• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• Journal of the Korean Society of Radiology
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• v.84 no.5
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• pp.1123-1133
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• 2023

Purpose Our study aimed to evaluate the association between automated quantified body composition on CT and pulmonary function or quantitative lung features in patients with chronic obstructive pulmonary disease (COPD). Materials and Methods A total of 290 patients with COPD were enrolled in this study. The volume of muscle and subcutaneous fat, area of muscle and subcutaneous fat at T12, and bone attenuation at T12 were obtained from chest CT using a deep learning-based body segmentation algorithm. Parametric response mapping-derived emphysema (PRM^emph), PRM-derived functional small airway disease (PRM^fSAD), and airway wall thickness (AWT)-Pi10 were quantitatively assessed. The association between body composition and outcomes was evaluated using Pearson's correlation analysis. Results The volume and area of muscle and subcutaneous fat were negatively associated with PRM^emph and PRM^fSAD (p < 0.05). Bone density at T12 was negatively associated with PRM^emph (r = -0.1828, p = 0.002). The volume and area of subcutaneous fat and bone density at T12 were positively correlated with AWT-Pi10 (r = 0.1287, p = 0.030; r = 0.1668, p = 0.005; r = 0.1279, p = 0.031). However, muscle volume was negatively correlated with the AWT-Pi10 (r = -0.1966, p = 0.001). Muscle volume was significantly associated with pulmonary function (p < 0.001). Conclusion Body composition, automatically assessed using chest CT, is associated with the phenotype and severity of COPD.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.2
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• pp.149-166
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• 2006

The purpose of this study is to produce time-distance cartograms based on the various Korean transportation networks, and to analyze the spatial structure of time-distance accessibilities. For the purpose this study attempts to develop continuous area cartogram by utilizing Wolf's algorithm for creating contiguous cartogram in ArcGIS 9. The absolute physical space was transformed to the functional space indexed by time-distances along various transportation networks in Korea. We examined the differences in the time-distance accessibilities among transportation networks. This study makes a comparison between the spatial structure of time-distance accessibility of KTX network with them of existing railroad network, as well as with them of road network. In order to clarify the spatial structures of time-distance accessibilities, we restructured them on the time-distance circular diagrams and performing Multi-Dimensional Scaling analysis. Overall structure of time-distance accessibilities shows similar patterns: The time distances are shrinked a lot along the Seoul-Busan axis, while coastal parts, in particular the eastern part of the county, are shrinked relatively little via all transportation networks. The Road network affects significantly on the accessibilities of cities in Gangwon-do and Gyeonggi-do, while railway network affects on the accessibilities of cities in Jeolla-do and Gyeongsang-do in general. When we compared the time-distance accessibilities based on the 5 largest cities, Seoul appears as the most accessible city from/to all other cities in Korea. We can also find significant changes in the time-distance accessibility between KTX network and existing railroad network. Cities along the KTX network, in particular cities which has KTX stops, improved significantly in time-distance accessibilities.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.301-312
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• 2013

Landslides are caused by complex interaction among a large number of interrelated factors such as topography, geology, forest and soils. In this study, a comparative study was carried out using fuzzy relationship method and artificial neural network to evaluate landslide susceptibility. For landslide susceptibility mapping, maps of the landslide occurrence locations, slope angle, aspect, curvature, lithology, soil drainage, soil depth, soil texture, forest type, forest age, forest diameter and forest density were constructed from the spatial data sets. In fuzzy relation analysis, the membership values for each category of thematic layers have been determined using the cosine amplitude method. Then the integration of different thematic layers to produce landslide susceptibility map was performed by Cartesian product operation. In artificial neural network analysis, the relative weight values for causative factors were determined by back propagation algorithm. Landslide susceptibility maps prepared by two approaches were validated by ROC(Receiver Operating Characteristic) curve and AUC(Area Under the Curve). Based on the validation results, both approaches show excellent performance to predict the landslide susceptibility but the performance of the artificial neural network was superior in this study area.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.162-174
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• 2012

To visualize the characteristics of vertical seawater temperature data, in the ocean having 3D spatial characteristics, 2D thematic maps like horizontal seawater temperature distribution map at each depth layer and 3D volume model using 3D spatial interpolation are used. Although these methods are useful to understand oceanographic phenomena visually, there is a limit to analyze the spatial pattern of vertical temperature distribution or the relationship between vertical temperature characteristics and other oceanic factors (seawater chemistry, marine organism, climate change, etc). Therefore, this study aims to determine the spatial distribution characteristics of vertical temperature profiles in the South Sea of Jeju by quantifying the characteristics of vertical temperature profiles by using an algorithm that can extract the thermocline parameters, such as mixed layer depth, maximum temperature gradient and thermocline thickness. For this purpose spatial autocorrelation index (Moran's I) was calculated including mapping of spatial distribution for three parameters representing the vertical temperature profiles. Also, after grouping study area as four regions by using cluster analysis with three parameters, the characteristics of vertical temperature profiles were defined for each region.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.69-79
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• 2013

