• Journal of Korea Water Resources Association
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• v.30 no.2
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• pp.155-163
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• 1997

In this study, drought analysis of annual flows of Jindong, Hyunpoong, and Waekwan stations located at Nakdong River Basins was performed based on multivariate stochastic models. The stochastic models used were multivariate autoregressive model (MAR) and multivariate contemporaneous (MCAR) model. MCAR(1) and MAR(1) models were selected to be a appropriate models for these stations based on skewness test of normality, test of uncorrelated residuals, and correlograms of the residual series of each model. The statistics generated by MCAR(1) model and MAR(1) model resembled very closely those computed from historical series. The drought characteristics such as run len호, run sum, and run intensity were fairly well reproduced for the various lengths of generated annual flows based on the MCAR(1) and MAR(1) models. Thus, these drought characteristics may give the important informations in planning mid or long term water supplying systems.

• ETRI Journal
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• v.40 no.1
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• pp.39-50
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• 2018

More people prefer using rail traffic for travel or for commuting owing to its convenience and flexibility. The railway scenario has become an important communication scenario in the fifth generation era. The communication system should be designed to support high-data-rate demands with seamless connectivity at a high mobility. In this paper, the channel characteristics are studied and modeled for the railway tunnel scenario with straight and curved route shapes. On the basis of measurements using the "Mobile Hotspot Network" system, a three-dimensional ray tracer (RT) is calibrated and validated for the target scenarios. More channel characteristics are explored via RT simulations at 25.25 GHz with a 500-MHz bandwidth. The key channel parameters are extracted, provided, and incorporated into a 3rd-Generation-Partnership-Project-like stochastic channel generator. The necessary channel information can be practically realized, which can support the link-level and system-level design of the communication system in similar scenarios.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.2
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• pp.21-36
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• 1979

Static muscle contractions when prolonged or frequently repeated result in discomfort, fatigue, and musculosketal injuries. An analytic and quantitative model has been developed in order to expand the working knowledge on muscle fatigue. In this paper, three Markov models of muscle fatigue are developed. These models are based on motor unit fatigue-recovery characteristics obtained from information on motor unit behavior as it relates to fatigue and graded exertions. Three successively more realistic models are developed that involve: (1) homogeneous motor units with intensity-dependent fatigue rates and state-independent recovery rates (the HMSI model); (2) homogeneous motor units, intensity-dependent fatigue rates and state-dependent recovery rates (the HMSD model); and (3) non-homogeneous motor units (i.e., Type S and Type F), intensity-dependent fatigue rates and state-dependent recovery rates (the HMSD model). The result indicate that a simple stochastic model provide a means to analyze the complex nature of muscle fatigue in sequential static exertions.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.687-695
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• 2009

The Bayesian multiple change-point estimation has been applied to the daily means of ozone and PM10 data in Seoul for the period 1999. We focus on the detection of multiple change-points in the ozone and PM10 bivariate vectors by evaluating the posterior probabilities and Bayesian information criterion(BIC) using the stochastic approximation Monte Carlo(SAMC) algorithm. The result gives 5 change-points of mean vectors of ozone and PM10, which are related with the seasonal characteristics.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.199-202
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• 2001

This article deals with stochastic reliability systems that include a repair facility and unreliable machines: the main facility of working and an auxiliary facility of "super-reserve" machines. The number of super-reserve machines are random number with a arbitrarily distribution and working machines break down exponentially. Defective machines line up for repair, whose durations are arbitrarily distributed. Refurbished machines return to the main facility. If the main facility is restored to its original quantity, the repair facility leaves on routine maintenance until all of super-reserve machines are exhausted. Then, the busy period is regenerated. The whole system also falls into the category of closed queues, with more options than those of basic models. The techniques include two-variate Markov and semi-regenerative processes, and a duality principle, to find the probability distribution of the number of intact machines. Explicit formulas obtained demonstrate a relatively effortless use of functionals of the main stochastic characteristics (such as expenses due to repair, maintenance, waiting, and rewards for higher reliability) and optimization of their objective function. Applications include computer networking, human resources, and manufacturing processes.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.3-12
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• 2002

