• Journal of Food Hygiene and Safety
• /
• v.31 no.5
• /
• pp.342-348
• /
• 2016

The objective of this study was to compare the change of S. Enteritidis with S. Typhimurium populations in liquid egg products. S. Enteritidis or S. Typhimurium was inoculated into egg white and egg yolk and stored at 8, 10, 15, 25, and $35^{\circ}C$, respectively. In egg white, no growth of S. Enteritidis and S. Typhimurium was observed at 8, 10, 15, and $35^{\circ}C$, while both S. Enteritidis and S. Typhimurium in egg white stored grew more than 1 log CFU/ml after 50 hours storage at $25^{\circ}C$. In egg yolk, there was no growth of S. Enteritidis and S. Typhimurium at $8^{\circ}C$ but growth of both strains was observed at 10, 15, 25, and $35^{\circ}C$. Since growth of S. Enteritidis and S. Typhimurium was only observed in egg yolk, primary growth models for both strains were developed using modified Gompertz equation and then secondary models for lag time (LT), specific growth rate (SGR), and maximum population density (MPD) were developed as a function of temperature. At all temperatures, more rapid growth of S. Enteritidis than S. Typhimurium was observed in egg yolk, indicating the greater risk of S. Enteritidis than S. Typhimurium in egg products. In conclusion, the results indicate that temperature control less than $8^{\circ}C$ is very important to ensure safety of liquid egg products, especially liquid egg yolk.

• The Journal of the Korea Contents Association
• /
• v.13 no.8
• /
• pp.275-283
• /
• 2013

The patient radiation dose is different depending on selection of Ion chamber when taking Chest PA which using AEC. In this paper, we studied acquiring the best diagnostic images according to selection of Ion chamber on AEC mode as well as minimizing patient radiation dose. Experimental methods were selection of Ion chamber and change of sensitivity under the same conditions as Chest PA projection. At AEC mode, two upper ion chambers sensors and one lower ion chamber sensor were divided into 7 cases according to selection of on/off. after measuring five times respectively, we obtained average value and calculated exposure dose. Image assessment was done with measured Modulation Transfer Function, Peak Signal to Noise Ratio, Root Mean Square, Signal to Noise Ratio, Contrast to Noise Ratio, Mean to Standard deviation Ratio respectively. In exposure assessment results, selection of two upper chambers was the lowest. In resolution assessment results, image of two upper chambers had the second high spatial frequency at sensitivity at 625(High) was 1.343 lp/mm. RMS value of image selecting two upper chambers was low secondly. SNR, CNR, MSR were the high value secondly. As the sensitivity was increased, radiation dose was decreased but better image could be obtained on image quality. In order to obtain the best medical images while minimizing the dose, usage of two upper ion chambers is considered to be clinically useful at sensitivity 625(High).

• Journal of Astronomy and Space Sciences
• /
• v.27 no.2
• /
• pp.153-160
• /
• 2010

We modified the optical system of 500 mm wide-field telescope of which point spread function showed an irregularity. The telescope has been operated for Near Earth Space Survey (NESS) located at Siding Spring Observatory (SSO) in Australia, and the optical system was brought back to Korea in January 2008. After performing a numerical simulation with the tested value of surface figure error of the primary mirror using optical design program, we found that the surface figure error of the mirror should be fabricated less than root mean square (RMS) $\lambda$/10 in order to obtain a stellar full width at half maximum (FWHM) below $28\;{\mu}m$. However, we started to figure the mirror for the target value of RMS $\lambda$/20, because system surface figure error would be increased by the error induced by the optical axis adjustment, mirror cell installation, and others. The radius of curvature of the primary mirror was 1,946 mm after the correction. Its measured surface figure error was less than RMS $\lambda$/20 on the table of polishing machine, and RMS $\lambda$/15 after installation in the primary mirror cell. A test observation performed at Daeduk Observatory at Korea Astronomy and Space Science Institute by utilizing the exiting mount, and resulted in $39.8\;{\mu}m$ of stellar FWHM. It was larger than the value from numerical simulation, and showed wing-shaped stellar image. It turned out that the measured-curvature of the secondary mirror, 1,820 mm, was not the same as the designed one, 1,795.977 mm. We fabricated the secondary mirror to the designed value, and finally obtained a stellar FWHM of $27\;{\mu}m$ after re-installation of the optical system into SSO NESS Observatory in Australia.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.3
• /
• pp.568-576
• /
• 2003

This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

• Journal of the Korean earth science society
• /
• v.34 no.1
• /
• pp.13-27
• /
• 2013

Quantitative precipitation estimation (QPE) is one of the most important elements in meteorological and hydrological applications. In this study, we adjusted the QPE from an S-band weather radar based on co-kriging method using the geostatistical structure function of error distribution of radar rainrate. In order to estimate the accurate quantitative precipitation, the error of radar rainrate which is a primary variable of co-kriging was determined by the difference of rain rates from rain gauge and radar. Also, the gauge rainfield, a secondary variable of co-kriging is derived from the ordinary kriging based on raingauge network. The error distribution of radar rain rate was produced by co-kriging with the derived theoretical variogram determined by experimental variogram. The error of radar rain rate was then applied to the radar estimated precipitation field. Locally heavy rainfall case during 6-7 July 2009 is chosen to verify this study. Correlation between adjusted one-hour radar rainfall accumulation and rain gauge rainfall accumulation improved from 0.55 to 0.84 when compared to prior adjustment of radar error with the adjustment of root mean square error from 7.45 to 3.93 mm.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.26 no.4
• /
• pp.207-216
• /
• 2014

