• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.133-144
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• 2021

This study aims to estimate location of land mammals habitat by analyzing spatial data and investigate how to apply environmental DNA monitoring methodology to lotic system in Yangpyeong-gun, Gyeonggi-do. Environmental DNA sampling points are selected through spatial analysis with QGIS open source program by overlaying Kernel density of wild boar(Sus scrofa), elevation, slope and land-cover map, and 81 samples are collected. After 240 mL of water was filtered in each sample, metabarcoding technique using MiMammal universal primer was applied in order to get a whole list of mammal species whose DNA particles contained in filtered water. 8 and 22 samples showed DNA of wild boar and water deer, respectively. DNA of raccoon dog, Eurasian otter, and Siberian weasel are also detected through metabarcoding analysis. This study is valuable that conducted in outdoor lotic system. The study suggests a new wildlife monitoring methodology integrating overlayed geographic data and environmental DNA.

• Journal of KIBIM
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• v.12 no.4
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• pp.104-115
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• 2022

Fine Dust in Korea has been classified as a social disaster since 2019 due to continuous increase in concentration of Particulate Matter 10(PM 10) and PM 2.5. The fine dust issue has negative physical and mental impacts, especially on vulnerable population including children and the elderly. Seoul metropolitan government have installed fine dust shelters since 2019. However, there is a lack of research that evaluates spatiotemporal distribution of these facilities. Therefore, the first aim of this study is to find the relationship between PM levels and dust scattering construction sites, or air pollutant emission sites through in depth spatial analyses. The second purpose is to analyze the spatial distribution of PM shelters in Seoul, and to evaluate the location efficiency of them. Kernel density, krigging, and network analyses were conducted, and floating population was considered instead of census data for this research. The reults of network analysis based on the road system showed that Yangcheon-gu, Songpa-gu, Seongbuk-gu, and Dobong-gu were found to need additional fine dust shelters. Also, the results from analyzing the floating population that includes children and the elderly showed that Songpa-gu, Seodaemun-gu, Gangdong-gu, Seocho-gu, and Dongdaemun-gu need more placements of find dust shelters. The results of this study are expected to provide implications for urban planners to enhance find dust shelter placement in urban areas, and vulnerable population issues would be considered in many ways.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.174-174
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• 2023

The impact of global warming on the south Asian summer monsoon is of critical importance for the large population of this region. This study aims to investigate the future changes of the precipitation extremes during pre-monsoon and monsoon, across this region in a more organized regional structure. The study area is divided into six major divisions based on the Köppen-Geiger's climate structure and 10 sub-divisions considering the geographical locations. The future changes of extreme precipitation indices are analyzed for each zone separately using five indices from ETCCDI (Expert Team on Climate Change Detection and Indices); R10mm, Rx1day, Rx5day, R95pTOT and PRCPTOT. 10 global climate model (GCM) outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are used. The GCMs are bias corrected using nonparametric quantile transformation based on the smoothing spline method. The future period is divided into near future (2031-2065) and far future (2066-2100) and then the changes are compared based on the historical period (1980-2014). The analysis is carried out separately for pre-monsoon (March, April, May) and monsoon (June, July, August, September). The methodology used to compare the changes is probability distribution functions (PDF). Kernel density estimation is used to plot the PDFs. For this study we did not use a multi-model ensemble output and the changes in each extreme precipitation index are analyzed GCM wise. From the results it can be observed that the performance of the GCMs vary depending on the sub-zone as well as on the precipitation index. Final conclusions are made by removing the poor performing GCMs and by analyzing the overall changes in the PDFs of the remaining GCMs.