• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.2
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• pp.87-93
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• 2009

The labyrinth weir can be defined that the plane shape of overflow part is not straight line and is a kind of weir having overflow length increased by changing its plane shape. Recently, the labyrinth weir can be widely applied to various hydraulic facilities such as dam spillway, irrigation facilities, and canal structures by increasing precipitation. This study was performed to analyze the hydraulic characteristics according to triangle labyrinth weir using hydraulic model experiments and finally estimate the discharge coefficients for triangle labyrinth weirs. The formulae of discharge coefficient provided in this study, which make it feasible to calculate the overflow rate by a coefficient of correlation. sum of residuals, MAPE(Mean Absolute Percentage Error), are expected to be widely applied to design of hydraulic facilities such as dam spillway and irrigation system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8791-8799
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• 2015

In this paper, One-way car-sharing System represents the verification system consider events in revenue effects. Revenue which the time and distance represented the graph, compare one-way vehicle relocate car-sharing system which proven in existing international papers with one-way vehicle relocate car-sharing system consider the event currently in the Korea. Especially, The maximum profit according to the distance and time were assessed through multiple linear regression analysis, and there are probable maximum loss allow for the maximum loss. The company suggested using the event as a discount coupon to customers through various marketing strategies, and then focused on increasing customer demand. So, Correlation analysis to determine the maximum revenue of the actual travel distance and time were carried out through Non-linear Regression.

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.107-117
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• 1999

A comparison of a neural network approach with the conventional statistical methods, multiple regression and band ratio analyses, for the estimation of water quality parameters in presented in this paper. The Landsat TM image of Lake Daechung acquired on March 18, 1996 and the thirty in-situ sampling data sets measured during the satellite overpass were used for the comparison. We employed a three-layered and feedforward network trained by backpropagation algorithm. A cross validation was applied because of the small number of training pairs available for this study. The neural network showed much more successful performance than the conventional statistical analyses, although the results of the conventional statistical analyses were significant. The superiority of a neural network to statistical methods in estimating water quality parameters is strictly because the neural network modeled non-linear behaviors of data sets much better.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3A
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• pp.227-234
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• 2011

Recently, a high strength concrete of more than 40 MPa has been increasingly used in practice. However, use of the high strength concrete may influence on design parameters, particularly stress distribution. This is very true since the current everyday practice employs equivalent rectangular stress distribution that is derived from normal strength concrete. Subsequently, the stress distribution seems to be reevaluated and then a new distribution with new parameters needs to be suggested for the high strength concrete. For this purpose, linear and multiple regression analyses have been carried out in term of using experimental data for the high strength concrete of 40 to 80 MPa available in literatures. Accordingly, new parameters associated with the stress distribution have been proposed and employed for the design of flexural and compressive members. Comparative design examples indicate that designs with new parameters reduce section dimensions compared to those with the current code parameters for concrete strengths of 40 to 70 MPa. In particular, for compressive members, design with new parameters exhibit conservative compressive force compared to those with the current code parameters.

• Journal of Korean Elementary Science Education
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• v.25 no.spc5
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• pp.556-566
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• 2007

The purpose of this study was to develop an electroencephalogram (EEG) based differential-scale for scientifically gifted students in elementary school. For this study, signals of EEG with 19 channels were recorded during the generation of our scientific hypothesis using 22 scientifically gifted students, and with 49 average students being used as the control group. IQ, TCT and knowledge generation (KG) as constructs of the scientifically gifted were administered for both the scientifically gifted and the normal, control group elementary students. A 'gifted' value was added to paper test scores of the IQ, TCT, and KG constructs in order to make a personal standardization score for the gifted students. As a dependent variable, the groups were divided by means of the standardization scores thus produced and as an autonomous variable, various EEG parameters were presented through linear analysis, nonlinear analysis, and interdependency measures of the EEG. Multiple linear regression analysis was applied successfully to explain the EEG parameters and to show the characteristics of the scientifically-gifted. The discrimination analysis was administered through the results of multiple linear regression of the EEG parameters thus produced. This study represents the foundation of the development of an EEG based discriminant-scale for scientifically gifted students in elementary school, because it will be able to faithfully discriminate between scientifically-gifted and average students. The results of this study indicates that most of the EEG parameters produced can contribute to predicting the characteristics of the scientifically-gifted in that they express the degree of mutual information and the coherence of mutuality. Accordingly, mutual connectivity which appears to originate in the brain seems to the core of discrimination.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.17-17
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• 2021

