• 전기의세계
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• v.15 no.5
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• pp.1-5
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• 1966

The stability and safety of operation of a reactor is determined mainly by the sign and magnitude of its reactivity responses to temperature changes. Reactors are subject to temperature fluctuations due to the changes in reactor power and ambient temperature. These temperature fluctuations cause reactivity disturbances through changes in the nuclear and physical properties of the core. Because of these important phenomena by the temperature effects, a large portion of study and testing on a reactor design has been conducted. In this experiment the overall temperature coefficient of the TRIGA MARK-II reactor is measured. The basic procedure is to change the tgemperature of the water moderator, and from the movements of a newly recalibrated control rod(this is necessary due to the effects of fuel burn-up and control rod depression) required to mintain criticality, the reactivity worth of the temperature change is determined. From this measurement, the overall temperature coefficient seems to be smoothly varying, almost a linear function of temperature, and a value of approximately -0.267${\c}$/$^{\circ}C$ can be obtained for an average temperature range from $17.6^{\circ}C$ to $32.5^{\circ}C$.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.873-882
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• 2010

This paper considers a Bayesian approach to replacement policy following the expiration of non-renewing combination warranty. The non-renewing combination warranty is the combination of the non-renewing free replacement warranty and the non-renewing pro-rata replacement warranty. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure times are assumed to follow a Weibull distribution with uncertain parameters, we propose the optimal replacement policy based on the Bayesian approach. The overall value function suggested by Jiang and Ji (2002) is utilized to determine the optimal replacement period. Also, the numerical examples are presented for illustrative purpose.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.3
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• pp.198-207
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• 2012

In product or process parameter design, the case of multiple performance characteristics appears more commonly than that of a single characteristic. Numerous methods have been developed to deal with such multi-characteristic parameter design (MCPD) problems. Among these, this paper considers three representative methods, which are respectively based on the desirability function (DF), grey relational analysis (GRA), and principal component analysis (PCA). These three methods are then used to solve the MCPD problems in ten case studies reported in the literature. The performance of each method is evaluated for various combinations of its algorithmic parameters and alternatives. Relative performances of the three methods are then compared in terms of the significance of a design parameter and the overall performance value corresponding to the compromise optimal design condition identified by each method. Although no method is significantly inferior to others for the data sets considered, the GRA-based and PCA-based methods perform slightly better than the DF-based method. Besides, for the PCA-based method, the compromise optimal design condition depends much on which alternative is adopted while, for the GRA-based method, it is almost independent of the algorithmic parameter, and therefore, the difficulty involved in selecting an appropriate algorithmic parameter value can be alleviated.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.61-77
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• 2011

One of the most important problems in the estimation of the parameter of the failure model, is the cost of experimental sampling units, which can be reduced by using any prior information available about ${\theta}$, and devising a two-stage pooling shrunken estimation procedure. We have proposed an estimator of the reliability function (R(t)) of the exponential model using two-stage time censored data when a prior value about the unknown parameter (${\theta}$) is available from the past. To compare the performance of the proposed estimator with the classical estimator, computer intensive calculations for bias, mean squared error, relative efficiency, expected sample size and percentage of the overall sample size saved expressions, were done for varying the constants involved in the proposed estimator (${\tilde{R}}$(t)).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.617-624
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• 2002

An equation of J-integral for a penny-shaped crack at the end of the fiber embedded in rubber matrix is proposed. The values of J-integral for the specimens with various crack and specimen radius are obtained by FEA(Finite Element Analysis). The dimensional analysis is applied to derive an equation of J-integral as a nonlinear elastic energy release rate. The geometry and deformation calibration function in an equation of J can be expressed in a separated form. The geometry calibration function characterizing the effects of cord and specimen size is expressed in a polynomial form of fourth order. The deformation calibration function characterizes the effect of the overall level of strain. As approaching the infinitesimal strain, the value of the deformation calibration function approaches the results of LEFM(Linear Elastic Fracture Mechanics).

• Architectural research
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• v.3 no.1
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• pp.21-27
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• 2001

This study addressing the underlying strategies for Andong municipal museum complex development is in timely view that Andong has obtained a worldwide reputation as a treasury of traditional Korean Confucian culture. Thus far, there has been a tendency that various local museums are proposed to meet architectural aspirations architects and users commonly hold. Overall, though, the major role they play in making overall city image has not been considered in a systematic manner. Based on Lee's (2001) two previous studies, this study summarized the utility of cognitive distance and cognitive map concepts, which are proposed by Kevin Lunch (1976) to evaluate city image, in planning Andong municipal museum complex (AMMC). Sample is stratified into city residents and outsiders, and also into the general public and design-related professionals to see if there is any group difference in constructing their mental image. Three major findings are obtained. First, familiarity, so-called the degree of knowing, is the function of the length of stay in a designated area. That is, the longer people stay in Andong, the more likely they are familiar with its overall environmental aspects. Second, mental proximity of Andong municipal museum complex relative to existing cultural landmarks is closely related to the degree of how people value those landmarks in terms of their significance. Dosan Seowon and Hahoe folk village are most highly valued, which means higher proximity. Third, functional diversity turned out to be the most important design dimension, while display mechanism are least valued. Cognitive simulations of this sort are meaningful in that projected composite image might be a rough first approximation of true public image.

• Journal of the Korean Society of Food Culture
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• v.34 no.1
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• pp.68-74
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• 2019

This study was conducted to evaluate the effects of adding gradually increasing concentrations of turmeric extract (0, 0.1, 0.2, and 0.4%) to smoked duck meat on its chromaticity, antibiosis, and antiseptic degree against food poisoning bacteria, number of bacteria, lipid rancidity, sensory evaluation, and preference. The brightness, red color intensity and yellow color intensity changed significantly when 0.2% turmeric extract was added and the sodium nitrate concentration was reduced. Additionally, no antibiosis or antiseptic activities against food poisoning bacteria were observed in any turmeric treated samples, whereas the number of bacteria was increased in control samples compared to turmeric treated samples after 10 days of preservation. The TBARS value decreased during storage when turmeric extract concentration increased, resulting in positive sensory evaluation of its color, succulence, taste and hardness. In the preference test, the surface and meat color increased as the concentration of turmeric extracts increased. Hardness was highest at 0.2%, whereas taste was highest between 0.2 and 0.4%. The overall preference test was highest for the 0.2% extract samples. Overall, the results indicated that addition of 0.2% turmeric to smoked duck meat will lead to better nutrition, function, and overall preference.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.133-142
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• 2012

The objective of this study was to correct the bias of the Representative Concentration Pathways (RCP)-based future precipitation data using a quantile mapping method. This method was adopted to correct extreme values because it was designed to adjust simulated data using probability distribution function. The Generalized Extreme Value (GEV) distribution was used to fit distribution for precipitation data obtained from the Korea Meteorological Administration (KMA). The resolutions of precipitation data was 12.5 km in space and 3-hour in time. As the results of bias correction over the past 30 years (1976~2005), the annual precipitation was increased 16.3 % overall. And the results for 90 years (divided into 2011~2040, 2041~2070, 2071~2100) were that the future annual precipitation were increased 8.8 %, 9.6 %, 11.3 % respectively. It also had stronger correction effects on high value than low value. It was concluded that a quantile mapping appeared a good method of correcting extreme value.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3188-3207
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• 2017

In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.