• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.3
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• pp.115-123
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• 2008

Evapotranspiration mapping using both meteorological ground-based measurements and satellite-derived information has been widely studied during the last few decades and various methods have been developed for this purpose. It is significant and necessary to estimate regional evapotranspiration (ET) distribution in the hydrology and water resource research. The study focused on analyzing the surface ET of Chungbuk region using Landsat 7 ETM imagery. For this process, we estimated the regional daily evapotranspiration on May 8, 2000. The estimation of surface evapotranspiration is based on the relationship between Temperature Vegetation Dryness Index (TVDI) and Morton's actual ET. TVDI is the relational expression between Normalized Difference of Vegetation Index (NDVI) and Land Surface Temperature (LST). The distribution of NDVI corresponds well with that of land-use/land cover in Chungbuk. The LST of several part of city in Chungbuk region is higher in comparison with the averaged LST. And TVDI corresponds too well with that of land cover/land use in Chungbuk region. The low evapotranspiration availability is distinguished over the large city like Cheongju-si, Chungju-si and the difference of evapotranspiration availability on forest and paddy is high.

• Publications of The Korean Astronomical Society
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• v.25 no.1
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• pp.23-28
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• 2010

We present results of a test-study of the large-scale survey using the multi-beam receiver system recently installed on the 14 m telescope at Taeduk Radio Astronomy Observatory (TRAO). We have tested several modes of mapping, and found suitable (time-saving) mapping parameters of 'ON-SOURCE' = 8, 'OFF-SOURCE' = 1 when using 'RPT' = 3 as a position-switching mode. We observed 504 spectra towards the NGC 7538, a star forming molecular cloud in the transition of J = 1 - 0 of $^{12}CO$. From the Outer Galaxy Survey database (Heyer et al., 1998) we obtained 504 spectra for the same region. We compared integrated intensities, line profiles of two databases, and found that they are consistent to each other. From the intensity ratio of these two databases we also found that the value of forward spillover scattering of the TRAO telescope system is 0.58.

• Smart Structures and Systems
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• v.22 no.2
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• pp.201-207
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• 2018

This paper proposes a line laser thermography scanning (LLTS) system for multiple crack evaluation on a concrete structure, as the core technology for unmanned aerial vehicle-mounted crack inspection. The LLTS system consists of a line shape continuous-wave laser source, an infrared (IR) camera, a control computer and a scanning jig. The line laser generates thermal waves on a target concrete structure, and the IR camera simultaneously measures the corresponding thermal responses. By spatially scanning the LLTS system along a target concrete structure, multiple cracks even in a large scale concrete structure can be effectively visualized and evaluated. Since raw IR data obtained by scanning the LLTS system, however, includes timely- and spatially-varying IR images due to the limited field of view (FOV) of the LLTS system, a novel time-spatial-integrated (TSI) coordinate transform algorithm is developed for precise crack evaluation in a static condition. The proposed system has the following technical advantages: (1) the thermal wave propagation is effectively induced on a concrete structure with low thermal conductivity of approximately 0.8 W/m K; (2) the limited FOV issues can be solved by the TSI coordinate transform; and (3) multiple cracks are able to be visualized and evaluated by normalizing the responses based on phase mapping and spatial derivative processes. The proposed LLTS system is experimentally validated using a concrete specimen with various cracks. The experimental results reveal that the LLTS system successfully visualizes and evaluates multiple cracks without false alarms.

• Journal of Microbiology and Biotechnology
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• v.28 no.9
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• pp.1517-1526
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• 2018

Investigating bacterial diversity and its metabolic capabilities is crucial for interpreting the ecological patterns in a desert environment and assessing the presence of exploitable microbial resources. In this study, we evaluated the spatial heterogeneity of physicochemical parameters, soil bacterial diversity and metabolic adaptation at meter scale. Soil samples were collected from two quadrats of a desert (Thar Desert, India) with a hot, arid climate, very little rainfall and extreme temperatures. Analysis of physico-chemical parameters and subsequent variance analysis (p-values < 0.05) revealed that sulfate, potassium and magnesium ions were the most variable between the quadrats. Microbial diversity of the two quadrats was studied using Illumina bar-coded sequencing by targeting V3-V4 regions of 16S rDNA. As for the results, 702504 high-quality sequence reads, assigned to 173 operational taxonomic units (OTUs) at species level, were examined. The most abundant phyla in both quadrats were Actinobacteria (38.72%), Proteobacteria (32.94%), and Acidobacteria (9.24%). At genus level, Gaiella represented highest prevalence, followed by Streptomyces, Solirubrobacter, Aciditerrimonas, Geminicoccus, Geodermatophilus, Microvirga, and Rubrobacter. Between the quadrats, significant difference (p-values < 0.05) was found in the abundance of Aciditerrimonas, Geodermatophilus, Geminicoccus, Ilumatobacter, Marmoricola, Nakamurella, and Solirubrobacter. Metabolic functional mapping revealed diverse biological activities, and was significantly correlated with physicochemical parameters. The results revealed spatial variation of ions, microbial abundance and functional attributes in the studied quadrats, and patchy nature in local scale. Interestingly, abundance of the biotechnologically important phylum Actinobacteria, with large proposition of unclassified species in the desert, suggested that this arid environment is a promising site for bioprospection.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.443-451
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• 2006

