• Environmental and Resource Economics Review
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• v.11 no.2
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• pp.321-333
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• 2002

Approximating bottled water consumption distribution is complicated by zero observations in the sample. To deal with the zero observations, a mixture model of bottled water consumption distributions is proposed and applied to allow a point mass at zero. The bottled water consumption distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for household bottled water consumption survey data. The mixture model can easily capture the common bimodality feature of the bottled water consumption distribution. In addition, when covariates were added to the model, it was found that the probability that a household has non-consumption significantly varies with some variables.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.251-260
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• 2016

Face recognition is a technology to extract feature from a facial image, learn the features through various algorithms, and recognize a person by comparing the learned data with feature of a new facial image. Especially, in order to improve the rate of face recognition, face recognition requires various processing methods. In the training stage of face recognition, feature should be extracted from a facial image. As for the existing method of extracting facial feature, linear discriminant analysis (LDA) is being mainly used. The LDA method is to express a facial image with dots on the high-dimensional space, and extract facial feature to distinguish a person by analyzing the class information and the distribution of dots. As the position of a dot is determined by pixel values of a facial image on the high-dimensional space, if unnecessary areas or frequently changing areas are included on a facial image, incorrect facial feature could be extracted by LDA. Especially, if a camera image is used for face recognition, the size of a face could vary with the distance between the face and the camera, deteriorating the rate of face recognition. Thus, in order to solve this problem, this paper detected a facial area by using a camera, removed unnecessary areas using the facial feature area calculated via a Gabor filter, and normalized the size of the facial area. Facial feature were extracted through LDA using the normalized facial image and were learned through the artificial neural network for face recognition. As a result, it was possible to improve the rate of face recognition by approx. 13% compared to the existing face recognition method including unnecessary areas.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.876-887
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• 2018

In this paper, we propose an robust CAMShift method to track stage objects with a camera. In order to solve the problem of tracking object misdetection in existing CAMShift technique, MBR region is detected to separate the background and the subject, and the subject size of the region of interest is calculated to solve the problem of erroneously detecting a large region having a similar color distribution ratio. Also, by applying the color corelogram and MB-LBP to the part that can not be solved by the color ratio and the size limitation, accurate texture tracking is enabled by reflecting the texture characteristics. Experimental results show that the proposed method has good tracking performance for objects that do not deviate from the size of the subject set in the area of interest and accurately extracts the texture characteristics of different subjects with similar color distribution ratios.

• Proceeding of KASS Symposium
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• 2008.05a
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• pp.3-8
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• 2008

The purpose of this study is to provide fundamental cooling design data for the large public enclosures as gymnasium. This study executed indoor thermal environment verification of the existing gymnasium by measuring temperature distribution with cooling the space in summer. Cooling loads from human body was not considered. We examined various indoor thermal environment factors of the large enclosed space in this study which include vertical and horizontal temperature distribution, supply and return air flow feature, thermal comfort environment feature, amount of ventilation and etc.

• Journal of Korean Association for Spatial Structures
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• v.7 no.6
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• pp.91-101
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• 2007

The purpose of this study is to provide fundamental cooling design data for the large public enclosures as gymnasium. This study executed indoor thermal environment verification of the existing gymnasium by measuring temperature distribution with and without cooling the space in summer. Colling loads from human body was not considered. We examined various indoor thermal environment factors of the large enclosed space in this study which include vertical and horizontal temperature distribution, supply and return air flow feature, thermal comfort environment feature, amount of ventilation and etc.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.82.1-82.1
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• 2010

We have investigated the spatial configuration of stars within the tidal radius of metal poor globular cluster NGC 6626 in the bulge direction. Data were obtained in near-IR J,H,Ks bands with wide-field ($20'\times20'$) detector, WIRCam at CFHT. To trace the stellar density around target cluster, we sorted cluster's member stars by using a mask filtering algorithm and weighting the stars on the color-magnitude diagram. From the weighted surface density map, we found that the stellar spatial distributions within the tidal radius appear asymmetric and distorted features. Especially, we found that more prominent over-density features are extending toward the direction of Galactic plane rather than toward the directions of the Galactic center and its orbital motion. This orientation of the stellar density distribution can be interpreted with result of disk-shock effect of the Galaxy that the cluster had been experienced. Indeed, this over-density feature are well represented in the radial surface density profile for different angular sections. As one of the metal poor globular clusters with extended horizontal branch (EHB) in the bulge direction, NGC 6626 is kinematically decoupled from the normal clusters and known to have disk motion of peculiar motion. Thus, our result will be able to add further constraints to understand the origin of this cluster and the formation of bulge region in early universe.

