• Journal of the Korean GEO-environmental Society
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• v.19 no.12
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• pp.47-58
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• 2018

Duncan & Chang(1970) proposed the Duncan-Chang model that a linear relation of transformed stress-strain plots was reconstituted from a nonlinear relation of stress-strain curve of triaxial compression test using hyperbolic theory so as to estimate an initial tangent modulus and ultimate deviator stress for the soil specimen. Although the transformed stress-strain plots show a linear relationship theoretically, they actually show a nonlinearity at both low and high values of strain of the test. This phenomenon indicates that the stress-strain curve is not a complete form of a hyperbola. So, if linear regression analyses for the transformed stress-strain plot are performed over a full range of strain of a test, error in the estimation of their linear equations is unavoidable depending on ranges of strain with non-linearity. In order to reduce such an error, a modified regression analysis method is proposed in this study, in which linear regression analyses for transformed stress-strain plots are performed over the entire range of strain except the range the non-linearity is shown around starting and ending of the test, and then the initial tangent modulus and ultimate deviator stresses are calculated. Isotropically consolidated-drained triaxial compression tests were performed on compacted weathered soil with a modified Proctor density to obtain their model parameters. The modified regression analyses for transformed stress-strain plots were performed and analyzed results are compared with results estimated by 2 points method (Duncan et al., 1980). As a result of analyses, initial tangent moduli are about 4.0% higher and ultimate deviator stresses are about 2.9% lower than those values estimated by Duncan's 2 points method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.3
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• pp.213-223
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• 2015

The helicopter initial design model was established by using the latest weight estimation equations based on the Tishchenko's methodology through the study existing initial design tools. The sequential decomposition method is used to reduce analysis time in the sizing. Empirical parameters of the weight estimation equation were also extracted from numerical and regression analysis for a helicopter database. Design input and output values were compared with the RISPECT design tool. Finally, comparison of the re-design resulting for several existing helicopters was presented and showed the good agreement within less than 5% in the weight estimation and main rotor sizing. Established initial design model was proved to be effectively used as initial design tool.

• Animal cells and systems
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• v.15 no.1
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• pp.73-78
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• 2011

Estimating the habitat potential of inland forest patches for birds requires the modeling of species-area relationships, or relationships between habitat size and numbers of bird species in each patch. The accurate estimation of speciesarea relationships significantly reduces the effort required to recognize the number of species living in each patch. The objective of this study was to estimate the relationship between forest patch size and bird species diversity in Dangjin County, in northwest South Korea, based on the sizes of inland forest patches. KOMPSAT-2 images were obtained and ortho-rectified to construct a map of the target forest patches. The numbers of birds per patch were surveyed four times: August 2008, September 2008, February 2009 and May 2009. Regression models were derived to explain the relationships between the numbers of bird species and patch size. A model that was derived using data from all four observation periods had the highest coefficient of determination ($R^2$). According to these models, the numbers of bird species at first increased linearly with increasing patch size; however, the curve then plateaued. Our model including observations from four seasons will be useful for estimating the numbers of bird species in other inland forest patches in South Korea.

• Journal of Korea Water Resources Association
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• v.43 no.3
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• pp.265-273
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• 2010

This study proposed the method that can calculate discharge using hydraulic characteristics that can acquire easily-comparatively such as hydraulic radius, bed slope, depth to improve the stage-discharge curve equation considering only stage. Roughness coefficient n value and C value that hydraulic characteristics of rivers is reflected from Manning's equation and Chezy's equation using the measured data of the natural open channel in the report of Albert University estimated and calculated discharge on the basis of this. The method proposed in this study was calculated stunningly to measured discharge. And that compared with discharge by existent stage-discharge curve.

• Geomechanics and Engineering
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• v.21 no.2
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• pp.179-186
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• 2020

Investigating damage potential of the railway infrastructure requires either large amount of case histories or in-depth numerical analyses, or both for which large amounts of effort and time are necessary to accomplish thoroughly. Rather than performing comprehensive studies for each damage case, in this study we collect and analyze a case history of the high-speed railway system damaged by the 2004 M6.6 Niigata Chuetsu earthquake for the development of the seismic fragility curve. The development processes are: 1) slice the railway system as 200 m segments and assigned damage levels and intensity measures (IMs) to each segment; 2) calculate probability of damage for a given IM; 3) estimate fragility curves using the maximum likelihood estimation regression method. Among IMs considered for fragility curves, spectral acceleration at 3 second period has the most prediction power for the probability of damage occurrence. Also, viaduct-type structure provides less scattered probability data points resulting in the best-fitted fragility curve, but for the tunnel-type structure data are poorly scattered for which fragility curve fitted is not meaningful. For validation purpose fragility curves developed are applied to the 2016 M7.0 Kumamoto earthquake case history by which another high-speed railway system was damaged. The number of actual damaged segments by the 2016 event is 25, and the number of equivalent damaged segments predicted using fragility curve is 22.21. Both numbers are very similar indicating that the developed fragility curve fits well to the Kumamoto region. Comparing with railway fragility curves from HAZUS, we found that HAZUS fragility curves are more conservative.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.27-35
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• 2019

There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Journal of Biomedical Engineering Research
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• v.27 no.3
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• pp.89-93
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• 2006

A simple algorithm that can be used to estimate a healthy person's blood pressure using pulse transit time is proposed in this paper. Fifty healthy students participated in the experiment that was conducted in line with the study. The subjects were asked to exercise on several exercise levels using a bicycle ergometer. Their blood pressures during the succeeding rest period were measured. A simple method was proposed to illustrate the relationship between blood pressure and pulse transit time. The systolic blood pressures as well as the heights and weights of the subjects were regarded as the proper parameters, and a second-order regression curve was produced to estimate the subjects' blood pressures. The mean error of estimation was less than 10 mmHg, which was the mean error of manual measurement. Although our estimation model is so simple, it can be used to estimate continuous blood pressure measurement for bicycle ergometer exercise. The electrocardiograms, photoplethysmograms, and blood pressures, however, could not be measured simultaneously As such, their estimation may be slightly different from the results taken from simultaneous measurements.

• Bulletin of the Society of Naval Architects of Korea
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• v.25 no.4
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• pp.28-38
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• 1988

This paper describes the statistical analysis method of predicting the ship resistance. The equation for the wavemaking resistance coefficient is derived as the principal dimensions and sectional area coefficients by using the wavemaking resistance theory and its regression coefficients are determined from the regression analysis of the resistance test results. The equation for the form factor is derived by purely regression analysis of the principal dimensions, sectional area coefficients and resistance test results. Also, it is shown that the wavemaking resistance can be minimize by varying the sectional area curve without changing the principal dimensions of the ship. This methods were applied to the resistance prediction of a bulk carrier. And the, the modified hull form with minimum wavemaking resistance was obtained and the reduction of effective power was confirmed by the resistance test.