• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.502-508
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• 2014

In this paper, a delay-dependent $H_{\infty}$ filtering problem is investigated for discrete-time delayed nonlinear systems which include a more general sector nonlinear function instead of employing the commonly used Lipschitz-type function. By using the Lyapunov-Krasovskii functional approach, a less conservative sufficient condition is established for the existence of the desired filter, and then, the corresponding solvability condition guarantee the stability of the filter with a prescribed $H_{\infty}$ performance level. Finally, two simulation examples are given to show the effectiveness of the proposed filtering scheme.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.62-69
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• 2020

Most people suffer from stress during day life because modernized society is very complex and changes fast. Because stress can affect to many kind of physiological phenomena it is even considered as a disease. Therefore, it should be detected earlier, then must be released. When a person is being stressed several bio-signals such as heart rate, etc. are changed. So, those can be detected using medical electronics techniques. In this paper, stress assessment system is studied using random forest algorithm based on heart rate, RR interval and Galvanic skin response. The random forest model was trained and tested using the data set obtained from the bio-signals. It is found that the stress assessment procedure developed in this paper is very useful.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.201-208
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• 2010

This research is about developing an efficient solution procedure for the vehicle routing problem under varying vehicle moving speeds for hour-based time interval. Different moving speeds for every hour is too difficult condition to solve for this type of combinatorial optimization problem. A methodology to divide the 12 hour based time interval offered by government into 5 different time intervals and then divide delivery area into 12 small divisions first and then re-organizing them into 5 groups. Then vehicle moving speeds are no longer varying in each of the 5 divisions. Therefore, a typical TSP solution procedure may be applied to find the shortest path for all 5 divisions and then connect the local shortest paths to form a delivery path for whole area. Developed solution procedures are explained in detail with 60 points example.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.1
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• pp.170-176
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• 2001

An optimization problem to obtain the optimal replacement interval considering the salvage values is studied. The system is minimally repaired at failure and is replaced by new one at age T(periodic replacement policy with minimal repair of Barlow and Hunter〔2〕). Our model assumes that the time horizon associated with the number of replacements is random The total expected cost considering the salvage values with random time horizon is obtained and the optimal replacement interval minimizing the cost is found by numerical methods. Comparisons between non-considered salvage values and this case are made by a numerical example.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1862-1870
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• 2016

A respiration is one of the most useful techniques for vital checking and an abnormal respiration is often the earliest sign of critical illness. Detection of respiration is based on the photo-plethysmography (PPG) with photodiode technique. Because PPG sensor using photodiode can be easily miniaturized, it is suitable for wearable devices. A system to measure respiration rate based on PPG signal is implemented and for a reliable measurement an improved algorithm in accuracy using PPG signal pattern is proposed in this paper. As results regarding to three types of respirations (regular interval, free interval, and weak respiration) the proposed algorithm showed error rate of 0.047, 0.067, and 0.122 respectively.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.60-70
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• 1998

When driving the expected loss generated by the quality deviation, Taguchi(1991b) assumed that an objective characteristic has the uniform distribution in its control limit. But it is reasonable to assume that an objective characteristic has the normal distribution than the uniform distribution. Since the triangular distribution is similar to the normal distribution and easy to handle as well, in this article, we first find the optimum measurement interval and the optimum control limit under the triangular distribution. Under the normal assumption, the modified method is compared to Taguchi's. Secondly we find the numerical value solution of the optimum measurement interval and the optimum control limit under the normal distribution.

• Applied Chemistry for Engineering
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• v.9 no.2
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• pp.300-305
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• 1998

Kinetics of termonomer emulsion polymerization during interval II (i.e, after completion of latex particle formation) were studied through pseudo-homopolymerization (PHP) method. Extended Smith-Ewart equation and equation of instantaneous polymer composition are respectively reduced to the corresponding equation for homopolymerization by defining average rate constants. Average number of radicals per particle and instantaneous polymer compositions were respectively predicted by varying termonomer composition within latex particles for systems containing no more than one growing radical per particle. Styrene-Methyl methacrylate-Acrylonitrile (SMA) system was used for model calculation.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.17-28
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• 1994

A statistical procedure is developed to estimate the relative difference between two parameters each obtained from either true model or approximate model. Double sample procedure is applied to find the additional number of simulation runs satisfying the preassigned absolute precision of the confidence interval. Two types of parameters, mean and standard deviation, are considered as the performance measures and tried to show the validity of the model by examining both queues and inventory systems. In each system it is assumed that there are three distinct means and their own standard deviations and they form the simultaneous confidence intervals but with control in the sense that the absolute precision for each confidence interval is bounded on the limits with preassigned confidence level. The results of this study may contribute to some situations, for instance, first, we need a statistical method to compare the effectiveness between two alternatives, second, we find the adquate number of replications with any level of absolute precision to avoid the unrealistic cost of running simulation models, third, we are interested in analyzing the standard deviation of the output measure, ..., etc.

• Journal of the military operations research society of Korea
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• v.10 no.2
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• pp.61-73
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• 1984

A block replacement policy using items with different reliability is discussed. We divide system unit failure modes into two modes and use less reliable unit when operating unit fails near the planned preventive replacement time. In this policy, item A has two failure modes. Mode-1 failure is removed by minimal repair, mode-2 failure by replacement. If mode-2 failure of item A happens in (0, $T-{\delta}$), failure item A is replaced by new item A. If mode-2 failure of item A happens in ($T-{\delta}$, T), failure item A is replaced by new item B. Item B should be cheaper and less durable than item A. Under this policy, we determine the preventive replacement interval $T^{*}$ and the interval ${\delta}^{*}$ of item B replacement which minimize the cost rate per unit time.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.101-109
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• 2008

In general, non-stationary or chaos time series forecasting is very difficult since there exists a drift and/or nonlinearities in them. To overcome this situation, we suggest a new prediction method based on multiple model TS fuzzy predictors combined with preprocessing of time series data, where, instead of time series data, the differences of them are applied to predictors as input. In preprocessing procedure, the candidates of optimal difference interval are determined by using con-elation analysis and corresponding difference data are generated. And then, for each of them, TS fuzzy predictor is constructed by using k-means clustering algorithm and least squares method. Finally, the best predictor which minimizes the performance index is selected and it works on hereafter for prediction. Computer simulation is performed to show the effectiveness and usefulness of our method.