• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.39 no.4
• /
• pp.1-9
• /
• 2002

The distribution characteristics of data retention time for DRAM was studied in connection with the probability distribution of the cell parameters. Using the cell parameters and the transient characteristics of cell node voltage, data retention time was investigated. The activation energy for dielectric layer growth on cell capacitance, the recombination trap energy for leakage current in the junction depletion region, and the sensitivity characteristics of sense amplifier were used as the random variables to perform the Monte Carlo simulation, and the probability distributions of cell parameters and distribution characteristics of cumulative failure bit on data retention time in DRAM cells were calculated. we found that the sensitivity characteristics of sense amplifier strongly affected on the tail bit distribution of data retention time.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2005.05a
• /
• pp.1129-1132
• /
• 2005

Based on a discrete-time version of the distributional Little's law, we present a simple computational procedure to obtain the queue-length distribution of the discrete-time GI/G/1 queue from its waiting-time distribution that is available by various existing methods. We also discuss our numerical experience and address a couple of remarks on possible extensions of the procedure.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.2D
• /
• pp.251-258
• /
• 2006

This study is to develop an estimation method of freeway design capacity through the analysis of time headway distribution in continuum flow. Traffic flow-speed diagram and time headway distribution plotted from individual vehicle data shows: a) a road capacity is not deterministic but stochastic, b) time headway distribution for each vehicle speed group follows pearson type V distribution. The freeway design capacity estimation model is developed by determining a minimum time headway for capacity with stochastic method. The estimated capacity values for each design speed are lower when design speed ${\leq}80km/h$, and higher when design speed ${\geq}106km/h$ in comparison with HCM(2000)'s values. In addition, The distinguish difference is that this model leads flexible application in planning level by defining the capacity as stochastic distribution. In detail, this model could prevent a disutility to add a lane for only one excess demand in a road planning level.

• Industrial Engineering and Management Systems
• /
• v.12 no.3
• /
• pp.281-287
• /
• 2013

In this paper, we introduce a roots method that uses the roots inside the unit circle of the associated characteristics equation to evaluate the steady-state system-length distribution at three epochs (pre-arrival, arbitrary, and post-departure) and sojourn-time distribution in GI/PH/1 queueing model. It is very important for an air base to inspect airplane oil because low-quality oil leads to drop or breakdown of an airplane. Since airplane oil inspection is composed of several inspection steps, it sometimes causes train congestion and delay of inventory replenishments. We analyzed interarrival time and inspection (service) time of oil supply from the actual data which is given from one of the ROKAF's (Republic of Korea Air Force) bases. We found that interarrival time of oil follows a normal distribution with a small deviation, and the service time follows phase-type distribution, which was first introduced by Neuts to deal with the shortfalls of exponential distributions. Finally, we applied the GI/PH/1 queueing model to the oil train congestion problem and analyzed the distributions of the number of customers (oil trains) in the queue and their mean sojourn-time using the roots method suggested by Chaudhry for the model GI/C-MSP/1.

• Journal of Digital Contents Society
• /
• v.8 no.1
• /
• pp.77-83
• /
• 2007

The handoff area is the region where a call can be handled by the base station in any of the adjacent cells, and duration time is viewed as the time a mobile station resides in the handoff area. In this paper, probability distribution about hand off time one of important parameter at traffic modelling in mobile communication system was estimated. First, point statistic is applied using sample data obtained from simulation result to choose the group of distribution of handoff duration time. Second, parameters are estimated to decide specific distribution function. For this, the value of parameters is calculated using MLE(Maximum Likelihood Estimate.) and goodness of fit test is performed. finally these results show that handoff duration time follows gamma distribution.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.14 no.23
• /
• pp.1-6
• /
• 1991

The physical distribution service(PDS) is essential to evaluate the business logistics system. The PDS combines the inventory service with the lead time to deliver. This paper is presented to model Mixed Zero-One integer programming which is to determine distribution center location and to allocation products, considering delivery lead time, from given candidate locations to given customer markets. A numerical example is given to demonstrate the applicability of Mixed Zero-One integer programming for Distribution-Location problem.

• Proceedings of the KSME Conference
• /
• 2001.06d
• /
• pp.104-109
• /
• 2001

The time to measure the size distribution using Condensation Nuclei Counter(CNC) and Differential Mobility Analyzer(DMA) can be shortened by classifying particles ramping the DMA voltage exponentially and continuously. In measurement, particles sampled at different time are mixed together going through sampling tube and CNC. Because the size distribution is inversed by using detector responses to sampling time intervals in this accelerated method, the mixing effects give inversion errors to the size distribution. The mixing effects can be considered by appling the transfer function with mixing effects to the data inversion. The inversion considering this effects gives birth to the size distribution shifted to the opposite direction of the size scanning.

• IE interfaces
• /
• v.17 no.4
• /
• pp.450-458
• /
• 2004

S-Distribution Center supplies parts to three plants of K-automobile manufacturing company. Since the three plants employ the JIT production system, it is important for S-Distribution Center to deliver small quantities of parts frequently and quickly on time. This paper presents a case study on the improvement of order-picking operation in S-Distribution Center. The study is focused on the reductions of move time and waiting time by redesigning the parts storage location, picking-order terminal location, retrieval policy, and equipment operation policy. The proposed operation system for S-Distribution Center is evaluated through a simple computation analysis and computer simulation. Furthermore, the reducible numbers of equipment and order pickers are investigated by performing a sensitivity analysis.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.2
• /
• pp.308-313
• /
• 2009

This paper presents a reliability analysis of S-bonds for AF track circuits, which detect train movement and transmit a speed control signal to the train. Field survey shows that S-bonds are exposed to very large vibrations transferred from rail, and suffer from frequent failures when they were installed on ballasted track. We collected the time-to-failure data of S-bonds from the maintenance field of Seoul metro line 2, and made a parametric approach to estimate the statistical distribution that fits the time-to-failure data. The analysis shows that S-bonds have time-to-failure characteristics described by Weibull distribution. The estimated shape parameter of Weibull distribution is 1.1, which means the distribution has constant failure rate characteristics like exponential distribution. The reliability function, hazard function, percentiles and mean lifetime are derived for maintenance support.

• Journal of Applied Reliability
• /
• v.17 no.3
• /
• pp.188-196
• /
• 2017

Purpose: The purpose of this research is to determine optimal replacement age using non-informative prior information and Bayesian method. Methods: We propose a novel approach using Bayesian method to determine the optimal replacement age in block replacement policy by defining the prior probability with data on failure time and repair time. The Marcov Chain Monte Carlo simulation is used to investigate the asymptotic distribution of posterior parameters. Results: An optimal replacement age of block replacement policy is determined which minimizes cost and nonoperating time when no information on prior distribution of parameters is given. Conclusion: We find the posterior distribution of parameters when lack of information on prior distribution, so that the optimal replacement age which minimizes the total cost and maximizes the total values is determined.