• Fire Science and Engineering
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• v.26 no.6
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• pp.24-30
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• 2012

This study is on the method of the detection for flame and series arc which can be happened at poor contact point added a vibration in part of contact point of low voltage line. In general, the causes of electric fire are over current, short circuit, poor contact, ect. The over-current or short circuit among those causes is detected by measuring a instant current value, but poor contact is difficult to detect by measuring a excessive value of the voltage and current and a distortion of waveforms. And therefore, in this paper, it is studied on the optimal technique of the arc judgement using fuzzy logic and MDET (Multi Dimension Estimation Technique). And it carries out the simulation for arc detection and the experiment for controller and load test. In result, the controller and detection algoristhm, is classified with normal wave and abnormal arc wave without relation with each loads and so the controller can detect a series arc successfully.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Horticultural Science & Technology
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• v.33 no.6
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• pp.845-853
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• 2015

The objective of this study was to predict the timing of nitrogen (N) demand through analyzing chlorophyll fluorescence (ChlF), soil-plant analysis development (SPAD), and normalized difference vegetation index (NDVI), which are positively correlated with foliar N concentration in star cluster (Pentas lanceolata). The plants were grown in potting soil under optimal conditions for 30 d, followed by weekly irrigation with five concentrations (0, 4, 8, 16, and 24 mM) of N for an additional 30 d. These five N application levels corresponded to leaf N concentrations of 2.62, 3.48, 4.00, 4.23, and 4.69%, respectively. We measured 13 morphological and physiological parameters, as well as the responses of these parameters to various N-fertilizer treatments. The general increases in Dickson's quality index (DQI), above-ground dry weight (DW), total DW, flowering rate, ${\Delta}F/Fm$', and qP in response to treatment with 0 to 8 mM N were similar to those of SPAD, NDVI, and Fv/Fm. Consistent and strong correlations ($R^2$= 0.60 to 0.85) were observed between leaf N concentration (%) and SPAD, NDVI, ${\Delta}F/Fm$', and above-ground DW. Validation of leaf S PAD, NDVI, and ${\Delta}F/Fm$' revealed that these vegetation indices are accurate predictors of leaf N concentration that can be used for non-destructive estimation of the proper timing for N-solution irrigation of P. lanceolata. Moreover, irrigation with 8 mM N-fertilizer i s recommended w hen leaf N concentration, SPAD, NVDI, and ${\Delta}F/Fm$' ratios are reduced from their saturation values of 4.00, 50.68, 0.64, and 0.137%, respectively.

• Journal of Oral Medicine and Pain
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• v.41 no.3
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• pp.85-90
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• 2016

Purpose: The aim of this study was to develop an automated software to extract tooth and pulpal area from sectional cone-beam computed tomography (CBCT) images, which can guarantee more reproducible, objective and time-saving way to measure pulp/tooth volume ratio. Methods: The software program was developed using MATLAB (MathWorks). To determine the optimal threshold for the region of interest (ROI) extraction, user interface to adjust the threshold for extraction algorithm was added. Default threshold was determined after several trials to make the outline of extracted ROI fitting to the tooth and pulpal outlines. To test the effect of starting point location selected initially in the pulpal area on the final result, pulp/tooth volume ratio was calculated 5 times with different 5 starting points. Results: Navigation interface is composed of image loading, zoom-in, zoom-out, and move tool. ROI extraction process can be shown by check in the option box. Default threshold is adjusted for the extracted tooth area to cover whole tooth including dentin, cementum, and enamel. Of course, the result can be corrected, if necessary, by the examiner as well as by changing the threshold of density of hard tissue. Extracted tooth and pulp area are reconstructed three-dimensional (3D) and pulp/tooth volume ratio is calculated by voxel counting on reconstructed model. The difference between the pulp/tooth volume ratio results from the 5 different extraction starting points was not significant. Conclusions: In further studies based on a large-scale sample, the most proper threshold to present the most significant relationship between age and pulp/tooth volume ratio and the tooth correlated with age the most will be explored. If the software can be improved to use whole CBCT data set rather than just sectional images and to detect pulp canal in the original 3D images generated by CBCT software itself, it will be more promising in practical uses.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.368-376
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• 2004