• International Journal of Fluid Machinery and Systems
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• v.9 no.1
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• pp.39-46
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• 2016

A high frequency hydraulic rock drill drifter with sleeve valve is developed to use on arm of excavator. In order to ensure optimal working parameters of impact system for the new hydraulic rock drill drifter controlled by sleeve valve, the performance test system is built using the arm and the hydraulic source of excavator. The evaluation indexes are gained through measurement of working pressure, supply oil flow and stress wave. The relations of working parameters to impact system performance are analyzed. The result demonstrates that the maximum impact energy of the drill drifter is 98.34J with impact frequency of 71HZ. Optimal pressure of YZ45 rock drill is 12.8 MPa-13.6MPa, in which the energy efficiency reaches above 58.6%, and feature moment of energy distribution is more than 0.650.

• Korean Journal of Computational Design and Engineering
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• v.13 no.4
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• pp.296-304
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• 2008

Recently, various attempts are being done to apply off-line programming system to field of paint robot. But most commercial simulation softwares have problems that are slow simulation speed and not support various painting paramenters on simulation. This paper proposes enhanced paint simulation method for off-line programming system. For these, this method used the mathematical model of flux field from a previous research. The flux field has the flux distribution function, which reflects on the feature of paint spray. A previous research derived this flux distribution function for an integral function and calculated paint thickness function for an integral function. But if flux distribution function is defined as an integral function, it is inadequate to use for real-time simulation because a number of calculation is needed for estimation of paint thickness distribution. Therefore, we defined the flux distribution function by numerical method for reducing a mount of calculation for estimation of paint thickness. We derived the equation of paint thickness function analytically for reducing a mount of calculation from the paint distribution function defined by numerical method. In order to prove proposed paint simulation method this paper compares the simulated and measured thickness. From this comparison this paper show that paint thickness distribution is predicted precisely by proposed spray paint simulation process.

• Journal of Energy Engineering
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• v.23 no.3
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• pp.36-41
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• 2014

The world's overall need for natural gas (NG) has been growing up fast, especially in the residential sector. The better the estimation of residential NG consumption (RNGC) distribution, the better decision-making for a residential NG policy such as pricing, demand estimation, management options and so on. Approximating the distribution of RNGC is complicated by zero observations in the sample. To deal with the zero observations by allowing a point mass at zero, a mixture model of RNGC distributions is proposed and applied. The RNGC distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for household RNGC survey data collected in Korea. The mixture model can easily capture the common bimodality feature of the RNGC distribution. In addition, when covariates were added to the model, it was found that the probability that a household has non-expenditure significantly varies with some variables. Finally, the goodness-of-fit test suggests that the data are well represented by the mixture model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.861-866
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• 2007

A clustering algorithm for Gaussian Probability Distribution Function (GPDF) data called Centroid Neural Network with a Bhattacharyya Kernel (BK-CNN) is proposed in this paper. The proposed BK-CNN is based on the unsupervised competitive Centroid Neural Network (CNN) and employs a kernel method for data projection. The kernel method adopted in the proposed BK-CNN is used to project data from the low dimensional input feature space into higher dimensional feature space so as the nonlinear problems associated with input space can be solved linearly in the feature space. In order to cluster the GPDF data, the Bhattacharyya kernel is used to measure the distance between two probability distributions for data projection. With the incorporation of the kernel method, the proposed BK-CNN is capable of dealing with nonlinear separation boundaries and can successfully allocate more code vector in the region that GPDF data are densely distributed. When applied to GPDF data in an image classification probleml, the experiment results show that the proposed BK-CNN algorithm gives 1.7%-4.3% improvements in average classification accuracy over other conventional algorithm such as k-means, Self-Organizing Map (SOM) and CNN algorithms with a Bhattacharyya distance, classed as Bk-Means, B-SOM, B-CNN algorithms.