• 한국소음진동공학회논문집
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• 제12권6호
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• pp.461-468
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• 기술혁신학회지
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• 제10권4호
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• pp.629-653
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• 2007

1998년 이후 한국정부는 산학연계의 성과를 증진시키기 위한 다양한 사업을 펼치고 있다. 본 연구는 대학의 역량요인이 산학협력성과에 어떠한 영향을 미치는지를, 한국의 61개 대학의 산학 협력성과와 역량요인에 관한 자료를 수집하여 다중회귀분석모형을 통해 분석해 보았다. 모형에서 종속변수로는 기술이전료수입, 기술이전건수, 스핀오프기업수 등을 사용하였으며, 독립변수로는 연구역량요인으로 SCI급 논문건수, 국내특허등록건수, 국제특허등록거수를, 관리역량요인으로 기술이 전전담조직의 크기, 기술이전전담인력규모 둥을 사용하였다. 분석결과 기술이전료수입에 대해서는 SCI급 논문 수 및 국제특허등록건수가, 기술이전건수에 대해서는 SCI급 논문수 및 국내특허등록 건수가, 스핀오프기업수에 대해서는 전담조직규모 및 기술이전전문가수가 통계적으로 유의미한 것으로 나타났다. 이러한 연구결과는 향후 산학협력성과를 촉진하기 위한 정부정책이 대학의 연구역량과 관리역량을 동시에 증진하는 방향으로 이루어져야 한다는 시사점을 제시하고 있다.

• 대한의생명과학회지
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• 제16권3호
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• pp.169-177
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• 2010

Osteoporosis is a disease that increases the fracture rates and a major cause of increased mortality and morbidity in the elderly people. This study is to determine which components of body composition and metabolic syndrome risk factors are important to bone health, we analysed the relationship among bone mineral density (BMD), body composition and metabolic syndrome risk factors in females. Totally 630 females participated in a medical check-up program (mean age 47 years) were selected for this study. Body composition analysis was performed by segmental bioelectrical impedance method, muscle mass, and percent body fat were measured. We also measured metabolic syndrome risk factors including abdominal obesity, HDL-cholesterol, triglyceride, blood pressure and fasting glucose level. Metabolic syndrome was defined by NCEP-ATP III criteria. The lumbar spine and femoral neck BMD were measured using the dual energy X-ray absorptiometry. Osteopenia and osteoporosis were observed in 180 and 51 persons, respectively. Muscle mass and HDL-cholesterol decreased in osteopenia and osteoporosis groups compared to the control group, and the grade was shown progressively by the symptoms. Significant positive correlation between BMD and muscle mass was observed. Multi variable regression analyses showed that % body fat and muscle mass were independent predictors of BMD after adjustment of age, height and weight. In conclusion, the BMD showed negative correlation with the metabolic and body composition was associated with BMD.

• 로봇학회논문지
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• 제4권1호
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• pp.10-16
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• 2009

This paper is concerned with Korean students' attitudes towards robots, presenting two survey studies. The first study was concerned with a group of college students, taking the perspective of international comparison. Data were collected by administering an online survey, where 106 volunteer students had participated. In the survey, the Negative Attitude towards Robot Scale(NARS) was adopted to compare the Korean students' scores with those of multi-national groups (U.S.A, Germany, Netherland, Japan, Mexico, and China) who responded to the same scale in Bartneck et al.'s research. The analysis of the data reveals that Korean students tend to be more concerned about social impacts that robots might bring to future society and are very conscious about the uncertain influences of robots on human life. The second study investigated factors that may affect K-12 students' attitudes towards robots, with survey data garnered from 298 elementary, middle, and high school students. The data were analyzed by the method of multiple regression analysis to test the hypothesis that a student's gender, age, the extent of interest in robots, and the extent of experiences with robots may influence his or her attitude towards robots. The hypothesis was partially supported in that variables of a student's gender, age, and the extent of interest in robots were statistically significant with regard to the attitude variable. Given the results, this paper suggests three points of discussions to better understand Korean students' attitudes towards robots: social and cultural context, individual differences, and theory of mind.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.1086-1092
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.

