• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.98-108
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• 2008

Terrain reconstruction from images is an ill-posed, yet commonly desired Structure from Motion task when compositing visual effects into live-action photography. These surfaces are required for choreography of a scene, casting physically accurate shadows of CG elements, and occlusions. We present a novel framework for generating the geometry of landscapes from extremely noisy point cloud datasets obtained via limited resolution techniques, particularly optical flow based vision algorithms applied to live-action video plates. Our contribution is a new statistical approach to remove erroneous tracks ('outliers') by employing a unique combination of well established techniques-including Gaussian Mixture Models (GMMs) for robust parameter estimation and Radial Basis Functions (REFs) for scattered data interpolation-to exploit the natural constraints of this problem. Our algorithm offsets the tremendously laborious task of modeling these landscapes by hand, automatically generating a visually consistent, camera position dependent, thin-shell surface mesh within seconds for a typical tracking shot.

• Journal of Environmental Science International
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• v.9 no.4
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• pp.295-302
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• 2000

This study was conducted to investigate the characteristics of surface ozone concentration and occurrence of high ozone concentration using hourly ozone, nitrogen dioxide and meteorological data for 1997~1998 in Pusan coastal area. Monthly mean ozone concentration was the highest at Dongsamdong in Spring(35.4ppb), at Kwangbokdong in Fall(25.1ppb) and the lowest Dongsamdong(22.2ppb) and Kwangbokdong(16.0ppb) in Winter. Relative standard deviation indicating clearness of observation site was 0.42 at Dongsamdong and 0.49 at Kwangbokdong that is similar to urban area. The diurnal variation of ozone concentration of Dongsamdong and Kwangbokdong showed maximum at 1500~1600LST and minimum 0700~0800LST that typical pattern of ozone concentration. In ozone episode period(Sept. 10~15, 1998), diurnal change of ozone concentration was very high, and ozone concentration was related to meteorological parameters such as temperature, relative humidity, wind speed, cloud amount and radiation on a horizontal surface. During the episode days peak ozone concentrations are much higher than the normal values, wind speeds are always lower, and solar radiation is high with the exception of the September episode.

• Journal of the Korean Society of Safety
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• v.14 no.2
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• pp.109-115
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• 1999

The release of gas from the LPG storage tank by the rupture or leakage can occure explosion and this causes serious damage to people and structures. In this study, the explosion effect and damaging distance were measured for the LPG cloud explosion to perform the quantitative risk assessment for the PSM, and the effective parameters on the explosion were found. The gas dispersion and mass contaminant in the explosion limits were calculated by using DEGADIS, and it was converted to TNT equivalency and damaging distance. As a result, the wind speed was the most effective parameter on the diffusion rate and TNT equivalency, and the damaging distance were increased with decrease of wind speed and surface roughness.

• Publications of The Korean Astronomical Society
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• v.9 no.1
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• pp.39-54
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• 1994

We present two codes which estimates virial mass and LTE mass using IMFORT interface within IRAF (Image Reduction and Analysis Facility). It is discussed that threshold value (temperature or CO integrated intensity), which defines a reasonable cloud boundary and size, is the most important parameter determining accurate results. Several virial masses are to be obtained using the vir task, as well as three velocity dispersions including the centroid velocity dispersion, a turbulence indicator. LTE mass is to be estimated by using task lte as well as three by-product images. The $^{13}CO$ abundance and threshold temperature of $^{13}CO$ and $^{12}CO$ peak temperatures are the most critical parameters in LTE technique.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.146-148
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• 2007

CMDPS (COMS Meteorological Data Processing System) is the operational meteorological products extraction system for data observed from COMS (Communication, Ocean and Meteorological Satellite) meteorological imager. CMDPS baseline products consist of 16 parameters including cloud information, water vapor products, surface information, environmental products and atmospheric motion vector. Additionally, CMDPS includes the function of calibration monitoring, and validation mechanism of the baseline products. The main objective of CMDPS validation module development is near-real time monitoring for the accuracy and reliability of the whole CMDPS products. Also, its long time validation statistics are used for upgrade of CMDPS such as algorithm parameter tuning and retrieval algorithm modification. This paper introduces the preliminary design on CMDPS validation module.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.511-512
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• 2003

