본 연구는 소래풀을 경관화훼로 이용하기 위해 온도조건에 따른 발아특성을 알아보고 회귀분석(bilinear, parabolic, beta distribution)모델을 통해 주요온도(최저, 최적 및 최고온 도)를 구명하고자 하였다. 소래풀 종자는 5, 10, 15, 20, 25, 30, 35℃ 항온 조건 중 25℃에서 약 6~7일만에 최종발아율이 100%에 도달하였으며, 발아세, 발아속도, 평균발아속도와 평균발아시간이 각각 100%, 21.37ea/day, 14.48, 4.39일 로 다른 처리보다 발아특성이 우수하였다. 이를 바탕으로 발아 속도(germination rate, GR)가 50%인 시점(GR50)을 역수로 (1/GR50)하여 주요온도를 분석한 결과, bilinear모델의 경우, 최저, 최적 및 최고온도는 4.8℃, 25.8℃, 35.6℃였으며 (R2=0.9566, p<0.001), parabolic모델은 최저온도 6.1℃, 최 적온도 21.6℃, 최고온도 36.7℃였다(R2=0.8818, p<0.001). 또한 beta distribution 모델의 주요온도는 최저온도 6.1℃, 최 적온도는 23.1℃, 최고온도 40.1℃였다(R2=0.9102, p<0.001). 본 연구에서 분석한 회귀모델 모두 0.1% 수준에서 통계적 유의 차가 인정된 것으로 보아 소래풀 종자의 발아 시 최저온도는 4.8~6.1℃, 최고온도는 35.6~40.1℃, 최적온도는 21.6~25.8℃ 이며, 50% 이상의 발아율을 기대하였을 때 온도의 범위는 20~25℃가 적합할 것으로 판단된다. 이와 같은 결과는 소래풀 을 이용하여 경관조성을 할 때 파종 및 발아시기를 예측할 수 있는 자료로 활용될 수 있을 것으로 판단된다. 그러나 경관조성 을 하는 현장에서 실질적인 도움을 제공할 수 있도록 발아의 주요온도 모델과 함께 식물의 생물계절 관점에서 추가적인 연구 가 필요할 것으로 판단된다.

Approximately 40,000 elevators are installed every year in Korea, and they are used as a convenient means of transportation in daily life. However, the continuous increase in elevators has a social problem of increased safety accidents behind the functional aspect of convenience. There is an emerging need to induce preemptive and active elevator safety management by elevator management entities by strengthening the management of poorly managed elevators. Therefore, this study examines domestic research cases related to the evaluation items of the elevator safety quality rating system conducted in previous studies, and develops a statistical model that can examine the effect of elevator maintenance quality as a result of the safety management of the elevator management entity. We review two types: odds ratio analysis and logistic regression analysis models.

Tomato is one of the major widely cultivated crops around the world. The leaf area is directly related to the total amount of photosynthesis, which affects the yield and quality of the fruit. Traditional methods of measuring the leaf area are time-consuming and can cause damage to the leaves. To address these problems, various studies are being conducted for measuring the leaf area. In this study, we introduced a model to estimate the leaf area using images of tomatoes. Using images captured by a camera, we measured the leaf length and width and used linear regression analysis to derive the leaf area estimation formula. Furthermore, we used a Neural Network (NN) for additional analysis to compare the accuracy of the models. Initially, to verify the reliability of the image data, we conducted a correlation analysis between the actual measurement data and the image data, which showed a high positive correlation. The leaf area estimation model presented 23 estimation formulas. We used regression analysis to estimate the coefficients of each model and also used employed an artificial neural network analysis to derive high R-squared (R2) values and low Root Mean Square Error (RMSE) values. Among the estimation formulas, the ninth model showed the highest reliability with an R-squared value of 0.863. We conducted a verification experiment to confirm the accuracy of the selected model, and the R-squared value was 0.925. This study confirmed the reliability of data measured from images and the reliability of the leaf area estimation model using image data. These methods are expected to be an important tool in agriculture, using imaging equipment for measuring and monitoring the crop growth.

