• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.63-70
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• 2011

In this paper, we proposed a method for estimating energy expenditure using the unfixed axis of the accelerometer. Most studies adopted waist-placement because of the fact that the waist is close to the center of mass of a whole human body. But we adopted pocket-placement, which is capable of using unfixed axis of sensor, that is more convenient than conventional methods. To evaluate the proposed method, 28 male subjects performed walking and running on a motor driven treadmill. All of subject put on the indirect calorimeter and fixed accelerometer, then data were simultaneously measured during exercise. The regression analysis was performed using the test group(n=20) and the regression equation was applied to the control group(n=8). A strong linear relationship between energy expenditure and unfixed accelerometer signal was found. Futhermore, the coefficient of determination was significantly reliable($R^2$=0.98) and showed zero of p-value. The error of energy expenditure estimation between indirect calorimeter and two types of accelerometer was 15.0%(fixed) and 17.0%(unfixed) respectively. These results show the possibilities that the unfixed accelerometer can be used in estimating the energy expenditure during exercise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.163-168
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• 2020

Since the industrialization in the 1960s, Korea has been expanding its transportation infrastructure, such as building bridges. Owing to bridge construction, studies on stability review have been carried out, and stability-securing technology has been developed. On the other hand, these were applied mainly to the upper part of the bridge, so applications to the lower part are limited. In particular, scour at the bridge pier causes erosion in the riverbed and bridge collapse. Hence, prevention studies and countermeasures are needed. In this study, an empirical formula was developed to evaluate the scour depth of a bridge, which was calculated through multiple linear regression analysis using the hydraulic model study data conducted in previous studies. The formula, which had a value of 0.91, was applied to the model test data that was not used for development to verify the developed formula. When the pier scour depths were compared in 23 cases, the error rate was less than 20% in 16 cases (70%). The empirical formula developed in this study is applicable to pier scour-depth calculations. Further research will be needed to develop a more accurate empirical formula for pier scour-depth calculations, and it is expected to reduce bridge damage caused by scour.

• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.125-133
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• 2008

According to longer and longer span, dynamic instability of stay cable should be prevented. Dynamic instability occurs mainly symmetric 1st mode and antisymmetric 1st mode in stay cable. Especially symmetric 1st mode has a lot of influence on sag. Therefore fundamental frequency of stay cable is different from that of taut sting. Irvine, Triantafyllou, Ahn etc. analyzed dynamic behavior of taut cable with sag through analytical technical and their researches give important results for large bounds of Irvine parameter. But each research shows mutually different values out of characteristic (cross-over or mode-coupled) point and each solution of frequency equations of all researchers can be very difficultly found because of their very high non-linearity. Presented study focuses on fundamental frequency of stay cable. Generalized mechanical energy with symmetric 1st mode vibration shape satisfied boundary conditions is evolved by Rayleigh-Ritz method. It is possible to give linear analytic solution within characteristic point. Error by this approach shows only below 3% at characteristic point against existing researches. And taut cable don't exceed characteristic point. I.e. high accuracy, easy solving techniques, and a little bit limitations. Therefore presented study can be announced that it is good study ergonomically.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.559-573
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• 2008

In this study, we newly proposed 3-D nonlinear wave driver utilizing the Navier-Stokes Eq. the numerical integration of which is carried out using SPH (Smoothed Particle Hydrodynamics), an internal wave generation with the source function of Gaussian distribution and an energy absorbing layer. For the verification of new 3-D nonlinear wave driver, we numerically simulate the sloshing problem within a parabolic water basin triggered by a Gaussian hump and uniformly inclined water surface by Thacker (1981). It turns out that the qualitative behavior of sloshing caused by relaxing the external force which makes a free surface convex or uniformly inclined is successfully simulated even though phase error is visible and an inundation height shrinks as numerical simulation more proceeds. For the more severe test, we also simulate the nonlinear shoaling and refraction over uniform beach of wedge shape. It is shown that numerically simulated waves are less refracted than the linear counterpart by Hamiltonian ray theory due to nonlinearity, energy dissipation at the bottom and side walls, energy loss induced by breaking, and the hydraulic jump occurring when breaking waves encounter a down-rush by the preceding wave.

