• Asian Pacific Journal of Cancer Prevention
• /
• 제16권2호
• /
• pp.707-712
• /
• 2015

Background: To evaluate use of magnetic resonance imaging (MRI) and a logistic model including risk factors for lymph node metastasis for improved diagnosis. Materials and Methods: The subjects were 176 patients with rectal cancer who underwent preoperative MRI. The longest lymph node diameter was measured and a cut-off value for positive lymph node metastasis was established based on a receiver operating characteristic (ROC) curve. A logistic model was constructed based on MRI findings and risk factors for lymph node metastasis extracted from logistic-regression analysis. The diagnostic capabilities of MRI alone and those of the logistic model were compared using the area under the curve (AUC) of the ROC curve. Results: The cut-off value was a diameter of 5.47 mm. Diagnosis using MRI had an accuracy of 65.9%, sensitivity 73.5%, specificity 61.3%, positive predictive value (PPV) 62.9%, and negative predictive value (NPV) 72.2% [AUC: 0.6739 (95%CI: 0.6016-0.7388)]. Age (<59) (p=0.0163), pT (T3+T4) (p=0.0001), and BMI (<23.5) (p=0.0003) were extracted as independent risk factors for lymph node metastasis. Diagnosis using MRI with the logistic model had an accuracy of 75.0%, sensitivity 72.3%, specificity 77.4%, PPV 74.1%, and NPV 75.8% [AUC: 0.7853 (95%CI: 0.7098-0.8454)], showing a significantly improved diagnostic capacity using the logistic model (p=0.0002). Conclusions: A logistic model including risk factors for lymph node metastasis can improve the accuracy of MRI diagnosis of rectal cancer.

• 산업경영시스템학회지
• /
• 제46권4호
• /
• pp.133-141
• /
• 2023

Approximately 40,000 elevators are installed every year in Korea, and they are used as a convenient means of transportation in daily life. However, the continuous increase in elevators has a social problem of increased safety accidents behind the functional aspect of convenience. There is an emerging need to induce preemptive and active elevator safety management by elevator management entities by strengthening the management of poorly managed elevators. Therefore, this study examines domestic research cases related to the evaluation items of the elevator safety quality rating system conducted in previous studies, and develops a statistical model that can examine the effect of elevator maintenance quality as a result of the safety management of the elevator management entity. We review two types: odds ratio analysis and logistic regression analysis models.

• 응용통계연구
• /
• 제19권3호
• /
• pp.587-598
• /
• 2006

본 논문에서는 마이크로어레이 (microarray) 자료에 판별분석을 적용 시 나타나는 고차원 및 소표본 문제의 해결방법으로서 직교요인을 새로운 특징변수로 사용한 비모수적 국소선형 로지스틱 판별분석을 제안한다. 제안된 방법은 국소우도에 기반한 것으로서 다범주 판별분석에 적용될 수 있으며, 고려된 직교인자는 주성분 요인, 부분최소제곱 요인, 인자분석 요인 등이다. 대표적인 두 가지 실제 마이크로어레이 자료에 적용한 결과 직교요인들 중에서 부분최소제곱 요인을 특징변수로 사용한 경우 고전적인 통계적 판별분석보다 향상된 분류 능력을 나타내고 있음을 확인하였다.

• 한국소음진동공학회논문집
• /
• 제20권6호
• /
• pp.555-561
• /
• 2010

Predicted noise level has been used to assess the annoyance response since noise map was generalized and being the normal method to assess the environmental noise. Unfortunately using predicted noise level to derive the annoyance prediction curve caused some problems. The data have to be grouped manually to use the annoyance prediction curve. The aim of this paper is to propose the method to handle the predicted noise level and the survey data for annoyance prediction curve. This paper used the percentage of persons annoyed(%A) and the percentage of persons highly annoyed as the descriptor of noise annoyance in a population. The logistic regression method was used for deriving annoyance prediction curve. It is concluded that the method of dichotomizing data and logistic regression was suitable to handle the predicted noise level and survey data.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.302-305
• /
• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• 대한산업공학회지
• /
• 제40권3호
• /
• pp.342-357
• /
• 2014

The present study analyzes the relationship between research and development (R&D) inputs and performance of a national technology innovation R&D program using successive binary Logistic regression models based on a typical R&D logic model. In particular, this study focuses on to answer the following three main questions; (1) "To what extent, do the R&D inputs have an effect on the performance creation?"; (2) "Is an obvious relationship verified between the immediate predecessor and its successor performance?"; and (3) "Is there a difference in the performance creation between R&D government subsidy recipient types and between R&D collaboration types?" Methodologically, binary Logistic regression models are established successively considering the "Success-Failure" binary data characteristic regarding the performance creation. An empirical analysis is presented analyzing the sample n = 2,178 R&D projects completed. This study's major findings are as follows. First, the R&D inputs have a statistically significant relationship only with the short-term, technical output, "Patent Registration." Second, strong dependencies are identified between the immediate predecessor and its successor performance. Third, the success probability of the performance creation is statistically significantly different between the R&D types aforementioned. Specifically, compared with "Large Company", "Small and Medium-Sized Enterprise (SMS)" shows a greater success probability of "Sales" and "New Employment." Meanwhile, "R&D Collaboration" achieves a larger success probability of "Patent Registration" and "Sales."

