• Journal of Environmental Science International
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• v.23 no.3
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• pp.387-397
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• 2014

This study is carried out to propose an empirical equation which can promptly predict the aircraft noise level at a specific point (a receptor) near Jeju international airport by using the information of the flight path data. For this purpose, Analyses of multiple linear regression with the slant distances (SD) calculated from the gate analyses of the flight path data, aircraft noise certification levels with unit of EPNL(effective perceived noise level) and noise levels measured at receptors are performed by SPSS package. From these regression analyses for approach and departure of aircraft, we can propose empirical equations which is statistically significant. The noise levels predicted by these empirical equations are highly correlated the measured data.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.401-410
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• 2017

Estimation of snow depth using optical image is conducted by using correlation with Snow Cover Fraction (SCF). Various algorithms have been proposed for the estimation of snow cover fraction based on Normalized Difference Snow Index (NDSI). In this study we tested linear, quadratic, and exponential equations for the generation of snow cover fraction maps using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua satellite in order to evaluate their applicability to the complex terrain of South Korea and to search for improvements to the estimation of snow depth on this landscape. The results were validated by comparison with in-situ snowfall data from weather stations, with Root Mean Square Error (RMSE) calculated as 3.43, 2.37, and 3.99 cm for the linear, quadratic, and exponential approaches, respectively. Although quadratic results showed the best RMSE, this was due to the limitations of the data used in the study; there are few number of in-situ data recorded on the station at the time of image acquisition and even the data is mostly recorded on low snowfall. So, we conclude that linear-based algorithms are better suited for use in South Korea. However, in the case of using the linear equation, the SCF with a negative value can be calculated, so it should be corrected. Since the coefficients of the equation are not optimized for this area, further regression analysis is needed. In addition, if more variables such as Normalized Difference Vegetation Index (NDVI), land cover, etc. are considered, it could be possible that estimation of national-scale snow depth with higher accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2093-2099
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• 2011

Speech signal and car noise signal such as muffler noise are segregated from the one which has both signals mixed using statistical method. To classify speech signal from the other in segregated signals, FFT coefficients were obtained for all segments of a signal where each segment consists of 128 elements of a signal. For several coefficients of FFT corresponding to the low frequencies of a signal, autocovariances are calculated between coefficients of same order of all segments of a signal. Then they were averaged over autocovariances. Linear equation was eatablished for the those autocovariances using the linear regression method for each siganl. The coefficient of the slope of the line gives reference to compare and decide what the speech signal is. It is what this paper proposes. The results show it is very useful.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.1
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• pp.160-169
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• 2000

Daily indoor and outdoor nitrogen dioxide ($NO_2$) concentration for 30 days were measured in 28 houses with questionnaire of housing characteristics in Brisbane, Australia. Using mass balance equation and regression analysis, penetration factors and source strength factors were calculated. The penetration factors of 27 houses except one house were between zero and 1, though penetration factor should be between zero and 1 by means of mass balance equation. Relationship between indoor and outdoor concentrations in each 27 house was calculated using regression analysis. According to the obtained linear regression equation, the slope means penetration factor and the intercept means source strength factor. Calculated mean and standard deviation of coefficients of determination ($R^2$) in electric and gas range houses were $0.70{\pm}0.13$ and $0.57{\pm}0.21$, respectively. The source strength factors were more than zero in 27 houses. Mean and standard deviation of slopes in electric and gas range houses were $0.65{\pm}0.18$ and $0.56{\pm}0.12$, respectively. Mean and standard deviation of intercepts in electric and gas range houses were $1.49{\pm}1.25$ and $5.77{\pm}3.55$, respectively. Air exchange rate and source strength were calculated from penetration factor and source strength factor, respectively. Geometric mean and standard deviation of calculated air exchange rates in 27 houses were $1.1/hr{\pm}1.5$. Presence of gas range was the most significant factor contributing to indoor $NO_2$ level in house characteristics (p=0.003). In gas range houses, source strengths ranged from 4.1 to $33.1cm^3/hr{\cdot}m^3$ with a mean $12.7cm^3/hr{\cdot}m^3$ and a standard deviation 9.8. The source strengths of gas range houses were significantly different from those of electric range houses by t-test (p<0.001)

• Imaging Science in Dentistry
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• v.46 no.1
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• pp.1-7
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• 2016

