• Journal of the Society of Naval Architects of Korea
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• v.56 no.2
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• pp.161-167
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• 2019

In general, fatigue analysis is performed by using deterministic model to estimate the optimal parameters. However, the deterministic model is difficult to clearly describe the physical phenomena of fatigue failure that contains many uncertainty factors. With regard to this, efforts have been made in this research to compare with the deterministic model and the stochastic models. Firstly, One deterministic S-N curve was derived from ordinary least squares technique and two P-S-N curves were estimated through Bayesian-linear regression model and Markov-Chain Monte Carlo simulation. Secondly, the distribution of Long-term fatigue damage and fatigue life were predicted by using the parameters obtained from the three methodologies and the long-term stress distribution.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.276-286
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• 2008

In this paper, we introduce an adaptive e-Learning system for engineering mathematics which is based on computer algebra system (Mathematica) and on-line authoring environment. The system provides an assessment tool for individual diagnosis using Bayesian inference network. Using this system, an instructor can easily develop mathematical web contents via web interface. Examples of such content development are illustrated in the area of linear algebra, differential equation and discrete mathematics. The diagnostic module traces a student's knowledge level based on statistical inference using the conditional probability and Bayesian updating algorithm via Netica. As part of formative evaluation, we brought this system into real university settings and analyzed students' feedback using survey.

• The KIPS Transactions:PartA
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• v.14A no.6
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• pp.383-390
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• 2007

This paper describes the e-learning system for science and engineering mathematics using computer algebra system and Bayesian inference network. The best feature of this system is using one of the most recent mathematical dynamic web content authoring model which is called client independent dynamic web content authoring model and using the Bayesian inference network for diagnosing student's learning. The authoring module using computer algebra system provides teacher-user with easy way to make dynamic mathematical web contents. The diagnosis module using Bayesian inference network helps students know the weaker parts of their learning, in this way our system determines appropriate next learning sequences in order to provide supplementary learning feedback.

• The KIPS Transactions:PartA
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• v.16A no.5
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• pp.403-410
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• 2009

In this paper, we present an on-line quiz authoring software that helps teachers create an intelligent on-line quiz. It is designed to give each student appropriate diagnostic report using Bayesian inference networks that represent the relationships among knowledge-items. Once the authors design and edit quizzes in quiz authoring page, the authoring tool automatically produces a knowledge-model based on Bayesian inference network, on-line quizzes, and student report pages. It turns out that the on-line quizzes generated by this tool help students identify their weak parts of subject, make learning strategies for the next learning steps and carry out supplementary learning for their weak knowledge-items.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.29-39
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• 2012

The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.796-801
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• 2009

In medical practice, the diagnosis or prediction models requiring complicated computations are not widely recognized due to difficulty in interpreting the course of reasoning and the complexity of computations. Medical personnel have used the nomograms which are a graphical representation for numerical relationships that enables to easily compute a complicated function without help of computation machines. It has been widely paid attention in diagnosing diseases or predicting the progress of diseases. A nomogram is constructed from a set of clinical data which contain various attributes such as symptoms, lab experiment results, therapy history, progress of diseases or identification of diseases. It is of importance to select effective ones from available attributes, sometimes along with parameters accompanying the attributes. This paper introduces a nomogram construction method that uses a naive Bayesian technique to construct a nomogram as well as a genetic algorithm to select effective attributes and parameters. The proposed method has been applied to the construction of a nomogram for a real clinical data set.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.125-141
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• 2010

The aim of this paper is to develop a web-based Virtual Learning System for discrete mathematics learning using CAS (Computer Algebra System), The system contains a series of contents that are common between secondary und university curriculum in discrete mathematics such as sets, relations, matrices, graphs etc. We designed and developed web-based virtual learning contents contained in the proposed system based on Mathematia, webMathematica and phpMath taking advantages of rapid computation and visualization. The virtual learning system for discrete math provides movie lectures and 'practice mode' authored with phpMath in order to enhance conceptual understanding of each movie lesson. In particular, matrix learning is facilitated with conceptual diagram that provides interactive quizzes. Once the quiz results are submitted, Bayesian inference network diagnoses strong and weak parts of learning nodes for generating diagnostic reports to facilitate personalized learning. As part of formative evaluation, the overall responses were collected for future revision of the system with 10 university students.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.163-165
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• 2003

도메인 지식은 텍스트의 포맷과 의미 정보를 이용하여 웹에 존재하는 텍스트의 다양한 의미를 이해할 수 있도록 도와준다. 그러나 도메인 지식은 텍스트에 데이터의 의미를 표현하는 레이블이 존재하지 알을 경우에 텍스트 인식을 제대로 수행할 수 없기 때문에 무용지물이 되고 만다. 이러한 문제를 해결하기 위해 본 논문에서는 레이블이 존재하지 않는 텍스트의 의미를 효과적으로 추론할 수 있는 엔티티 인식 모델을 제안한다 엔티티 인식 모델은 베이지언 모델과 컨텍스트 정보를 결합한 방법으로서, 구조 분석을 수행한 HTML 문서의 텍스트 토큰에 대해서 어떤 엔티티에 속할 것인가를 결정하는 기능을 수행한다. 실험 결과 본 모델을 사용할 경우 기존에는 레이블이 없어서 인식되지 않았던 텍스트들을 효과적으로 인식하는 것을 확인할 수 있었다.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.3
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• pp.175-181
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• 2020

For the success of a structural integrity management, it is essential to acquire structural response data at some critical locations with limited number of sensors. In this study, the structural response of numerical model was estimated by data fusion approach based on the Kalman filter known as stochastic recursive filter. Firstly, transient direct analysis was conducted to calculate the acceleration and strain of the numerical standing beam model, then the noise signals were mixed to generate the numerical measurement signals. The acceleration measurement signal was provided to the Kalman filter as an information on the external load, and the displacement measurement, which was transformed from the strain measurement by using strain-displacement conversion relationship, was provided into the Kalman filter as an observation information. Finally, the Kalman filter estimated the displacement by combining both displacements calculated from each numerically measured signal, then the estimated results were compared with the results of the transient direct analysis.

• Journal of the Korean School Mathematics Society
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• v.10 no.1
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• pp.27-43
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• 2007

The aim of this paper is to develop a web-based learning system in order to motivate college students in the area of science and engineering to study college calculus. We designed and developed web-based contents, named MathBooster, using Mathematica, webMathematica and phpMath taking advantages of rapid computation and symbolic computation. The features of MathBooster consists of four parts: graphical representation of calculus concepts, textual illustrations of conceptual understanding, example-based step-by-step learning with phpMath, and quizzes with diagnostic feedback. After the MathBooster was practiced with engineering students, the formative evaluation was conducted with survey items composed in four categories: user responses, screen layout, practicing examples and diagnostic feedback in solving quizzes. The overall level of user satisfaction was statistically measured using SPSS. Those results indicate which parts of MathBooster are needed for future enhancement.