• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

• Journal of the Korean Society of Tobacco Science
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• v.4 no.2
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• pp.57-61
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• 1982

For evaluating kinetic parameters of various reactions and materials a straight- forward method has been studied by the variable heating rate method in DSC analysis. Based on the linear relationship between the logarithm of the heating rate and reciprocal Peak temperature, this method allows calculation of activation energy and the Arrhenius frequency factor by only one observation of the peak temperature versus the heating rate. According to tile D function, D=-In P(x)/dx, to x(=$\frac{E}{RT}$) we can calculate reasonably accurate activation energy, tile Arrhenius factor and the rate constant, and predict half-life times of various materials from the kinetic calculation.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1239-1242
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• 2003

The neural networks are a famous model to learn the nonlinear function or nonlinear system. The main point of neural network is that the difference actual output from desired output is used to update weights. Usually, the gradient descent method is used for the learning process. On training process, if learning rate is too large, neural networks hardly guarantee convergence of neural networks. On the other hand, if learning rate is too small, the training spends much time. Therefore, one major problem in use of neural networks are to decrease the teaming time while neural networks are guaranteed convergence. In this paper, we suggest the model of fuzzy logic to neural networks to calibrate learning rate. This method is to tune learning rate dynamically according to error and demonstrates the optimization of training.

• Communications of the Korean Mathematical Society
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• v.13 no.3
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• pp.603-627
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• 1998

The leaky bucket scheme is a promising method that regulates input traffics for preventive congestion control. In the ATM network, the input traffics are bursty and transmitted at high-speed. In order to get the low loss probability for bursty input traffics, it is known that the leaky bucket scheme with static leaky rate requires larger data buffer and token pool size. This causes the increase of the mean waiting time for an input traffic to pass the policing function, which would be inappropriate for real time traffics such as voice and video. We present the leaky bucket scheme with dynamic leaky rate in which the token generation period changes according to buffer occupancy. In the leaky bucket scheme with dynamic leaky rate, the cell loss probability and the mean waiting time are reduced in comparison with the leaky bucket scheme with static leaky rate. We analyze the performance of the proposed leaky bucket scheme in discrete-time case by assuming arrival process to be Markov-modulated Bernoulli process (MMBP).

• Journal of the Korea Concrete Institute
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• v.12 no.2
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• pp.31-42
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• 2000

This paper discusses the validity of models predicting the compressive strength of concrete subjected to various temperature histories and the shortcomings of existing rate constant model and apparent activation energy concept. Based on the discussion, a modified rate constant model is proposed. The modified rate constant model, in which apparent activation energy is a nonlinear function of curing temperature and age, accurately estimates the development of the experimental compressive strengths by a few researchers. Also, the apparent activation energy of concrete cured with high temperature decreases rapidly with age, but that of concrete cured with low temperature decreases gradually with age. Finally generalized models to predict apparent activation energy and compressive strength are proposed, which are based on the regression results.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.346-353
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• 2002

The steam generator feedwater flow rate in a nuclear power plant was estimated by means of artificial neural networks with the wavelet analysis for enhanced information extraction. The fouling of venturi meters, used for steam generator feedwater flow rate in pressurized water reactors, may result in unnecessary plant power derating. The backpropagation network was used to generate models of signals for a pressurized water reactor. Multiple-input single-output heteroassociative networks were used for evaluating the feedwater flow rate as a function of a set of related variables. The wavelet was used as a low pass filter eliminating the noise from the raw signals. The results have shown that possible fouling of venturi can be detected by neural networks, and the feedwater flow rate can be predicted as an alternative to existing methods. The research has also indicated that the decomposition of signals by wavelet transform is a powerful approach to signal analysis for denoising.

• BMB Reports
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• v.48 no.12
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• pp.677-684
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• 2015

Cardiovascular function is regulated by the rhythmicity of circadian, infradian and ultradian clocks. Specific time scales of different cell types drive their functions: circadian gene regulation at hours scale, activation-inactivation cycles of ion channels at millisecond scales, the heart's beating rate at hundreds of millisecond scales, and low frequency autonomic signaling at cycles of tens of seconds. Heart rate and rhythm are modulated by a hierarchical clock system: autonomic signaling from the brain releases neurotransmitters from the vagus and sympathetic nerves to the heart's pacemaker cells and activate receptors on the cell. These receptors activating ultradian clock functions embedded within pacemaker cells include sarcoplasmic reticulum rhythmic spontaneous Ca²⁺ cycling, rhythmic ion channel current activation and inactivation, and rhythmic oscillatory mitochondria ATP production. Here we summarize the evidence that intrinsic pacemaker cell mechanisms are the end effector of the hierarchical brain-heart circadian clock system.

• Korean Journal of Pharmacognosy
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• v.5 no.4
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• pp.217-222
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• 1974

Oxygen consumption rate has been determined to study the effect of 'Gal Geun Tang' upon stress resistance of rats. The oxygen consumption rate of liver tissue increased slightly when normal rats were given the Gal Geun Tang infusion only. When rats were given the infusion after an injection of typhoid vaccine, the elevated boby temperature and oxygen consumption rate due to typhoid vaccine fell to normal level. From this result, it is concluded that 'Gal Geun Tang' has a function that may normalize abnormally strained liver metabolism. Oxygen consumption rate of the rats significantly increased when rats were exposed to cold condition. However, under the same condition it rather maintained the normal consumption rate when the rats were given previously "Gal Geun Tang". It is suggested that 'Gal Geun Tang' has an effects that impairs the immune response from cold stress. The rats that were given Cinnamomi Ramulus('Ge Ji Tang') showed less effect than the group of 'Gal Geun Tang'.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.52-63
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• 2017

The inventory level of concurrent spare parts (CSP) has a significant impact on the availability of a weapon system. A failure rate function might be of particular importance in deciding the CSP inventory level. We developed a CSP optimization model which provides a compromise between purchase costs and shortage costs on the basis of the Weibull and the exponential failure rate functions, assuming that a failure occurs according to the (non-) homogeneous Poisson process. Computational experiments using the data obtained from the Korean Navy identified that, throughout the initial provisioning period, the optimization model using the exponential failure rate tended to overestimate the optimal CSP level, leading to higher purchase costs than the one using the Weibull failure rate. A Pareto optimality was conducted to find an optimal combination of these two failure rate functions as input parameters to the model, and this provides a practical solution for logistics managers.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.39-49
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• 1997

The objective of this study was to make comparison of the psychophysical MAWLs for different manual materials handling tasks. Lifting activities with four different lifting frequencies (2, 5, 8, 11 lifts/min) for one lifting range from floor to 76cm height were studied. The oxygen consumption rate and heart rate were measured or recorded while subjects were lifting their MAWLs. Psychophysical MAWL decreased from 22.38 kg to 7.48 kg, while th oxygen consumption rate with the MAWL increased from 717.8 ml/min to 1114.7 ml/min as the frequency increased from 2 to 11 Lifts/min. Heart rate also increased from 104.5 to 120.7 bpm. It was found that the relationship between MAWL and frequency can be described best by the exponentaial function with the R-sq value 0.9865 for this study. The percent ratio of oxygen consumption rate with the MAWL and PWC ranged from 28% to 43%.