This paper presents a two-stage geostatistical integration approach that aims at downscaling of coarse scale remote sensing data. First, downscaling of the coarse scale sedoncary data is implemented using area-to-point kriging, and this result will be used as trend components on the next integration stage. Then simple kriging with local varying means that integrates sparse precise observation data with the downscaled data is applied to generate thematic information at a finer scale. The presented approach can not only account for the statistical relationships between precise observation and secondary data acquired at the different scales, but also to calibrate the errors in the secondary data through the integration with precise observation data. An experiment for precipitation mapping with weather station data and TRMM (Tropical Rainfall Measuring Mission) data acquired at a coarse scale is carried out to illustrate the applicability of the presented approach. From the experiment, the geostatistical downscaling approach applied in this paper could generate detailed thematic information at various finer target scales that reproduced the original TRMM precipitation values when upscaled. And the integration of the downscaled secondary information with precise observation data showed better prediction capability than that of a conventional univariate kriging algorithm. Thus, it is expected that the presented approach would be effectively used for downscaling of coarse scale data with various data acquired at different scales.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.7
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• pp.402-413
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• 2004

This paper presents an Implementation of Korean standard 128-bit block cipher SEED for the small (8 or 16-bits) embedded system using a low-cost FPGA(Field Programmable Gate Array) chip. Due to their limited computing and storage capacities most of the 8-bits/16-bits small embedded systems require a separate and dedicated cryptography processor for data encryption and decryption process which require relatively heavy computation job. So, in order to integrate the SEED with other logic circuit block in a single chip we need to invent a design which minimizes the area demand while maintaining the proper performance. But, the straight-forward mapping of the SEED specification into hardware design results in exceedingly large circuit area for a low-cost FPGA capacity. Therefore, in this paper we present a design which maximize the resource sharing and utilizing the modern FPGA features to reduce the area demand resulting in the successful implementation of the SEED plus interface logic with single low-cost FPGA. We achieved 66% area accupation by our SEED design for the XC2S100 (a Spartan-II series FPGA from Xilinx) and data throughput more than 66Mbps. This Performance is sufficient for the small scale embedded system while achieving tight area requirement.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1292-1299
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• 2014

Weather radar systems can provide weather information of the ground, sea, and air in extensive spatial coverage in near real time. However, it becomes problematic when ground clutter signal exists around precipitation because strong signals of ground can cause a false precipitation report. A large percentage of land coverage of Korea consists of mountainous regions where ground clutter needs to be mitigated for more accurate prediction. Thus, it is considered necessary to introduce a new suitable ground clutter removal technique specifically adequate for Korea. In this paper, the C-Map(Clutter Map) method using raw radar signals is proposed for removing ground clutter using a terrain-adaptive clutter map. A clutter map is generated using raw radar signals(I/Q) of clear days, then it is subtracted from received radar signals in frequency domain. The proposed method is applied to the radar data acquired from Sobaeksan rain radar and the result shows that the clutter rejection ratio is about 91.17 %.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.373-380
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• 2003

Most of low cost digital cameras reveal relatively high lens distortion. The purpose of this research is to compensate the degradation of image quality due to the geometrical distortion of a lens system. The proposed method consists of two stages : calculation of a lens distortion coefficient by a simplified version of Tsai´s camera calibration and subsequent image warping of the original distorted image to remove geometrical distortion based on the calculated lens distortion coefficient. In the lens distortion coefficient calculation stage, a practical method for handling scale factor ratio and image center is proposed, after which its feasibility is shown by measuring the performance of distortion correction using a quantitative image quality measure. On the other hand, in order to apply image warping via inverse spatial mapping using the result of the lens distortion coefficient calculation stage, a cubic polynomial derived from an adopted radial distortion lens model must be solved. In this paper, for the purpose of real-time operation, which is essential for embedding into an information device, an approximated solution to the cubic polynomial is proposed in the form of a solution to a quadratic equation. In the experiment, potential for real-time implementation and equivalence in performance as compared with that from cubic polynomial solution are shown.

• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.363-383
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• 2007

Global map of science, which is visualizing large scientific domains, can be used to visually analyze the structural relationships between major areas of science. This paper reviewed previous efforts on global science map, and then tried to making a science map of Korea with some new methods. There are several research groups on making global map of science including Dr. Small and Dr. Garfield of ISI (now Thompson Scientific), SCImago research group at the University of Granada, and Dr. Borner's InfoVis Lab at the Indiana University. They called their maps as science map or scientogram and called the activity of mapping science as scientography. Most of the previous works are based on citations between scientific articles. However citation database for Korean journal articles is still under construction. This research tried to make a Korean science map with the text in the proposals suggested for funding from Korean Research Foundation. Two kinds of method for generating networks of scientific fields are used. One is Pathfinder network (PFNet) alogorithm which has been used in several published bibliometric studies. The other is clustering-based network (CBnet) algorithm which was proposed recently as an alternative to PFNet. In order to take into account both views of the two algorithms, the resulting maps are combined to a final science map of Korea.