DEM has been used for various purposes overall fields of engineering, the fields of civil engineering, military, communication, environment, and so forth and its applications are being extending increasingly. It is well hewn that LiDAR DEM is definitely superior to the other surveying methods. But LiDAR DEM run short of a full study about vertical accuracy. In order to assess LiDAR DEM, total 35 stations were selected and surveyed by GPS for utilizing as reference data. And then accuracy of LiDAR DEM was analyzed by comparison between both LiDAR DEM and CPS surveying. The RMSE of ${\pm}0.109m$ was shown in vertical direction. It is within the permissible accuracy required for mapping on a scale of 1 to 500 and 1 to 1000 on the mapping rule notified by the National Geographic Information Institute. It is expected that the results of this study will be fully used in the field of large scale DEM generation and be utilized as basic information in applied field of LiDAR DEM.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.617-625
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• 2014

The Rational Function Model has been used as a replacement sensor model in most commercial photogrammetric systems due to its capability of maintaining the accuracy of the physical sensor models. Although satellite images with rational polynomial coefficients have been used to determine three-dimensional position, it has limitations in the accuracy for large scale topographic mapping. In this study, high resolution stereo satellite images, QuickBird-2, were used to investigate how much the three-dimensional position accuracy was affected by the No. of ground control points, polynomial order, and distribution of GCPs. As the results, we can confirm that these experiments satisfy the accuracy requirements for horizontal and height position of 1:25,000 map scale.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2010.10a
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• pp.11-11
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• 2010

The Korean ginseng, Panax ginseng C. A. Meyer is a popular medicinal herb in Araliaceae. Genetic map in crops provides valuable information for breeding, genetic and genomic researches. However, little information is available for construction of genetic map in ginseng. Up to now, we have produced large amounts of expressed sequence tags (ESTs) from four ginseng cultivars (37Mb, 49Mb, 39Mb, 47Mb from Gopoong, Gumpoong, Chunpoong and Yunpoong respectively using pyrosequencing technique and 5Mb from normalized full-length cDNA library of Chunpoong) to obtain comprehensive information of gene expression, and constructed EST database including ESTs from public database. Till now, we designed 261 SSR primer sets using EST sequences and identified 106 intergenic polymorphic markers. And 44 of the 106 showed polymorphisms among panax ginseng cultivars. Among 44 markers, 27 SSR polymorphic markers were inspected to 51 $F_2$ population from Yunpoong x Chunpoong, which showed good at the fitness of Mendellian segregation ratio 1:2:1. To enrich the number of markers, and thus construct high resolution genetic map which can be used as frame map for further genome sequencing. we are planning to develop large scale EST-derived SNP markers which are available in the F2 population. This study provides genetic information as well as foundation for ginseng researches such as genetics, genomics, breeding, and the final goal for whole genome sequencing. This study was supported by Technology Development Program for Agriculture and Forestry, Ministry for Food, Agriculture, Forestry and Fisheries, Republic of Korea (Grant No. 609001-051SB210).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3984-4005
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• 2017

Image recognition has become an increasingly important topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The recognition systems rely on a key component, i.e. the low-level feature or the learned mid-level feature. The recognition performance can be potentially improved if the data distribution information is exploited using a more sophisticated way, which usually a function over hidden variable, model parameter and observed data. These methods are called generative score space. In this paper, we propose a discriminative extension for the existing generative score space methods, which exploits class label when deriving score functions for image recognition task. Specifically, we first extend the regular generative models to class conditional models over both observed variable and class label. Then, we derive the mid-level feature mapping from the extended models. At last, the derived feature mapping is embedded into a discriminative classifier for image recognition. The advantages of our proposed approach are two folds. First, the resulted methods take simple and intuitive forms which are weighted versions of existing methods, benefitting from the Bayesian inference of class label. Second, the probabilistic generative modeling allows us to exploit hidden information and is well adapt to data distribution. To validate the effectiveness of the proposed method, we cooperate our discriminative extension with three generative models for image recognition task. The experimental results validate the effectiveness of our proposed approach.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.355-361
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• 2006

In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.481-490
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• 2018

Recently, the spatiotemporal patterns of flood disasters have become more complex and unpredictable due to climate change. Flood hazard map including information on flood risk level has been widely used as an unstructured measure against flooding damages. In order to product a high-precision flood hazard map by combination of hydrologic and hydraulic modeling, huge digital information such as topography, geology, climate, landuse and various database related to social economic are required. However, in some areas, especially in developing countries, flood hazard mapping is difficult or impossible and its accuracy is insufficient because such data is lacking or inaccessible. Therefore, this study suggests a method to delineate large scale flood-prone area based on topographic factors produced by linear binary classifier and ROC (Receiver Operation Characteristics) using globally-available geographic data such as ASTER or SRTM. We applied the proposed methodology to five different countries: North Korea Bangladesh, Indonesia, Thailand and Myanmar. The results show that model performances on flood area detection ranges from 38% (Bangladesh) to 78% (Thailand). The flood-prone area detection based on the topographical factors has a great advantage in order to easily distinguish the large-scale inundation-potent area using only digital elevation model (DEM) for ungauged watersheds.