• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.297-309
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• 2007

The first Korean geostationary weather satellite, Communications, Oceanography and Meteorology Satellite (COMS) will be launched in 2008. The ground station for COMS needs to perform geometric correction to improve accuracy of satellite image data and to broadcast geometrically corrected images to users within 30 minutes after image acquisition. For such a requirement, we developed automated and fast geometric correction techniques. For this, we generated control points automatically by matching images against coastline data and by applying a robust estimation called RANSAC. We used GSHHS (Global Self-consistent Hierarchical High-resolution Shoreline) shoreline database to construct 211 landmark chips. We detected clouds within the images and applied matching to cloud-free sub images. When matching visible channels, we selected sub images located in day-time. We tested the algorithm with GOES-9 images. Control points were generated by matching channel 1 and channel 2 images of GOES against the 211 landmark chips. The RANSAC correctly removed outliers from being selected as control points. The accuracy of sensor models established using the automated control points were in the range of $1{\sim}2$ pixels. Geometric correction was performed and the performance was visually inspected by projecting coastline onto the geometrically corrected images. The total processing time for matching, RANSAC and geometric correction was around 4 minutes.

• Spatial Information Research
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• v.2 no.1
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• pp.93-101
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• 1994

A river space means the river related environments such as rIver and floodplain. Because river space data include two-dimensional and three¬dimensional characters. geographic informat ion system is an effect ive tool to manage the data. The objective of this study is to construct the pilot system called RSDB '93 and to simulate the system in practical aspects. The local area for the study was limited about 12km from Jamsil cheolgyo to Dongjak daegyo of the Han River. PC ARC/INFO was selected which can be used on PC 386DX. The Graphic data in an establ ished database contain river layer. floodplain layer. road layer. profile site and hydraulic structure site8 layer. Attributes include water prof i Ie. ut i I i ty status. ecological data. landmark data. hyd¬rology data. water quality data. aerial photo and other photos. RSDB '93 is a system presenting the potentials for the effective river space management which can be applied to all the domestic rivers.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.43-50
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• 2016

This paper introduces an appearance-based facial expression recognition method using ASM landmarks which is used to acquire a detailed face region. In particular, EHMM-based algorithm and SVM classifier with histogram feature are employed to appearance-based facial expression recognition, and performance evaluation of proposed method was performed with CK and JAFFE facial expression database. In addition, performance comparison was achieved through comparison with distance-based face normalization method and a geometric feature-based facial expression approach which employed geometrical features of ASM landmarks and SVM algorithm. As a result, the proposed method using ASM-based face normalization showed performance improvements of 6.39% and 7.98% compared to previous distance-based face normalization method for CK database and JAFFE database, respectively. Also, the proposed method showed higher performance compared to geometric feature-based facial expression approach, and we confirmed an effectiveness of proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1139-1145
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• 2014

Creation of a human skeleton model and characterization of the variation in the bone shape are fundamentally important in many applications of biomechanics. In this paper, we present a parametric shape modeling method for femurs that is based on extracting the main parameter of variations of the femur shape from a 3D model database by using statistical shape analysis. For this shape analysis, principal component analysis (PCA) is used. Application of the PCA to 3D data requires bringing all the models in correspondence to each other. For this reason, anatomical landmarks are used for guiding the deformation of the template model to fit the 3D model data. After subsequent application of PCA to a set of femur models, we calculate the correlation between the dominant components of shape variability for a target population and the anatomical parameters of the femur shape. Finally, we provide tools for visualizing and creating the femur shape using the main parameter of femur shape variation.

• Korean Circulation Journal
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• v.53 no.12
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• pp.829-839
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• 2023

Background and Objectives: There is limited data on the impact of type 2 myocardial infarction (T2MI) during the coronavirus disease 2019 (COVID-19) pandemic. Methods: The National Inpatient Sample (NIS) database from January 2019 to December 2020 was queried to identify T2MI hospitalizations based on the appropriate International Classification of Disease, Tenth Revision-Clinical Modification codes. Monthly trends of COVID-19 and T2MI hospitalizations were evaluated using Joinpoint regression analysis. In addition, the multivariate logistic and linear regression analysis was used to compare inhospital mortality, coronary angiography use, and resource utilization between 2019 and 2020. Results: A total of 743,535 patients hospitalized with a diagnosis of T2MI were identified in the years 2019 (n=331,180) and 2020 (n=412,355). There was an increasing trend in T2MI hospitalizations throughout the study period corresponding to the increase in COVID-19 hospitalizations in 2020. The adjusted odds of in-hospital mortality associated with T2MI hospitalizations were significantly higher in 2020 compared with 2019 (11.1% vs. 8.1%: adjusted odds ratio, 1.19 [1.13-1.26]; p<0.01). In addition, T2MI hospitalizations were associated with lower odds of coronary angiography and higher total hospitalization charges, with no difference in the length of stay in 2020 compared with 2019. Conclusions: We found a significant increase in T2MI hospitalizations with higher in-hospital mortality, total hospitalization costs, and lower coronary angiography use during the early COVID-19 pandemic corresponding to the trends in the rise of COVID-19 hospitalizations. Further research into the factors associated with increased mortality can increase our preparedness for future pandemics.