• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.24.2-24.2
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• 2008

We have examined the relative contributions of representative space weather proxies (geomagnetic aa index) to global warming (Global temperature anomaly) and compared them with that of green house effect characterized CO2 content from 1868 to 2005. For this we used Hadcrut3 temperature anomaly (Ta) data, aa index taken at two anti-podal subauroral stations (Canberra Australia and hartland England), and the CO2 data come from historical ice core records. From the comparison between Ta and aa index, we found several interesting results: (1) the linear correlation coefficient between two parameters increases until 1990 and then decreases rapidly, and (2) the scattered plots between two parameters shows different patterns before and after 1990. A partial correlation of Ta and two quantities (aa, CO2) also shows that the geomagnetic effect (aa index) is dominant until about 1990 and the CO2 effect becomes much more important after then. These results imply that the green house effect become very important since at least 1990. For a further analysis, we simply assume that Ta (total) = Ta (aa) + Ta (CO2) and made a linear regression between Ta and aa index from 1868 to 1990. A linear model is then made from the linear regression between energy consumption (a proxy of CO2 effect) and Ta (total) - Ta (aa) since 1990. This linear model makes it possible to predict the temperature anomaly in 2030, about 1 degree higher than the present temperature, which is much larger than in the previous century.

• Journal of Welding and Joining
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• v.17 no.4
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• pp.85-92
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• 1999

In GMAW, the spatter is generated because of the variation of the arc state. If the arc state is quantitatively assessed, the control method to make the spatter be reduced is able to develop. This study was attempted to develop the optimal model that could estimate the arc state quantitatively. To do this, the generated spatters was captured under the limited welding conditions, and the waveforms of the arc voltage and of the welding current were collected. From the collected waveforms, the waveform factors and their standard deviations were produced, and the linear and non-linear regression models constituted using the factors and their standard deviations are proposed to estimate the arc state. the performance test to the proposed models was practiced. Obtained results are as follow. From the results of correlation analysis between the factors and the amount of the generated spatters, the standard deviations of the waveform factors have more the multiple regression coefficients than the waveform factors. Because the correlation coefficient between T and {TEX}$T_{a}${/TEX}, and s[T] and s[{TEX}$T_{a}${/TEX}] was nearly one, it was found that these factors have the same effect to the spatter generation. In the regression models to estimate the arc state, it was fond that the linear and the non linear models were also consisted of similar factors. In addition, the linear regression model was assessed the optimal model for estimating the arc state because the variance of data was narrow and multiple regression coefficient was highest among the models. But in the welding conditions which the amount of the generated spatters were small, it was found that the non linear regression model had better the estimation performance for the spatter generation than the linear.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.33-39
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• 2019

In this paper, we propose a parametric model for analyzing the motion information obtained from the acceleration sensors to measure the activity of the human body. The motion of the upper body and the lower body does not occur at the same time, and the motion analysis method using a single motion sensor involves a lot of errors. In this study, the 3-axis accelerometer is attached to the arms and legs, the body's activity data are measured, the momentum of the arms and legs are calculated for each channel, and the linear predictive coefficient is obtained for each channel. The periodicity of the upper body and the lower body is determined by analyzing the correlation between the channels. The linear predictive coefficient and the periodic value are used as data to measure the type of exercise and the amount of exercise. In the proposed method, we measured four types of movements such as walking, stair climbing, slow hill climbing, and fast hill descending. In order to verify the usefulness of the parameters, the recognition results are presented using the linear predictive coefficient and the periodic value for each motion as the neural network input.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.517-522
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• 2019

The purpose of this study is to determine the effective energy of CT X-ray beams by using the CT slice images of a CT number calibration insert part in the AAPM CT performance phantom. The CT number calibration insert part in the AAPM CT performance phantom was scanned five times by using a CT canner for 80, 100 and 120 kVp X-ray beams. The average value of CT numbers of each pin were measured for each CT slice image. The correlation coefficients were obtained by linear fit between the average value of CT numbers measured and liner attenuation coefficient under different energy at each pin calculated from data of NIST. A photon energy corresponding to the maximum value of the obtained correlation coefficient was determined as an effective energy. As a result, the effective energy was 56, 62 and 66~67 keV, respectively, for 80, 100 and 120 kVp X-ray beams.

• Journal of Environmental Science International
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• v.19 no.3
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• pp.295-304
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• 2010

Actual evapotranspiration (AET) in the Suyeong-gu was estimated and correlations between AET and meteorological factors were analyzed. The study area was Suyeong-gu lay at the east longitude $129^{\circ}$ 05' 40" ~ 129$^{\circ}$ 08' 08" and north latitude $35^{\circ}$ 07' 59" ~ $35^{\circ}$ 11' 01". The Kumryun mountain, the Bae mountain, the Suyeong river and the Suyeong bay are located on west, north, northeaster and south side in the study area, respectively. AET was estimated using precipitation (P), potential evapotranspiration (PET) and plant-available water coefficient. Meteorological factors to estimate PET were air temperature, dewpoint temperature, atmospheric pressure, duration of sunshine and mean wind speed (MWS). PET and AET were estimated by a method of Allen et al. (1998) and Zhang et al. (2001), respectively. PET was the highest value (564.45 mm/yr) in 2002 year, while it was the lowest value (449.95 mm/yr) in 2003 year. AET was estimated highest value (554.14 mm/yr) in 2002 year and lowest value (427.91 mm/yr) in 2003 year. Variations of PET and AET were similar. The linear regression function of AET as PET using monthly data was AET=0.87$\times$PET+3.52 and coefficient of determination was high, 0.75. In order to analyze relationship between the evapotranspiration and meteorological factors, correlation analysis using monthly data were accomplished. Correlation coefficient of AET-PET was 0.96 high, but they of AET-P and PET-P were very low. Correlation coefficients of AET-MWS and PET-MWS were 0.67 and 0.73, respectively. Thus, correlation between evapotranspiration and MWS was the highest among meteorological factors in Suyong-gu. This means that meteorological factor to powerfully effect for the variation of evapotranspiration was MWS. The linear regression function of AET as MWS was AET=84.73$\times$MWS+223.05 and coefficient of determination was 0.54. The linear regression function of PET as MWS was PET=83.83$\times$MWS+203.62 and coefficient of determination was 0.45.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.272-277
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• 2001