The Terra/MODIS data set over Yellow River Basin, China is generated for the purpose of an input parameter into the water resource management model, which has been developed in the Research Revolution 2002 (RR2002) project. This dataset is mainly utilized for the land cover classification and radiation budget analysis. In this paper, the outline of the dataset generation, and a simple land cover classification method, which will be developed to avoid the influence of cloud contamination and missing data, are introduced.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.81-84
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• 2021

In this paper, a rate-distortion optimization (RDO) model is proposed to find the joint bit allocation of geometry data and color data based on geometry-based point cloud compression (G-PCC) of Moving Picture Experts Group (MPEG). The mechanism of the method is to construct the RD models for geometry and color data through the training process. Afterward, two rate-distortion (RD) models are integrated as well as the decision of the parameter λ to obtain the final RDO model. The experimental results show that the proposed method can decrease 20% of the geometry Bjøntegaard delta bit rate and increase 37% of the color Bjøntegaard delta bit rate compared to the MPEG G-PCC TMC13v12.0 software.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.6
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• pp.1-14
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• 2019

Carbon storage is one of the regulating ecosystem services provided by urban street trees. It is important that evaluating the economic value of ecosystem services accurately. The carbon storage of street trees was calculated by measuring the morphological parameter on the field. As the method is labor-intensive and time-consuming for the macro-scale research, remote sensing has been more widely used. The airborne Light Detection And Ranging (LiDAR) is used in obtaining the point clouds data of a densely planted area and extracting individual trees for the carbon storage estimation. However, the LiDAR has limitations such as high cost and complicated operations. In addition, trees change over time they need to be frequently. Therefore, Structure from Motion (SfM) photogrammetry with unmanned Aerial Vehicle (UAV) is a more suitable method for obtaining point clouds data. In this paper, a UAV loaded with a digital camera was employed to take oblique aerial images for generating point cloud of street trees. We extracted the diameter of breast height (DBH) from generated point cloud data to calculate the carbon storage. We compared DBH calculated from UAV data and measured data from the field in the selected area. The calculated DBH was used to estimate the carbon storage of street trees in the study area using a regression model. The results demonstrate the feasibility and effectiveness of applying UAV imagery and SfM technique to the carbon storage estimation of street trees. The technique can contribute to efficiently building inventories of the carbon storage of street trees in urban areas.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.2
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• pp.53-62
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• 2020

This study is to evaluate the accuracy of the meteorological information provided for the aircraft operating at low altitude. At first, it is necessary to identify crucial elements of weather information closely related to flight safety during low altitude flights. The study conducted a survey of pilots of low altitude aircraft, divided into pre-flight and in-flight phases, and reached an opinion that wind direction, wind speed, cloud coverage and ceiling and visibility are important items. Related to these items, we compared and calculated the accuracy of TAFs and METARs from Taean Airfield, Seosan Airport and Gunsan Airport because of their high number of domestic low-altitude flights. Accuracy analysis evaluated the accuracy of two numerical variables, Mean Absolute Error(MAE) and Root Mean Square Error(RMSE), and the cloud coverage which is categorical variable was calculated and compared by accuracy. For numeric variables, one-way ANOVA, which is a parameter-test, was approached to identify differences between actual forecast values and observations based on absolute errors for each item derived from the results of MAE and RMSE accuracy analyses. To determine the satisfaction of both normality assumptions and equivalence variability assumptions, the Shapiro-Wilk test was performed to verify that they do not have a normality distribution for numerical variables, and for the non-parametric test, Kruscal-Wallis test was conducted to determine whether or not they are satisfied.