• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.227-238
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• 2006

Line density index(LDI) was developed to quantify a densely isothermal line rate as standard index in the ocean environment. Theoretical background on the LDI development process restricting index range 0 to 100 was described. And validation test was done for the LDI application condition that total line length is not greater than 1/10 of unit area. NOAA SST(Sea Surface Temperature) data were used for the experimental application of LDI in the South Sea of Korea. Using GIS, $0.1^{\circ}C$ isothermal lines were linearized as vector data form SST raster data, and unit area were built as polygon data. For the LDI calculation, spatial overlapping(line in polygon) was implemented. To analyze the effect of unit area size for the LDI distribution, two cases of unit area size were designed and descriptive statistics was calculated including performing normality test. The results showed no change of LDI's essential characteristics such as mean and normality except for the range of value, variance and standard deviation. Accordingly, it was found that complex structure of thermal front and even smaller scale of front width than unit area size could influence on the LDI distribution. Also, correlation analysis performed between LDI and difference of temperature(${\Delta}T^{\circ}C$), and horizontal thermal gradient(${\Delta}T^{\circ}C/km$) on the front was obtained from linear regression model. This obtained value was compared with the results from previous researches. Newly developed LDI can be used to compare the thermal front regions changing spatio-temporally in the ocean environment using absolute index value. It is considered to be significant to analyze the relationship between thermal front and marine environment or front and marine organisms in a quantitative approach described in this study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.12B
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• pp.2094-2108
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• 2000

오류를 수반하는 통신망을 통한 멀티미디어 데이터의 응용은 최근 그 수요가 급증하고 있다. 하지만 그 구현은 많은 문제점들을 야기하는데, 전송된 비디오 데이터에 발생한 오류를 처리하는 문제가 그 중 하나이다. 이는 압축된 비트열에 발생한 오류가 영상의 시-공간 방향으로 심각한 전파 현상을 수반하기 때문이다. 이러한 심각한 오류 전파를 완화하기 위해 본 논문에서는 EREC라 알려진 오류 제한 기법을 적용하고, 적용된 EREC의 오류 전파 특성을 분석하였다. 이를 통해, 압축 부호화된 하나의 기본 블록 (매크로 블록)이 복호시 오류가 생길 확률을 추정하였으며, 추정된 확률의 근사를 통해 양 끝단(전송단과 수신단)에서의 비디오 화질 열화를 예측하였다. 추정 확률의 근사는 매 기본 블록에서 발생된 비트수에 대한 그 기본 블록이 복호시 오류가 생길 확률을 간단한 1차식을 통한 선형 회귀법으로 모델링 되었으며, 따라서 간단한 방법을 통해 양 끝단의 화질 열화를 효과적으로 예측할 수 있었다. 부호화된 비트열이 전송 오류에 보다 강인하게 되도록 하기 위해, 본 논문에서 개발된 화질 열화 모델을 양자화기 선택에 적용함으로써, 새로운 최적 양자화 기법을 제시하였다. 본 논문에서 제안된 최적 양자화 기법은, 기존의 양자기 최적화 기법들과는 달리, 복호단에서의 복원 영상 화질이 주어진 비트율에서 최적이 되도록 양자화를 수행한다. H.263 비디오 압축 규격에 적용한 제안 양자화 기법의 실험 결과를 통해, 제안 기법이 매우 적은 계산상의 부하를 비용으로 객관적 화질은 물론 주관적 화질까지 크게 개선할 수 있음을 확인할 수 있었다.내었다.Lc. lacti ssp. lactis의 젖산과 초산의 생성량은 각각 0.089, 0.003과 0.189, 0.003M이었다. 따라서 corn steep liquor는 L. fermentum와 Lc. lactis ssp, lactis 의 생장을 위해 질소 또는 탄소 공급원으로서 배지에 첨가 될 수 있는 우수한 농업 부산물로 판단되었다.징하며 WLWQ에 적용되는 몇 가지 제약을 관찰하고 이를 일반적인 언어원리로 설명한다. 첫째, XP는 주어로만 해석되는데 그 이유는 XP가 목적어 혹은 부가어 등 다른 기능을 할 경우 생략 부위가 생략의 복원 가능선 원리 (the deletion-up-to recoverability principle)를 위배하기 때문이다. 둘째, WLWQ가 내용 의문문으로만 해석되는데 그 이유는 양의 공리(the maxim of quantity: Grice 1975) 때문이다. 평서문으로 해석될 경우 WP에 들어갈 부분이 XP의 자질의 부분집합에 불과하므로 명제가 아무런 정보제공을 하지 못한다. 반면 의문문 자체는 정보제공을 추구하지 않으므로 앞에서 언급한 양의 공리로부터 자유롭다. 셋째, WLWQ의 XP는 주제어 표지 ‘는/-은’을 취하나 주어표지 ‘가/-이’는 취하지 못한다(XP-는/-은 vs. XP-가/-이). 이는 IP내부 에 비공범주의 존재 여부에 따라 C의 음운형태(PF)가 시성이 정해진다는 가설로 설명하고자 했다. WLWQ에 대한 우리의 논의가 옳다면, 본 논문은 다음과 같은 이론적 함의를 기닌다. 첫째, WLWQ의 존재는 생략에 대한 두 이론 즉 LF 복사 이론과 PF 삭제 이론

