• Journal of Korean Society of Forest Science
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• v.76 no.4
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• pp.390-396
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• 1987

The model and its example were provided to predict wood production for a district forest planning. The method of Gentan probability is widely accepted for the prediction of wood production. The suggested model is different in the decision of cutting age distribution from that of Prof. Suzuki; the former can use either Weibull distribution or Gamma distribution, but the latter is possible only by Gamma distribution. This developed system can be used not only for establishing a district forest planning, but also for providing forest management information, such as periodic harvest volume, growing stock, labor requirement, and so forth.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.611-620
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• 2021

The maintenance industry is mainly progressing based on condition-based maintenance after corrective maintenance and preventive maintenance. In condition-based maintenance, maintenance is performed at the optimum time based on the condition of equipment. In order to find the optimal maintenance point, it is important to accurately understand the condition of the equipment, especially the remaining useful life. Thus, using simulation data (C-MAPSS), a prediction model is proposed to predict the remaining useful life of a turbofan engine. For the modeling process, a C-MAPSS dataset was preprocessed, transformed, and predicted. Data pre-processing was performed through piecewise RUL, moving average filters, and standardization. The remaining useful life was predicted using principal component analysis and the k-NN method. In order to derive the optimal performance, the number of principal components and the number of neighbor data for the k-NN method were determined through 5-fold cross validation. The validity of the prediction results was analyzed through a scoring function while considering the usefulness of prior prediction and the incompatibility of post prediction. In addition, the usefulness of the RUL prediction model was proven through comparison with the prediction performance of other neural network-based algorithms.

• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.41-56
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• 2009

The purpose of this paper is to present a statistical model that can predict the rapid shift of users' attention by analyzing the lifecycle patterns of news in a social news aggregation service. Internet news service sites have a distinct characteristic in a sense that users' attention change very quickly in a short period of time. In this research, we propose a regression model for each news category which can model the decay pattern of users' attention and the content promotion policy of a social news aggregator is proven to be a major source of the rapid growth in the popularity of news. The proposed model is expected to be useful for evaluation of the social news aggregation service provider's content promotion policy that attempts to maximize users' attention as well as the diversity of news contents.

• Korean Journal of Food Science and Technology
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• v.23 no.3
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• pp.306-310
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• 1991

A simplified mathematical model to estimate changes in total acidity of Chinese cabbage kimchi during fermentation was developed as a function of temperature and salt concentration. Assuming that tolerable acceptability reached at 0.75% total acidity, the shelf-life of kimchi was predicted by the model. The predicted value was in good agreement with the actual shelf-life measured by organoleptic tests.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.154-156
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• 2017

Constant variance of degradation data over time has been generally assumed to estimate storage lifetime using destructive, accelerated degradation data over time. However, performance data of ammunitions deteriorate over time, and the standard deviation would tend to increase over time. This paper shows storage lifetime comparison results for constant variance and time-variant variance assumptions of degradation data over time, and proposes that time-variant variance assumption should be considered to increase accuracy in lifetime estimation.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.345-348
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• 2011

구조요소의 설계에서 유한요소해석은 매우 효과적인 방법이다. 이 방법은 시험 수행에 드는 시간과 비용을 줄여준다. 그러나 공정 과정과 환경에 의하여 생기는 입력 물성치들의 변화 때문에 우리는 유한요소해석의 결과를 전적으로 믿어서는 안 된다. 따라서 유한요소해석의 신뢰성을 증명하는 것은 매우 중요하다. 본 연구에서는 현장에 축적된 피로 수명 시험 데이터를 바탕으로 유한요소해석을 이용하여 피로수명 파라미터를 역 추정 하는 연구를 수행하였다. 베이지안 접근법을 이용하여 불확실성 피로 수명 파라미터의 사후분포를 구하였고, 마코프체인몬테카를로(Markov Chain Monte Carlo) 기법을 이용하여 역 추정된 파라미터의 샘플 데이터를 생성하였다. 얻어진 샘플 데이터를 기반으로 새로운 형상의 스프링에 대한 피로 수명을 예측한다. 신뢰성 기반 형상 최적화(RBDO)는 서스펜션 코일 스프링의 요구수명을 만족시키기 위하여 수행된다. 또한 크리깅 근사 모델은 유한요소해석의 연산 량 감소를 위해 이용한다.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1993.04a
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• pp.70-79
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• 1993

세라믹은 금속에 비해서 밀도가 낮고, 내마멸성이 우수하고, 열팽창계수가 작고, 높은 온도범위에 걸쳐서 안정성과 경도를 유지함으로 기계구조용재료로서 유망시 되고 있다. 앞으로 세라믹부품에 대한 수요는 더욱 증가하리라고 예상하고 있으며, 세라믹의 응용이 시도되고 있는 부품은 더욱 다양화되어가고 있는 추세이다. 그러나, 세라믹재료에 관한 신뢰할만한 데이터베이스는 확립되지 못한 상태이고, 트라이보시스템에 관한 수명예측과 설계를 위한 기초 자료도 확립하지 못한 상태에 있다. 세라믹재료에 관한 수명예측과 설계를 위해서는 세라믹재료의 트라이보시스템(tribosystem)에서의 마멸기구의 규명과 마멸율을 평가할 수 있는 마멸식을 구하는 것이 가장 기본적인 과제라 할 수 잇다. 따라서 본 연구에서는 최신 기법에 의해서 제조된 HIP제 질화규소와 지르코니아를 실험재료로 하여 무윤활하에서의 미끄럼 마찰$\cdot$마멸실험을 수행하여 마찰$\cdot$마멸특성을 규명하고, SEM을 이용한 마멸면의 미시적 관찰을 통해서 세라믹의 마멸기구를 조사하여 세라믹마멸기구의 마멸모델을 제히하고자 한다. 제시된 마멸모델에 파괴역학을 도입하여 이론해석과 고찰을 수행하여 보다 실용적인 세라믹의 마멸율을 평가할 수 있는 새료운 무차원파라메타를 제안하고자 한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2828-2835
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• 2000

This paper presents the fatigue behavior of composite materials with impact-induced damage. The impact damage parameter is proposed to evaluate the effect of impact damage on fatigue life. Subsequently, a new model is developed to predict the fatigue life of impacted composite materials. Also, a stochastic model is proposed to describe the variation of fatigue life due to the material nonhomogeneity. For these models, the fatigue tests were performed on the unimpacted and impacted composite materials, The effect of impact damage on fatigue life can be characterized by the impact damage parameter. Additionally, the results by the present fatigue life prediction model agree will with experimental results regardless of applied impact energy. Also, the variation of fatigue life can be described by the present stochastic model and is reduced with applied impact energy.

• Composites Research
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• v.14 no.2
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• pp.50-59
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• 2001

The predictions of residual strength evolution and fatigue life of full scale composite rotor blade for multipurpose helicopter were studied using a strength degradation model. Flight-by-flight load spectrum was developed on the basis of FELIX standard spectrum data. The laminated structural analysis was also performed to obtain corresponding local stress and/or strain spectra for each ply of laminate skin and glass roving spar structures around the blade root where fatigue damage was severely anticipated.