• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.9-19
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• 2024

As using public monitoring data, analysing a trends of water quality change, establishing a criteria to determine abnormal status and constructing a regression model that can predict Chlorophyll-a, an indicator of eutrophication, was studied. Accordingly, the three freshwater lakes were selected, approximately 20 years of water quality monitoring data were analyzed for periodic changes in water quality each year using regression analysis, and a method for determining abnormalities was presented by the standard deviation at confidence level 95%. By calculating the temporal change rate of Chlorophyll-a from irregular observed data, analyzing correlations between the rate and other water quality items, and constructing regression models, a method to predict changes in Chlorophyll-a was presented. The results of this study are expected to contribute to freshwater lake water quality management as an approximate water quality prediction method using the statistical model.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1787-1793
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• 2018

Shadow is a common phenomenon observed in natural scenes, but it has a negative influence on image analysis such as object recognition, feature detection and scene analysis. Therefore, the process of detecting and removing shadows included in digital images must be considered as a pre-processing process of image analysis. In this paper, the existing methods for acquiring 1D invariant images, one of the feature elements for detecting and removing shadows contained in a single natural image, are described, and a method for obtaining 1D invariant images based on linear regression has been proposed. The proposed method calculates the log of the band-ratio between each channel of the RGB color image, and obtains the grayscale image line by linear regression. The final 1D invariant images were obtained by projecting the log image of the band-ratio onto the estimated grayscale image line. Experimental results show that the proposed method has lower computational complexity than the existing projection method using entropy minimization, and shadow detection and removal based on 1D invariant images are performed effectively.

• Journal of the Korean Society of Radiology
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• v.9 no.6
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• pp.349-356
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• 2015

The study is to recognize the interactions with bone ages by measuring the length between the end of the bone and the growth plate on selected highest weight of regions of seven for bone maturity in TW3 method. The experiment is subjected on seventy-two children (36 males, 36 females) who have examined the growth plate test from March, 2014 to March, 2015 and implemented a regression analysis by measuring the length between the end of the bone and the growth plate in Hand AP image of the children. In result, each bone age has produced a mean value and a standard deviation corresponding to the specific range and as bone age increases the length between the end of the bone and the growth plate decreased. In addition, female children showed lower mean value in comparison to male and also the measurement of the length between the end of the bone and the growth plate and its bone age are shown to be statistically valid(p<0.001) according to the results of regression analysis using its result value. Therefore, the probability of prediction on the bone age read off through the applied TW3 method and regression equation in the Hand AP image of the children.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.931-940
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• 2011

Classification is to generate a rule of classifying objects into several categories based on the learning sample. Good classification model should classify new objects with low misclassification error. Many types of classification methods have been developed including logistic regression, discriminant analysis and tree. This paper presents a new classification method using penalized partial least squares. Penalized partial least squares can make the model more robust and remedy multicollinearity problem. This paper compares the proposed method with logistic regression and PCA based discriminant analysis by some real and artificial data. It is concluded that the new method has better power as compared with other methods.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3523-3529
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• 1999

In this paper, we propose an improved regression testing method, which use method as the basic unit of changing. The testing method consists of three steps. We represent the relationship of classes using the notation of UML(Unified Modeling Language), find the nodes of the modified methods and affected methods by node analysis, and then select changed test cases from the original test cases. The proposed object-oriented regression testing method can reduce the number of test cases, testing time and cost through reuse of test cases.

• Journal of Fashion Business
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• v.6 no.5
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• pp.136-150
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• 2002

In this study, we proposed a method to be standing customers as the supporting system for the improvement of fashion garment industry which was the marginal growth getting into full maturity of market. As for the customer creation method of Fashion garment company is developing a marketing program to be standing customer as customer scoring to estimate a existing customer‘s buying power, and figure out minimum fixed sales of company to use a future purchasing predict. This study was a result of data from total sixty thousands data to be created for the 11 months from september. 2000 to July. 2001. The data is part of which the company leading the Korean fashion garment industry has a lot of a customer purchasing history data. But this study used only 48,845 refined purchased data to discriminate from sixty thousands data and 21,496 customer case with the exception of overlapping purchased data among of those. The software used to handle sixty thousands data was SAS e-miner. As the analysis process is put in to operation the analysis of the purchasing customer’s profile firstly, and the second come into basket analysis to consider the buying associations for Association goods, the third estimate the customer grade of Customer loyalty by 3 ways of logit regression analysis, decision tree, Artificial Neural Network. The result suggested a method to be estimate the customer loyalty as 3 independent variables, 2 coefficients. The 3 independent variables are total purchasing amount, purchasing items per one purchase, payment amount by one purchasing item. The 2 coefficients are royal and normal for customer segmentation. The result was that this model use a logit regression analysis was valid as the method to be estimate the customer loyalty.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.11-22
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• 2019