본 연구는 한국인 인구집단에서 폭식행동, 음식중독을 식별하고, 해당 증상들이 비만 및 섭식행 동, 정신건강, 인지적 특성과 어떠한 연관성을 보이는지 규명하고자 하였다. 이를 위하여 정상체중 및 비만 체중에 해당하는 한국인 성인 257명을 대상으로 섭식문제(예: 폭식, 음식중독, 음식갈망), 정신건강(예: 우 울), 인지기능(예: 충동성, 정서조절)에 관한 임상심리검사 척도를 측정하였다. 비만 여부와 성별에 따라 그 룹을 나누었을 때, 비만체중 여성에서 폭식행동이 46.6%, 음식중독이 29.3%로 가장 빈도가 높았다. 성향 점수 매칭 후 데이터로 독립성 검정을 수행한 결과, 폭식행동 및 음식중독이 비만체중 집단에서 정상체중 집단보다 더 많이 나타나는 것을 확인하였다. 또한 폭식행동과 음식중독 유무에 각 심리검사 척도 요인이 미치는 영향력을 파악하고자, 전진선택법을 적용한 로지스틱 회귀모델을 구축하였다. 로지스틱 회귀분석 결과, 폭식행동에는 섭식장애, 음식갈망, 상태불안, 정서조절(인지적 재해석) 및 음식중독이 주로 관여하였 고, 음식중독에는 음식갈망, 폭식행동과 함께 비만과 연령의 교호작용, 교육년수가 유의하게 작용하는 것으 로 나타났다. 본 연구는 한국인 성인을 대상으로 한 체계적 연구로서, 폭식행동과 음식중독이 여성 및 비만 인에서 특히 더 많이 나타남을 확인하였다. 폭식행동과 음식중독에는 일부 섭식문제(예: 음식갈망)가 공통되게 관여하나, 정신건강 및 인지적 위험요인에는 차이가 있었다. 따라서 음식중독과 폭식행동은 서로 구 별되는 개념으로 두고, 각각의 기질적·환경적 위험요인을 깊이 있게 탐구하는 것이 필요하다.

PURPOSES : This study aims to conduct a sensitivity analysis to determine the major factors affecting traffic accidents involving elderly pedestrians. METHODS : In this study, a regression tree model was built based on a non-parametric statistical model using data on traffic accidents involving elderly pedestrians. Using this model, we analyzed the degree of change in the probability of pedestrian fatalities. RESULTS : Results of the model analysis show that the first major factor combination affecting traffic accidents involving elderly pedestrians is speeding, night time, and road markers. The second combination is night time and arterial roads (national and local highways). The last combination that may lead to such accidents is heavy vehicles and federally funded local highways. CONCLUSIONS : Preventive measures, such as speed control, proper lighting, median strips, designation of pedestrian protection zones, and guidance of detours, are necessary to manage high-risk combinations causing accidents of the elderly.

본 논문에서는 3차원 엮임 재료의 유체투과율 향상을 목적으로 수치해석 데이터 기반의 물성치 회귀 분석 및 최적설계를 소개한다. 우선 3차원 엮임 재료를 구성하는 와이어 사이의 간격을 결정하는 배율 계수를 매개변수화 하여 다양한 배율 조합을 가지는 수치 모 델을 생성하였고, 전산 수치해석을 통해 계산된 각 모델의 체적 탄성계수, 열전도 계수, 유체투과율 데이터를 이용하여 다항식 기반의 회귀 분석을 수행하였다. 이를 사용해서 체적 탄성계수와 유체투과율 사이의 다목적함수 최적설계를 통한 파레토 최적해를 도출하였 으며, 두 물성치가 서로 상충 관계에 있음을 확인하였다. 한편 3차원 엮임 재료의 열전달 효율을 높이기 위해서 유체투과율을 최대화 시키는 것을 목적으로 경사도 기반 최적설계를 수행하였고, 제약조건인 체적 탄성계수의 크기별 유체투과율의 변화율을 분석하였다. 그 결과 설계자가 원하는 최소한의 강성을 가지는 최대 유체투과율 설계 모델을 얻어낼 수 있음을 확인하였으며, 회귀 방정식을 통해 서 얻어진 설계가 높은 정확도를 가지고 있음을 추가적으로 검증하였다.

