• Journal of Information Technology Applications and Management
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• 제26권3호
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• pp.19-27
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• 2019

In this study, we propose a methodology for predicting the movie audience based on movie information that can be easily acquired before opening and effectively distinguishing qualitative variables. In addition, we constructed a model to estimate the number of movie audiences at the time of data acquisition through the configured variables. Another purpose of this study is to provide a criterion for categorizing success of movies with qualitative characteristics. As an evaluation criterion, we used information gain ratio which is the node selection criterion of C4.5 algorithm. Through the procedure we have selected 416 movie data features. As a result of the multiple linear regression model, the performance of the regression model using the variables selection method based on the information gain ratio was excellent.

• Computers and Concrete
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• 제13권2호
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• pp.173-185
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• 2014

Multivariate analysis is a statistical technique that investigates relationship between multiple predictor variables and response variable and it is a very commonly used statistical approach in cement and concrete industry. During model building stage, however, many predictor variables are included in the model and possible collinearity problems between these predictors are generally ignored. In this study, use of partial least squares (PLS) analysis for evaluating the relationships among the cement and concrete properties is investigated. This regression method is known to decrease the model complexity by reducing the number of predictor variables as well as to result in accurate and reliable predictions. The experimental studies showed that the method can be used in the multivariate problems of cement and concrete industry effectively.

• Journal of the Korean Data and Information Science Society
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• 제28권3호
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• pp.533-545
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• 2017

분위수 회귀모형은 반응변수의 조건부 분포에 대하여 포괄적이고 유용한 통계적 정보를 제공한다. 그러나 많은 실제 자료는 설명변수와 반응변수가 비선형의 관계를 갖고 있어 전통적인 선형 분위수 회귀모형은 왜곡되고 잘못된 결과를 초래할 수 있다. 또한 자료의 복잡성이 증가하여 반응변수가 여러개인 다변량 자료의 분석에 대한 보다 정확한 예측과 더불어 풍부한 해석에 대한 요구가 증가하고 있다. 이러한 이유로 본 연구에서는 다변량 분위수 회귀나무 모형을 제안하였다. 본 연구에서는 기존의 다변량 회귀나무 모형의 분할변수 선택 알고리즘의 문제점을 지적하고 향상된 분할변수 선택 알고리즘을 제안하였다. 제안한 알고리즘은 합리적인 계산시간으로 적용 가능하며 분할변수 선택에서 편향 발생의 문제를 갖지 않는 동시에 기존 방법보다 더 정확하게 분할변수를 선택할 수 있있다. 본 연구에서는 모의실험과 실증 예제를 통해 제안한 방법의 우수한 성능과 유용성을 확인하였다.

• 한국측량학회지
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• 제25권6_2호
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• pp.613-623
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• 2007

본 연구의 주요 목적은 서로 다른 측지기준계인 동경측지계와 세계측지계간의 좌표 변환을 위한 연구이다. 이를 위하여 Bursa-Wolf 모델, Molodensky-Badekas 모델 및 Veis 모델을 이용하여 7변환 계수를 결정하였다. 또한 동경데이텀으로부터 세계측지계로 변환하기 위한 다중회귀식 방법도 적용하였다. 공통점 중에서 비상사성인 과대 오차인 점을 분석하고 제거하여 935점의 국가기준점 성과를 변환 계수 결정을 위한 공통점으로 이용하였다. 각 모델별로 결정한 변환 계수를 적용하여 상사 변환에 의한 3, 4등 삼각점 9,917점에 대한 좌표변환을 수행하였으며 변환 정확도를 평가하였다. 그 결과, Bursa-Wolf 모델과 Molodensky-Badekas 모델을 이용하여 결정한 변환 계수가 Veis 모델에 비하여 더 적합하다는 것을 알 수 있었다. 다중회귀식에 의한 변환 정확도는 상사 변환 모델보다는 다소 저하되는 경향을 보였다. 변환 계수의 추정 정밀도와 변환 정확도 및 변환 잔차의 패턴을 분석한 결과, 최적의 국가 좌표변환 모델은 Molodensky-Badekas 모델이라고 판단된다.

• 생물환경조절학회지
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• 제23권3호
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• pp.181-191
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• 2014

Modern commercial greenhouse requires the use of advanced climate control system to improve crop production and to reduce energy consumption. As an alternative to classical sensor-based control method, this paper introduces a model-based control method that consists of two models: the predictive model and the evaluation model. As a first step, this paper presents straightforward models to predict the effect of natural ventilation in a greenhouse according to meteorological factors, such as outdoor air temperature, soil temperature, solar radiation and mean wind speed, and structural factor, opening rate of roof ventilators. A multiple regression analysis was conducted to develop the predictive models on the basis of data obtained by computational fluid dynamics (CFD) simulations. The output of the models are air temperature drops due to ventilation at 9 sub-volumes in the greenhouse and individual volumetric ventilation rate through 6 roof ventilators, and showed a good agreement with the CFD-computed results. The resulting predictive models have an advantage of ensuring quick and reasonable predictions and thereby can be used as a part of a real-time model-based control system for a naturally ventilated greenhouse to predict the implications of alternative control operation.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2019년도 추계학술대회
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• pp.19-19
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• 2019

