• 한국환경과학회지
• /
• 제27권7호
• /
• pp.509-518
• /
• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• 응용통계연구
• /
• 제6권2호
• /
• pp.421-433
• /
• 1993

회귀분석에서 몇 개의 관측치가 모형선택과정이나 최소제곱방법에의한 모형의 적합에서 지 대한 영향을 끼칠 수 있다. 그러나 그러한 관측치가 회귀분석의 모든 면에 같은 정도의 영 향을 끼치는 것은 아니다. 본 논문에서는 개개의 관측치가 적합성의 총체적 측도에 미치는 영향을 측정할 수 있는 영향측도를 제시하였다. 이 측도는 자료를 모형에 적합시켜 구해진 잔차와 적합치 사이에 만족되는 비상관성의 성질을 이용하여 구해진 것이다. 마지막으로, 본 논문에서 소개된 통계량들과 가장 많이 사용되고 있는 영향측도들을 실제자료의 분석을 통 하여 그 성질과 효율성을 비교하였다.

• Communications for Statistical Applications and Methods
• /
• 제27권6호
• /
• pp.701-714
• /
• 2020

Quantitative high throughput screening (qHTS) assays are used to assess toxicity for many chemicals in a short period by collectively analyzing them at several concentrations. Data are routinely analyzed using nonlinear regression models; however, we propose a new method to analyze qHTS data using a nonlinear mixed effects model. qHTS data are generated by repeating the same experiment several times for each chemical; therefor, they can be viewed as if they are repeated measures data and hence analyzed using a nonlinear mixed effects model which accounts for both intra- and inter-individual variabilities. Furthermore, we apply a one-step approach incorporating robust estimation methods to estimate fixed effect parameters and the variance-covariance structure since outliers or influential observations are not uncommon in qHTS data. The toxicity of chemicals from a qHTS assay is classified based on the significance of a parameter related to the efficacy of the chemicals using the proposed method. We evaluate the performance of the proposed method in terms of power and false discovery rate using simulation studies comparing with one existing method. The proposed method is illustrated using a dataset obtained from the National Toxicology Program.

• 지구물리와물리탐사
• /
• 제9권1호
• /
• pp.73-85
• /
• 2006

상시진동의 수직 성분에 대한 배열 관측은 상시진동이 대부분 레일리파의 기본 모드로 이루어졌다는 가정하에 지하 층서구조를 추정하기 위해 자주 수행된다. 자료획득, 처리 및 분석의 유용한 도구로서 공간 자기상관(SPAC) 방법이 많이 사용되는데 이는 실제로 M개의 원형 수진기 배열과 중앙의 하나 측점으로 이루어진다 (M 측점 원형 배열). 이 논문에서는 분석 효율 및 현장 노력의 관점에서 효율적인 자료획득을 위한 원형 배열에 필요한 측점의 최소 수에 대해 연구하였다. 이 연구에서는 먼저 M 무한대의 원형 배열을 위한 SPAC 계수들이 단지 Bessel 함수 J0(rk)(r은 반지름, k는 파수)로서 표현되는 SPAC 알고리듬의 이론적 배경을 재정리하였다. 두번째로 M 측점 원형 배열에 대해 상시진동 에너지장과 무관한 오차항을 포함하는 SPAC 계수들을 배열을 가로지르는 파의 방향에 한해 해석적으로 유도해 내고 수치적으로 이들 오차항들에 대해서 평가하였다. 주요 평가 결과들은: 1) 만약 SPAC 계수들이, 계수가 첫번째 최소값을 갖는 주파수까지 이용되면 다른 4-, 5-, 9-측점 배열들에 비교했을 때 3-측점 원형배열이 상시진동의 관측에 효율적이고 유리하다. 2) 나이퀴스트 파수가 유효한 SPAC 계수가 평가될 수 있는 주파수의 상한선을 결정하는데 가장 영향을 끼치는 요소이다.

• 대한토목학회논문집
• /
• 제35권1호
• /
• pp.9-17
• /
• 2015

강-콘크리트 슬립실험으로 결정된 계면 계수값을 휨하중을 받는 콘크리트 충전강관 실험의 결과예측에 적용하여 콘크리트 충전강관의 계면거동과 구속효과를 평가하였다. 이를 위해 ${\phi}100mm$ 및 ${\phi}200mm$의 두 종류 강관 직경을 갖는 콘크리트 충전 강관(CFT)을 제작하여 휨 거동실험을 수행하였으며, 계면거동을 고려하는 유한요소 해석을 수행하여 거동을 예측하였다. 실험 및 해석결과의 분석을 통해 충전 콘크리트에 대한 강관의 구속효과는 강도의 계산에서 고려할 만한 정도의 영향성은 없는 것을 확인하였다. 또한, 강관과 충전콘크리트 간의 계면슬립변위는 하중 재하점 부근에서 가장 크게 발생하고 단부에 가까울수록 감소하며 전단지간 내의 계면에 작용하는 부착력이 단부에서 콘크리트의 압출을 억제함을 유한요소해석 결과를 통해 확인하였다.

