• Journal of Korean Society of Water and Wastewater
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• v.16 no.6
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• pp.710-716
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• 2002

A General Pipe Break Prediction Model that incorporates linear and exponential models in its form is developed. The model is capable of fitting pipe break trends that have linear, exponential or in between of linear and exponential trend by using a weighting factor. The weighting factor is adjusted to obtain a best model that minimizes the sum of squared errors of the model. The model essentially plots a best curve (or a line) passing through "cumulative number of pipe breaks" versus "break times since installation of a pipe" data points. Therefore, it prevents over-predicting future number of pipe breaks compared to the conventional exponential model. The optimal replacement time equation is derived by using the Threshold Break Rate equation by Loganathan et al. (2002).

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.04a
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• pp.181-188
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• 1994

Generally, the structural material shows rate dependent behaviors, which require to constitute different strain-stress relations according to strain rates. Conventional rate- independent constitutive equations used in general purpose finite analysis programs are inadequate for dynamic finite strain problems. In this paper, a rate dependent constitutive equation for elastic-plastic material was developed. The plastic stretch rate was modeled based on slip model with dislocation velocity and density so that there is no yielding condition, and no loading conditions. Non-linear hardening rule was also introduced for finite strain. Material constants of present constitutive equation were determined by experimental data of mild steel. The constitutive equation was applied to uniaxile tension. It was appeared that the present constitutive equation well simulates rate dependent behaviors of mild steel.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.93-101
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• 1995

We present a brief survey concerning the relations between mean residual life and failure rate. Change points of mean residual life and failure rate are known to be different in general and we explore such situations in this paper. A few parametric models which show bathtub-shaped failure rate are examined in details, including the shape of its corresponding mean residual life function. We give some graphical comparisons of trend changes of mean residual life and failure rate for various choices of parameters for each parametric model.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.12
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• pp.68-74
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• 1991

This paper proposes a HMM model based on fuzzy, as a method on the speech recognition of speaker-independent. In this recognition method, multi-observation sequences which give proper probabilities by fuzzy rule according to order of short distance from VQ codebook are obtained. Thereafter, the HMM model using this multi-observation sequences is generated, and in case of recognition, a word that has the most highest probability is selected as a recognized word. The vocabularies for recognition experiment are 146 DDD are names, and the feature parameter is 10S0thT LPC cepstrum coefficients. Besides the speech recognition experiments of proposed model, for comparison with it, we perform the experiments by DP, MSVQ and general HMM under same condition and data. Through the experiment results, it is proved that HMM model using fuzzy proposed in this paper is superior to DP method, MSVQ and general HMM model in recognition rate and computational time.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.65-75
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• 1989

A general software reliability model is developed, which includes the Jelinski-Moranda model, the Goel-Okumoto model, the Shanthikumar model and the Ross model as special cases. In each of above models estimators of the software failure rate and the number of remaining errors are presented and compared in terms of the expected absolute error loss and the expected squared error loss by a Monte Carlo simulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.39-47
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• 1993

In this paper, We develop performance evaluation model for Twin fork Automated Storage/Retrieval systems. The system is modeled as a modified bulk service queueing system consisting of one exponential server with limited system capacity. The differance between this model and general bulk service queueing model is the inequality of transition service rate of each stage. The ejective of this model is to provide system characteristics for Twin fork AS/R system design problems, which are the number of customers in system, wait time in system and queue, the system queue size.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.06a
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• pp.129-134
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• 2003

In this paper, we determine optimal reduction in the lead time and setup cost for some stochastic inventory models. And we propose more general model that allow the backorder rate as a control variable. We first assume that the lead time demand follows a normal distribution. And we assume that the backorder rate is dependent on the length of lead time through the amount of shortages. The stochastic models analyzed in this paper are the classical continuous and periodic review policy models with a mixture of backorders and lost sales. For each of these models, we provide a sufficient conditions for the uniqueness of the optimal operating policy. We also develop algorithms for solving these models and provide illustrative numerical examples.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.1-9
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• 2020

Interest rate spreads indicate the conditions of the economy and serve as an indicator of the recession. The purpose of this study is to predict Korea's interest rate spreads using US data with long-term continuity. To this end, 27 US economic data were used, and the entire data was reduced to 5 dimensions through principal component analysis to build a dataset necessary for prediction. In the prediction model of this study, three RNN models (BasicRNN, LSTM, and GRU) predict the US interest rate spread and use the predicted results in the SVR ensemble model to predict the Korean interest rate spread. The SVR ensemble model predicted Korea's interest rate spread as RMSE 0.0658, which showed more accurate predictive power than the general ensemble model predicted as RMSE 0.0905, and showed excellent performance in terms of tendency to respond to fluctuations. In addition, improved prediction performance was confirmed through period division according to policy changes. This study presented a new way to predict interest rates and yielded better results. We predict that if you use refined data that represents the global economic situation through follow-up studies, you will be able to show higher interest rate predictions and predict economic conditions in Korea as well as other countries.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2923-2925
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• 1999

The objective of camera calibration is to determine the internal optical characteristics of camera and 3D position and orientation of camera with respect to the real world. Calibration procedure applicable to general purpose cameras and lenses. The general method to revise the accuracy rate of calibration is using mathematical distortion of lens. The effective og calibration show big difference in proportion to distortion of camera lens. In this paper, we propose the method which calibration distortion model by using neural network. The neural network model implicity contains all the distortion model. We can predict the high accuracy of calibration method proposed in this paper. Neural network can set properly the distortion model which has difficulty to estimate exactly in general method. The performance of the proposed neural network approach is compared with the well-known Tsai's two stage method in terms of calibration errors. The results show that the proposed approach gives much more stable and acceptabke calibration error over Tsai's two stage method regardless of camera resolution and camera angle.

• Journal of Pharmaceutical Investigation
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• v.20 no.2
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• pp.79-88
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• 1990

A numerical model for diffusion and dissolution controlled transport from dispersed matrix is presented. The rate controlling process for transport is considered to be diffusion of drug through a concentration gradient coupled with time-dependent surface change and/or disappearance of the dispersed drug in response to the dissolution. The transport behavior of drug was explained in terms of ${\nu}$ parameter: ${\nu}$ value means a ratio of diffusion time constant and dissolution time constant. This general model has wide range of application from where release is controlled by the diffusion rate to where release is governed by the dissolution rate. Based on this model, theoretical drug concentration, particle size distributions in the polymer matrix system and the resulting release rate were also investigated.