• Journal of Ecology and Environment
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• v.48 no.2
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• pp.196-206
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• 2024

Background: Most of the biomass equations were developed using sample trees collected mainly from pan-tropical and tropical regions that may over- or underestimate biomass. Site-specific models would improve the accuracy of the biomass estimates and enhance the country's measurement, reporting, and verification activities. The aim of the study is to develop site-specific biomass estimation models and validate and evaluate the existing generic models developed for pan-tropical forest and newly developed allometric models. Total of 140 trees was harvested from each diameter class biomass model development. Data was analyzed using SAS procedures. All relevant statistical tests (normality, multicollinearity, and heteroscedasticity) were performed. Data was transformed to logarithmic functions and multiple linear regression techniques were used to develop model to estimate aboveground biomass (AGB). The root mean square error (RMSE) was used for measuring model bias, precision, and accuracy. The coefficient of determination (R² and adjusted [adj]-R²), the Akaike Information Criterion (AIC) and the Schwarz Bayesian information Criterion was employed to select most appropriate models. Results: For the general total AGB models, adj-R² ranged from 0.71 to 0.85, and model 9 with diameter at stump height at 10 cm (DSH₁₀), ρ and crown width (CW) as predictor variables, performed best according to RMSE and AIC. For the merchantable stem models, adj-R² varied from 0.73 to 0.82, and model 8) with combination of ρ, diameter at breast height and height (H), CW and DSH₁₀ as predictor variables, was best in terms of RMSE and AIC. The results showed that a best-fit model for above-ground biomass of tree components was developed. AGB_Stem = exp {-1.8296 + 0.4814 natural logarithm (Ln) (ρD²H) + 0.1751 Ln (CW) + 0.4059 Ln (DSH₃₀)} AGB_Branch = exp {-131.6 + 15.0013 Ln (ρD²H) + 13.176 Ln (CW) + 21.8506 Ln (DSH₃₀)} AGB_Foliage = exp {-0.9496 + 0.5282 Ln (DSH₃₀) + 2.3492 Ln (ρ) + 0.4286 Ln (CW)} AGB_Total = exp {-1.8245 + 1.4358 Ln (DSH₃₀) + 1.9921 Ln (ρ) + 0.6154 Ln (CW)} Conclusions: The results demonstrated that the development of local models derived from an appropriate sample of representative species can greatly improve the estimation of total AGB.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.80-90
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• 2014

The objective of this research is to estimate the stand volume of Pinus koraiensis, by using the investigated volume and the information of remote sensing(RS), in the research forest of Kangwon National University. The average volume of the research forest per hectare was $307.7m^3/ha$ and standard deviation was $168.4m^3/ha$. Before and after carrying out 3 by 3 majority filtering on TM image, eleven indices were extracted each time. Independent variables needed for linear regression equation were selected using mean pixel values by indices. The number of indices were eleven: six Bands(except for thermal Band), NDVI, Band Ratio(BR1:Band4/Band3, BR2:Band5/Band4, BR3:Band7/Band4), Tasseled Cap-Greeness. As a result, NDVI and TC G were chosen as the most suitable indices for regression before and after filtering, and R-squared was high: 0.736 before filtering, 0.753 after filtering. As a result of error verification for an exact comparison, RMSE before and after filtering was about $69.1m^3/ha$, $67.5m^3/ha$, respectively, and bias was $-12.8m^3/ha$, $9.7m^3/ha$, respectively. Therefore, the regression conducted with filtering was selected as an appropriate model because of low RMSE and bias. The estimated stand volume applying the regression was $160,758m^3$, and the average volume was $314m^3/ha$. This estimation was 1.2 times higher than the actual stand volume of Pinus koraiensis.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.2
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• pp.142-149
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• 1995

This study was conducted to investigate the relationships between yearly variation of climatic components and yearly variations of productivity in monoculture cotton. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components from the four varieties(Kinggus, Yongdang local. 113-4, 380) were collected from 1978 to 1992 in Mokpo area. The meteorological data gathered at the Mokpo Weather Station for the same period were used to find out the relationships between climatic components and productivity. Yearly variation of the amount of precipitation and number of stormy days in July are large with coefficients of the variations(C.V)84.89 and 97.05%, respectively, while yearly variation, of the average temperature, maximum temperature, minimum temperature from May to Sep. are relatively small. Seed cotton yield before frost in Sep. and Oct. very greatly with C.V. of 68.77, 78.52%, respectively. Number of boll bearing branches and lint percentage show more or less small in C.V. with 11.77 and 19.13%, respectively and flowering date and boll opening date show still less variation. Correlation coefficients between precipitation in May and number of boll bearing branches, duration of sunshine in July and number of bolls per plant, maximum temperature in July and total seed cotton before the frost in Sep., Oct., and Nov. evaporation in Aug. are positively sig-nificant at the 1% level. There are highly significantly positive correlated relationships among yield(total seed cotton) and yield components. Total seed cotton yield(Y) can be predicted by multiple regression equation with independent variables of climatic factors in July such as monthly averages of average temperature($X_1$), maximum temperature($X_2$) and minimum temperature($X_3$), monthly amount of precipitation ($X_4$), evaporation($X_5$), monthly average of relative humidity($X_6$), monthly hours with sunshine($X_7$) and number of rainy days($X_8$). The equation is estimatedas Y =-1080.8515 + 144.7133$X_1$+15.8722$X_2$ + 164.9367$X_3$ + 0.0802$X_4$ + 0.5932$X_5$ + 11.3373$X_6$ + 3.4683$X_7$- 9.0846$X_8$. Also, total seed cotton yield(Y) can be predicted by the same method with climatic components in Aug., Y =2835.2497 + 57.9134$X_1$ - 46.9055$X_2$ - 41.5886X$_3$ + 1.2559$X_5$ - 21.9687$X_6$ - 3.3763$X_7$- 4.1080$X_8$- 17.5586$X_9$. And the error between observed and theoretical yield were less with approached linear regression.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• The Journal of the Korean life insurance medical association
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• v.4 no.1
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• pp.44-76
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• 1987

