• 한국융합학회논문지
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• 제9권12호
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• pp.355-363
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• 2018

2017년 한국을 비롯한 세계 각국에서 살충제 오염 달걀이 발견되어 큰 이슈가 되었다. 본 연구는 살충제 오염 달걀 사태의 맥락에서 건강 관련 연구에서 자주 인용되는 건강신념모형의 두 가지 변인인 지각한 민감성과 심각성, 정부에 대한 지각인 정부에 대한 신뢰성과 정부 출처 정보에 대한 평가, 및 관련 지식에 대한 개인의 확신을 의미하는 주관적 지식이 예방행동의도에 영향을 미치는지를 알아보았다. 단계적 회귀분석 결과 최종적으로 지각한 심각성(${\beta}=.262$, t=3.531, p<0.001), 정부에 대한 신뢰성(${\beta}=.252$, t=3.281, p<0.001), 정부 출처 정보에 대한 평가(${\beta}=.226$, t=2.936, p<0.01)가 예방적 행동의도를 예측하는 것으로 나타났다. 이러한 결과는 향후 유사한 사태가 발생할 때 정부가 신뢰성, 정확성, 일관성의 견지에서 정책을 시행해야 함을 시사한다.

• PNF and Movement
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• 제18권3호
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• pp.305-313
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• 2020

Purpose: The aim of this study was to investigate the relationship between a functional evaluation model and the Fugl-Meyer assessment (FMA) scale in evaluating the upper extremities of stroke patients Methods: Thirty-eight stroke patients were evaluated using the FMA and performed reaching and grasping motions using a three-dimensional motion analysis (Qquas 1 series, Qualisys AB, Sweden). The participants sat on a chair with a backrest. The position of the cup was located at a distance of 80% to the front arm length. The markers were attached to the sternum, acromion, elbow lateral epicondyle, ulnar styloid process, three metacarpal heads, and the distal phalanges of the thumb and index finger. The variables of the correlation between the functional evaluation model and the FMA scale were analyzed. Multiple regression (stepwise) was used to investigate the effect of the kinematic variables. Results: A significant negative correlation was found between the movement time (p < 0.05), movement unit (p < 0.05), and trunk displacement values (p < 0.05) in the FMA total scores, while a positive correlation was found between the peak velocity (p < 0.05) and maximum grip aperture values (p < 0.05). As a result of the multiple regression analysis, the most significant factor was the movement unit, followed by the general movement assessment and trunk displacement. The explained FMA total score value was 62%. Conclusion: This study presents a new functional evaluation model for assessing the reaching and grasping ability of stroke patients. The factors of the proposed functional evaluation model showed significant correlations with the FMA scale scores and confirmed that the new functional evaluation model explained the FMA by 67%. This suggests a new functional evaluation model for reaching and grasping stroke patients.

• Journal of Biosystems Engineering
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• 제43권2호
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• 한국학교수학회논문집
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• 제10권1호
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• pp.113-127
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• 2007

본 고는 5년 간의 고등학교 연합학력평가자료 분석을 통하여 수리영역의 난이도 예측요인을 분석하였다. 난이도 예측을 위한 통계적 모형을 산출하기 위하여 먼저 문항분석을 통해 수리영역의 난이도 예측에 영향을 미칠 것으로 판단되는 주요 변인들을 '내용영역', '행동영역', '문항의 형식' 등의 범주에 따라 추출하였다. 추출된 독립 변인들에 대하여 단계선택방법을 사용한 다중회귀분석을 실시함으로써 정답률 예측에 유의미한 변수들을 선택하였으며, 교차 타당도를 통하여 최종적으로 선택된 예측 모형이 독립적으로 수집된 자료에 대하여 어느 정도의 설명력을 보이는지 검증하였다. 본 연구는 대학수능시험 출제나 현장에서 수리영역의 평가문항을 개발하는데 있어서 사전 정답률을 예측하는데 있어 고려해야 할 요인을 제시함으로써 보다 정확한 정답률 예측에 필요한 기초정보를 제공하는데 그 의의를 두고 있다.

• 성인간호학회지
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• 제16권4호
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• pp.575-584
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• 2004

Purpose: To describe the performance in the health-promoting lifestyle and to identify the major factors affecting the health-promoting relationships between self care behaviors and health promoting lifestyle profile in patients with pulmonary tuberculosis. Method: A convenience sample for this study was 172 pulmonary tuberculosis patients who have taken TB medications in urban city. The HPLP-II was selected to measure the concept of health-promoting lifestyle because of the number of research studies conducted using both the original HPLP and the revised HPLP-II. The statistical methods used in this study were t-test, ANOVA, Pearson correlations, and multiple regression. Result: The differences of the HPLP-II were found to have a significance of age, marital status, education level, and health service center. The level of self care behaviors was related positively to the level of health promoting lifestyle and their subcategories. Based on stepwise multiple regression analysis, the model that predicted factors included self care behaviors, age, health service center and education. Conclusion: After decades of decreasing rates, TB has reemerged as a serious national problem in Korea. The careful clinical management and more national concern of TB may help to improve the outcomes of many patients. The findings of this study suggest that TB patients who are more fulfilled in health-promoting lifestyles and self-care behaviors may be able to make better decisions regarding positive health-promoting behaviors.