• Journal of the Korean Data Analysis Society
• /
• 제20권6호
• /
• pp.2721-2731
• /
• 2018

This study purposes to derive the predictive model for the cold tolerance of Brassica napus, using the data collected in the Tree Breeding Lab of Gyeongsang National University during July and August of 2016. Three Brassica napus samples were treated at each of low temperatures from $4^{\circ}C$ to $-12^{\circ}C$ by decrement of $4^{\circ}C$, step by step, and electrolyte leakage levels were measured at each stage. Electrolyte leakages were observed tangibly from $-4^{\circ}C$. We tried to fit the six nonlinear regression models to the electrolyte leakage data of Brassica napus: 3-parameter logistic model, baseline logistic model, 4-parameter logistic model, (4-1)-parameter logistic model, 3-parameter Gompertz model, and (3-1)-parameter Gompertz model. The baseline levels of the electrolyte leakage estimated by these models were 4.81%, 4.07%, 4.19%, 4.07%, 4.55%, and 0%, respectively. The estimated median lethal temperature, LT50, were $-5.87^{\circ}C$, $-6.31^{\circ}C$, $-6.05^{\circ}C$, $-6.35^{\circ}C$, $-4.98^{\circ}C$, and $-5.15^{\circ}C$, respectively. We compared and discussed the measures of goodness of fit to select the appropriate nonlinear regression model.

• 유통과학연구
• /
• 제21권5호
• /
• pp.31-41
• /
• 2023

Purpose: Electric vehicle (EV) technology started in 2015 in Thailand. The Thai Government has indicated that 30% of all cars produced in Thailand by 2025 will be EVs. Using EVs in Thailand will reduce road pollution and increase energy efficiency, especially in major cities. Hence, the adoption of EVs in the country has been promoted. This study pointed out that social influence, facilitating conditions, perceived enjoyment, environmental concern, attitude, and perceived behavioral control are key factors affecting the behavioral intention to adopt EVs among logistic and distribution firms in Thailand. Research design, data, and methodology: 500 top management, middle management and purchasing managers of logistic and distribution firms in Thailand are surveyed. The study employed judgmental, convenience, and snowball sampling. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) are the main statistical tools for data analysis. Results: The results show that all determinants impact customers' willingness to adopt EVs, except perceived enjoyment and environmental control. Conclusions: The study proposes to promote the incentives by decreasing electricity prices and endorsing EVs purchase to accelerate the adoption of EVs in Thailand. Therefore, future policies should focus on behavioral intention toward EVs amongst logistic and distribution firms for enhancing the future of mobility in Thailand.

• 한국지반공학회논문집
• /
• 제31권6호
• /
• pp.59-69
• /
• 2015

최근 들어 집중호우로 인한 산사태 및 토석류 피해가 종종 발생하고 있다. 이에 따라 산사태 재해 예측에 관한 연구 중 산사태 민감도 분석과 토석류 위험도 분석 관련 연구는 활발하게 진행되어 왔지만, 사면 지역에 적용하기 적합한 전이 분석 관련 연구는 부족한 실정이다. 본 연구에서는 판별분석과 로지스틱 회귀 분석과 같은 통계적 방법을 이용하여 실제 토석류가 발생했던 지역에서 추출한 지형학적 인자, 지질학적 인자 등을 토대로 토석류 전이규준을 제시하였다. 10개의 지형학적 및 지질학적 인자가 독립변수로 사용되었으며 실제 466개소(비전이: 228개소, 전이: 238개소)의 토석류 비전이 및 전이 데이터가 수집되었다. 우선, Fisher의 판별 분석이 수행되었으며, 수행 결과 실제경우와 91.6%의 분류 정확도를 보였다. 하지만 전이와 비전이 두 그룹간의 공분산 동질성이 만족되지 않았으며 또한 독립변수들이 정규분포를 보이지도 않았다. 두 번째로 이항 로지스틱 회귀분석이 수행되었으며, 분석 결과 92.3%의 분류 정확도를 나타냈으며 모든 통계적 조건들도 유의하게 나타났다. 따라서 이항 로지스틱 회귀 분석을 이용한 전이 규준은 토석류 재해 발생 여부를 예측하는데 효과적으로 사용될 수 있을 것으로 판단된다.

• 한국정보처리학회논문지
• /
• 제4권9호
• /
• pp.2309-2314
• /
• 1997

본 연구는 보험 회사의 파산 예측을 위하여 신경회로망이 사용되는데 이를 최적화하기 위하여 유전자 알고리즘이 사용된다. 유전자 알고리즘은 최적의 네트워크 구조와 매개변수들을 제시해 준다. 유전자 알고리즘에 의해 설계된 신경회로망은 파산 예측을 함에 있어 discriminant analysis, logistic regression, ID3, CART 등과 비교되는데 가장 좋은 성능을 보여준다.