Present study was undertaken to establish the modified Broca's indices to estimate standard body weight by using a total of 5,496 insured persons who were medically examined at the Honam Medical Room of Dong Bang Life Insurance Company Ltd. from January, 1983 to January, 1986. The results were as follows: 1. The linear regression equations of body weight to $height^3$ to estimate standard body weight were as follows: In male, for $18{\sim}19$ age group $y=7.272{\times}10^{-6}{\times}x^3+23.560$ for $20{\sim}29$ age group $y=8.187{\times}10^{-6}{\times}x^3+22.031$ for $30{\sim}39$ age group $y=8.627{\times}10^{-6}{\times}x^3+23.169$ for $40{\sim}49$ age group $y=9.561{\times}10^{-6}{\times}x^3+20.994$ for $50{\sim}59$ age group $y=8.604{\times}10^{-6}{\times}x^3+23.081$ and for all ages group $y=7.778{\times}10^{-6}{\times}x^3+25.929$ In female, for $18{\sim}19$ age group $y=8.252{\times}10^{-6}{\times}x^3+18.920$ for $20{\sim}29$ age group $y=7.715{\times}10^{-6}{\times}x^3+22.409$ for $30{\sim}39$ age group $y=8.808{\times}10^{-6}{\times}x^3+21.440$ for $40{\sim}49$ age group $y=9.691{\times}10^{-6}{\times}x^3+21.940$ for $50{\sim}59$ age group $y=12.550{\times}10^{-6}{\times}x^3+11.031$ and for all ages group $y=7.300{\times}10^{-6}{\times}x^3+26.601$ In both sexes, for all ages group $y=8.342{\times}10^{-6}{\times}x^3+22.998$ 2. The modified Broca's index is expressed by formula $\{height(cm)-100\}{\times}K(kg)$. K is obtained from the following formula standard weight to average height estimated $\frac{by\;means\;of\;linear\;regression\;equation(kg)}{\{Average\;height(cm)-100\}{\times}K(kg)}$=1 Author's modified Broca's indices are as follows: In male, for $18{\sim}19$ age group $\{height(cm)-100\}{\times}0.85(kg)$ for $20{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ for $30{\sim}39$ age group $\{height(cm)-100\}{\times}0.95(kg)$ for $40{\sim}49$ age group $\{height(cm)-100\}{\times}1.00(kg)$ for $50{\sim}59$ age group $\{height(cm)-100\}{\times}0.95(kg)$ and for all ages group $\{height(cm)-100\}{\times}0.95(kg)$ In female, for $18{\sim}19$ age group $\{height(cm)-100\}{\times}0.90(kg)$ for $20{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ for $30{\sim}39$ age group $\{height(cm)-100\}{\times}1.00(kg)$ for $40{\sim}49$ age group $\{height(cm)-100\}{\times}1.05(kg)$ for $50{\sim}59$ age group $\{height(cm)-100\}{\times}1.05(kg)$ and for all ages group $\{height(cm)-100\}{\times}1.00(kg)$ In both sexes, for all age group $\{height(cm)-100\}{\times}0.95(kg)$ 3. Several types of modified Broca's index recommended by author are as follows: I. In male, for $18{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ and for $30{\sim}59$ age group $\{height(cm)-100\}{\times}0.95(kg)$ In female, for $18{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ and for $30{\sim}39$ age group $\{height(cm)-100\}{\times}1.00(kg)$ II. In male, for all ages group $\{height(cm)-100\}{\times}0.95(kg)$ In female, for all ages group $\{height(cm)-100\}{\times}1.00(kg)$ III. In both sexes, for all ages group $\{height(cm)-100\}{\times}0.95(kg)$ Note: The first type of modified Broca's index is the most precise one in estimating standard body weight among several types established by author. 4. Error of estimated standard body weight appearing by applying modified Broca's indices is generally greater in short build persons than in tall build persons and is more dominant especially in female group.