The objective of this study was to improve the cross-sectional area and height estimation method using stream width. Stream water levels should be calculated together to simulate inundation of agricultural land. However, cross-sectional survey data of small rural rivers are insufficient. The previous study has developed regression equations between the width and the cross-sectional area and between the width and the height of stream cross-section, but can not be applied to a wide range of stream widths. In this study, cross-sectional survey data of 6 streams (Doowol, Chungmi, Jiseok, Gam, Wonpyeong, and Bokha stream) were collected and divided into upstream, midstream and downstream considering the locations of cross-sections. The regression equations were estimated using the complete data. $R^2$ between the stream width and cross-sectional area was 0.96, and $R^2$ between width and height was 0.81. The regression equations were also estimated using divided data for upstream, midstream and downstream considering the locations of cross-sections. The range of $R^2$ between the stream width and cross-sectional area was 0.86 - 0.91, and the range of $R^2$ between width and height was 0.79 ? 0.92. As a result of estimating the cross-sections of 6 rivers using the regression equations, the regression equations considering the locations of cross-sections showed better performance both in the cross-sectional area and height estimation than the regression equations estimated using the complete data. Hydrologic Engineering Center - River Analysis System (HEC-RAS) was used to simulate the flood stage analysis of the estimated and the measured cross-sections for 50-year, 100-year, and 200-year frequency floods. As a result of flood stage analysis, the regression equations considering the locations of cross-sections also showed better performance than the regression equations estimated using the complete data. Future research would be needed to consider the factors affecting the cross-sectional shape such as river slope and average flow velocity. This study can be useful for inundation simulation of agricultural land adjacent to an unmeasured stream.

• International Journal of Highway Engineering
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• v.15 no.6
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• pp.79-91
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• 2013

PURPOSES : The methods of measuring the sound from the noise source are Pass-by method and NCPX (Noble Close Proximity) method. These measuring methods were used to determine the linkage of TAPL (Total Acoustic Pressure Level) and SPL (Sound Pressure Level) in terms of frequencies. METHODS : The frequency analysis methods are DFT (Discrete Fourier Transform) and FFT (Fast Fourier Transform), CPB (Constant Percentage Bandwidth). The CPB analysis was used in this study, based on the 1/3 octave band option configured for the frequency analysis. Furthermore, the regression analysis was used at the condition related to the sound attenuation effect. The MPE (Mean Percentage Error) and RMSE (Root Mean Squared Error) were utilized for calculating the error. RESULTS : From the results of the CPB frequency analysis, the predicted SPL along the frequency has 99.1% maximum precision with the measured SPL, resulting in roughly 1 dB(A) error. The TAPL results have precision by 99.37% with the measured TAPL. The predicted TAPL results at this study by using the SPL prediction model along the frequency have the maximum precision of 98.37% with the vehicle velocity. CONCLUSIONS : The Predicted SPL model along the frequency and the TAPL result by using the predicted SPL model have a high level of accuracy through this study. But the vehicle velocity-TAPL prediction model from the previous study by using the log regression analysis cannot be consistent with the TAPL result by using the predicted SPL model.

• Journal of the Korean Society for Nondestructive Testing
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• v.11 no.2
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• pp.22-31
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• 1991

Various types of ultrasonic techniques have been used for the estimation of compressive strength of concrete structures. However, conventional ultrasonic velocity method using only longitudial wave cannot be determined the compressive strength of concrete structures with accuracy. In this paper, by using the introduction of multiple parameter, e. g. velocity of shear wave, velocity of longitudinal wave, attenuation coefficient of shear wave, attenuation coefficient of longitudinal wave, combination condition, age and preservation method, multiple regression analysis method was applied to the determination of compressive strength of concrete structures. The experimental results show that velocity of shear wave can be estimated compressive strength of concrete with more accuracy compared with the velocity of longitudinal wave, accuracy of estimated error range of compressive strength of concrete structures can be enhanced within the range of ${\pm}$10% approximately.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.03a
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• pp.215-222
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• 2001

Uncertainty study of shear strength characteristics of the marine clays was carried out based ell In-situ tests and laboratory tests on tile south-east coastal region of the Korean peninsula. Theoretical analyses were studied using both tile spherical cavity expansion theory in finite soil mass and the strain path method to determine tile cone factor using the undrained shear strengths obtained by in-situ tests, and the empirical methods in accordance with the ultimate resistance theory were also discussed. Analysis show that the empirical methods suggest more reasonable value than that of theoretical methods in terms of comparing the cone factor estimated using linear regression and frequency distribution analyses. The cone factors obtained by the empirical methods are 18, 15, and 6 respectively, from the results of total cone resistance, effective cone resistance, and excess porewater cone resistance method, and the estimated were similar to those of previous researcher's.