• 대한기계학회논문집A
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• 제27권10호
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• pp.1785-1792
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• 2003

Methods to predict fatigue crack growth are compared in a quantitative manner for crack growth test data of 2024- T351 aluninum alloy under narrow and wide band random loading. In order to account for the effect of load ratio, crack closure model, Hater's equation and NASGRO's equation have been employed. Load interaction effect under random loading has been considered by crack closure model, Willenborg's model and Wheeler's model. The prediction method using the measured crack opening results provides the best result among the prediction methods discussed for narrow and wide band random loading data.

• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1263-1272
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• 2014

경시적 범주형자료 (longitudinal categorical data)는 의학, 보건학, 그리고 사회과학에서 많이 발생하는 자료이다. 이러한 자료는 반복측정으로 인한 결과치들의 상관관계를 설명하면서 공변량의 효과를 설명해야 한다. 이 논문에서 모집단에 대한 공변량의 효과를 추정하면서 우도함수에 기초한 모형인 주변화 변량효과모형 (marginalized random effects model)을 소개하고, 그 모형의 어떻게 발전했는지를 고찰한다. 그리고 실제 자료를 이용하여 제시된 모형을 설명한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2532-2553
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• 2014

In Asiacrypt 2003, Al-Riyami and Paterson proposed the notion of certificateless cryptography, a technique to remove key escrow from traditional identity-based cryptography as well as circumvent the certificate management problem of traditional public key cryptography. Subsequently much research has been done in the realm of certificateless encryption and signature schemes, but little to no work has been done for the identification primitive until 2013 when Chin et al. rigorously defined certificateless identification and proposed a concrete scheme. However Chin et al.'s scheme was proven in the random oracle model and Canetti et al. has shown that certain schemes provable secure in the random oracle model can be insecure when random oracles are replaced with actual hash functions. Therefore while having a proof in the random oracle model is better than having no proof at all, a scheme to be proven in the standard model would provide stronger security guarantees. In this paper, we propose the first certificateless identification scheme that is both efficient and show our proof of security in the standard model, that is without having to assume random oracles exist.

• 국토계획
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• 제54권3호
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• pp.106-118
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• 2019

In order to develop pedestrian navigation service that provides optimal pedestrian routes based on pedestrian satisfaction levels, it is required to develop a prediction model that can estimate a pedestrian's satisfaction level given a certain condition. Thus, the aim of the present study is to develop a pedestrian satisfaction prediction model based on three machine learning algorithms: Logistic Regression, Random Forest, and Artificial Neural Network models. The 2009, 2012, 2013, 2014, and 2015 Pedestrian Satisfaction Survey Data in Seoul, Korea are used to train and test the machine learning models. As a result, the Random Forest model shows the best prediction performance among the three (Accuracy: 0.798, Recall: 0.906, Precision: 0.842, F1 Score: 0.873, AUC: 0.795). The performance of Artificial Neural Network is the second (Accuracy: 0.773, Recall: 0.917, Precision: 0.811, F1 Score: 0.868, AUC: 0.738) and Logistic Regression model's performance follows the second (Accuracy: 0.764, Recall: 1.000, Precision: 0.764, F1 Score: 0.868, AUC: 0.575). The precision score of the Random Forest model implies that approximately 84.2% of pedestrians may be satisfied if they walk the areas, suggested by the Random Forest model.

• 한국IT서비스학회지
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• 제14권4호
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• pp.121-135
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• 2015

Ensemble classification is to utilize multiple classifiers instead of using a single classifier. Recently ensemble classifiers have attracted much attention in data mining community. Ensemble learning techniques has been proved to be very useful for improving the prediction accuracy. Bagging, boosting and random subspace are the most popular ensemble methods. In random subspace, each base classifier is trained on a randomly chosen feature subspace of the original feature space. The outputs of different base classifiers are aggregated together usually by a simple majority vote. In this study, we applied the random subspace method to the bankruptcy problem. Moreover, we proposed a method for optimizing the random subspace ensemble. The genetic algorithm was used to optimize classifier subset of random subspace ensemble for bankruptcy prediction. This paper applied the proposed genetic algorithm based random subspace ensemble model to the bankruptcy prediction problem using a real data set and compared it with other models. Experimental results showed the proposed model outperformed the other models.

• Structural Engineering and Mechanics
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• 제90권1호
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• pp.41-49
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• 2024

In recent years, China's high-speed railway (HSR) line continues to expand into seismically active regions. Analyzing the features of earthquake rail irregularity is crucial in this situation. This study first established and experimentally validated a finite element (FE) model of bridge-track. The FE model was then combined with earthquake record database to generate the earthquake rail irregularity library. The sample library was used to construct a model of desired earthquake rail irregularity based on signal processing (SFT) and hypothesis principle. Finally, the effects of random pier height and random span number on desired irregularity were analyzed. Herein, an equivalent method of calculating earthquake rail irregularities for random structures was proposed. The results of this study show that the amplitude of desired irregularity is found to increase with increasing pier height. When calculating the desired irregularity of a structure with unequal pier heights, the structure can be regarded as that with equal pier heights (taking the largest pier height). For a structure with the span number large than 9, its desired irregularity can be considered equal to that of a 9-span structure. For the structures with both random pier heights and random span number, their desired irregularities are obtained by equivalent calculations for pier height and span number, respectively.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 추계학술발표회
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• pp.543-547
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• 2003

We applied the modified invasion percolation (MIP) model to the migration of DNAPL within a two-dimensional random fracture network. The MIP model was verified against laboratory experiments, which was conducted using a two-dimensional random fracture network model. The results showed that the MIP needs modification. To remove TCE trapped in a random fracture network, the density-surfactant-motivated removal method was applied and found very effective to remove TCE from dead-end fractures.

• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.296-302
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• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.

• 응용통계연구
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• 제30권6호
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• pp.957-981
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• 2017

관측되지 않는 효과 또는 고정효과로 설명할 수 없는 분산 구조가 포함되어 정확한 모수 추정이 어려운 경우 체계적인 분석을 위해 일반화 선형 모형은 임의효과가 포함된 일반화 선형 혼합 모형으로 확장되었다. 본 연구에서는 일반화 선형 모형 중에서도 이분적인 반응변수를 다루는 로지스틱 회귀모형에 임의효과를 포함한 최대 우도 추정 방법을 설명한다. 그중에서도 라플라스 근사법, 가우스-에르미트 구적법, 적응 가우스-에르미트 구적법 그리고 유사가능도 우도에 대한 최대우도 추정법을 자세히 알아본다. 또한 제안한 방법을 사용하여 한국 복지 패널 데이터에서 정신건강과 생활만족도가 자원봉사활동에 미치는 영향에 대해 분석한다.

• 대한교통학회지
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• 제20권5호
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• pp.67-79
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• 2002

교통량, 교통밀도, 교통류 속도 등, 교통류 변수에 대한 현재까지의 불확실한 정의와 연속적 파동방정식의 거시적 교통류 해석상의 문제점을 지적하고 이를 개선하기 위해 교통류 변수들에 대한 새로운 확률적 정의를 제시하고 이들의 성격을 규명하였다. 이러한 새로운 교통류 변수들에 대한 새로운 정의를 바탕으로 미시적 운전자 행동을 세밀하게 수용할 수 있고 많은 교통환경에서 연속적 파동 방정식을 대체하여 교통류 변수들과 통행시간을 예측할 수 있는 미분방정식 체계를 확률 미분방적식을 이용하여 도출하였다. 도출된 미분 방정식을 단일 차량의 시공 괘적에 적용해 보았다.