In order to evaluate variation of fatigue data of the LP steam turbine blade steel, it is important to estimate P - S - N curves to accurately define the probability distributions. In this study, new procedure is introduced to determine the expression of P - S - N curves. For this purpose, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probability distributions of the fatigue life were examined by the proposed analysis. Furthermore, parameter estimation for P - S - N curves was performed using various optimization to maximize the correlation coefficient. As a result of this, sequential linear programing method is used for estimation of P - S - N curves.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.262-267
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• 2001

In this study, the Reliability of degraded steam turbine blade was evaluated using the limited fatigue data. The statistical estimation of limited fatigue data implies that some unknown uncertainties which may be involved in fatigue reliability analysis. Therefore, an appropriate distribution in the fatigue strength was determined by the characteristic distribution - linear correlation coefficient, fatigue physics, error parameter. 3-parameter Weibull distribution is the most appropriate distribution to assume for infinite region. The load applied on the blade is mainly tensile. The maximum Von-Mises stress is 219.4 MPa at the steady state service condition. The failure probability($F_p$) derived from the strength-stress interference model using Monte carlo simulation under variable service condition is 0.25% at the 99.99% confidence level.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.3
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• pp.235-240
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• 2001

This study was performed to compare the lead levels of 20 quality control standard samples(KOSHA:18-2000) and 72 field samples in lead-acid battery manufacturing plant between ICP and portable-XRF methods. 1. While the proficiencies of 20 quality control standard samples by ICP were 100%, those of analytic result values by XRF were 75%. 2. The correlation coefficient(r) between the reference values for quality control (REF) and the analytic result values by ICP (ICP) was 1.0(p<0.05), and simple linear regression equation and the coefficient(R2) were REF = -0.0009 + 1.016 ICP and 0.9997, respectively. 3. The correlation coefficient(r) between the analytic result values of quality control standard samples by ICP (ICP) and by XRF (XRF) was 0.975(p<0.05), and simple linear regression equation and the coefficient(R2) were ICP = -0.0003 + 1.002 XRF and 0.950, respectively. 4. The correlation coefficient(r) between the analytic result values for lead samples of a lead-acid battery manufacturing plant by ICP (ICP) and by XRF (XRF) was 0.993(p<0.05), and simple linear regression equation and the coefficient(R2) were ICP = -2.058 + 0.996 XRF and 0.987, respectively. 5. While the frequency distributions of XRF /ICP(Ratio) for each ICP concentration levels in a lead-acid battery manufacturing plant revealed high proportion in ratio range of 0.876-1.125 than in ration range of 1.126-1.375. Also, ICP concentration level in ration range of 0.786-1.125 was increased with increase of frequency distribution of XRF/ICP. 6. The limit of detection of XRF on lead was determined to be $6.11{\mu}g$/filter The data presented in this study indicated that relationship for lead level of quality control samples and field samples in a lead -acid battery manufacturing plant by ICP and portable-XRF methods was proved. The practicing industrial hygienist can use portable-XRF to produce a rapid on-site determination of lead exposure that can immediately becommunicated to workers and help identify appropriate levels of personal protection.

• Journal of Environmental Science International
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• v.15 no.9
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• pp.887-895
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• 2006

Through this research of the analysis on the frequency flood discharges regarding basin property factors, a linear regression system was introduced, and as a result, the item with the highest correlation with the frequency flood discharges from Nakdong river basin is the basin area, and the second highest is the average width of basin and the river length. The following results were obtained after looking at the multi correlation between the flood discharge and the collected basin property factors using the data from the established river maintenance master plan of the one hundred twenty-five rivers in the Nakdong river basin. The result of analysis on multivariate correlation between the flood discharges and the most basic data in determining the flood discharges as basin area, river length, basin slope, river slope, average width of basin, shape factor and probability precipitation showed more than 0.9 of correlation in terms of the multi correlation coefficient and more than 0.85 for the determination coefficient. The model which induced a regression system through multi correlation analysis using basin property factors is concluded to be a good reference in estimating the design flood discharge of unmeasured basin.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.1017-1025
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• 2015

In mathematical statistics education, we can use mutual information as a tool for evaluating the degree of dependency between two random variables. The ordinary correlation coefficient provides information only on linear dependency, not on nonlinear relationship between two random variables if any. In this paper as a measure of the degree of dependency between random variables, we suggest the use of symmetric uncertainty and ${\lambda}$ which are defined in terms of mutual information. They can be also considered as generalized correlation coefficients for both linear and non-linear dependence of random variables.