• Journal of environmental and Sanitary engineering
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• v.22 no.2
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• pp.61-73
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• 2007

PCBs의 대기 중 농도는 고용량 PUF sampler를 이용하여 2000년부터 2002년까지 주 1회 수도권 인근지역인 경기도 안성에서 측정하였다. 본 논문은 비선형 회귀모델을 이용하여 대기 중 가스상 PCBs의 연간, 월간 사이클을 평가 하고자 한다. Clausius-Clepeyron 식을 이용한 가스상 PCBs의 기울기는 고분자로 갈수록 증가하는 경향이었다. 이는 고분자 PCBs는 저분자 PCBs에 비해 온도 의존성이 크다는 것을 의미한다. 다시 말해, 고분자 PCBs는 다른 지역에서 장거리 이송되어 오는 오염물질의 영향 보다는 지역적인 오염원(예, 토양, 수계 등)에 의해 영향을 크게 받고 있다는 것을 시사한다. Lorentzian 모델을 이용한 총 PCBs의 일별, 월별 회귀식의 결정계수($R^2$)는 각각 0.62(p<0.0001), 0.88(p<0.0001)로 나타나 유의한 결과를 보였다. 또한, 비선형 회귀식 모델을 활용하여 구한 가스상 PCBs의 일별, 월별 싸이클을 모사한 방정식도 매우 유의한 결과(p<0.0001)를 나타내었다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.53-66
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• 2023

Role models are also known to influence an individual's job or career choice. The positive effect of role models on entrepreneurship has already been revealed through many precious researches. It is said that people choose not only family members who are related by blood, such as parents, siblings, and relatives, but also acquaintances whom they have met through social relationships as role models. In this study, we divided into entrepreneurs with no role models other than themselves and entrepreneurs with role models. In addition, we classified parental siblings and relative role models as role models with strong ties, and acquaintance role models as role models with weak ties. We analyzed the differences in personal attributes, entrepreneurial orientation factors, and learning orientation between the entrepreneurs with role models and those without role models. Also, the differences in personal attributes, innovativeness, proactiveness, risk-taking propensity, and learning orientation between the entrepreneurs with strong ties role models and those with weak ties role models were examined. The empirical analysis results are as follows. First, it was found that the proportion of women entrepreneurs without role models is higher. Second, the entrepreneurs with role models with weak ties tend to run larger scale start-ups. Third, it was found that the entrepreneurs with role models of weak ties tend to have higher learning orientation. Fourth, gender shows the greatest influence on th absence or presence of role models. Fifth, it was found that learning orientation and startup size have the greatest influence on the decision of the role model with weak ties or that with strong ties.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.631-633
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• 2022

인체 선형 모델 (이하 SMPL 모델)은 3 차원 사람 모델로, 3 차원 컴퓨터 그래픽 기술이 발전함에 따라 활용 범위가 확대될 수 있다. 다운샘플링 (Down-sampling)으로 여러 해상도의 SMPL 모델이 사용가능 하다면, 3 차원 컴퓨터 그래픽 기술 발전에 도움이 될 것이다. 3 차원 모델의 다운샘플링을 위한 많은 메쉬 단순화 (Mesh simplification) 기법이 존재한다. 하지만 기존의 기법만을 사용하면 다운 샘플링 한 모델의 자세 (Pose)를 변경했을 때 기대한 것과 다른 결과물이 만들어지는 문제가 발생한다. 본 논문에서는 가장 가까운 정점으로 SMPL 모델의 관절 회귀자 (Joint regressor) 값을 넘겨주어 문제를 해결하는 다운샘플링 (Down-sampling) 방법을 제시한다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.1-8
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• 2016

In the recently, violent crime and accidental crime has been generated continuously. Consequently, people anxiety has been heightened. The Closed Circuit Television (CCTV) has been used to ensure the security and evidence for the crimes. However, the video captured from CCTV has being used in the post-processing to apply to the evidence. In this paper, we propose a flexible multi-level models for estimating whether dangerous behavior and the environment and context for pedestrians. The situation analysis builds the knowledge for the pedestrians tracking. Finally, the decision step decides and notifies the threat situation when the behavior observed object is determined to abnormal behavior. Thereby, tracking the behavior of objects in a multi-region, it can be seen that the risk of the object behavior. It can be predicted by the behavior prediction of crime.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.355-356
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• 2021

본 논문에서는 Python 3의 Keras 모듈을 이용하여 특정 자동차에 대한 최적의 판매자권장소비자가격(MSRP)을 예측하는 시스템을 제안한다. 이 시스템은 2004년에 미국에서 시판된 428종류의 자동차에 대한 정보를 제조사, 차종, 생산지, 엔진 크기, 실린더 수, 시내 주행 시 연비, 고속도로 주행 시 연비, 마력, 차체 무게, 차체 길이의 독립변수를 사용하여 자체적으로 딥러닝한 회귀모델을 통해 특정 지표가 주어진 차량에 대해 종속변수인 판매자권장소비자가격을 예측한다. Optimizer를 adam으로, 학습률을 0.005으로 설정한 경우의 검증 MAE 값이 3842.98로 가장 낮게 산출되었고, 해당 모델의 결과는 예측값과 실제값의 오차율이 ±15% 정도 내외로 예측된 표본의 비율이 약 80.14%로 측정되었다. 위 모델은 향후 신차 가격 결정 및 중고차 시장에서 구매, 판매 결정을 돕는 등 특정 시장 내에서 다양한 자동차의 가치를 판단하기에 유용할 것으로 전망된다.