PURPOSES : To efficiently manage pavements, a systematic pavement management system must be established based on regional characteristics. Suppose that the future conditions of a pavement section can be predicted based on data obtained at present. In this case, a more reasonable road maintenance strategy should be established. Hence, a prediction model of the annual surface distress (SD) change for national highway pavements in Gangwon-do, Korea is developed based on influencing factors. METHODS : To develop the model, pavement performance data and influencing factors were obtained. Exploratory data analysis was performed to analyze the data acquired, and the results show that the data were preprocessed. The variables used for model development were selected via correlation analysis, where variables such as surface distress, international roughness index, daily temperature range, and heat wave days were used. Best subset regression was performed, where the candidate model was selected from all possible subsets based on certain criteria. The final model was selected based on an algorithm developed for rational model selection. The sensitivity of the annual SD change was analyzed based on the variables of the final model. RESULTS : The result of the sensitivity analysis shows that the annual SD change is affected by the variables in the following order: surface distress ˃ heat wave days ˃ daily temperature range ˃ international roughness index. CONCLUSIONS : An annual SD change prediction model is developed by considering the present performance, traffic volume, and climatic conditions. The model can facilitate the establishment of a reasonable road maintenance strategy. The prediction accuracy can be improved by obtaining additional data, such as the construction quality, material properties, and pavement thickness.

이 연구의 목적은 머신러닝 분석방법을 활용하여 대학생의 소속 학과 만족도에 영향을 미치는 주요 요 인을 분석하여 대학생의 진로지도와 중도탈락 예방 관련 정책 및 제도 수립을 위한 기초 연구 자료를 제 공하기 위함이다. 이를 위해 한국교육고용패널 􎟯(KEEP 􎟯)자료의 4년제 대학 진학생 1,298명을 연구대 상으로 머신러닝 분석방법인 로지스틱 회귀분석과 랜덤포레스트 방법을 통하여 분석을 진행하였다. 주요 분석 결과는 다음과 같다. 첫째, 대학 입학년도에는 대학 생활 관련 변수 이외에도 고등학교 재학 시기 및 고등학교 졸업 후 진로 계획과 관련한 설명변수들이 중요도 상위 10개 항목 중 상당수를 차지하였으며, 입학년도와 졸업년도를 제외한 기간에는 전공 학습과 진로활동에 대한 변수들이, 졸업년도에는 취업준비 및 교육훈련 경험 등이 로지스틱 회귀분석과 랜덤포레스트 분석 결과에서 공통적으로 높은 중요도를 기록하였다. 둘째, 두 분석방 법에 따른 학년별 중요도 상위 10개 변수의 일치도는 63.3%로 나타났다. 셋째, 로지스틱 회귀분석과 달리 랜덤포레스트 분석에서는 설문의 응답자가 다수의 척도를 사용하여 응답한 설명변수들이 중요도 상위 10 개 설명변수에 포함된 경우가 상대적으로 많았다. 이 연구는 교육패널 자료를 단일 분석방법이 아닌 두 가지 머신러닝 방법을 사용하여 공통 요소를 도출하고, 결과의 비교를 시도했다는 점에 의의가 있다.

재해석 자료는 공간해상도가 저해상도이지만 풍력자원의 장기간 보정이나 수치기상예측 또는 전산유체역학과 연동하여 고 해상도로의 축소화에 활용될 수 있다. 본 연구에서는 재해석 자료의 전세계 풍속을 지형요소 등의 함수로 회귀 분석하였으며 향후 고 해상도 축소화에의 활용 가능성을 시험하였다. 다중선형회귀와 기계학습 모델로서 신경망, 랜덤 포레스트 모델을 적용하여 다양한 지 형형태별로 회귀 분석한 결과에 의하면 접합도(R2)가 각각 0.71, 0.95, 1.00으로 향상되었으며, 지형요소 중 위도, 셀 면적, 지형고도, 경 도, 지형 개방도 순으로 설명력이 높은 것으로 나타났다. 기본 신경망에 비해 수정 쌍둥이 신경망 모델은 불균질 데이터 대상 성능 개 선 효과가 있는 것으로 나타났다. 그럼에도 불구하고 본 연구에서 활용한 신경망 모델로는 데이터의 비선형성을 재현하는데 한계가 있 었으나 랜덤 포레스트 모델을 통해 이를 극복하였다.

