• Journal of the Korean Solar Energy Society
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• v.31 no.1
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• pp.100-106
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• 2011

This study proposes a $CO_2$ emission reduction method through correlation analysis of a sample building. First, energy saving factors of heating, cooling, lighting were determined for the correlation analysis and $CO_2$ emission contribution rate of the design parameters have been analyzed. Then optimal combination of each design parameter has been drawn. Heat transfer coefficient of walls and windows, air permeability, windows area ratio, and shading devices were selected as applicable energy saving factors of the sample building. Also computer simulation was conducted using experimental design by Orthogonal Arrays of the statistical method. And the contribution rate was estimated by Analysis of Variance-ANOVA. As a result, the $CO_2$ emission in heating was reduced to 51.9%; in cooling to 16.8%; and in lighting to 2% compared to the existing building. The majority of the reduction was presented by heating energy.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.429-439
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• 2008

Canonical correlation biplot is 2-dimensional plot for investigating the relationship between two sets of variables and the relationship between observations and variables in canonical correlation analysis graphically. In general, biplot is useful for giving a graphical description of the data. However, this general biplot and also canonical correlation biplot do not give some concise interpretations between variables and observations when the number of observations are large. Recently, for overcoming this problem, Choi and Kim (2008) suggested a method to interpret the biplot analysis by applying the K-means clustering analysis. Therefore, in this study, we will apply their method for investigating the relationship between skill and competition score factors of KLPGA players using canonical correlation biplot and cluster analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.21-33
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• 2006

The reliability analysis can be conducted more effectively by formulating the stochastic finite element method suitable for the reliability theory about the cable stayed bridge. After conducting the initial equilibrium analysis of the cable stayed bridge, the program which can conduct the linear and nonlinear stochastic finite element analysis using the perturbation method and the reliability analysis considered to the correlation of the random variable is developed. Using the results of this program about the cable stayed bridge, the characteristic of the node displacement, element force and cable tension according to the correlation of the random variable is investigated quantitatively. Also the reliability index and the failure probability are examined by the compounding the correlation of the random variable.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.347-355
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• 2001

We propose a method for detecting influential observations that have a large influence on the likelihood ratio test statistic for the two sets of variables are uncorrelated with one another. For this purpose we derive a local influence measure for the likelihood ratio test statistic under certain perturbation scheme. An illustrative example is given to show the effectiveness of the proposed method on the identification of influential observations.

• Explosives and Blasting
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• v.39 no.4
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• pp.1-11
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• 2021

In this study, the vibration data were obtained to analyze the vibration generated during dismantling of slab using the mechanical dismantling method. The obtained vibration data were classified according to the attachment device and then the waveform and dominant frequency analysis were performed. And the correlation was analyzed by the different methods of measuring the distance between the work section and the measurement point. As a result of the waveform analysis for each attachment device, there was little change in the phase of the vibration waveform and only the change in amplitude, which is the magnitude of the vibration velocity. And as a result of frequency analysis, the frequency band was lower when using a crusher method than a braker method and frequency band were close of the natural frequency of the structure to be dismantled. As a result of the correlation analysis, the separation distance was estimated a higher correlation when evaluated as the path through which the vibration propagates along the structure frame than the straight distance between the measurement point and the working section.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.495-513
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• 2020

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Journal of Integrative Natural Science
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• v.5 no.2
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• pp.120-126
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• 2012

This paper describes the algorithm that lowers the dimension, maintains the gesture recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.82-88
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• 2014

The government expands its investment on R&D programs for economic growth, thus there is growing attention on the result of R&D Programs. This study proposes more improved measuring method for efficiency when the number of R&D programs is not enough to be for measuring efficiency analysis. It provides more various application method of factors on efficiency analysis. This study analyzes the influence of each input factor on efficiency by using partial efficiency concept. And it also determines input factors in similar influence throughout Spearman correlation coefficient. Finally, it suggests new method to improve discriminatory power of efficiency analysis by determining representative factors. Also, the proposed method can be practiced not only for national R&D programs, but also for other fields of research.

• Structural Engineering and Mechanics
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• v.4 no.6
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• pp.703-715
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• 1996

In stochastic analysis, the randomness of the structural parameters is taken into consideration and the response variability is obtained in addition to the conventional (mean) response. In the present paper the structural response variability of plate structure is calculated using the weighted integral method and is compared with the results obtained by different methods. The stochastic field is assumed to be normally distributed and to have the homogeneity. The decomposition of strain-displacement matrix enabled us to extend the formulation to the stochastic analysis with the quadratic elements in the weighted integral method. A new auto-correlation function is derived considering the uncertainty of plate thickness. The results obtained in the numerical examples by two different methods, i.e., weighted integral method and Monte Carlo simulation, are in a close agreement. In the case of the variable plate thickness, the obtained results are in good agreement with those of Lawrence and Monte Carlo simulation.