• 산업경영시스템학회지
• /
• 제40권1호
• /
• pp.114-123
• /
• 2017

The global small and mid-sized display market is changing from thin film transistor-liquid crystal display to organic light emitting diode (OLED). Reflecting these market conditions, the domestic and overseas display panel industry is making great effort to innovate OLED technology and incease productivity. However, current OLED production technology has not been able to satisfy the quality requirement levels by customers, as the market demand for OLED is becoming more and more diversified. In addition, as OLED panel production technology levels to satisfy customers' requirement become higher, product quality problems are persistently generated in OLED deposition process. These problems not only decrease the production yield but also cause a second problem of deteriorating productivity. Based on these observations, in this study, we suggest TRIZ-based improvement of defects caused by glass pixel position deformation, which is one of quality deterioration problems in small and medium OLED deposition process. Specifically, we derive various factors affecting the glass pixel position shift by using cause and effect diagram and identify radical reasons by using XY-matrix. As a result, it is confirmed that glass heat distortion due to the high temperature of the OLED deposition process is the most influential factor in the glass pixel position shift. In order to solve the identified factors, we analyzed the cause and mechanism of glass thermal deformation. We suggest an efficient method to minimize glass thermal deformation by applying the improvement plan of facilities using contradiction matrix in TRIZ. We show that the suggested method can decrease the glass temperature change by about 23% through an experiment.

• 자원리싸이클링
• /
• 제21권3호
• /
• pp.28-38
• /
• 2012

이 논문에서는 시멘트를 전혀 사용하지 않고 결합재로서 플라이애쉬를 100% 사용한 알칼리 활성 콘크리트를 개발할 목적으로 알칼리 활성화제의 화학적 변화에 따른 모르타르의 압축강도에 미치는 영향과 SEM/ EDS 및 XRD 등의 미세구조 분석을 검토하였다. 그 결과, 몰농도가 높을수록 초기강도에 큰 영향을 미치는 것으로 분석되었고, 압축강도의 크기에 비례하여 $Si^{4+}$ 및 $Al^{3+}$량이 용출되었다. 또한 SEM 및 EDS로 조직을 분석한 결과 모르타르의 조직구조에 큰 영향을 미치는 성분은 Al 및 Si 성분이었고, XRD 분석결과 활성화제 성분차이에 따른 세기(intensity)의 차이는 거의 없는 것으로 나타났다.

• 한국치위생학회지
• /
• 제18권4호
• /
• pp.535-546
• /
• 2018

Objectives: This study is to assess the correlation of the changes in dental health-related quality of life before, during, and after orthodontic treatments in the patients. Methods: The self-administered survey was conducted in the patients who completed orthodontic treatments living in Seoul and metropolitan areas using Oral Impact on Daily Performances (OIDP) to identify the relevant factors. Data were analyzed with descriptive statistics of variables, independent t-test, one way ANOVA, and multiple regression analysis. Results: From observations of OIDP before, during, and after orthodontic treatment, discomfort associated with three factors including physical, psychological and social ones showed the statistically significant increases during orthodontic treatment than before the treatment; whereas, it was dramatically dropped afterward. Multiple regression analysis to find the influential factors of satisfaction level on orthodontic treatment by setting before, during, and after OIDP as independent variables and satisfaction on orthodontic treatment as a dependent variable revealed that OIDP before orthodontic treatment and after orthodontic treatment significantly affected satisfaction on orthodontic treatment. Conclusions: The above analysis on the change in patients' dental health-related quality of life showed that the quality of life improved after the orthodontic treatment. Accordingly, patients' quality of life and satisfaction level on orthodontic treatment are expected to improve if they strive to maintain healthy dental health through orthodontic treatment.

• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• 제2권1호
• /
• pp.1-14
• /
• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Geomechanics and Engineering
• /
• 제30권3호
• /
• pp.259-272
• /
• 2022

Rockburst is a dynamic, multivariate, and non-linear phenomenon that occurs in underground mining and civil engineering structures. Predicting rockburst is challenging since conventional models are not standardized. Hence, machine learning techniques would improve the prediction accuracies. This study describes decision based uncertainty models to predict rockburst in underground engineering structures using gradient boosting algorithms (GBM). The model input variables were uniaxial compressive strength (UCS), uniaxial tensile strength (UTS), maximum tangential stress (MTS), excavation depth (D), stress ratio (SR), and brittleness coefficient (BC). Several models were trained using different combinations of the input variables and a 3-fold cross-validation resampling procedure. The hyperparameters comprising learning rate, number of boosting iterations, tree depth, and number of minimum observations were tuned to attain the optimum models. The performance of the models was tested using classification accuracy, Cohen's kappa coefficient (k), sensitivity and specificity. The best-performing model showed a classification accuracy, k, sensitivity and specificity values of 98%, 93%, 1.00 and 0.957 respectively by optimizing model ROC metrics. The most and least influential input variables were MTS and BC, respectively. The partial dependence plots revealed the relationship between the changes in the input variables and model predictions. The findings reveal that GBM can be used to anticipate rockburst and guide decisions about support requirements before mining development.