• KDI Journal of Economic Policy
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• v.11 no.3
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• pp.39-59
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• 1989

본고(本稿)는 Sims가 개발한 방법을 이용하여 우리나라와 같이 경제구조(經濟構造)가 급히 변하는 상황에서의 경제예측(經濟豫測)의 정확도(正確度)를 제고하고자 하는 시도의 일환이다. 본고(本稿)는 예측자의 사전신뢰(事前信賴)를 이용하여 계수의 값에 대하여 사전제약(事前制約)을 부과(賦課)하고 시간변동(時間變動)을 허용하는 변동계수(變動係數)벡타자귀(自歸)(TBVAR)모형(模型)의 추정방법뿐만 아니라 사전제약(事前制約)의 모수(母數)를 선택하는 방법과 오차(誤差)의 분산(分散)이 자기회귀(自己回歸)할 경우의 대처방법 등 예측(豫測)의 정확도(正確度)를 제고시키는 데 실제 사용되는 방법을 설명하고, 6변수모형(變數模型)을 이용하여 TBVAR 모델의 정확도(正確度)를 타(他) 모델과 비교한다. 정부건설(政府建設), 총통화(總通貨), 사채시장이자율(社債市場利子率), 민간건설(民間建設), 실질(實質)GNP 및 소비자(消費者) 물가지수(物價指數) 등 6변수(變數)에 대한 예측의 정확도를 "타일 U"값을 기준으로 비교할 때 TBVAR은 시간변동(時間變動)을 고려하지 않고 사전제약(事前制約)만 적용한 BVAR이나 사전제약(事前制約)도 적용하지 않은 VAR보다 대부분의 변수의 예측에 있어 더 정확하며 민간건설(民間建設)을 제외하고는 OLS보다 예측오차(豫測誤差)가 작게 나타난다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.428-431
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• 2017

기업의 성장성과 기업 주식가치를 매출, 매출원가, 영업이익율 등의 정형데이터와 경제, 경영관련 뉴스 등 비정형 데이터를 토대로 다양한 알고리즘을 활용해 분석하고, 그 결과의 유의성을 검증한다. 주성분회귀분석, 인공신경망, 나이브 베이지안 분류자, 긍/부정 사전분석 모델을 통해 분석된 결과를 검토하여 각 분석모델 별 성능을 확인하고, 기업 성장성 예측을 위해 활용 가능한 모델과 필요한 데이터를 제시한다.

• Land and Housing Review
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• v.12 no.4
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• pp.93-101
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• 2021

As the number of small households (1 to 2 persons per household) in Korea gradually increases, so does the importance of housing supply policies for small households. In response to the increase in small households, the government has been continuously supplying urban housing for these households. Since housing for small households is a sales and rental business similar to apartments and general business facilities, it is important for the building owner to calculate the project's estimated construction duration during the planning stage. Review of literature found a model for estimating the duration of construction of large-scale buildings but not for small-scale buildings such as urban housing for small households. Therefore this study aimed to develop and verify a model for estimating construction duration for urban housing at the planning stage based on multiple regression analysis. Independent variables inputted into the estimation model were building site area, building gross floor area, number of below ground floors, number of above ground floors, number of buildings, and location. The modified coefficient of determination (R_a²) of the model was 0.547. The developed model resulted in a Root Mean Square Error (RMSE) of 171.26 days and a Mean Absolute Percentage Error (MAPE) of 26.53%. The developed estimation model is expected to provide reliable construction duration calculations for small-scale urban residential buildings during the planning stage of a project.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.453-463
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• 2018

An analysis including ASE model accessing based on the intention of behavior performance of online university students is a new approach to improve academic persistence considering the characteristics of students with extensive personal variables, a uniqueness of learning environment. This study aimed to identify the relationship between ASE model including academic stress and academic persistence, and the effect of these factors on academic persistence of online university students. Data were collected from 181 sophomores in K open university from March to June, 2018. Frequency analysis, ${\chi}^2-test$, t-test, F-test, Pearson's correlation analysis, and multiple regression analysis used for data analysis. For factors affecting academic persistence, academic stress (${\beta}=-.16$, p=.016), online learning attitude (${\beta}=.44$, p<.001), and social support among social influential factors (${\beta}=.16$, p=.045) were statistically significant and the prediction model of academic persistence showed 29% explanation power (F=15.76, p<.001). To enhance academic persistence of online university students, it is needed to develop programs to reduce academic stress, improve attitude toward online learning, and improve social support.