• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.404-407
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• 2021

석유개발 현장에서 시추장비의 고장으로 인한 장비교체 및 시추시간 증가는 막대한 비용소모를 발생시킨다. 본 논문은 딥러닝 기반의 시추장비 중 드릴비트의 동력을 구동시키는 디젤엔진의 고장 요소를 분류하고 이 요소에 따른 고장여부를 판별하는 딥러닝 기반의 이상 예측 및 진단 모델을 개발하였다. 또한 제안한 모델의 우수성을 확인하기 위해 로지스틱 회귀분석 분류모델과의 예측성능 비교분석도 수행하였다.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.73-77
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• 2005

본 논문은 시계열에 내재된 설${\cdot}$추석 등 음력 명절효과의 존재를 검정하기 위해 RegARIMA 모형의 잔차에 대한 t-검정 통계량을 제시하였으며 Box-plot에 의한 그래프적 진단을 시도하였다. 제시된 t-검정 결과를 X-12-ARIMA의 AICC-사전검정 및 RegARIMA 모형에 의해 추정된 명절효과 회귀계수의 t-값과 비교하였다. 사용된 명절효과 변수는 Bell과 Hillmer(1983)의 명절효과 변수이다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.25
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• pp.103-113
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• 1992

This paper is to study the various diagnostic measures for detecting outliers and influential cases in linear regression. In this paper we review the most common diagnostic measures and show the inter-relationships the exist among them. Based on the PRESS(Predicted REsidual Sum of Squares ) offered by Allen(1974) as a criterion for model selection, we propose three measures for detecting outliers and influential cases. Examples are given illustrating various diagnostic measures including Proposed measures.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.5
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• pp.83-93
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• 2017

This study proposed the new weighting values and fault points of condition assessment items for reinforced earth retaining walls based on the combination the inspection data and hybrid weighting technique. Utilizing the inspection data of 161 reinforced earth retaining walls, multi regression analysis and entropy technique were applied to gain the weighting values of condition assessment items. In addition, the weighting values by AHP technique was analyzed based on the opinion of experts. By appling hybrid weighting technique to the calculated weighting values obtained by the individual technique, the new weighting values of condition assessment items were proposed, and the fault points and fault indices of reinforced earth retaining walls were proposed. Results showed that the rank of the weighting value of the condition evaluation items was fluctuated according to the multiple regression analysis, AHP technique, and entropy technique. There was no duplication of the rank of the weighting value while the current weighting value was overlapped. Specially, in the rsults of multi regression analysis, two condition assessment items were occupied 70% of the total weights. When the proposed weighting values were applied to existing reinforced earth retaining wall of 161, 16 reinforced earth retaining walls showed the increased risk rank and 31 represented the decreased risk rank.

• Journal of the korean academy of Pediatric Dentistry
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• v.38 no.4
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• pp.317-326
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• 2011

QLF-D system composed with DSLR(digital single-lens reflex) camera, and the images of natural enamel caries and artificial caries was developed from 2 days to 14 days captured by QLF-D system. The correlation between lesion depth of the polarized microscope and luminosity ratio of QLF-D image was analyzed and the results were summarized as follows: 1. The Pearson correlation value between the lesion depth of polarized microscope images and luminosity ratio of QLF-D images was 0.969(p<0.01). 2. From Regression analysis of lesion depth from polarized image by demineralized period, the equation was y = 8.67x - 1.16(p<0.05). 3. From Regression analysis of luminosity ratio from QLF-D image by demineralized period, the equation was y = 3.53x + 6.42(p<0.05). From the results, QLF-D system can detect the enamel caries at the very early stage and can monitor the progression of demineralization and remineralization. For the convenient use of QLF-D system in the laboratory, the image analysing software was needed to analyze of interest site of enamel caries lesion.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.509-512
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• 2010

본 논문에서는 지방환자의 서울진료의 추이와 치료결과를 살펴보기 위해 2005년, 2008년의 퇴원환자 조사 자료를 재원일수를 이용하여 분석하였다. 그 결과 2005년 퇴원환자 333,280명과 2008년 퇴원환자 419,873명의 성별, 연령별, 주진단 분포는 유사한 것으로 나타났으며 치료결과 재원일수는 2005년에 30일 이상이 7.2%, 20~29일이 5.9%인데 비해 2008년은 30일이상이 6.2%, 20~29일 6.0%로 나타나 재원일수는 절감되었다. 전체퇴원환자의 재원일수에 영향을 끼치는 요인에 대해 회귀분석 결과 연도, 성, 보험유형, 의료기관유형, 입원경로, 내원 경유, 주진단, 거주지의 효과를 통제한 후 지방환자의 진료지역에 따른 재원일수를 살펴본 결과 서울이 가장 낮은 것으로 나타났다. 또한 암환자의 재원일수에 영향을 끼치는 요인에 대해서도 연도, 성, 보험유형, 의료기관유형, 입원경로, 내원 경우, 주진단, 거주지의 효과를 통제한 후 지방환자의 진료지역에 따른 재원일수를 살펴본 결과 서울이 가장 낮은 것으로 나타났다. 즉, 지방환가 거주지에서 진료를 받는 것에 비해 서울에서 진료를 받는 것이 치료결과가 짧았다. 이는 타 지역 진료의 간접의료비 영향으로 서울지역에서 조기 퇴원하여 거주지에서 진료하였거나 서울 진료자가 중증도가 낮은 환자가 많아 재원일수가 낮을 수 있다는 것도 배제 할 수 없다. 이에 대한 중증도 보정 후 서울 진료환자의 재원일수가 낮은 요인을 분석하는 추후 연구가 필요하다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.289-290
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• 2022