계획하폭의 수리설계는 수문분석에 의하여 결정되는 설계홍수량을 주변지역 주택이나 농지 침수를 방지하지 않도록 하도내에서 수위를 과다하게 상승시키지 않은 상태에서 안전하게 하류로 소통시킬 수 있는 가장 경제적인 하도의 폭을 결정하는 것이라 할 수 있다. 현재 소하천 하폭의 수리설계는 지형 또는 현장 여건에 따라 계획홍수량을 결정하고, 경험식에 의한 방법 또는 도식에 의한 방법(방정식과 수리학 공식에 의한 방법)등을 이용하여 하류수위를 산정함으로써 이루어진다. 그러나 하도내 흐름이 자유수면을 가지는 개수로 흐름인 경우 도표 또는 간략화된 경험식을 이용해서는 정확한 하폭을 산정할 수 없다. 기존에 개발된 계획하폭 경험식은 홍수량에 기반한 단일 회귀식과 다양한 하천특성과 흐름특성을 이용한 다중 회귀식으로 구분된다. 그러나 현재 계획하폭 결정에 가장 많이 사용되는 경험식은 홍수량을 이용한 단일 회귀식인데, 이들은 자료수집의 어려움 때문에 지역과 하천특성을 고려하지 않고 모든 하천에 적용 가능하도록 개발되어 적용 시 세심한 주의가 요구된다. 본 연구에서는 기존의 경험식을 보완함으로써 적용성을 제고하기 위하여 전국 소하천을 지역에 따라 세분화하고 흐름특성과 하천특성 자료를 수집하였다. 이렇게 수집된 자료를 위치에 따라 세분화하고 기존에 개발된 경험식과 동일한 형태로 계획하폭 경험식을 개발하였다. 개발된 경험식을 검증하는 방법은 자료를 두 개의 그룹으로 분리하고 개발에 사용되지 않은 자료 그룹을 사용함으로써 검증의 신뢰성을 확보하였다. 더불어 기존의 경험식과 비교하는 방법으로 개발된 회귀식의 적용성을 검증하였다. 본 연구에서 개발한 계획하폭 경험식은 지역특성과 흐름특성을 고려한 계획하폭 산정에 활용이 가능함으로써 홍수에 안전한 소하천 수리설계에 활용이 가능할 것으로 기대된다.

• Journal of Soil and Groundwater Environment
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• v.13 no.3
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• pp.27-36
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• 2008

This paper presents a comprehensive laboratory study that examines the effects of porosity, water content, density and grain size distribution on the thermal conductivity of soils which were sampled from 16 synoptic stations of Korea. The experimental results clearly demonstrate that porosity and water content are important parameters which strongly affect the thermal conductivity of soils. Soils with lower porosities and higher water contents have higher thermal conductivities. On the contrary, increase of the matrix density slightly increases the thermal conductivity, and grain size distribution hardly affects the thermal conductivity. Dry soils with the same porosity tend to have more scattered values of thermal conductivity than wet soils. Based on the experimental results, a multiple linear regression model and a nonlinear regression model, having two regression variables of porosity and water content, were presented to predict thermal conductivity. Both models show a high accuracy of prediction with $R^2$ values of 0.74 and 0.82, respectively. Thus, it is expected that the suggested empirical models can be used for predicting thermal conductivity of soils by measuring porosity and water content.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.45-50
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• 2012

This paper on analysis of roundness error after boring turning of Al-6061 materials with CNC lathe. Experiment applying turning parameters is based on experimental design method. A design and analysis of experiments is conducted to study the effects of these parameters on the roundness error using the S/N ratio and analysis of ANOVA. Multiple linear regression analysis is applied to compare experimental with predicted data in consideration of roundness error. To fixation pressure and the opening which are a turning parameter, the cutting depth and feed speed respected the objective attainment of dissertation and to be applied the result they investigated.

• Proceedings of the Korean Printing Society Conference
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• 2000.12a
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• pp.0.2-0
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• 2000

Most important step for the color matching in scanner is the color coordinate transformation from the scanner RGB space to device independent uniform color space. A variety of color calibration technologies have been developed for input device. Linear or nonlinear matrices have been conveniently applied to correct the color filter\`s mismatch with color matching function in scanners. The color matching accuracy is expected to be further improved when the nonlinear matrices are optimized into subdivided smaller color spaces than in single matrix of the entire color space. This article proposed the scanner calibration method using subspace division regression analysis and it were compared with conventional method.