줄이는 조절효과가 있었으나, 우울과 음주에 대한 사회적 관계만족도 중 사회친분관계만족도는 조절효과가 없는 것으로 나타났다. 본 연구결과에 근거하여 사회적 관계만족도 중 특히 가족관계만족도를 향상시키고 음주를 낮출 수 있는 실천 및 정책적 제언을 제시하였다.

• 한국치위생학회지
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• 제21권1호
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• pp.41-51
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• 2021

Objectives: This study analyzes the demands of dental hygiene college students for English courses and proposes ways to improve English courses for college students majoring in dental hygiene that would take advantage of English for specific purposes (ESP) in the future. Methods: Using a structured questionnaire, four universities by region with departments of dental hygiene were selected at random, and out of a total of 260 college students majoring in dental hygiene, data of 258 students, excluding data with missing values, were considered for investigating the needs of English curriculum development using the SPSS program. Results: Total 82.1% of the students expected English programs, and they said that English was important, The proposal for English curriculum development indicated that although the number of English programs was sufficient, diversification of English programs or changes in methods of managing classes were required. As for the need for English programs (66.4%), they required more ESP, such as practical English for dental or dental terminology, which can be used clinically and more than English for general purposes (EGP). Conclusions: Students in dental hygiene showed a higher demand for more professional ESP that can use clinically as dental hygienists in the future. It is necessary to consider the reorganization of the curriculum or changes in the method of managing English classes by reflecting one demands of dental hygiene students.

• 대한원격탐사학회지
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• 제37권4호
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• pp.777-788
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• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

• 산업경영시스템학회지
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• 제44권4호
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.