• 한국초지조사료학회지
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• 제36권3호
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• pp.223-236
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• 2016

The objective of this study was to construct Italian ryegrass (IRG) dry matter yield (DMY) estimation models in South Korea based on climatic data by locations. Obviously, the climatic environment of Jeju Island has great differences with Korean Peninsula. Meanwhile, many data points were from Jeju Island in the prepared data set. Statistically significant differences in both DMY values and climatic variables were observed between south areas of Korean Peninsula and Jeju Island. Therefore, the estimation models were constructed separately for south areas of Korean Peninsula and Jeju Island separately. For south areas of Korean Peninsula, a data set with a sample size of 933 during 26 years was used. Four optimal climatic variables were selected through a stepwise approach of multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the selected four climatic variables and cultivated locations as dummy variables was constructed. The model could explain 37.7% of the variations in DMY of IRG in south areas of Korean Peninsula. For Jeju Island, a data set containing 130 data points during 17 years were used in the modeling construction via the stepwise approach of multiple regression analysis. The model constructed in this research could explain 51.0% of the variations in DMY of IRG. For the two models, homoscedasticity and the assumption that the mean of the residuals were equal to zero were satisfied. Meanwhile, the fitness of both models was good based on most scatters of predicted DMY values fell within the 95% confidence interval.

• 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.

• Spatial Information Research
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• 제18권5호
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• pp.107-117
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• 2010

본 연구는 최근 다수 도시개발사업들이 활발히 진행되고 있는 화성시 동부권을 사례대상지로하여 행정구역 단위 인구데이터를 격자형 인구분포자료로 변환한 후 인구유인을 유발할 것으로 예상되는 주요 도시계획관련 공간변수들을 GIS로 측정 대입하여 제네틱 알고리즘기법과 회귀분석기법 두 가지 방법으로 일종의 도시인구분포모형을 구축하였다. 두 가지 모형의 분석결과를 통해 도시환경 해석에 있어서의 두 기법의 성능상 특장점을 비교해 보았으며, 분석결과 GA기법은 변수 설명력에 관한 변별력에 있어 일반회귀분석보다 우월한 특징이 있음을 알 수 있었고 따라서 회귀분석과 병행할 경우 매우 직관적이며 보완적인 도시분석기법이 될 수 있음을 확인할 수 있었다.

• 디지털콘텐츠학회 논문지
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• 제19권1호
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• pp.141-147
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• 2018

본 연구는 기업에서 채용 전형 시 진행되는 인성시험 결과 데이터를 기반으로, 입사 3년 미만의 조기 퇴사자를 분석하였다. 예측 모형은 적합성 및 향후 활용성을 고려하여 제조(manufacture)직군과 R&D직군 2개 그룹으로 구분하여 분석하였으며, 독립변수 선택은 전진(stepwise)선택법에 따라 직군별로 유의미한 독립변수를 선택하였다. 예측 모형은 지도학습(supervised learning) 방법 중 로지스틱 회귀분석 알고리즘을 선택하였으며, 과잉적합(overfitting) 또는 과소적합(underfitting)을 방지하고자 교차 검증(cross validation)을 통해 예측 모형을 훈련시켰다. 혼동행렬(confusion matrix)을 통해 2개 그룹의 정확도(accuracy)를 확인하였으며, 조기 퇴직에 가장 영향을 많이 미치는 요인으로 제조직군에서는 '몰입', R&D직군에서는 '반사회성' 항목으로 확인되었다. 기존 퇴직 관련 연구는 설문 방식으로 데이터를 수집하고, 퇴직과 관련성이 높은 요인을 확인하는데 집중하였다면, 본 연구는 채용 전형 시 진행되는 인성 결과 분석을 통해 향후에도 지속 가능한 조기 퇴직 예측 모형을 제시했다는 면에서 의의를 갖는다.

• Journal of Biosystems Engineering
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• 제33권1호
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• pp.30-37
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• 2008

Dynamic excitation and response analysis is an acceptable method to determine some of physical properties of agricultural product for quality evaluation. There is a difference in the internal viscoelasticity between sound and defective fruits due to the difference of geometric structures, thereby showing different vibration characteristics. This study was carried out to develop a portable piezoelectric film-based glove sensor system that can separate internally damaged watermelons from sound ones using an acoustic impulse response technique. Two piezoelectric sensors based on polyvinylidene fluoride (PVDF) films to measure an impact force and vibration response were separately mounted on each glove. Various signal parameters including number of peaks, energy ratio, standard deviation of peak to peak distance, zero-crossing rate, and integral value of peaks were examined to develop a regression-estimated model. When using SMLR (Stepwise Multiple Linear Regression) analysis in SAS, three parameters, i.e., zeros value, number of peaks, and standard deviation of peaks were selected as usable factors with a coefficient of determination ($r^2$) of 0.92 and a standard error of calibration (SEC) of 0.15. In the validation tests using twenty watermelon samples (sound 9, defective 11), the developed model provided good capability showing a classification accuracy of 95%.

