• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1011-1020
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• 2018

This study aims to develop a drought monitoring scheme based on groundwater which can be exploit for water supply under drought stress. In this context, groundwater level can be used as a proxy for better understanding the temporal evolution of drought state. First, kernel density estimator is presented in the monthly groundwater level over the entire national groundwater stations. The estimated cumulative distribution function is then utilized to map the monthly groundwater level into the standardized groundwater level index (SGI). The SGI for each station was eventually converted into the index for major cities through the Thiessen polygon approach. We provide a drought classification for a given SGI to better characterize the degree of drought condition. Ultimately, we conclude that the proposed monitoring framework enables a more reliable estimation of the drought stress, especially for a limited water supply area.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.525-534
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• 2017

The open set recognition method should be used for the cases that the classes of test data are not known completely in the training phase. So it is required to include two processes of classification and the validation test. This kind of research is very necessary for commercialization of face recognition modules, but few domestic researches results about it have been published. In this paper, we propose an open set face recognition method that includes two sequential validation phases. In the first phase, with dummy classes we perform classification based on sparse representation. Here, when the test data is classified into a dummy class, we conclude that the data is invalid. If the data is classified into one of the regular training classes, for second validation test we extract four features and apply them for the proposed decision function. In experiments, we proposed a simulation method for open set recognition and showed that the proposed validation test outperform SCI of the well-known validation method

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.251-264
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• 2008

In this study, a nonhomogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrologic variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and flood in the watershed, and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase. Therefore, with the proposed approach, the non-homogeneous markov model can be used to estimate variables for the purpose of design of hydraulic structures and analyze uncertainties associated with rainfall input in the hydrologic models.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1319-1324
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• 2013

The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color histograms or kernel density estimates of the target and candidate image. However, it is sensitive to the noises due to objects or background having similar color distributions. In addition, occlusion by another object often causes a face region to change in size and position although a face region is a critical clue to perform face recognition or compute face orientation. We assume that depth and color are effective to separate a face from a background and a face from objects, respectively. From the assumption we devised a bilateral filter using color and depth and incorporate it into the mean-shift algorithm. We demonstrated the proposed method by some experiments.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.247-256
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• 2012

Recently, estimation of greenhouse gas (GHG) emission has continuously emerged as an important global issue. This study compares various statistical methods for estimation of fuel consumption, which is necessary for calculation of GHG emission in road transportation sector. Existing methods have focused on using merely transportation fuel supply or distance traveled for calculation of fuel consumption. Estimates of GHG emission based on fuel supply, however, cannot reflect various vehicle types or model year. This study suggests and compares, from statistical point of view, several methods, which can be applied to estimate fuel consumption of each vehicle, by combining distance traveled and fuel efficiency (mileage), and total fuel consumption of all vehicles. It also suggests practical measures that can reflect vehicle types and model year to suggested methods for future research.

• Smart Structures and Systems
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• v.20 no.6
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• pp.769-780
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• 2017

Cable force monitoring is an essential and critical part of the safety evaluation of cable-supported bridges. A reasonable cable force monitoring scheme, particularly, sensor placement related to accurate safety assessment and budget cost-saving becomes a major concern of bridge administrative authorities. This paper presents optimal sensor placement for cable force monitoring by selecting representative sensor positions, which consider the spatial correlativeness existing in the cable group. The limited sensors would be utilized for maximizing useful information from the monitored bridges. The maximum information coefficient (MIC), mutual information (MI) based kernel density estimation, as well as Pearson coefficients, were all employed to detect potential spatial correlation in the cable group. Compared with the Pearson coefficient and MIC, the mutual information is more suitable for identifying the association existing in cable group and thus, is selected to describe the spatial relevance in this study. Then, the bond energy algorithm, which collects clusters based on the relationship of surrounding elements, is used for the optimal placement of cable sensors. Several optimal placement strategies are discussed with different correlation thresholds for the cable group of Nanjing No.3 Yangtze River Bridge, verifying the effectiveness of the proposed method.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.681-687
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• 2007

Face recognition technique is very popular for a personal information security and user identification in recent years. However, the face recognition system is very hard to be implemented due to the difficulty where change in illumination, pose and facial expression. In this paper, we consider that an illumination change causing the variety of face appearance, virtual image data is generated and added to the D-LDA which was selected as the most suitable feature extractor. A less sensitive recognition system in illumination is represented in this paper. This way that consider nature of several illumination directions generate the virtual training image data that considered an illumination effect of the directions and the change of illumination density. As result of experiences, D-LDA has a less sensitive property in an illumination through ORL, Yale University and Pohang University face database.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.595-604
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• 2005

Precipitation simulation for making the data size larger is an important task for hydrologic analysis. The simulation can be divided into two major categories which are the parametric and nonparametric methods. Also, precipitation simulation depends on time intervals such as daily or hourly rainfall simulations. So far, Markov model is the most favored method for daily precipitation simulation. However, most models are consist of state transition probability by using the homogeneous Markov chain model. In order to make a state vector, the small size of data brings difficulties, and also the assumption of homogeneousness among the state vector in a month causes problems. In other words, the process of daily precipitation mechanism is nonstationary. In order to overcome these problems, this paper focused on the nonparametric method by using uni-variate and multi-variate when simulating a precipitation instead of currently used parametric method.

• Journal of the Korea Institute of Building Construction
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• v.19 no.1
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• pp.39-46
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• 2019

A three-dimensional flow simulation model for high flow concrete was developed using Incompressible Smoothed Particle Hydrodynamics (ISPH), which can solved Navier-Stokes equation with the assumption of a fluid to be incompressible. For the simulation, a computer program code for ISPH was implemented with MATALB programming code. A piecewise cubic spline function was used for the kernel function of ISPH. Projetion method was used to calculate the velocity and pressure of particles as a function of time. Fixed ghost particle was used for wall boundary condition. Free surface boundaries were determined by using virtual density of particles. In order to validate the model and the code, the simulation results of slump flow test, $T_{500}$ test and L-box test were compared with experimental ones. The simulation results were well matched with the experimental results. The simulation described successfully the characteristics of the flow phenomenon according to the change of the viscosity and yield stress of high flow concrete.

• Journal of the Korea Computer Graphics Society
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• v.25 no.1
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• pp.13-22
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• 2019

In this paper, we propose a new method to improve the details of the fluid surface by removing liquid sheets that are over-preserved in particle-based water simulation. A variety of anisotropic approaches have been proposed to address the surface noise problem, one of the chronic problems in particle-based fluid simulation. However, a method of stably expressing the preservation and breakup of the liquid sheet has not been proposed. We propose a new framework that can dynamically add and remove the water particles based on anisotropic kernel and density to simultaneously represent two features of liquid sheet preservation and breakup in particle-based fluid simulations. The proposed technique well represented the characteristics of a fluid sheet that was breakup by removing the excessively preserved liquid sheet in a particle-based fluid simulation approach. As a result, the quality of the liquid sheet was improved without noise.