• Journal of the military operations research society of Korea
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• v.9 no.2
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• pp.23-30
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• 1983

A simulation study was conducted to determine optimum capacity of Navy drydock facility using GASP-IV, an advanced FORTRAN-based simulation language, under demands of regular overhauls and emergency repairs by ships of an hypothetical fleet composition. Three year dock usage data was analyzed to produce probability distributions underlying drydock repair demands. The present facility size of two drydocks was simulated and was found to be somewhat short of adequate service capability, showing excessive average waiting time and average queue length. The simulation model was then modified to include an additional drydock of similar size as the other two and a year's simulation was again conducted. All repair needs were quite satisfactorily met and all docks showed very high utilization factor (0.98). This contributed to an increase in the fleet's ship availability from 0.95 to 0.99. This study illustrates the usefulness of simulation technique as a tool for analyzing policy alternatives in military long-term investment areas.

• Journal of Powder Materials
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• v.10 no.3
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• pp.201-208
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• 2003

Distributions of diamond particles protruding on the surface of worn diamond segments in circular saw has been investigated. Scanning electron microscope was used to examine the worn ,surface and radial saw blade wear and grinding ratio was measured. The number of protruded diamond particle was approximately 50% of the total number of particles, and that was independent of diamond particle concentration and table speed. It was also noted that the inter-particle distance did not follow a symmetric function like Gaussian distribution function, instead it fitted well with a probability density function based on gamma function. The distribution of inter-particle spacing, therefore, was analyzed using a gamma function model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.313-321
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• 2014

In the current era of data-intensive services, the handling of big data is a crucial issue that affects almost every discipline and industry. In this study, we propose a classification method for large volumes of numeric data, which is implemented in a distributed programming framework, i.e., MapReduce. The proposed method partitions the data space into a grid structure and it then models the probability distributions of classes for grid cells by collecting sufficient statistics using distributed MapReduce tasks. The class labeling of new data is achieved by k-nearest neighbor classification based on Bayesian inference.

• Journal of the Korea Safety Management & Science
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• v.9 no.1
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• pp.145-156
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• 2007

This paper is to propose model classification and evaluation of measurement uncertainty. In order to obtain type A and B uncertainty, variety of measurement mathematical models are illustrated by example. The four steps to evaluate expanded uncertainty are indicated as following; First, to get type A standard uncertainty, measurement mathematical models of single, double, multiple, design of experiment and serial autocorrelation are shown. Second, to solve type B standard uncertainty measurement mathematical models of empirical probability distributions and multivariate are presented. Third, type A and B combined uncertainty, considering sensitivity coefficient, linearity and correlation are discussed. Lastly, expanded uncertainty, considering degree of freedom for type A, B uncertainty and coverage factor are presented with uncertainty budget. SPC control chart to control expanded uncertainty is shown.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.901-909
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• 2013

A skewed double power function distribution is defined by a double power function distribution. We shall evaluate the coefficient of the skewness of a skewed double power function distribution. We shall obtain an approximate maximum likelihood estimator (MLE) and a moment estimator (MME) of the skew parameter in the skewed double power function distribution, and compare simulated mean squared errors for those estimators. And we shall compare simulated MSEs of two proposed reliability estimators in two independent skewed double power function distributions with different skew parameters.

• Journal of the Korean Society of Safety
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• v.25 no.6
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• pp.186-196
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• 2010

It has been well known that traffic accidents occur under combined functional contributions of drivers, vehicles and road facilities, and that evaluation of safety levels for a specific road section or point is generally much complicated. Additionally, most of traffic accidents occur randomly implicating it is necessary to be evaluated in terms of probability theory. Thus, the evaluation model which reflects various characteristics and probabilistic distributions of traffic accidents has been necessary. The present paper provides a reliability based model with variables of probabilistic operating speeds and design speeds together which have been individually explaining associated characteristics in traffic accidents. Consequently, the model made it possible for speed management and road improvement projects to be evaluated in a common index. Application studies were performed in three cases. Through the studies, couples of facts were identified that the model successfully considered the probabilistic operating speeds and design speeds together and that then, the model evaluated road safety alternatives relatively which are complicatedly characterized and differently located.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.191-212
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• 2012

Since a social network by definition is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications, which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary; estimating a user's interests typically involves non-stationary distributions. The consequent time varying nature of the distribution to be tracked imposes stringent constraints on the "unlearning" capabilities of the estimator used. Therefore, resorting to strong estimators that converge with a probability of 1 is inefficient since they rely on the assumption that the distribution of the user's preferences is stationary. In this vein, we propose to use a family of stochastic-learning based Weak estimators for learning and tracking a user's time varying interests. Experimental results demonstrate that our proposed paradigm outperforms some of the traditional legacy approaches that represent the state-of-the-art technology.

• Wind and Structures
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• v.22 no.5
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• pp.525-541
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• 2016

An offshore wind turbine supported by a spar buoy floating platform is the subject of this study on tower and rotor extreme loads. The platform, with a 120-meter draft and assumed to be sited in 320 meters of water, supports a 5 MW wind turbine. A baseline model for this turbine developed at the National Renewable Energy Laboratory (NREL) is employed in stochastic response simulations. The support platform, along with the mooring system consisting of three catenary lines, chosen for loads modeling, is based on the "Hywind" floating wind turbine concept. Our interest lies in gaining an understanding of the dynamic coupling between the support platform motion and the turbine loads. We first investigate short-term response statistics using stochastic simulation for a range of different environmental wind and wave conditions. From this study, we identify a few "controlling" environmental conditions for which long-term turbine load statistics and probability distributions are established.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.21-31
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• 1999

This paper considers how to structure the incentive system between a buy and a single supplier of raw materials when early shipments are forbidden. And this paper is used to take the supplier's behavior into account in the buyer's choice of incentives. Combinations of two types of incentives that the buyer might offer are considered : (1) a fixed value incentive and (2) an incentive that decreases in value as time elapses. Given a desired probability of on time delivery, optimal incentives are found by specifying indifference curves for on time delivery and assessing the expected total cost of incentive schemes along that curve. Difficulties of using incentive to achieve 100% on time delivery are considered and two example flow time distributions are presented.

• Kyungpook Mathematical Journal
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• v.57 no.3
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• pp.493-502
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• 2017

We propose an accurate approximation method via discrete Krawtchouk orthogonal polynomials to the distribution of a sum of independent but non-identically distributed binomial random variables. This approximation is a weighted binomial distribution with no need for continuity correction unlike commonly used density approximation methods such as saddlepoint, Gram-Charlier A type(GC), and Gaussian approximation methods. The accuracy obtained from the proposed approximation is compared with saddlepoint approximations applied by Eisinga et al. [4], which are the most accurate method among higher order asymptotic approximation methods. The numerical results show that the proposed approximation in general provide more accurate estimates over the entire range for the target probability mass function including the right-tail probabilities. In addition, the method is mathematically tractable and computationally easy to program.