The estimation of the diffusion coefficients of the Gaussian plume model and the release rate by assimilation of tracer-gas measurements on Younggwang site was tested. Diffusion coefficients were modified by linear programming of both the measurements and the simulated using the Gaussian plume model. The application of the modified diffusion coefficients improved the prediction ability of the Gaussian plume model on both 3 km and 8 km arc lines. And, the release rate of tracer gas was estimated using least squares method. The optimal source rate was estimated by minimizing the errors between the measured concentrations and the computed ones by the Gaussian plume model. The obtained release rate showed a good agreement with the real release rate of the Younggwang experiment in 24%.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.2 s.105
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• pp.158-164
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• 2006

In this paper, we proposed a new algorithm of the inverse scattering for the reconstruction of unknown dielectric scatterers using the finite-difference time-domain method and the design sensitivity analysis. We introduced the design sensitivity analysis based on the gradient information for the fast convergence of the reconstruction. By introducing the adjoint variable method for the efficient calculation, we derived the adjoint variable equation. As an optimal algorithm, we used the steepest descent method and reconstructed the dielectric targets using the iterative estimation. To verify our algorithm, we will show the numerical examples for the two-dimensional $TM^2$ cases.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1245-1256
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• 2014

The physical nature of fatigue shows the considerable amount of scatter from intrinsic and extrinsic factors. In this study, some degradation models, such as the gamma process model, were reviewed in terms of uncertainties associated with the continuous, gradual, and monotonic nature of fatigue crack growth. Statistically varying fatigue crack growth data obtained from Lu and Meeker were used as an example to demonstrate the use of the gamma process model. This model can describe the condition and lifetime as statistical distribution curves whose shapes vary with cycles. From the skewness of the statistical distribution curves, it was confirmed that the median is suitable for being considered as the expected life. The use of the gamma process model enables the optimum replacement period and percentile life to be employed as criteria for preventive maintenance policy.

• Korean Journal of Food Science and Technology
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• v.26 no.6
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• pp.659-664
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• 1994

Waxy rice, Oryza sativa, and foxtail millet, Setaria italitica, and mixture (1 : 1, w/w) of the cereals were saccharified by barley malt. The optimum conditions of saccharification were at $50^{\circ}C$ for 3 hrs on waxy rice and $55^{\circ}C$for 3 hrs on foxtail millet, respectively. The equilibrium of saccharification were reached at $20^{\circ}Brix$ on waxy rice and mixture, and $17^{\circ}Brix$ in foxtail millet. The free sugars in saccharifying liquids were found maltose, glucose and fructose with the contents of ca. 13%, 1% and trace, respectively, by HPLC analysis. The close relationships (r=0.954) between $^{\circ}{Brix}$ and reducing sugar of saccharifying liquids were observed. The result may be useful for the estimation of the end point of the saccharification.

• Journal of Distribution Research
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• v.8 no.1
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• pp.69-89
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• 2003

This study aims to find out the relationship between purchase intention of fashion products and affecting factors. Measurement was not on the general Web environment but on the individual websites. It was modeled that the likeness of shopping malls affects purchase intention. Flow, which Csikszentmihalyi(1990) introduced as the state of optimal experience, was to affect purchase intention through the likeness of shopping malls. In addition, characteristics of fashion products were to affect purchase intention. A structural equation modeling was used for estimation. The result shows that the likeness of shopping malls affect purchase intention more than characteristics of fashion products. The difference from other studies is that the sign of Skills on Flow is negative. The effect of Flow on purchase intention is the largest and the next is the characteristics of the shopping malls. These results imply that internet shopping malls have to increase the likeness of shopping malls in addition to interests of the products. In addition, fashion consciousness was tested as a moderator by dividing the subjects into two groups of high and low fashion consciousness. The result shows that fashion consciousness works as a moderator for the variables affecting purchase intention.

• Nuclear Engineering and Technology
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• v.38 no.1
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• pp.81-92
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• 2006

In this study, the core dynamics of a PWR reactor is identified online by a recursive least-squares method. Based on the identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to designing an automatic controller for the thermal power control of PWR reactors. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, this procedure for solving the optimization problem is repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired temperature, as well as minimizing the variation of the control rod positions. In addition, the objectives are subject to the maximum and minimum control rod positions as well as the maximum control rod speed. Therefore, a genetic algorithm that is appropriate for the accomplishment of multiple objectives is utilized in order to optimize the model predictive controller. A three-dimensional nuclear reactor analysis code, MASTER that was developed by the Korea Atomic Energy Research Institute (KAERI) , is used to verify the proposed controller for a nuclear reactor. From the results of a numerical simulation that was carried out in order to verify the performance of the proposed controller with a $5\%/min$ ramp increase or decrease of a desired load and a $10\%$ step increase or decrease (which were design requirements), it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.