It is necessary to maintain stable crop productions under the unsuitable environments, because the drought and flood may be frequently caused by the global warming. Therefore, it is agent to improve the crop growth model corresponded to soil moisture status. Chili pepper (Capsicum annuum) is one of the useful crop in Asia, and then it is affected by change of precipitation in consequence drought and flood occur however crop model to evaluate water stresses on chili pepper is not enough yet. In this study, development of crop model under different soil moisture status was attempted. The experiment was conducted on the slope fields in the greenhouse. The water level was kept at 20cm above the bottom of the container. Habanero (C. chinense) was used as material for crop model. Sap bleeding rate, SPAD value, chlorophyll content, stomatal conductance, leaf water potential, plant height, leaf area and shoot dry weight were measured at 10 days after treatment (DAT) and 13 DAT. Moreover, temperature and RH in the greenhouse, soil volume water contents (VWC) and soil water potential were measured. As a result, VWC showed 4.0% at the driest plot and 31.4% at the wettest plot at 13 DAT. The growth model was calculated using WVC and the growth analysis parameters. It was considered available, because its coefficient of determination showed 0.84 and there are significant relationship based on plants physiology among the parameters and the changes over time. Furthermore, we analyzed the important factors for higher accuracy prediction using multiple regression analysis.

• The Korean Journal of Pain
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• 제32권2호
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• pp.120-128
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• 2019

Background: We aimed to explore the American College of Rheumatology (ACR) 1990 and 2011 fibromyalgia (FM) classification criteria's items and the components of Fibromyalgia Impact Questionnaire (FIQ) to identify features best discriminating FM features. Finally, we developed a combined FM diagnostic (C-FM) model using the FM's key features. Methods: The means and frequency on tender points (TPs), ACR 2011 components and FIQ items were calculated in the FM and non-FM (osteoarthritis [OA] and non-OA) patients. Then, two-step multiple logistic regression analysis was performed to order these variables according to their maximal statistical contribution in predicting group membership. Partial correlations assessed their unique contribution, and two-group discriminant analysis provided a classification table. Using receiver operator characteristic analyses, we determined the sensitivity and specificity of the final model. Results: A total of 172 patients with FM, 75 with OA and 21 with periarthritis or regional pain syndromes were enrolled. Two steps multiple logistic regression analysis identified 8 key features of FM which accounted for 64.8% of variance associated with FM group membership: lateral epicondyle TP with variance percentages (36.9%), neck pain (14.5%), fatigue (4.7%), insomnia (3%), upper back pain (2.2%), shoulder pain (1.5%), gluteal TP (1.2%), and FIQ fatigue (0.9%). The C-FM model demonstrated a 91.4% correct classification rate, 91.9% for sensitivity and 91.7% for specificity. Conclusions: The C-FM model can accurately detect FM patients among other pain disorders. Re-inclusion of TPs along with saving of FM main symptoms in the C-FM model is a unique feature of this model.

• 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.

• 한국수자원학회논문집
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• 제34권6호
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• pp.627-640
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• 2001

일반적으로 합성단위도법은 강우-유출기록이 없는 유역의 설계홍수량 산정을 위해 제안되었다. 그러나 국내에서는 아직까지 자료의 부족 등으로 외국에서 개발된 각종 유출모의 모형이 주로 이용되고 있다. 따라서 그 동안 축적된 국내의 강우-유출 자료를 이용하여 국내의 수문특성엥 적합한 유출모형의 개발이 절실한 상황이다. 이를 위해 본 연구에서는 설마천 유역의 2개 지점과 IHP 대표유역인 평강창, 보청천, 위천의 17개 지점에 대해 그 동안 축 (중략) 특성 관련 연구결과를 종합하여 새로운 합성단위도법을 개발하였다. 개발된 합성단위도는 유역특성인자와 단위도치식 치(첨두시간, 첨두유량)와의 다중회귀분석을 통해 유역면적-유로연장-유로경사의 3가지 변수로 구성되는 효 (중략) 전국을 있었다. 따라서 우리나라에서는 아직까지 수계별로 합성단위도를 분리하여 제시하기는 무리라고 보여지 (중략)

• Journal of Periodontal and Implant Science
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• 제46권3호
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• pp.197-206
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• 2016

Purpose: The aim of this study was to evaluate alterations of papilla dimensions after orthodontic closure of the diastema between maxillary central incisors. Methods: Sixty patients who had a visible diastema between maxillary central incisors that had been closed by orthodontic approximation were selected for this study. Various papilla dimensions were assessed on clinical photographs and study models before the orthodontic treatment and at the follow-up examination after closure of the diastema. Influences of the variables assessed before orthodontic treatment on the alterations of papilla height (PH) and papilla base thickness (PBT) were evaluated by univariate regression analysis. To analyze potential influences of the 3-dimensional papilla dimensions before orthodontic treatment on the alterations of PH and PBT, a multiple regression model was formulated including the 3-dimensional papilla dimensions as predictor variables. Results: On average, PH decreased by 0.80 mm and PBT increased after orthodontic closure of the diastema (P<0.01). Univariate regression analysis revealed that the PH (P=0.002) and PBT (P=0.047) before orthodontic treatment influenced the alteration of PH. With respect to the alteration of PBT, the diastema width (P=0.045) and PBT (P=0.000) were found to be influential factors. PBT before the orthodontic treatment significantly influenced the alteration of PBT in the multiple regression model. Conclusions: PH decreased but PBT increased after orthodontic closure of the diastema. The papilla dimensions before orthodontic treatment influenced the alterations of PH and PBT after closure of the diastema. The PBT increased more when the diastema width before the orthodontic treatment was larger.