• 조명전기설비학회논문지
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• 제30권3호
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• pp.53-58
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• 2016

The underground transmission lines which have been built to expand the suppling facilities will be continuously accompanying with high growth of the increase of power demand in the metropolitan area in recent years. So, it is necessary to maximize the ability and reliability of power supply with the current-carrying capability of the underground transmission lines. Design criteria of KEPCO is to be presented and used frequently. But it has to be studied about the installation methods of power cable buried in ground. In this study, we used the program for calculating the current-carrying capability of underground transmission power cables. We estimated the maximum permissible current values by the horizontal arrangement in the installation methods of power cable(154kV XLPE $600mm^2$) buried ducts in ground. To see the general tendency of the analysis, we researched a statistical analysis with such parameters as the maximum permissible current values. Through the regression analysis, we analyze the most highly values of the maximum permissible current on the Ra type duct arrangement.

• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.171-177
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• 2021

In terms of distribution planning, accurate electric load prediction is one of the most important factors. The future load prediction has manually been performed by calculating the maximum electric load considering loads transfer/switching and multiplying it with the load increase rate. In here, the risk of human error is inherent and thus an automated maximum electric load forecasting system is required. Although there are many existing methods and techniques to predict future electric loads, such as regression analysis, many of them have limitations in reflecting the nonlinear characteristics of the electric load and the complexity due to Photovoltaics (PVs), Electric Vehicles (EVs), and etc. This study, therefore, proposes a method of predicting future electric loads on distribution lines by using Machine Learning (ML) method that can reflect the characteristics of these nonlinearities. In addition, predictive models were developed based on actual data collected at KEPCO's existing distribution lines and the adequacy of developed models was verified as well. Also, as the distribution planning has a direct bearing on the investment, and amount of investment has a direct bearing on the maximum electric load, various baseline such as maximum, lowest, median value that can assesses the adequacy and accuracy of proposed ML based electric load prediction methods were suggested.

• Asian Pacific Journal of Cancer Prevention
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• 제13권5호
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• pp.2355-2362
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• 2012

The SH2B1 adaptor protein is recruited to multiple ligand-activated receptor tyrosine kinases that play important role in the physiologic and pathologic features of many cancers. The purpose of this study was to assess SH2B1 expression and to explore its contribution to the non-small cell lung cancer (NSCLC). Methods: SH2B1 expression in 114 primary NSCLC tissue specimens was analyzed by immunohistochemistry and correlated with clinicopathological parameters and patients' outcome. Additionally, 15 paired NSCLC background tissues, 5 NSCLC cell lines and a normal HBE cell line were evaluated for SH2B1 expression by RT-PCR and immunoblotting, immunofluorescence being applied for the cell lines. Results: SH2B1 was found to be overexpressed in NSCLC tissues and NSCLC cell lines. More importantly, high SH2B1 expression was significantly associated with tumor grade, tumor size, clinical stage, lymph node metastasis, and recurrence respectively. Survival analysis demonstrated that patients with high SH2B1 expression had both poorer disease-free survival and overall survival than other patients. Multivariate Cox regression analysis revealed that SH2B1 overexpression was an independent prognostic factor for patients with NSCLC. Conclusions: Our findings suggest that the SH2B1 protein may contribute to the malignant progression of NSCLC and could offer a novel prognostic indicator for patients with NSCLC.

• 한국콘텐츠학회논문지
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• 제19권2호
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• pp.349-367
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• 2019