Monte-Carlo simulation technique has advantages over deterministic simulation in various engineering analysis since Monte-Carlo simulation can take into consideration of scattering of various design variables, which is inherent characteristics of physical world. In this work, Monte-Carlo simulation of steady-state cornering behavior of a truck with design variables like hard points and busing stiffness. The purpose of the simulation is to improve understeer gradient of the truck, which exhibits a small amount of instability when the lateral acceleration is about 0.4g. Through correlation analysis, design variables that have high impacts on the cornering behavior were selected, and significant performance improvement has been achieved by appropriately changing the high impact design variables.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.04a
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• pp.145-150
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• 1999

In the nonlinear dynamic structural analysis, the given ground excitation as an input should be well defined. Because of the lack of recorded accelerograms in Korea, it is required to generate an artificial earthquake by a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms. It is well known that earthquake motions are generally non-stationary with time-varying intensity and frequency content. Many researchers have proposed non-stationary random process models. Yeh and Wen (1990) proposed a non-stationary stochastic process model which can be modeled as components with an intensity function, a frequency modulation function and a power spectral density function to describe such non-stationary characteristics. This paper shows the process to generate nonstationary artificial earthquake ground motions considering target design response spectrum chosen by ATC14.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.117-126
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• 1992

This study proposes a new interactive multicriteria method for determining the best levels of the decision variables needed to optimize a stochastic computer simulation with multiple response variables. The method, called the Pairwise Comparison Stochastic Cutting Plane (PCSCP) method, combines good features from interactive multiple objective mathematical programming methods and response surface methodology. The major characteristics of the PCSCP algorithm are: (1) it interacts progressively with the decision maker (DM) to obtain his preferences, (2) it uses good experimental design to adequately explore the decision space while reducing the burden on the DM, and (3) it uses the preference information provided by the DM and the sampling error in the responses to reduce the decision space. This paper presents the basic concepts of the PCSCP method along with its performance for solving randomly selected test problems.

• Journal of ILASS-Korea
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• v.5 no.2
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• pp.43-52
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• 2000

Numerical simulation of steady, non-evaporating hollow-cone sprays interacting with concentric annular air jets is performed using the discrete stochastic particle method in KIVA. The spray characteristics such as SMD, mean droplet velocity, liquid volume flux, air/liquid mass ratio, and droplet number density arc obtained and compared with the measurements involving different air flow rates in large and small annuli. Overall satisfactory agreement is achieved between calculation and experiment except for the deviation in the downstream SMD arising from uncertainty in the size distribution function at injection, and inaccuracy in the averaged spray parameters due to the small volumes of axisymmetric 2-D sector meshes close to the axis.

• Magazine of the Korean Society of Agricultural Engineers
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• v.18 no.4
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• pp.4232-4241
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• 1976

This study was carried out to clarify the stochastic characteristics of monthly rainfalls and to select a proper model for generating the sequential monthly rainfall amounts. The results abtained are as follows: 1. Log-Normal distribution function is the best fit theoretical distribution function to the empirical distribution of monthly rainfall amounts. 2. Seasonal and random components are found to exist in the time series of monthly rainfall amounts and non-stationarity is shown from the correlograms. 3. The Monte Carlo model shows a tendency to underestimate the mean values and standard deviations of monthly rainfall amounts. 4. The 1st order Markov model reproduces means, standard deviations, and coefficient of skewness with an error of ten percent or less. 5. A correlogram derived from the data generated by 1st order Markov model shows the charaterstics of historical data exactly. 6. It is concluded that the 1st order Markov model is superior to the Monte Carlo model in their reproducing ability of stochastic properties of monthly rainfall amounts.