• 대한간호학회지
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• 제34권7호
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• pp.1288-1297
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• 2004

Purpose: The purpose of this study was to investigate the factors influencing health promoting lifestyle in the elderly. Method: The subject of this study was 305 elderly person over the age of 60, living in rural and urban, Korea. For the analysis of collected data, descriptive statistics, t-test, analysis of variance and stepwise multiple regression were used for statistical analysis with SPSS statistical program. Results: The average item score for the health promoting lifestyle was 2.46, The higher score on the subscale was nutrition(2.65). The lowest score on the subscale were physical activity(2,36) and stress management(2,36). General characteristics showing statistically significant difference in health promoting lifestyle were age, residential district, live together spouse, education, religion and pocket money in the elderly. Stepwise multiple regression analysis revealed that the most powerful predictor of health promoting lifestyle in the elderly was prior related behavior(R2=.554). A combination of prior related behavior, perceived benefits of action, perceived self-efficacy, commitment to a plan of action, and interpersonal influences accounted for $64.3\%$ of the variance in health promoting lifestyle in the elderly, Conclusion: The factors influencing on health promoting lifestyle for elderly were prior related behavior, perceived benefits of action, perceived self-efficacy, commitment to a plan of action, and interpersonal influences.

• 가정과삶의질연구
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• 제5권2호
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• pp.11-27
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• 1987

This study examined job satisfaction levels between employed single women and employed married women. The specific objectives of this study were; (1) to investigate differences in the level of job satisfaction between employed single women and employed married women; (2)to investigate the factors which influence the level of job satisfaction; (3)to investigate the relationship between job satisfaction and life satisfaction. the data used in this study included 441 working women from 290 (65.8 %) single women and 151 (34.2%) married women. Statistical analyses were conducted using frequencies, percentiles, mean , t-test , ANOVA, pearson's correlation and a stepwise multiple regression. The major findings were ; (1) at the P<.005 level, there was a significant difference in the job Satisfaction Index (JSI) between employed single and married women by using the t-test ; (2) Occupation, type of organization , job experiences, travel time from home to work. unionization, age, and health status were significantly related to the JSI by using the one-way ANOVA; (3) Thee was an interaction effect between income and marital status on the JSI, and between education and marital status on the JSI; (4) Using a stepwise multiple regression method, the order of variables as they were entered in the model were different between employed single and married women; (5) There was a positive relationship between the JSI and Life Satisfaction Index(r=.41)

• Journal of Hospice and Palliative Care
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• 제23권3호
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• pp.139-150
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• 2020

Purpose: The purpose of this study was to investigate the levels of end-of-life care competency; knowledge, attitudes, and experiences regarding advance directives; perceptions of good death; and end-of-life care obstacles and supportive behaviors among tertiary care nurses. Methods: The participants were 150 nurses at a tertiary hospital in Jinju, Korea. The data collected using a questionnaire were analyzed using descriptive statistics, the t-test, analysis of variance, Pearson correlation coefficients, and stepwise multiple regression in SPSS for Windows version 24.0. Results: The mean (±SD) score of end-of-life care competency was 3.63 (±0.53) on a 5-point scale. A significant difference in end-of-life care competency was found according to whether nurses had experienced the death of a family member or acquaintance (P=0.029). According to stepwise multiple regression analysis, the factors affecting end-of-life care competency were the frequency of end-of-life care supportive behaviors (β=0.38, P<0.001), experience with advance directives (β=0.29, P<0.001), and marriage (β=0.15, P=0.039). This model had an explanatory power of 27.9% (F=18.87, P<0.001). Conclusion: In order to improve nurses' end-of-life care competency, it is important to strengthen end-of-life care supportive behaviors by exposing nurses to those behaviors and providing frequent experience with advance directives.

• 한국생활과학회지
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• 제16권6호
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• pp.1131-1140
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• 2007

The purpose of this study is to investigate the effect of parenting behavior and parent-child communication on internet use among school-aged children. The subjects were 215 children whose grade are 3rd and 5th selected from an elementary school in Incheon. The statistics used for this data were t-test, one-way ANOVA(Duncan's test), and stepwise regression. The findings from the present study suggested that academic achievement and birth order turned out to be significant variables on children's internet use, except for sex and grade. Results of the stepwise regression analyses that the etiologic model of this study was more proper, and parenting behavior is more effective variable than parent-child communication in predicting internet use among school-aged children. Implications based on this study are as follows; In order to decrease the degree of school-aged children's internet use, parents should do less permissive parenting behavior and problematic communication with their children.

• 수산경영론집
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• 제44권3호
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• pp.77-84
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• 2013

While some steps in laver aquaculture production can be controlled artificially to a certain extent, the culturing process is largely affected by natural factors, such as the characteristics of seawater, climatic and oceanographic conditions, etc. This study aims to find a direct relationship between climatic and oceanographic factors (water temperature, air temperature, salinity, rainfall, sunshine duration and wind speed) and laver aquaculture production in Wando region, the biggest aquaculture production area of laver, located in the southwest coast of Korea using a multiple regression analysis. Despite the small sample size of a dependent variable, the goodness of model fit appeared acceptable. In addition, the R-squared value was 0.951, which means that the variables were very explanatory. Model results indicated that duration of sunshine, temperature, and rainfall during the farming period from the end of September to the end of April would be important factors affecting significantly to the laver aquaculture production.