• Journal of the East Asian Society of Dietary Life
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• v.16 no.4
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• pp.429-437
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• 2006

The quality of Jeung-pyun made with frozen rice batter was evaluated according to variations in the freezing temperature of the batter. The physicochemical sensory and rheological characteristics of Jeung-pyun were analyzed. The rice batter was stored at -20$^{\circ}C$, -40$^{\circ}C$, and -70$^{\circ}C$ for up to 4 weeks. Statistical data analysis was completed using the SAS program. The pH, and brix percentage of Jeung-pyun batter decreased during the fermentation. In carbon dioxide evolution during fermentation, the levels of the sample stored at -40$^{\circ}C$:, and -70$^{\circ}C$ for 3$\sim$4 weeks were significantly higher than that of the sample stored at -20$^{\circ}C$. The Jeung-pyun moisture content was not significantly affected by freezing temperature or storage times. Specific volume of Jeung-pyun made with rice batter stored at -40$^{\circ}C$, and -70$^{\circ}C$ for 4 weeks was significantly higher than that stored at -20$^{\circ}C$. In sensory evaluation of the stored sample for 4 weeks, the overall quality of Jeung-pyun was not significantly different between with the control and the -20$^{\circ}C$ sample, and between the control and the -40$^{\circ}C$ sample. Among the rheological properties measured with a rheometer on Jeung-pyun made with batter stored sample for 4 weeks at -20$^{\circ}C$, -40$^{\circ}C$ and unfrozen batter, the hardness was increased over the storage time, but the difference was not significant. In conclusion, the most suitable freezing temperature of the rice batter for the manufacture of Jeung-pyun was proposed to be -40$^{\circ}C$.

• The Korean Journal of Applied Statistics
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• v.4 no.2
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• pp.117-127
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• 1991

Coefficient of determination $R^2$ is most frequently used descriptive measure in practical use of linear regression analysis. But there have been controversies on defining this measure in the cases of linear regression without the intercept, weighted linear regression and robust linear regression. Several authors such as Kvalseth(1985) and Willet and Singer(1988) proposed many variations of $R^2$ to meet the situations. However, theire measures are not satisfactory due to the lack of a universal principle. In this study, we propose a unfied approach to defining the coefficient of determination $R^2$ using the concept of likelihood distance. This new measure is in good accordance with typical $R^2$ in linear regression and, moreover, can be applied to nonlinear regression models and generalized linear models such as logit and log-linear models.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.93.1-93.1
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• 2013

The Earth's radiation belts consist of an inner belt and an outer belt, being separated by the slot region. It is well known that the variations of the inner edge of the outer belt and the location of the plasmapause (Lpp) are closely related to each other. Different waves exist inside and outside the plasmasphere, playing different roles in the particle dynamics. The plasmapause is well known to be influenced by solar wind conditions and geomagnetic disturbances. Therefore, it is important to precisely determine the location of the plasmapause and develop a prediction scheme. In this study, we identified the location of the plasmapause using the plasma density data from the Time History of Events and Macroscale Interactions During Substorms (THEMIS). The plasmapause is determined by requiring density gradient of a factor of 15 within L-change = 0.5. We statistically determined Lpp as a function of preceding geomagnetic indices. Also, we determined the relations between Lpp and preceding solar wind conditions by estimating correlation coefficients. These relations give us predicting models of Lpp as a function of preceding solar wind parameters and geomagnetic indices. As our database covers a period over the ascending phase from near-sunspot minimum, our statistical results differ somewhat from previous works that cover near-sunspot maximum. Finally, we give some comparative examples obtained from the Van Allen Probes data.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.15 no.4
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• pp.214-223
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• 2003

A reliability analysis is straightforwardly applied to the sloped coastal structures against the random wave overtopping. A reliability function can be directly derived from a empirical formula in which may take into account many variables associated with the random wave overtopping. The probability of failure exceeded the allowable overtopping discharge can be evaluated as a function of dimensionless crest height with some reasonable statistical properties and distribution functions of each random variable. Some differences of probabilities of failure occurred from variations of the slopes of structures as well as types of armour are investigated into quantitatively. Additionally, the effects of the crest width of units placed in front of the concrete cap on the probability of failure may be analyzed. Finally, the sensitivity analyses are carried out with respect to the uncertainties of random variables. It is found that the overall characteristics similar to the known experimental results are correctly represented in this reliability analyses. Also, it should be noted that the probabilities of failure may be quantitatively obtained for several structural and hydraulic conditions, which never assess in the deterministic design method. Thus, it may be possible for determination on the crest height of sloped coastal structures to consider the probability of failure of wave overtopping, by which may be increased the efficiency of practical design.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.208-217
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• 2020

The classification of plant diseases by images captured by a camera sensor has been studied over past decades. A method that has gained much interest is to use image segmentation, from which statistical features are derived and analyzed by machine learning. Recently, deep learning has been adopted in this area. However, image segmentation is still a difficult task to achieve stable performance due to a variety of environmental variations. The end-to-end learning in neural network has a demerit that train images may be different from real images acquired in outdoor fields. To solve these problems, we propose superpixel-based disease classification method using end-to-end CNN (convolutional neural network) learning. Based on experiments performed on PlantVillage apple images, the classification accuracy is 98.29% and 92.43% for full-image and superpixel. As well, the multivariate F1-score is (0.98, 0.93). Therefore we validate that the method of using superpixel is comparable to that of full-image.