선박의 주묘 위험성을 평가할 수 있는 프로그램이 개발되어 있지만 선박의 제원에 해당되는 다양한 입력요소들을 직접 찾아서 입력해야 하므로 VTS 관제사가 정박지에 정박 중인 선박들로부터 이러한 입력요소들을 모두 확인하여 프로그램을 활용하는 것은 현실적으로 어려운 상황이다. 이에 본 연구에서는 VTS 관제사 입장에서 선박으로부터 쉽게 획득할 수 있는 총톤수(GT)를 독립변수로 설정하고 프로그램 입력요소들을 종속변수로 하여 선형 및 비선형 회귀분석을 실시하였다. 다항식 모델(선형)과 멱급수 모델(비선형)의 적합도를 비교한 결과, 컨테이너선과 벌크선의 경우에는 모든 입력요소에서 멱수급 모델이 적합한 것으로 평가되었다. 하지만 탱커선의 경우에는 수선간장, 선폭, 흘수는 멱수급 모델이 적합하고, 정면풍압면적, 앵커의 무게, 의장수, 묘쇄공으로부터 선저까지의 높이는 다항식 모델이 더 적합한 것으로 평가되었다. 또한 탱커선의 정면풍압면적 요소를 제외한 다른 나머지 종속변수들은 모두 결정계수가 0.7 이상으로 높은 적합도를 보였다. 따라서 주묘 위험성 평가 프로그램의 입력요소 중 외력 요소, 해저 저질, 수심 및 앵커 체인의 신출량을 제외한 나머지 입력요소들은 선박의 총톤수만 입력하면 회귀분석 모델식에 의해 자동으로 입력됨으로써 주묘 위험성 평가가 가능할 것으로 판단된다.

In this study, a drifting test using a experimental vessel (2,966 tons) in the northern waters of Jeju was carried out for the first time in order to obtain the fundamental data for drift. During the test, it was shown that the average leeway speed and direction by GPS position were 0.362 m/s and 155.54° respectively and the leeway rate for wind speed was 8.80%. The analysis of linear regression modes about leeway speed and direction of the experimental vessel indicated that wind or current (i.e. explanatory variable) had a greater influence upon response variable (e.g. leeway speed or direction) with the speed of the wind and current rather than their directions. On the other hand, the result of multiple regression model analysis was able to predict that the direction was negative, and it was demonstrated that predicted values of leeway speed and direction using an experimental vessel is to be more influential by current than wind while the leeway speed through variance and covariance was positive. In terms of the leeway direction of the experimental vessel, the same result of the leeway speed appeared except for a possibility of the existence of multi-collinearity. Then, it can be interpreted that the explanatory variables were less descriptive in the predicted values of the leeway direction. As a result, the prediction of leeway speed and direction can be demonstrated as following equations. However, many drift tests using actual vessels and various drifting objects will provide reasonable estimations, so that they can help search and rescue fishing gears as well.

In addition to physical risks such as electrical, chemical, and mechanic ones in the workplace, psychosocial risks are also raising as an important issue in recent years in connection with human rights and work-life balance policies. The purpose of this study is to confirm the degree of effect of the psychosocial risk management plan at the workplace on workers through logistic regression analysis. Input data for logistic regression analysis is the results of a survey of 4,558 people conducted by the Institute for Occupational Safety and Health were used. There are 9 independent variables, including the change a workplace and confidential counseling, and the dependent variable is whether the worker feels the effect on the psychosocial risk management plan. As a result of this study, changes in work organization, dispute resolution procedures, provision of education program, notification of the impact of psychosocial risks on safety and health, and the persons in charge of solving psychosocial problems are shown effective in reducing worker’s psychosocial risks. This study drives which of the management plans implemented to reduce the psychosocial risk of workers in the workplace are effective, so it can contribute to the development of psychosocial risk management plans in the future.

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

본 논문에서는 고리 1호기 해체 비용 추정을 위해 외국 원자력발전소 해체 비용 데이터를 현가화한 후 원자력발전소 해체 비용 추정 회귀 분석모델을 개발하였다. 이 모델 개발에 사용된 데이터는 해체 또는 진행 중인 BWR 13기, PWR 16기의 해체 비용 데이터이다. 회귀 분석모델 도출을 위해, 해체 비용을 종속변수로 정하고, 해체 원전의 운전 특성을 반영할 수 있게 고 안된 Contamination factor와 해체 기간을 독립변수로 선정하였다. 빅데이터 분석 도구인 R language의 통계패키지를 이용 하여 회귀 분석모델을 도출하였다. 이 회귀 분석 모델을 적용하여 고리 1호기 해체 비용을 예측한 결과, 미화 663.40~928.32 백만 달러, 한화 약 7,828.12억~1조 954.18억 원이 소요될 것으로 예측되었다.