• 한국해양공학회지
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• 제35권4호
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• pp.257-265
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• 2021

Many studies have been performed to predict a reliable and accurate stress-range distribution and fatigue damage regarding the Gaussian wide-band stress response due to multi-peak waves and multiple dynamic loads. So far, most of the approximation models provide slightly inaccurate results in comparison with the rain-flow counting method as an exact solution. A step-by-step study was carried out to develop new approximate spectral moments that are close to the rain-flow counting moment, which can be used for the development of a fatigue damage model. Using the special parameters and bandwidth parameters, four kinds of parameter-based combinations were constructed and estimated using the R-squared values from regression analysis. Based on the results, four candidate empirical formulas were determined and compared with the rain-flow counting moment, probability density function, and root mean square (RMS) value for relative distance. The new approximate spectral moments were finally decided through comparison studies of eight response spectra. The new spectral moments presented in this study could play an important role in improving the accuracy of fatigue damage model development. The present study shows that the new approximate moment is a very important variable for the enhancement of Gaussian wide-band fatigue damage assessment.

• 대한지리학회지
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• 제49권3호
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• pp.405-422
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• 2014

부동산 가격을 추정하기 위한 헤도닉 모형(hedonic model)의 적용에서 가장 중요한 사안은 모형의 정확한 구성과 하부시장의 구획이라 할 수 있다. 모형의 구성에 대해서는 비교적 활발한 개선 노력이 있었으나 하부시장 구획은 상대적으로 큰 관심을 받지 못하였다. 그러나 부동산 가격형성 과정의 공간적 범위 파악이 선행되지 않으면 헤도닉 모형의 적용 결과는 그 정확성이 저하될 수밖에 없다. 본 연구는 헤도닉 모형의 성능 개선에 초점을 두고, 서울시 25개 자치구 중 상대적으로 이질적인 부동산 집단으로 구성된 강남구와 비교적 균일한 부동산 집단으로 이루어진 중랑구를 사례지역으로 하여 하부시장 구획을 시도하였다. 먼저 하부시장 구획을 위한 투입변수로 혼합 GWR(Mixed GWR) 모형에서 산출된 가변 회귀계수(variable coefficients)를 사용하였다. 헤도닉 모형의 회귀계수는 부동산을 구성하는 속성항목(attributes)의 잠재가격(shadow price)으로 해석할 수 있기 때문이다. 다음으로 공간적으로 연접된 하부시장을 구획하기 위해 최소신장트리(minimum spanning tree)에 기반한 SKATER 앨고리듬을 사례지역에 적용하였다. 마지막으로 다수준 모형(multi-level model)을 적용하여 구획된 하부시장 결과의 적정성을 검토하였다. 검토 결과, 중랑구는 하부시장이 존재하지 않음을, 강남구는 간선도로를 중심으로 한 5개의 하부시장으로 구분하는 것이 합리적임을 확인하였다. 간선도로와 같은 도시의 인프라는 하부시장 구획에 있어 지금까지 큰 주목을 받지 못한 변수였으나 본 연구를 통해 그 중요성이 실증적으로 확인되었다.

• 한국동물위생학회지
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• 제32권3호
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• pp.265-273
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• 2009

A cross-sectional survey was undertaken to identify risk factors and clinical signs associated with parasitic helminth infections of cattle in Mymensignh district of Bangladesh. A nonrandom convenience sampling method was used to select 138 animals from 40 farmers/herds. The eggs per gram of faeces (epg) for nematodes and trematodes were determined by McMaster and Stoll's methods respectively. Animal-level and herd-level data were recorded by means of a questionnaire. Multi-collinearity amongst explanatory variables were assessed using $2{\times}2{\times}\;X^2$ test and one variable in a pair was dropped if $P{\leq}0.05$ formultiple logistic regression models. Association study between outcome and explanatory variables was conducted using classification tree, random forests and multiple logistic regression. A positive epg was considered as infected. Analyses were performed using $STATA^{(R)}$, version 8.0/Intercooled and $R^{(R)}$, Version 2.3.0. Seventy eight percent of the cattle were found to be infected with at least one type of helminth. Twenty four pairs of combinations of explanatory variables showed significant associations. Male animals (OR=3.3, P=.006, 95% CI=1.4, 7.7) were associated with significantly increased prevalence of nematode infection. Female cattle of the study area are mostly cross-breed, kept indoor, fed relatively good diet and not used for draught purpose. Males are used for draught purpose thereby more exposed to nematode infective stage and provided with relatively poor diet. So stressed male cattle may become more susceptible to nematode infection. All of the three statistical techniques selected gender and lumen motility as most important variables in association with nematode infection in cattle. The result of this survey can only be extrapolated to the periurban cattle population of traditional management system.