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.461-470
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• 2020

This study analyzed the determinants of land compensation costs using the CALS (Continuous Acquisition & Life-Cycle Support) system to generate data for the construction (planning, design, building, management) process. For analysis, variables used in the related research on land costs were used, which included eight variables (Land Area, Individual Public Land Price, Appraisal & Assessment, Land Category, Use District 1, Terrain Elevation, Terrain Shape, and Road). Also, the variables were analyzed using the machine learning-based Xgboost algorithm. Individual Public Land Price was identified as the most important variable in determining land cost. We used a linear multiple regression analysis to verify the determinants of land compensation. For this verification, the dependent variable included was the Individual Public Land Price, and the independent variables were the numeric variable (Land Area) and factor variables (Land Category, Use District 1, Terrain Elevation, Terrain Shape, Road). This study found that the significant variables were Land Category, Use District 1, and Road.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.6
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• pp.706-714
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• 2007

This study suggested a method for prediction of residual chlorine and THMs in water distribution system by measurement of residual chlorine, THMs, and other parameters, estimation of chlorine decay coefficients and THM formation coefficients, and simulation of water qualities using pipe network analysis. Bulk decay coefficients of parallel first-order were obtained by bottle tests, and pipe wall decay coefficients of first-order were estimated through evaluation of 5 models, which showed the lowest values of 0.03 for MAE(mean absolute error) and 0.037 MAE in comparison with the observed in field. And bottle tests were conducted to model first-order reaction of THM formation by nonlinear least square regression and the resultant coefficients were compared with the observed in field. As a result, the coefficients of determination$(R^2)$ for the observed and the predicted values were 0.98 in September and 0.82 in November, and the formation of THMs was predicted by modeling.

• Journal of Nutrition and Health
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• v.52 no.6
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• pp.552-558
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• 2019

Purpose: Although vitamin D deficiency is common among Korean adolescent girls and young women, few studies have explored the potential health effects of vitamin D deficiency in this vulnerable population. This study examined the association between vitamin D deficiency and anemia in Korean adolescent girls and young women. Methods: The data from the Korea National Health and Nutrition Examination Survey 2008 ~ 2014 were used. A total of 3,643 girls and adult women aged 12 to 29 who provided all the information (including serum 25-hydroxy vitamin D, hemoglobin, and/or serum ferritin) needed for the analysis were included in the analysis. Demographic, lifestyle, and health data were obtained through survey questionnaires. Anemia and iron deficiency anemia were defined according to the World Health Organization cut-offs. Multivariable logistic regression, and restricted cubic spline regression were used in the analysis. Results: In fully adjusted logistic regression models, the vitamin D deficiency was significantly associated with higher prevalences of anemia (odds ratio (OR): 1.61, 95% confidence interval (CI): 1.04 ~ 2.49) and iron deficiency anemia (OR: 1.43, 95% CI: 1.01 ~ 2.03). In a cubic spline regression model, we observed a dose-response relationship between serum 25(OH)D concentration and anemia, and this linear relationship was also clearly observed between serum 25(OH)D concentration and iron deficiency anemia. Conclusion: Vitamin D deficiency may be associated with a higher prevalence of iron deficiency anemia and anemia in adolescent girls and young women. Alternatively, vitamin D deficiency may be a concurrent event for patients with anemia, which we cannot distinguish in this cross-sectional study. Further studies are needed to verify the causality in this population of low vitamin D levels.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.209-220
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• 2002

