• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.605-616
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• 2000

Three primary interests frequently raised by mortgage companies are introduced and the corresponding statistical approaches for the default probability in mortgage companies are examined. Statistical models considered in this paper are time series, logistic regression, decision tree, neural network, and discrete time models. Usage of the models is illustrated using an artificially modified data set and the corresponding models are evaluated in appropriate manners.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4B
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• pp.308-315
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• 2002

This paper proposes new probability models for wideband code division multiple access (W-CDMA) signals. The performance of a W-CDMA system is evaluated by calculating the average bit error rate(BER) which is derived from the probability distribution of the W-CDMA receiver output. If a probability model of the receiver output is available, the performance evaluation becomes much simpler and it enables diverse analyses of the system for channel coding and other purposes. In this paper, probability distributions of W-CDMA signals, more specifically those of the receiver output, are represented as Rayleigh and noncentral chi distribution, considering various bandwidths and channel environments. The adequacy of a probability model is verified by chi-square test of 1% significance level. The BER of the system obtained from the simulation results is compared to that obtained from the probability model to demonstrate the usefulness of the proposed models.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.83-91
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• 2011

This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.

• Research in Mathematical Education
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• v.17 no.1
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• pp.1-14
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• 2013

Stochastic phenomena induce us to construct a probability model and structure our thinking; corresponding models help us to understand and interpret the reality. They in turn equip us with tools to recognize, reconstruct and solve problems. Therefore, various implications in terms of methodology as well as epistemology naturally flow from different adoptions of models for probability. Right from the basic scenarios of different perspectives to explore reality, students are occasionally exposed to misunderstanding and misinterpretations. With realistic examples a multi-faceted image of probability and different interpretation will be considered in mathematical modelling activities. As an exploratory investigation, mathematical modelling activity for probability learning was elaborated through semiotic analysis. Especially, the coherence structure in mathematical modelling discourse was reviewed form a semiotic perspective. The discourses sampled from group activities were analyzed on the basis of semiotic perspectives taxonomical coherence relations.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.1
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• pp.1-6
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• 2006

Queueing models are good models for fragments of communication systems and networks, so their investigation is interesting for theory and applications. Theses queues may play an important role for the validation of different decomposition algorithms designed for investigating more general queueing networks. So, in this paper we illustrate that the batch size distribution affects the loss probability, which is the main performance measure of a finite buffer queues.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.139-149
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• 2002

This paper presents an approach to derive probability models for use in structural reliability studies. Two main points are made. First, that it is possible to translate engineering and physics knowledge into a requirement on the form of a probability model. And second, that making assumptions about a probability model for structural failure implies either explicit or hidden assumptions about material and structural properties. The work is foundational in nature, but is developed with explicit examples taken from planar and general stress problems, the von Mises failure criterion, and a modified Weibull distribution.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.483-491
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• 2010

This study provides the explicit computation of the ruin probability of a Le￠vy process on finite time horizon in Theorem 1 with the help of a fluctuation identity. This paper also gives the numerical results of the ruin probability in Variance Gamma(VG) and Normal Inverse Gaussian(NIG) models as illustrations. Besides, the paths of VG and NIG processes are simulated using the same parameter values as in Madan et al. (1998).

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.77-82
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• 2004

Being in an internet era, the rapid transmission of 3D mesh models is getting more important and efforts toward the compression of various aspects of mesh models have been provided. Even though a mesh model usually consists of coordinates of vertices and properties such as colors and normals, topology plays the most important part in the compression of other information in the models. Despite the extensive studies on Edgebreaker, the most frequently used and rigorously evaluated topology compressor, the probability distribution of its five op-codes, C, R, E, S, and L, has never been rigorously analyzed yet. In this paper, we present probability distribution of the op-codes which is useful for both the optimization of the compression performance and a priori estimation of compressed file size.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.201-209
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• 2013

A new dynamic reliability analysis of structure under repeated random loads is proposed in this paper. The proposed method is developed based on the idea that the probability density of several times random loads can be derived from the probability density of single-time random load. The reliability prediction models of structure based on time responses under several times random loads with and without strength degradation are obtained by using the stress-strength interference theory and probability density evolution method. The resulting differential equations in the prediction models can be solved by using the forward finite difference method. Then, the probability density functions of strength redundancy of the structures can be obtained. Finally, the structural dynamic reliability can be calculated using integral method. The efficiency of the proposed method is demonstrated numerically through a speed reducer. The results have shown that the proposed method is practicable, feasible and gives reasonably accurate prediction.