부산광역시의 시내버스 준공영제 실시 이후 운영 효율성 요인을 실증적으로 분석하였다. DEA 분석결과, CRS의 경우 지하철 1호선과 환승 가능한 버스노선의 연도별 효율성은 2010년도가 가장 높았다. 지하철 2호선과 환승 가능한 버스노선의 연도별 효율성은 CRS 평균이 연차적으로 점차 향상되어 2016년 0.923로 가장 크게 나타났다. 지하철 3호선과 환승 가능한 버스노선의 연도별 효율성이 2009년부터 2015년까지는 점차 향상되는 모습을 보이다가 2016년도에는 다시 하락하였다. 전체 134개 노선의 4개 연도 536개 노선 중 비효율적으로 나타난 노선은 205개이다. 205개 노선의 효율성을 제고하기 위해서는 규모의 축소 즉, 노선의 운행횟수 등을 감축해야 함을 시사하고 있다. 또한 Tobit 회귀분석을 활용하여 분석결과, 운영 효율성 지수에 유의미한 영향을 미치는 요인으로서는 소요시간이 가장 컸고, 그 다음으로 이용객수, 환승객수의 순으로 나타났다.

• 한국수학교육학회지시리즈A:수학교육
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• 제37권1호
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• pp.1-13
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• 1998

In this paper, we have represented the efficient way how to enumerate the optimal number-right scores to adjust the item difficulty and to improve item discrimination. To estimate the optimal number-right scores in two equivalent math-tests by linear score equating a measurement error model was applied to the true scores observed from a pair of equivalent math-tests assumed to measure same trait. The model specification for true scores which is represented by the bivariate model is a simple regression model to inference the optimal number-right scores and we assume again that the two simple regression lines of raw scores and true scores are independent each other in their error models. We enumerated the difference between mean value of $\chi$＊ and ${\mu}$$\_$$\chi$/ and the difference between the mean value of y＊and a＋b${\mu}$$\_$$\chi$/ by making an inference the estimates from 2 error variable regression model. Furthermore, so as to distinguish from the original score points, the estimated number-right scores y’$\^$*/ as the estimated regression values of true scores with the same coordinate were moved to center points that were composed of such difference values with result of such parallel score moving procedure as above mentioned. We got the asymptotically normal distribution in Figure 5 that was represented as the optimal distribution of the optimal number-right scores so that we could decide the optimal proportion of number-right score in each item. Also by assumption that equivalence of two tests is closely connected to unidimensionality of a student’s ability. we introduce new definition of trait score to evaluate such ability in each item. In this study there are much limitations in getting the real true scores and in analyzing data of the bivariate error model. However, even with these limitations we believe that this study indicates that the estimation of optimal number right scores by using this enumeration procedure could be easily achieved.

• 한국화재소방학회논문지
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• 제28권2호
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• pp.69-75
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• 2014

본 연구에서는 방화발생에 영향을 미치는 요인을 도출하기 위하여 발생건수를 종속변수로 하고 경제 인구 사회적 요인을 독립변수로 하는 다중회귀분석을 실시하였다. 다중회귀분석은 선형함수, 준로그함수, 역준로그함수, 이중로그함수 4가지 함수형태에 대해 적용하였으며, 각 단계별로 변수의 선택과 제외를 고려하는 단계적선택 방식을 적용하였다. 다중공선성 문제와 자기상관 문제를 해결하기 위하여 분산확대지수(VIF)와 Durbin-Watson 계수 이용하였으며, 4가지 함수모형에 대하여 수정된 R 제곱(설명력) 값이 0.935 (93.5%)로 가장 값이 높고 통계적으로 유의한 선형함수모형을 최적의 모형으로 결정하고 모형에 대한 해석을 진행하였다. 선형함수모형 결과 방화발생에 영향을 미치는 요인은 범죄발생건수(0.829), 일반이혼율(0.151), 재정자주도(0.149), 소비자물가상승률(0.099) 순으로 도출되었다.

• 한국철도학회논문집
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• 제16권4호
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• pp.318-330
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• 2013

도시철도를 건설하고 운영하기 위해서는 운영비용 예측이 필요하다. 본 연구에서는 중간규모(MRT)의 도시철도를 대상으로 하여 운영비용 추정함수모형을 개발하였다. 운영비용에 영향을 주는 변수들로서 전동차 보유량, 전동차 편성수, 정거장수, 영업구간(km), 열차운행횟수, 일일수송인원, 차량기지 등의 독립변수를 선정하였다. 이를 바탕으로 Excel 프로그램을 통해서 회귀분석을 수행하였고, 3가지 모형의 운영비용 추정함수모형을 개발하였으며, 모두 적합한 모형으로 나타났다. 이 모형함수들을 적용하여 각 운영사의 운영비를 실제운영비용과 예측비용을 비교하였다. 결과가 모두 비슷하여 유용한 식으로 판단된다. 따라서, 변수조건에 따른 추정함수를 선택사용이 가능하다.