• 한국간호교육학회지
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• 제24권4호
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• pp.367-375
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• 2018

Purpose: This purpose of this study was to examine the effects of self-efficacy and activities of daily living on the level of depression among elderly nursing home residents. Methods: A descriptive study was conducted using a self-reported questionnaires completed by 163 elderly. Data were analyzed using t-test, one-way ANOVA, Scheff? test, Pearson correlation coefficients, and multiple regression analysis using SPSS 20.0. Results: The mean score for depression was 9.24, for self-efficacy 3.19, and for activities of daily living 1.85. Stepwise multiple regression analyses were used to examine the influences of research variables. Activities of daily living and self-efficacy were significant predictors of depression. The model explained 24.0% of the variables. Conclusion: As a result of this study, the activities of daily living and self-efficacy were defined as an important influential on depression. Therefore, the development nursing intervention programs is needed to reduce depression levels in the elderly to enhance daily living activities and self-efficacy.

• Near Infrared Analysis
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• 제2권1호
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• pp.55-58
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• 2001

The object of this work was to investigate the influence of growing district and harvest year on calibration for sweetness (Brix) determination of Fuji apple fruit using near infrared (NIR) reflectance spectroscopy, and to develop the robust calibration across these variation. The calibration models was based on wavelength range of 1100∼2500 nm using a stepwise multiple linear regression. A calibration model by sample set of one growing district was not transferable to other growing districts. The combined calibration (data of three growing districts) predicted reasonable well against a population set drawn from all growing districts (SEP=0.69, Bias=0.075). A calibration model by sample set of one harvest year was not also transferable to other harvest years. The combined calibration (data of three harvest years) predicted well against a population set drawn from all harvest years (SEP=0.53, Bias=0.004).

• Bulletin of the Korean Chemical Society
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• 제29권10호
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• pp.2009-2016
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• 2008

The relationship between thermal decomposition temperature and structure of a new data set of eighty monomers of different polymers were studied by multiple linear regression (MLR). The stepwise method was used in order to variable selection. The best descriptors were selected from over 1400 descriptors including; topological, geometrical, electronic and hybrid descriptors. The effect of number of descriptors on the correlation coefficient (R) and F-ratio were considered. Two models were suggested, one model having four descriptors ($R^2$ = 0.894, $Q^2_{cv}$ = 0.900, F = 172.1) and other model involving 13 descriptors ($R^2$ = 0.956, $Q^2_{cv}$ = 0.956, F = 125.4).

• Asian Pacific Journal of Cancer Prevention
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• 제13권12호
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• pp.6181-6185
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• 2012

Background: The aim of the study was to evaluate the available breast nomograms (MSKCC, Stanford, Tenon) to predict non-sentinel lymph node metastasis (NSLNM) and to determine variables for NSLNM in SLN positive breast cancer patients in our population. Materials and Methods: We retrospectively reviewed 170 patients who underwent completion axillary lymph node dissection between Jul 2008 and Aug 2010 in our hospital. We validated three nomograms (MSKCC, Stanford, Tenon). The likelihood of having positive NSLNM based on various factors was evaluated by use of univariate analysis. Stepwise multivariate analysis was applied to estimate a predictive model for NSLNM. Four factors were found to contribute significantly to the logistic regression model, allowing design of a new formula to predict non-sentinel lymph node metastasis. The AUCs of the ROCs were used to describe the performance of the diagnostic value of MSKCC, Stanford, Tenon nomograms and our new nomogram. Results: After stepwise multiple logistic regression analysis, multifocality, proportion of positive SLN to total SLN, LVI, SLN extracapsular extention were found to be statistically significant. AUC results were MSKCC: 0.713/Tenon: 0.671/Stanford: 0.534/DEU: 0.814. Conclusions: The MSKCC nomogram proved to be a good discriminator of NSLN metastasis in SLN positive BC patients for our population. Stanford and Tenon nomograms were not as predictive of NSLN metastasis. Our newly created formula was the best prediction tool for discriminate of NSLN metastasis in SLN positive BC patients for our population. We recommend that nomograms be validated before use in specific populations, and more than one validated nomogram may be used together while consulting patients.

• Advances in environmental research
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• 제7권2호
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• pp.109-120
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• 2018

In the present study research air quality analyses for $PM_{10}$, were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The averages concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of $PM_{10}$ occurs generally in the night while the least concentration was found at the afternoon. Monthly concentrations of $PM_{10}$ showed highest value in August, while least value was found in January. The seasonal concentrations showed the least amounts in autumn while the highest amounts in summer. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions SPSS software. RMSE test showed that among different prediction models, stepwise model is the best option.