Arteriosclerosis is a disease in which the carotid vessel wall becomes thick, and it is important to monitor the thickness of the vessel wall for diagnosis. In this study, we propose a model for extracting 324 radiomics features from carotid MRI images and diagnosing arteriosclerosis using machine learning techniques. We learned a total of four classification models: logistic regression, support vector machine, random forest, and XGBoost through radiomics features. XGBoost model, which showed the highest performance in 5-fold cross-validation, shows the results of accuracy 0.9023, sensitivity 0.9517, specificity 0.8035, AUC 0.8776.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.148-148
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• 2022

콩[(Glycine max(L.)]은 우리나라에서 벼와 더불어 주요한 식량작물이다. 농촌진흥청에서는 콩 생육데이터를 수집하여 생산성 향상모델을 개발하기 위해 '농업빅데이터수집및생산성향상모델개발' 사업을 수행하고 있다. 수집되는 콩 데이터는 농가정보, 콩 생육정보, 토양정보 부분으로 구성되어 있으며 농가정보는 시군, 시군구, 품종, 파종량, 종자확보경로 등이 수집되고 있다. 그리고 콩 생육정보는 경장, 줄기굵기, 마디수, 가지수, 꼬투리수, 꼬투리립수, 개체당 입수, 종실수량 등이 수집되어 있다. 토양정보는 수분, 지온, EC 등이 수집되고 있다. 주요 항목의 평균은 경장 47.4 cm, 줄기굵기 11.1 mm 마디수 12.7 개, 꼬투리수 54.0 개, 꼬투리립수 2.7 개, 종실수량 227.9 kg/10a 정도이며 토양수분은 26.3 %, 지온은 27.1 ℃ EC는 2.58 ds/CM 정도이다. 주요 형질의 상관관계는 종실수량과 개체당 협수가 0.651로 나타났으며 가지수, 꼬투리수, 개체당협수와 줄기굵기는 각각 0.783, 0.653, 0.663 정도로 나타났다. 추후 이를 기반으로 다중회귀 등 분석 가능한 방법(머신러닝 등)을 적용하여 콩수량을 예측할 수 있는지 검토할 필요가 있다. 또한 본 사업으로 수집된 자료를 분석하여 콩 수량에 영향을 미치는 주요 요인을 평가한 결과는 콩 생산성 향상을 위한 모델 작성에 중요한 자료로 활용될 수 있을 것으로 예상된다.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.629-643
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• 2014

It is common to check the validity of an assumed model with the heavy use of diagnostics tools when conducting data analysis with regression techniques; however, outliers and influential data points often distort the regression output in undesired manner. Jang and Anderson-Cook (2013) proposed a graphical method called a firework plot for exploratory analysis that could visualize the trace of the impact of possible outlying and/or influential data points on individual regression coefficients and the overall residual sum of squares(SSE) measure. They developed 3-D plot as well as pair-wise plot for the appropriate measures of interest. In this paper, the approach was extended further to tell the strength of their approach; in addition, a more meaningful interpretation was possible by adding a measure not mentioned in their paper. This approach was applied to the mixture experiment because we felt that a detailed analysis of statistical measure sensitivity is required in a small experiment.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.267-275
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• 2013

Among data mining techniques, the association rule is the most recently developed technique, and it finds the relevance between two items in a large database. And it is directly applied in the field because it clearly quantifies the relationship between two or more items. When we determine whether an association rule is meaningful, we utilize interestingness measures such as support, confidence, and lift. Interestingness measures are meaningful in that it shows the causes for pruning uninteresting rules statistically or logically. But the criteria of these measures are chosen by experiences, and the number of useful rules is hard to estimate. If too many rules are generated, we cannot effectively extract the useful rules.In this paper, we designed a variety of non-linear regression equations considering all association thresholds between the number of rules and three interestingness measures. And then we diagnosed multi-collinearity and autocorrelation problems, and used analysis of variance results and adjusted coefficients of determination for the best model through numerical experiments.