• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1559-1565
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• 2004

Railway system is consisted of various resources such as rail-line, signal, and railcar. It is necessary to efficiently utilize these limited and expensive resources as much as possible up to given line capacity. So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. In this paper, we present an improved systematic line capacity model. The proposed model has three main components ; TPS(tain performance simulator), PES (parameter evaluation simulator), LCS(line capacity simulator). The concept of each sub-component is described, including the evaluation method of capacity parameters. And capacity parameter evaluation and estimation results using sample line section data are presented.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.748-750
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• 1995

An early detection of cancer is very important for the complete cure of cancer. Therefore, it is considered a diagnosis of cancer via the detection of an abrupt change from the healthy state to the cancerous state. It includes the development of algorithm for the detection of parameter change for conditionally-linear stochastic systems for the cancer diagnosis. The statistical testing is proposed to implement a parameter change algorithm. The detection algorithm studied in this research is based on sequential hypotheses testing in a so-called local asymptotic framework. Here a simple numerical example is provided to highlight some of the concepts and to provide a basis for further investigation. Despite its simplicity this research may have practical application in clinical oncology.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.410-418
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• 1999

This paper describes the use of residual and parameter identification methods for fault detection in an air handling unit. Faults can be detected by comparing expected condition with the measured faulty data using residuals. Faults can also be detected by examining unmeasurable parameter changes in a model of a controlled system using a system identification technique. In this study, AutoRegressive Moving Average with seXtrnal input(ARMAX) and AutoRegressive with eXternal input(ARX) models with both single-input/single-input and multi-input/single-input structures are examined. Model parameters are determined using the Kalman filter recursive identification method. Regression equations are calculated from normal experimental data and are used to compute expected operating variables. These approaches are tested using experimental data from a laboratory's variable-air-volume air-handling-unit.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.126-137
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• 1994

Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Importance of perfomance management is growing as many functions of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to determine the magnitude and direction of parameter adjustment. This paper is the first part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of performance evaluation which utilizes the principle of perturbation analysis of discrete event dynamic systems. The developed algorithm can estimate the network performance under a perturbed protocol parameter setting from observations of the network operations under a nominal parameter setting.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.410-419
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• 2018

Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.103-117
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• 1991

Two important sensitivity issues over shortest path problems have been discussed. One is the problem of updating shortest paths when nodes are added and when the lengths of some arcs are increased or decreased. The other is the problem of calculating arc tolerances, that is the maximum increase of decrease in the length of a single arc without changing a given optimal tree. In this paper, assuming that there exists a parameter of interest whose perturbation causes the simultaneous changes in arc lengths, we find the invariance condition on these simultaneous changes such that the shortest path between two specified nodes remains unchanged.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.501-522
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• 2007

We propose an estimation procedure that can be used for detecting structural changes in the seasonal cointegrated vector autoregressive model. The asymptotic properties of the estimates and the test statistics for the parameter change are provided. A simulation example is presented to illustrate this method and its concept.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.19-30
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• 2006

The purpose of this article is to develop a program for teaching Type I and Type II errors in one sample. In this program, the concepts of two errors are visually explained, and the probabilities of two errors are also visually displayed as the rejection region changes or the sample size changes. Also, in this program, the power curve and the operating characteristic curve are visually displayed in terms of the parameter value of interest.

• Structural Engineering and Mechanics
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• v.27 no.4
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• pp.425-438
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• 2007

Large changes in stiffness associated with cracking and yielding of reinforced concrete sections may be expected to occur during the dynamic response of reinforced concrete frames to earthquake ground shaking. These changes in stiffness in stories that experience cracking might be expected to cause relatively large peak interstory drift ratios. If so, accounting for such changes would add complexity to seismic design procedures. This study evaluates changes in an index parameter to establish whether this effect is significant. The index, known as the coefficient of distortion (COD), is defined as the ratio of peak interstory drift ratio and peak roof drift ratio. The sensitivity of the COD is evaluated statistically for five- and nine-story reinforced concrete frames having either uniform story heights or a tall first story. A suite of ten ground motion records was used; this suite was scaled to five intensity levels to cause varied degrees of damage to the concrete frame elements. Ground motion intensity was found to cause relatively small changes in mean CODs; the changes were most pronounced for changes in suite scale factor from 0.5 to 1 and from 1 to 4. While these changes were statistically significant in several cases, the magnitude of the change was sufficiently small that values of COD may be suggested for use in preliminary design that are independent of shaking intensity. Consequently, design limits on interstory drift ratio may be implemented by limiting the peak roof drift in preliminary design.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3097-3107
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• 1999

Recently many studies have been done on the Random Early Detection(RED) algorithm as an active queue management and congestion avoidance scheme in the Internet. In this paper we first overview the characteristics of RED and the modified RED algorithms in order to understand the current status of these studies. Then we analyze the RED dynamics by investigating how RED parameters affect router queue behavior. We show the cases when RED fails since it cannot react to queue state changes aggressively due to the deterministic use of its parameters. Based on the RED parameter analysis, we propose a self-adaptive algorithm to cope with this RED weakness. In this algorithm we make two parameters be adjusted themselves depending on the queue states. One parameter is the maximum probability to drop or mark the packet at the congestion state. This parameter can be adjusted to react the long burst of traffic, consequently reducing the congestion disaster. The other parameter is the queue weight which is also adjusted aggressively in order for the average queue size to catch up with the current queue size when the queue moves from the congestion state to the stable state.