• 대한토목학회논문집
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• 제31권5B호
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• pp.431-438
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• 2011

본 연구에서는 레이더 및 우량계 강우자료가 대수정규분포를 따른다고 가정하는 경우의 편의보정 문제를 살펴보았다. 이를 위해 대수정규분포를 따르는 두 강우자료의 평균, 중앙값 및 최빈값에 대한 회귀선을 유도하였으며, 레이더 강우 보정에 대한 각 회귀선의 효용성을 검토하였다. 추가로 강우자료가 정규분포를 따른다고 가정하는 경우와의 비교를 수행하였다. 본 연구는 2003년 발생한 태풍 매미의 강우자료에 대한 회귀분석 결과를 적용 예로 살펴보았다. 그 결과, 레이더 강우를 독립변수로 적용한 경우, 세 개의 회귀선을 이용한 레이더 강우의 보정결과가 모두 과소 추정된 것으로 나타났다. 반대로 우량계 강우를 독립변수로 한 경우의 세 회귀선에 대한 결과에서는 레이더 강우가 모두 과대 보정되었다. 고려한 경우 중에는 평균값에 대한 결과가 가장 우수한 것으로 나타났다. 그러나 이 경우도 정규분포로 가정하는 경우 중 우량계 강우를 독립변수로 한 원점을 통과하는 회귀선에 비해 열등한 결과를 주는 것으로 확인되었다. 따라서 이를 통해 레이더 강우의 편의 보정에 대수정규분포를 고려한 회귀식을 이용해야 한다고 결론 내리기는 힘들 것으로 보인다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.326-328
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• 2000

The paper proposes the scheme of skew detection for Thai printed document images by using linear regression algorithm. It intends to use with the Thai character recognition systems to reduce the skew detection time. This scheme begins by finding the center of gravity of a document image. This point is used as the starting point for gathering data in the scheme. The data is obtained by scanning incrementally one pixel in vertically with the width of 20-pixels. After the scanning process, if data Is different from it's neighbor more than ${\pm}$ 15 pixels, it will be considered as noise or data in other lines and will be deleted. The last step is the operation by using linear regression algorithm on these selected data and the skew angle will be obtained. The proposed method has been tested with 45 document images with different fonts, sizes and skew angles. The experiment results show that the proposed method can detect the skew angle with the error of less then one degree. The average processing time is about 19 times faster than that of the Hough Transform method.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권1호
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• pp.48-55
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• 2016

Purpose: The purpose of this study is to identify the object-oriented metrics which have strong impact on the reliability and fault-proneness of software products. The reliability and fault-proneness of software product is closely related to the design properties of class diagrams such as coupling between objects and depth of inheritance tree. Methods: This study has empirically validated the object-oriented metrics to determine which metrics are the best to predict fault-proneness. We have tested the metrics using logistic regressions and artificial neural networks. The results are then compared and validated by ROC curves. Results: The artificial neural network models show better results in sensitivity, specificity and correctness than logistic regression models. Among object-oriented metrics, several metrics can estimate the fault-proneness better. The metrics are CBO (coupling between objects), DIT (depth of inheritance), LCOM (lack of cohesive methods), RFC (response for class). In addition to the object-oriented metrics, LOC (lines of code) metric has also proven to be a good factor for determining fault-proneness of software products. Conclusion: In order to develop fault-free and reliable software products on time and within budget, assuring quality of initial phases of software development processes is crucial. Since object-oriented metrics can be measured in the early phases, it is important to make sure the key metrics of software design as good as possible.