While the vehicle has a wide front view, making it easy to recognize obstacles while driving, the rear side has a narrow view and the inconvenience of having to turn its head to check. A side mirror developed to address this discomfort is mounted outside the front door of a passenger car and used to identify rear objects. In this study, heat transfer analysis was performed and analyzed in order to obtain optimal defrost conditions using regression analysis method for removing mirror condensation and frost. As a result of this study, the coefficient of determination, R2, which represents the regression to the total variation through regression analysis, showed a good reliability of 85.3%. Comparing the predicted and interpreted values of the maximum temperature distribution in the regression equation established in this study, it was included in the 95% confidence interval, enabling the prediction of the maximum temperature distribution over the heat conduction time.

Background: The prevalence of neck pain and neck dysfunction is high in general population. However, there is little literature on the relationship and factors affecting neck pain and neck dysfunction. Objective: To investigate the correlation between neck and shoulder pain, headaches, neck and shoulder dysfunction, and sleep quality in adults with chronic neck pain, and factors affecting neck pain and neck dysfunction. Design: Cross-sectional study Methods : The sample included 114 subjects, who had complained of chronic neck pain for more 12 weeks. We conducted a Pearson’s correlation between neck and shoulder pain, headaches, neck and shoulder dysfunction and sleep quality and a regression analysis of the related variables, thereby analyzing factors affecting neck pain and neck dysfunction. Results : In the present study, in adults with chronic neck pain, neck pain was positively correlated with the Neck Disability Index (NDI), Shoulder Pain and Disability Index (SPADI)-Pain score, and SPADI-Total score (p<.05). The NDI was positively correlated with neck pain, SPADI-Pain score, and SPADI-Total score, as well as with Pittsburgh Sleep Qulity Index(PSQI-K) (p<.05). Among the factors affecting neck pain, shoulder disability as assessed by the SPADI was a significantly associated with neck pain, while shoulder pain and shoulder disability determined by the SPADI were identified as significant variables among the factors affecting neck disability. Conclusion : These results indicated that as neck pain worsened , shoulder pain and neck and shoulder dysfunction also increased, which suggested that shoulder disability affected neck pain. In addition, as the neck dysfunction increased, neck pain and shoulder pain and shoulder dysfunction increased, and sleep quality deteriorated, which suggested that shoulder pain and shoulder disability affected neck disability.

The prediction of Jominy hardness curves and the effect of alloying elements on the hardenability of boron steels (19 different steels) are investigated using multiple regression analysis. To evaluate the hardenability of boron steels, Jominy end quenching tests are performed. Regardless of the alloy type, lath martensite structure is observed at the quenching end, and ferrite and pearlite structures are detected in the core. Some bainite microstructure also appears in areas where hardness is sharply reduced. Through multiple regression analysis method, the average multiplying factor (regression coefficient) for each alloying element is derived. As a result, B is found to be 6308.6, C is 71.5, Si is 59.4, Mn is 25.5, Ti is 13.8, and Cr is 24.5. The valid concentration ranges of the main alloying elements are 19 ppm < B < 28 ppm, 0.17 < C < 0.27 wt%, 0.19 < Si < 0.30 wt%, 0.75 < Mn < 1.15 wt%, 0.15 < Cr < 0.82 wt%, and 3 < N < 7 ppm. It is possible to predict changes of hardenability and hardness curves based on the above method. In the validation results of the multiple regression analysis, it is confirmed that the measured hardness values are within the error range of the predicted curves, regardless of alloy type.

In recent year, marine safety has been one of top concerns in Korea. In this paper, general statistics of ship in 159 waterways in Korea from 2007 to 2017 were considered. Main objective of this research is to investigate the relationship between the number of marine accidents and traffic conditions in narrow waterways by multiple regression analysis method. The result shows that the number of vessels, the width, the length and the depth of narrow waterway have an influence on the number of maritime accidents in corresponding area. Additionally, the number of vessels sailing has the most significant impact on the number of accidents in narrow waterway area.