• Ocean and Polar Research
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• 제40권1호
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• pp.1-13
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• 2018

Previous studies have indicated a great regional difference in Sea Level Rise (SLR) in the Pacific and it has been suggested that this is linked to climate variability over the past two decades. In this study, we seek to identify the possible linkage between regional sea level and Pacific climate variability from altimetry-based sea level data (1993-2012) and further investigate how the Pacific sea level has changed spatially and temporally over the past 60 years from long-term sea level reconstruction data (1953-2008). Based on the same method as Zhang and Church (2012), the Inter-annual Climate Index (ICI) associated with the El $Ni{\tilde{n}}o-Southern$ Oscillation (ENSO) and the Decadal Climate Index (DCI) associated with Pacific Decadal Oscillation (PDO) are defined and then the multiple variable linear regression is used to analyze quantitatively the impact of inter-annual and decadal climate variability on the regional sea levels in the Pacific. During the altimeter period, the ICI that represents ENSO influence on inter-annual time scales strongly impacts in a striking east-west "see-saw mode" on sea levels across the tropical Pacific. On the other hand, the decadal sea level pattern that is linked to the DCI has a broad meridional structure that is roughly symmetric in the equator with its North Pacific expression being similar to the PDO, which largely contributes to a positive SLR trend in the western Pacific and a negative trend in the eastern Pacific over the two most recent decades. Using long-term sea level reconstruction data, we found that the Pacific sea levels have fluctuated in the past over inter-annual and decadal time scales and that strong regional differences are presented. Of particular interest is that the SLR reveals a decadal shift and presents an opposite trend before and after the mid-1980s; i.e., a declining (rising) trend in the western (eastern) Pacific before the mid-1980s, followed by a rising (declining) trend from the mid-1980s onward in the western (eastern) Pacific. This result indicates that the recent SLR patterns revealed from the altimeters have been persistent at least since the mid-1980s.

• 지능정보연구
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• 제26권1호
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• pp.23-45
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• 2020

기업의 경쟁력 확보를 위해 판별 알고리즘을 활용한 의사결정 역량제고가 필요하다. 하지만 대부분 특정 문제영역에는 적합한 판별 알고리즘이 어떤 것인지에 대한 지식은 많지 않아 대부분 시행착오 형식으로 최적 알고리즘을 탐색한다. 즉, 데이터셋의 특성에 따라 어떠한 분류알고리즘을 채택하는 것이 적합한지를 판단하는 것은 전문성과 노력이 소요되는 과업이었다. 이는 메타특징(Meta-Feature)으로 불리는 데이터셋의 특성과 판별 알고리즘 성능과의 연관성에 대한 연구가 아직 충분히 이루어지지 않았기 때문이며, 더구나 다중 클래스(Multi-Class)의 특성을 반영하는 메타특징에 대한 연구 또한 거의 이루어진 바 없다. 이에 본 연구의 목적은 다중 클래스 데이터셋의 메타특징이 판별 알고리즘의 성능에 유의한 영향을 미치는지에 대한 실증 분석을 하는 것이다. 이를 위해 본 연구에서는 다중 클래스 데이터셋의 메타특징을 데이터셋의 구조와 데이터셋의 복잡도라는 두 요인으로 분류하고, 그 안에서 총 7가지 대표 메타특징을 선택하였다. 또한, 본 연구에서는 기존 연구에서 사용하던 IR(Imbalanced Ratio) 대신 시장집중도 측정 지표인 허핀달-허쉬만 지수(Herfindahl-Hirschman Index, HHI)를 메타특징에 포함하였으며, 역ReLU 실루엣 점수(Reverse ReLU Silhouette Score)도 새롭게 제안하였다. UCI Machine Learning Repository에서 제공하는 복수의 벤치마크 데이터셋으로 다양한 변환 데이터셋을 생성한 후에 대표적인 여러 판별 알고리즘에 적용하여 성능 비교 및 가설 검증을 수행하였다. 그 결과 대부분의 메타특징과 판별 성능 사이의 유의한 관련성이 확인되었으며, 일부 예외적인 부분에 대한 고찰을 하였다. 본 연구의 실험 결과는 향후 메타특징에 따른 분류알고리즘 추천 시스템에 활용할 것이다.