Total organic carbon (TOC) is an important indicator used as an direct biological index in the research field of the marine carbon cycle. It is possible to produce the sufficient TOC estimation data by using the Chemical Oxygen Demand(COD) data because the available TOC data is relatively poor than the COD data. The outlier detection and treatment (removal) should be carried out reasonably and objectively because the equation for a COD-TOC conversion is directly affected the TOC estimation. In this study, it aims to suggest the optimal regression model using the available salinity, COD, and TOC data observed in the Korean coastal zone. The optimal regression model is selected by the comparison and analysis on the changes of data numbers before and after removal, variation coefficients and root mean square (RMS) error of the diverse detection methods of the outlier and influential observations. According to research result, it is shown that a diagnostic case combining SIQR (Semi - Inter-Quartile Range) boxplot and Cook's distance method is most suitable for the outlier detection. The optimal regression function is estimated as the TOC(mg/L) = $0.44{\cdot}COD(mg/L)+1.53$, then determination coefficient is showed a value of 0.47 and RMS error is 0.85 mg/L. The RMS error and the variation coefficients of the leverage values are greatly reduced to the 31% and 80% of the value before the outlier removal condition. The method suggested in this study can provide more appropriate regression curve because the excessive impacts of the outlier frequently included in the COD and TOC monitoring data is removed.

• Journal of Food Hygiene and Safety
• /
• v.28 no.2
• /
• pp.168-173
• /
• 2013

This study was carried out to develop and validate predictive models of E. coli O157:H7 growth. Growth data of E. coli O157:H7 in Paprika were collected at 12, 24, 30 and $36^{\circ}C$. The population increased into 3.0 to 3.8 log10 CFU/g within 4 days, then continued to increase at a slower rate through 10 days of storage at $12^{\circ}C$. The lag time (LT) and maximum specific growth rate (SGR) obtained from each primary model was then modeled as a function of temperature using Davey and square root equations, respectively. For interpolation of performance evaluation, growth data for a mixture of E. coli O157:H7 were collected at time intervals in paprika incubated at the different temperatures, which was not used in model development. Results of model performance for interpolation data demonstrated that induced secondary models showed acceptable goodness of fit. Relative errors in the LT and SGR model for interpolation data (18 and $27^{\circ}C$) was 100%, which show acceptable goodness of fit and validated for interpolation. The primary and secondary models developed in this study can be used to establish tertiary models to quantify the effects of temperature on the growth of E. coli O157:H7 in paprika.

• Journal of Korea Water Resources Association
• /
• v.48 no.12
• /
• pp.981-993
• /
• 2015

The analysis of hydrologic time series data is crucial for the effective management of water resources. Therefore, it has been widely used for the long-term forecasting of hydrologic variables. In tradition, time series analysis has been used to predict a time series without considering exogenous variables. However, many studies using decomposition have been widely carried out with the assumption that one data series could be mixed with several frequent factors. In this study, the empirical mode decomposition method was performed for decomposing a hydrologic time series data into several components, and each component was applied to the time series models, autoregressive moving average (ARMA). After constructing the time series models, the forecasting values are added to compare the results with traditional time series model. Finally, the forecasted estimates from ARMA model with empirical mode decomposition method showed better performance than sole traditional ARMA model indicated from comparing the root mean square errors of the two methods.

• Ecology and Resilient Infrastructure
• /
• v.7 no.2
• /
• pp.114-125
• /
• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).

• Science of Emotion and Sensibility
• /
• v.21 no.1
• /
• pp.71-82
• /
• 2018

Stress involves changes in behavior, autonomic function and the secretion of hormones. Autonomic nervous system (ANS) contributes to physiological adaptive process in short durations. In particular, heart rate variability (HRV) analysis is commonly used as a quantitative marker depicting the ANS activity related to mental stress. The aim of this study is to investigate correlations between psychological responses to stress and HRV indices induced by the cognitive stressor. Thirty-three participants rated their mental and physical symptoms occurred during the past two weeks on Stress Response Inventory (SRI), which is composed of seven stress factors that may influence the status of mental stress levels. Then, they underwent the psychophysiological procedures, which are collected electrocardiogram (ECG) signals during a cognitive stress task. HRV indices, the standard deviation of R-R interval (SDNN), root mean square of successive R-R interval difference (RMSSD) and low frequency (LF)/high frequency (HF) ratio were extracted from ECG signals. Physiological responses were calculated stress responses by subtracting mean of the baseline from the mean of recovery. Stress factors such as tension, aggression, depression, fatigue, and frustration were positively correlated to HRV indices. In particular, aggression had significant positive correlations to SDNN, RMSSD and LF/HF ratio. Increased aggressive responses to stress correlated with the increases of all HRV indices. This means the increased autonomic coactivation. Additionally, tension, depression, fatigue, and frustration were positively associated with RMSSD reflecting increases in parasympathetic activation. The autonomic coactivation may represent an integrated response to specific cognitive reactions such as the orienting response.