• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.67.2-67.2
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• 2014

The presence of multiple populations is now well-established in most globular clusters in the Milky Way. In light of this progress, here we suggest a new model explaining the origin of the Sandage period-shift and the difference in mean period of type ab RR Lyrae variables between the two Oosterhoff groups. In our models, the instability strip in the metal-poor group II clusters, such as M15, is populated by second generation stars (G2) with enhanced helium and CNO abundances, while the RR Lyraes in the relatively metal-rich group I clusters like M3 are mostly produced by first generation stars (G1) without these enhancements. This population shift within the instability strip with metallicity can create the observed period-shift between the two groups, since both helium and CNO abundances play a role in increasing the period of RR Lyrae variables. The presence of more metal-rich clusters having Oosterhoff-intermediate characteristics, such as NGC 1851, as well as of most metal-rich clusters having RR Lyraes with longest periods (group III) can also be reproduced, as more helium-rich third and later generations of stars (G3) penetrate into the instability strip with further increase in metallicity. Therefore, although there are systems where the suggested population shift cannot be a viable explanation, for the most general cases, our models predict that the RR Lyraes are produced mostly by G1, G2, and G3, respectively, for the Oosterhoff groups I, II, and III.

• Atmosphere
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• v.17 no.4
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• pp.365-379
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• 2007

Global warming may shift the properties and dynamics of ENSO. We study the changes in ENSO characteristics in a coupled general circulation model, ECHO-G/S. First, we analyse the mean state changes by comparing present day simulation and various high $CO_2$ climates. The model shows a little El Nino-like changes in the sea surface temperature and wind stress in the eastern tropical Pacific. As the mean temperature rises, the ENSO amplitude and the frequency of strong El Ninos and La Nina decrease. The analysis shows that the weakening of the oceanic sensitivities is related to the weakening of ENSO. In addition to the surface changes, the remote subsurface sea temperature response in the western Pacific to the wind stress in the eastern Pacific influences the subsequent ENSO amplitude. However, ENSO amplitude does not show linear response to the greenhouse gas concentrations.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.87-93
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• 1999

To propose a useful modelling method for an actual muffler, the noise attenuation effects of muffler was investigated according to the flow condition and the hole shape of tubes. In this work, the finite element method was used to calculate the transmission loss of muffler, The noise attenuation characteristics of four different types of muffler in the hole shape of tubes were compared mutually to find a more simple equivalent model. Analytical results showed that the overall value of transmission loss increases and the peaks of transmission loss curve shift to the low frequency with mean flow for the given muffler, Also the noise attenuation characteristics of the equivalent model having the split holes is almost the same as those of the actual muffler having many circular holes.

• Journal of Nutrition and Health
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• v.51 no.6
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• pp.567-579
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• 2018

Purpose: This study examined the mediation effects of dietary habits, nutrient intake, daily life in the relationship between the working hours of Korean shift workers and metabolic syndrome. Methods: Data were collected from the sixth (2013-2015) Korea National Health and Nutrition Examination Survey (KNHANES). The stochastic regression imputation was used to fill missing data. Statistical analysis was performed in Korean shift workers with metabolic syndrome using the SPSS 24 program for Windows and a structural equation model (SEM) using an analysis of moment structure (AMOS) 21.0 package. Results: The model fitted the data well in terms of the goodness of fit index (GFI) = 0.939, root mean square error of approximation (RMSEA) = 0.025, normed fit index (NFI) = 0.917, Tucker-Lewis index (TLI) = 0.984, comparative fit index (CFI) = 0.987, and adjusted goodness of fit index (AGFI) = 0.915. Specific mediation effect of dietary habits (p = 0.023) was statistically significant in the impact of the working hours of shift workers on nutrient intake, and specific mediation effect of daily life (p = 0.019) was statistically significant in the impact of the working hours of shift workers on metabolic syndrome. On the other hand, the dietary habits, nutrient intake and daily life had no significant multiple mediator effects on the working hours of shift workers with metabolic syndrome. Conclusion: The appropriate model suggests that working hours have direct effect on the daily life, which has the mediation effect on the risk of metabolic syndrome in shift workers.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.545-561
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• 2018

Over the North East Asia, extreme anomalous precipitation were observed in 2013 and 2014. During 2013 summer the precipitation was found to be higher (two standard deviation) than the climatological mean of the region; whereas during 2014, which was a borderline El Ni?o year, precipitation was found to be lower (one standard deviation). To understand the differences of these two anomalous years the Global/Regional Integrated Model system (GRIMs) has been used. The study found that low landsurface temperature and high sea-surface temperature over ocean caused a smaller land-sea contrast of surface temperature between East Asia and North West Pacific Ocean in 2014, which could have caused an eastward shift of mean monsoon circulation in that year compared to the circulation in 2013. Due to a change in the lower level circulation and wind field over East Asia the evaporation and moisture transport patterns became very different in those two years. In 2013, this study found high latent heat flux over Eastern China, which implies an increased surface evaporation over that region, and the moisture transported to the north by the mean monsoon circulation; whereas, there was no correlated transport of moisture to the North East Asia during 2014. The precipitable water over North East Asia has a stronger correlation with the latent heat flux over southern land region than that from Ocean region in the eastern side in both the years. A new approach is proposed to estimate the sub-grid scale hydrometeors from GRIMs, overestimated in the existing model.