We carried out studies on SAR image intensity and interferometric phase over oyster sea farms. Strong backscattering was observed in amplitude images, and that was considered as a radar signal double bouncing from horizontal bars. These sea farming structures are not visible in satellite optical images except IKONOS image, so that it demonstrates the value of radar remote sensing as an effective tool in support of sea farm detection. The intensity of the image is sensitive to system parameters including wavelength, polarization, and look direction, but does not correlate to tide height. We found that the strongest backscattering can be obtained by L-band HH-polarization with a look direction perpendicular to the horizontal bar. We also succeeded in generating 21 coherent JERS-1 SAR interferometric pairs over the oyster farms. The general trend of the fringe rate of the interferometric phases appeared to be governed by altitude of ambiguity. The general trend was modeled by an inverse function and removed to have a residual phase. The residual phase showed a linear relation with the tide height. The results demonstrate for the first time that SAR can possibly be used to estimate sea level. However, the r.m.s. error of a regression line is 11.7 cm, and that is so far too large to make reliable assessments of sea level in practical applications. Further studies is required to improve the accuracy specifically using multi-polarization SAR data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.438-446
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• 2019

This study examined the effects of non - personality behavior of supervisors on the job exhaustion and organizational effectiveness of nurses. A survey in the form of a questionnaire was completed by 250 nurses working at three general hospitals located in Seoul and Gyeonggi from September 20 to October 31, 2014. The collected data were analyzed by frequency analysis, factor analysis, correlation, and linear regression analysis using the SPSS program. The results of the analysis were as follows. First, the effects of the non-personality behavior of supervisors on the job exhaustion of nurses were statistically significant. Second, the effects of non-personality behavior of supervisors on the organizational effectiveness of nurses were statistically significant in job satisfaction, organizational commitment, and organizational citizenship behavior. Third, the effects of job exhaustion on organizational effectiveness of nurses was statistically significant for job satisfaction, job exhaustion, and organizational citizenship behavior. Because the non-personality behavior of a supervisor can have a negative effect on the exhaustion of a nurse's job and the organizational effectiveness, there should be a wide range of human resources and effective task allocations in a hospital to reduce job burnout and increase job satisfaction. In addition, it is necessary for the boss to develop desirable leadership education, appropriate modeling, and reduce their negative influence in the workplace.

• Journal of Industrial Convergence
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• v.21 no.6
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• pp.61-71
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• 2023

The objective of this research is to examine the mediating roles of nursing professional values and occupational stress in the relationship between self-leadership and patient-centered nursing among nurses employed at COVID-19 designated hospitals. This study were 160 nurses at a COVID-19 designated hospitals, and the data were collected from January 10 to February 30, 2022. The collected data were analyzed by independent t-test, one-way ANOVA, correlation analysis, multiple linear regression analysis, and SPSS PROCESS Macro model No 4 bootstrapping method. The average score for self-leadership was 61.3±8.55, nursing professional values was 95.5±11.66, occupational stress was 51.3±4.76, and patient-centered nursing was 59.3±7.63. The mediating effect of nursing professional values and occupational stress was confirmed in the influence relationship between self-leadership and patient-centered nursing of nurses at COVID-19 designated hospitals. This result suggests that the content related to improve nursing professional values and reduce occupational stress should be considered when applying the patient-centered nursing enhancement program.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.61 no.1
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• pp.70-77
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• 2016

The object of this study was to evaluate the effects of climatic elements on potato yield and create a model for estimating the potato yield. We used 35 yield data of Sumi variety produced in mulching cultivation from 17 regions over 11 years. According to the results, some climatic elements showed significant level of correlation coefficient with marketable yield of potato. Totally 22 items of climatic elements appeared to be significant. Especially precipitation for 20 days after planting (Prec_1 & 2), relative humidity during 11~20 days after planting (RH_2), precipitation for 20 days before harvest (Prec_9 & 10), sunshine hours during 50~41 days before harvest (SH_6) and 20 days before harvest (SH_9 & 10), and days of rain during 10 days before harvest (DR_10) were highly significant in quadratic regression analysis. 22 items of predicted yield ($Y_i=aX_i{^2}+bX_i+c$) were induced from the 22 items of climatic elements (step 1). The correlations between the predicted yields and marketable yield were stepwised using SPSS, statistical program, and we selected a model (step 2), in which 4 items of independent variables ($Y_i$) were used. Subsequently the $Y_i$ were replaced with the equation in step 1, $aX_i{^2}+bX_i+c$. Finally we derived the model to predict the marketable yield of potato as below. $$Y=-336{\times}DR_-10^2+854{\times}DR_-10-0.422{\times}Prec_-9^2+43.3{\times}Prec_-9\\-0.0414{\times}RH_-2^2+46.2{\times}RH_-2-0.0102{\times}Prec_-2^2-7.00{\times}Prec_-2-10039$$.