• Fire Science and Engineering
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• v.32 no.2
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• pp.118-129
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• 2018

This study analyzed the recent serious disaster cases of chemical extinguishing agent poisoning and suffocation investigated by KOSHA and proposed the safe use of chemical substances, including the chemical extinguishing agent. An analysis of the statistical figures an increase in the number and variations of chemical poisoning and suffocation cases in industry between 2011~2016 increased. Unlike other physical accidents, chemical accidents are very high in severity and it is difficult to identify the chemical hazard and risk. To prevent chemical disasters, it is essential to develop and use an easy chemical risk assessment tool. For the safe use of chemical substances, in which it is difficult to carry out hazard identification and risk assessments, this thesis presents the useful chemical recognition and risk assessment tools, CHEM-i and CHARM developed by KOSHA.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.403-406
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• 2005

In order to evaluate the Capability of ETM+ remotely- sensed data to provide 'Forest-shrub land-Rangeland' cover type map in areas near the timberline of northern forests of Iran, the data were analyzed in a portion of nearly 790 ha located in Neka-Zalemroud region. First, ortho-rectification process was used to correct the geometric errors of the image, yielding 0/68 and 0/69 pixels of RMS. error in X and Y axis, respectively. The original and panchromatic bands were fused using PANSHARP Statistical module. The ground truth map was made using 1 ha field plots in a systematic-random sampling grid, and vegetative form of trees, shrubs and rangelands was recorded as a criteria to name the plots. A set of channels including original bands, NDVI and IR/R indices and first components of PCI from visible and infrared bands, was used for classification procedure. Pair-wise divergence through CHNSEL command was used, In order to evaluate the separability of classes and selection of optimal channels. Classification was performed using ML classifier, on both original and fused data sets. Showing the best results of $67\%$ of overall accuracy, and 0/43 of Kappa coefficient in original data set. Due to the results represented above, it's concluded that ETM+ data has an intermediate capability to fulfill the spectral variations of three form- based classes over the study area.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.79-89
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• 1997

In order to reduce the outbreaks of short-term high concentrations and its impacts, we developed the models which predicted tomorrow's maximum hourly concentrations of $O_3$, TSP, SO$_2$, NO$_2$ and CO. Statistical methods like multi regressions were used because it must be operated easily under the present conditions. 47 independent variables were used, which included observed concentrations of air pollutants, observed and forcasted meteorological data in 1994 at Seoul and its surrounding areas. We subdivided Seoul into 4 areas coinciding with the present ozone warning areas. 4 kinds of seasonal models were developed due to the seasonal variations of observed concentrations, and 2 kinds of data models for the unavailable case of forecasted meteorological data. By comparing the $R^2$and root mean square error(hearafter 'RMSE') of each model, we confirmed that the models including forecasted data showed higher accuracy than ones using observed only. It was also shown that the higher the seasonal mean concentrations, the larger the RMSE. There was no distinct difference between the results of 4 areal models. In case of test run using 1995's data, the models predicted well the trends of daily variation of concentrations and the days when the possibility of outbreak of high concentarion was high. This study showed that it was reasonable to use those models as operational ones, because the $R^2$ and RMSE of models were smaller than those of operational/research models such as in South Coast Air Basin, CA, USA.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.201-210
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• 2008

The government employment statistics show the close comovement of the whole domestic unemployment rate with the youth unemployment rate for the past 10 years, implying the dominant influence of the unemployment of the youth age. This study investigates the structure of the short-run variation and the process of the long-run adjustment in the unemployment rates of the youth and middle ages by formulating the dynamic equation system. The estimation result consistently reflects the vulnerability of the youth class in the aggravation of the employment condition. The effect of exogenous changes is found to be persistent in the unemployment rates of both ages, which appear to have similar structures of the long-run time path. However, the youth unemployment rate turns out to have a relatively long adjustment process to the long-run equilibrium.

• Atmosphere
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• v.19 no.3
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• pp.269-287
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• 2009

CAT (clear-air turbulence) forecasting algorithm, the Graphical Turbulence Guidance (GTG) system developed at NCAR (national center for atmospheric research), is evaluated with available observations (e.g., pilot reports; PIREPs) reported in South Korea during the recent 5 years (2003-2008, excluding 2005). The GTG system includes several steps. First, 44 CAT indices are calculated in the domain of the Regional Data Assimilation and Prediction System (RDAPS) analysis data with 30 km horizontal grid spacing provided by KMA (Korean Meteorological Administration). Second, 10 indices that performed ten best forecasting scores are selected. Finally, 10 indices are combined by measuring the score based on the probability of detection, which is calculated using PIREPs exclusively of moderate-or-greater intensity. In order to investigate the best performance of the GTG system in Korea, various statistical examinations and sensitivity tests of the GTG system are performed by yearly and seasonally classified PIREPs. Performances of the GTG system based on yearly distributed PIREPs have annual variations because the compositions of indices are different from each year. Seasonal forecasting is generally better than yearly forecasting, because selected CAT indices in each season represent meteorological condition much more properly than applying the selected CAT indices to all seasons. Wintertime forecasting is the best among the four seasonal forecastings. This is likely due to that the GTG system consists of many CAT indices related to the jet stream, and turbulence associated with the jet stream can be activated mostly in wintertime under strong jet magnitude. On the other hand, summertime forecasting skill is much less than other seasons. Compared with current operational CAT prediction system (KITFA; Korean Integrated Turbulence Forecasting System), overall performance of the GTG system is better when CAT indices are selected seasonally.