• Agricultural and Biosystems Engineering
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• v.2 no.2
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• pp.63-68
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• 2001

The objective of this study was to develop a real-time soil moisture meter using RF impedance. The impedance suchas capacitance and resistance (or conductance) was analyzed using parallel cylinder type capacitance probe(C-probe) and Q-meter (HP4342). The capacitance and conductance of soil increased as volumetric water content increased. The 5 MHz of modified Colpitts type crystal oscillator was designed to detect the capacitance change of the C-probe with moist soil. A third order polynomial regression model was proposed to describe the relationship between RF impedance and volumetric water content. The prototype real time moisture meter consisted of the C-probe, sample container, oscillator, frequency counter and related signal processing units. The calibration equation for measurement of volumetric moisture content of soil was developed and validated. The correlation coefficient and root mean square error between measured volumetric water content by oven method and predicted values by prototype moisture meter for unknown soil samples were 0.984 and 0.032$cm^3$$cm\^3$, respectively.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4022-4032
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• 2021

In this study, machine learning (ML) techniques were used to model surveillance test data of nuclear power plants from an international database of the ASTM E10.02 committee. Regression modeling was conducted using various techniques, including Cubist, XGBoost, and a support vector machine. The root mean square deviation of each ML model for the baseline dataset was less than that of the ASTM E900-15 nonlinear regression model. With respect to the interpolation, the ML methods provided excellent predictions with relatively few computations when applied to the given data range. The effect of the explanatory variables on the transition temperature shift (TTS) for the ML methods was analyzed, and the trends were slightly different from those for the ASTM E900-15 model. ML methods showed some weakness in the extrapolation of the fluence in comparison to the ASTM E900-15, while the Cubist method achieved an extrapolation to a certain extent. To achieve a more reliable prediction of the TTS, it was confirmed that advanced techniques should be considered for extrapolation when applying ML modeling.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.158-168
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• 2024

There is hardly any person in modern times who has not taken soft drinks instead of drinking water. The rate of people taking soft drinks being surprisingly high, researchers around the world have cautioned from time to time that these drinks lead to weight gain, raise the risk of non-communicable diseases and so on. Therefore, in this work an image-based tool is developed to monitor the nutritional information of soft drinks by using deep convolutional neural network with transfer learning. At first, visual saliency, mean shift segmentation, thresholding and noise reduction technique, collectively known as 'pre-processing' are adopted to extract the location of drinks region. After removing backgrounds and segment out only the desired area from image, we impose Discrete Wavelength Transform (DWT) based resolution enhancement technique is applied to improve the quality of image. After that, transfer learning model is employed for the classification of drinks. Finally, nutrition value of each drink is estimated using Bag-of-Feature (BoF) based classification and Euclidean distance-based ratio calculation technique. To achieve this, a dataset is built with ten most consumed soft drinks in Bangladesh. These images were collected from imageNet dataset as well as internet and proposed method confirms that it has the ability to detect and recognize different types of drinks with an accuracy of 98.51%.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.35-43
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• 2017

The purpose of this study was to analyze the converged influencing factors on the stages of exercise behavior changes in shift work nurses. The subjects were 120 shift work nurses working in hospitals who understood the purpose of the study and agreed to participate in the study. Data were analyzed using frequency, percentage, mean, standard deviation, t-test, $X^2$ test, and multiple logistic regression analysis. The exercise motivation factors of shift work nurses had a significant effect on stages of exercise behavior change (${\beta}=2.480$, p=.022), health status perceptions(${\beta}=1.151$, p=.013). Social support factors (${\beta}=1.819$, p=.002) and marital status (${\beta}=-1.820$, p=.004) also had significant effects on the stages of exercise behavior change of shift work nurses. In other words, subjects with change in exercise behavior had 11.9 times higher motivation and 3.1 times higher health status perception than those without change in exercise behavior, social support was 6.1 times higher, and unmarried subjects showed 16 times showed higher than that of married subjects. Therefore, it is important to develop a strategy to practice continuous and regular exercise in consideration of the exercise motivation, social support, and health status perception of the nurses in shift work.

• Journal of Korean Society for Quality Management
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• v.43 no.4
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• pp.471-488
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• 2015

Purpose: Double sampling $T^2$ chart is a useful tool for detecting a relatively small shift in process mean when the process is controlled by multiple variables. This paper finds the optimal design of the double sampling $T^2$ chart in both economical and statistical sense under Weibull failure model. Methods: The expected cost function is mathematically derived using recursive equation approach. The optimal designs are found using a genetic algorithm for numerical examples and compared to those of single sampling $T^2$ chart. Sensitivity analysis is performed to see the parameter effects. Results: The proposed design outperforms the optimal design of the single sampling $T^2$ chart in terms of the expected cost per unit time and Type-I error rate for all the numerical examples considered. Conclusion: Double sampling $T^2$ chart can be designed to satisfy both economic and statistical requirements under Weibull failure model and the resulting design is better than the single sampling counterpart.