• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1231-1246
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• 2016

Cause-specific hazard model (Prentice et al., 1978) and subdistribution hazard model (Fine and Gray, 1999) are mostly used for the right censored survival data with competing risks. Some other models for survival data with competing risks have been subsequently introduced; however, those models have not been popularly used because the models cannot provide reliable statistical estimation methods or those are overly difficult to compute. We introduce simple and reliable competing risk regression models which have been recently proposed as well as compare their methodologies. We show how to use SAS and R for the data with competing risks. In addition, we analyze survival data with two competing risks using five different models.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.368-376
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• 2021

Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.41-47
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• 2006

The Renewal process and the Non-homogeneous Poisson process (NHPP) process are probably the most popular models for describing the failure pattern of repairable systems. But both these models are based on too restrictive assumptions on the effect of the repair action. For these reasons, several authors have recently proposed point process models which incorporate both renewal type behavior and time trend. One of these models is the Modulated Power Law Process (MPLP). The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose Bayes estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model. Numerical examples illustrate the estimation procedure.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.10a
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• pp.64-69
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• 2003

This paper describes a study on the tearing damage of the ship's bottom plating during a grounding. It has been known widely that difference scaling laws are applied for bodies undergoing simultaneously plastic flow and crack propagation in the deformation of the plate tearing. Especially, the basic scaling law is not followed for the fracture. In this study plate cutting experiments for the geometrically similar models have been performed in order to verify the problem. From the experimental results, it has been observed that the cutting forces and energy for the larger models are significantly lower than those of the smaller models the damage become large. A simplified analytical method for the estimation of tearing is proposed based on the experiments and it has been observed that the results of the present formula are correlated very well with the experiments

• Environmental Analysis Health and Toxicology
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• v.18 no.1
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• pp.1-13
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• 2003

To estimate the annual WTP for risk reduction of environmental problems such as outdoor and indoor air pollution, and drinking water contamination, a questionnaire survey was conducted by dichotomous contingent valuation method in Seoul. Several covariate models based on Turnbull, Weibull and Spike models were developed and applied to WTP estimation with uncertainty analysis. WTP estimates for risk reduction of air pollution were 13,000 won, 12,000 won, and 10,000 won per month in low-bounded Turnbull, Weibull and Spike models, respectively. The estimates for indoor air pollution were 17,000 won,20,000 won and 21,000 won and these for drinking water contamination were 10,000 won, 13,000 won and 14,000 won in each model, respectively. Goodness of fit for Weibull model was better than those for other models. WTP estimates for indoor air pollution were higher than those for other pollution problems.

• Journal of Ocean Engineering and Technology
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• v.18 no.1
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• pp.41-46
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• 2004

This paper describes a study on the tearing damage of a ship's bottom plating, during a grounding. It is widely known that different scaling laws are applied for bodies undergoing simultaneous plastic flow and crack propagation in the deformation of plate tearing. Specifically, the basic scaling law is not followed for the fracture. In this study, in order to verify the problem, plate cutting experiments for geometrically similar models have been performed. From the experimental results, it has been observed that the cutting forces and energy for the larger models are significantly lower than those of the smaller models. A simplified analytical method for the estimation of tearing is proposed, based on the experiments. It has been observed that the results of the present formula are highly correlated with the experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.239-241
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• 2009

In this paper, an estimation methodology for stand-by energy savings of electric appliances is proposed and some case studies are carried out for televisions. The methodology is based on learning curves and diffusion models, which are able to explain the market characteristics such as market prices and the diffusion speed. Some models were developed to estimate power and energy savings for high-efficient appliances and these model have been used broadly. These models are also applied to this study and modified to estimate stand-by energy savings.

• Journal of Korean Society of Water and Wastewater
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• v.10 no.2
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• pp.88-103
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• 1996

The objective of this study is to develop stochastic and deterministic models which could be used to synthesize water application time series. Adaptive models using mulitivariate ARIMA(Transfer Function Model) are developed for daily urban water use forecasting. The model considers several variables on which water demands is dependent. The dynamic response of water demands to several factors(e.g. weekday, average temperature, minimum temperature, maximum temperature, humidity, cloudiness, rainfall) are characterized in the model by transfer functions. Daily water use data of Kumi city in 1992 are employed for model parameter estimation. Meteorological data of Seonsan station are utilized to input variables because Kumi has no records about the meteorological factor data.To determine the main factors influencing water use, autocorrelogram and cross correlogram analysis are performed. Through the identification, parameter estimation, and diagnostic checking of tentative model, final transfer function models by each month are established. The simulation output by transfer function models are compared to a historical data and shows the good agreement.

• The Journal of Society for e-Business Studies
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• v.15 no.1
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• pp.139-155
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• 2010

The purpose of this paper is to develop a framework of software cost estimation guidelines and to derive a mid-long term direction for development of the software cost estimation guidelines. In this paper, all the steps in the software life cycle are researched in the view of cost estimation, and current software cost estimation guidelines and models have been reviewed and analysed first. Second, a plan to separate unit cost per function point from standard procedure in current software cost estimation guidelines is presented to strengthen maket self-regulating function as a mid-long term developmental direction for software cost estimation guidelines. Third, construction of cost repository, making standard procedure for software cost estimation guidelines, development of various kinds of software cost estimation models, and a system for experts on software cost estimation are presented as the prerequisites for the future model framework of software cost estimation guidelines. Finally a roadmap for establishing the future model is proposed.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.495-506
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• 1998

The proposed class of generalized logistic models, indexed by an extra parameter, can be used to model or to examine symmetric or asymmetric discrepancies from the logistic model. When there are a finite number of different design points, we are mainly concerned with maximum likelihood estimation of parameters and in deriving their large sample behavior A score test and a bootstrap hypothesis test are also considered to check if the standard logistic model is appropriate to fit the data or if a generalization is needed .