Purpose: This study assessed the accuracy of age estimates produced by a regression equation derived from lower third molar development in a Thai population. Materials and Methods: The first part of this study relied on measurements taken from panoramic radiographs of 614 Thai patients aged from 9 to 20. The stage of lower left and right third molar development was observed in each radiograph and a modified Gat score was assigned. Linear regression on this data produced the following equation: Y=9.309+1.673 mG+0.303S (Y=age; mG=modified Gat score; S=sex). In the second part of this study, the predictive accuracy of this equation was evaluated using data from a second set of panoramic radiographs (539 Thai subjects, 9 to 24 years old). Each subject's age was estimated using the above equation and compared against age calculated from a provided date of birth. Estimated and known age data were analyzed using the Pearson correlation coefficient and descriptive statistics. Results: Ages estimated from lower left and lower right third molar development stage were significantly correlated with the known ages (r=0.818, 0.808, respectively, $P{\leq}0.01$). 50% of age estimates in the second part of the study fell within a range of error of ${\pm}1year$, while 75% fell within a range of error of ${\pm}2years$. The study found that the equation tends to estimate age accurately when individuals are 9 to 20 years of age. Conclusion: The equation can be used for age estimation for Thai populations when the individuals are 9 to 20 years of age.

• Journal of Radiation Industry
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• v.11 no.1
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• pp.27-31
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• 2017

Reliable follow-up of bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA) is essential in clinical practice. When there is a difference in the BMD values from DXA systems in the same patient, cross calibration equation is required for the reliable follow-up. Unfortunately, no equation is existed in BMD measure between GE Lunar Prodigy Advance (US, GE Healthcare; LPA) and Osteosys Dexxum T (Korea, Osteosys; ODT) DXA systems. In this study, we evaluate the agreement of BMD values between LPA and ODT and suggest the cross calibration equation using European spine phantom (ESP) with two systems. We performed BMD measurements using ten scans with ESP in each DXA systems. We compared BMD values and calculated cross calibration equation by linear regression analysis. The comparison between the LPA and ODT bone densitometers used the ESP. Compared to the ESP BMD values, ODT underestimated 14.36% and LPA overestimated 12.96%. The average of total BMD measurement values acquired with ODT were 21.44% lower than those from LPA. Cross-calibration equation for LPA and ODT was derived from ESP. We calculated simple cross calibration equation for LPA and ODT DXA systems. Cross-calibration equation is necessary for the reliable follow-up of BMD values in two different systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4A
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• pp.365-371
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• 2009

It is time-consuming to estimate chloride diffusivity of concrete by concentration difference test. For the reason chloride diffusivity of concrete is mainly tested by electrically accelerated method, which is accelerating the movement of chloride ion by potential difference. In this study, portland cement concrete and concrete containing with ground granulated blast-furnace slag (40 and 60% of cement by weight) with water-cementitious material ratio 40, 45, 50 and 60% were manufactured. To compare with chloride diffusivity calculated from the electrically accelerated test and immersed test in artifical seawater, chloride diffusivity tests were conducted. From the results of regression analysis, regression equation between accelerated chloride diffusivity and immersed chloride diffusivity was linear function. And the determinant coefficient was 0.96 for linear equation.

• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.326-331
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• 2018

Crop growth models are useful tools for understanding and integrating knowledge about crop growth. Models for predicting plant height, net photosynthesis rate, and plant growth of quinoa (Chenopodium quinoa Willd.) as a leafy vegetable in a closed-type plant factory system were developed using empirical model equations such as linear, quadratic, non-rectangular hyperbola, and expolinear equations. Plant growth and yield were measured at 5-day intervals after transplanting. Photosynthesis and growth curve models were calculated. Linear and curve relationships were obtained between plant heights and days after transplanting (DAT), however, accuracy of the equation to estimate plant height was linear equation. A non-rectangular hyperbola model was chosen as the response function of net photosynthesis. The light compensation point, light saturation point, and respiration rate were 29, 813 and $3.4{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. The shoot fresh weight showed a linear relationship with the shoot dry weight. The regression coefficient of the shoot dry weight was 0.75 ($R^2=0.921^{***}$). A non-linear regression was carried out to describe the increase in shoot dry weight of quinoa as a function of time using an expolinear equation. The crop growth rate and relative growth rate were $22.9g{\cdot}m^{-2}{\cdot}d^{-1}$ and $0.28g{\cdot}g^{-1}{\cdot}d^{-1}$, respectively. These models can accurately estimate plant height, net photosynthesis rate, shoot fresh weight, and shoot dry weight of quinoa.

• Journal of Industrial Technology
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• v.41 no.1
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• pp.15-20
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• 2021

This work proposes a simple method to use the added absorption per person values to predict the expected values of the acoustical conditions in occupied classrooms. This method is based on the effects of the values of added absorption per person on the unoccupied total absorption values of the classrooms and on other room acoustical parameters. The total sound absorption in an unoccupied classroom can be calculated from measured reverberation times in the classroom. The expected occupied absorption can be calculated using equation which was obtained in a previous study (Choi, 2017) by fitting a linear regression line to a plot of total occupied absorption versus the corresponding unoccupied total absorption values measured in 12 university classrooms. The ratios of occupied-to-unoccupied sound absorption are used to predict increments in the values of acoustical parameters that result when occupants are added to the rooms.