• The Journal of Engineering Geology
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• v.23 no.4
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• pp.477-491
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• 2013

Natural radionuclides in groundwater in the Danyang area were investigated to characterize the behaviors of uranium and radon with respect to lithology and physico-chemical components, which can aid our understanding of their occurrence, properties, and origins. To this end, a total of 100 groundwater samples were collected and analyzed, and radionuclide levels were used to construct detailed concentration maps. The water type of the groundwater, assessed using a Piper diagram, is mainly Ca-Na-$HCO_3$. The concentrations of uranium range from 0.02 to $251.0{\mu}g/L$ (average, $3.85{\mu}g/L$) and only 1% exceed USEPA's MCL (Maximum Contaminant Level). Uranium is enriched in groundwaters of Cretaceous granites and Precambrian metamorphic rocks, whereas it is depleted in groundwaters of sedimentary rocks. The concentrations of radon range from 13 to 28,470 pCi/L (average, 2397 pCi/L). Only 15% of the samples exceed AMCL (Alternative Maximum Contaminant Level) of 4000 pCi/L. The radon concentration is highest in groundwater of Cretaceous granites and lowest in groundwater of sedimentary rocks. In conclusion, the distribution and occurrence of radionuclides are intimately related to the basic geological characteristics of the rocks in which the radiogenic minerals are primarily contained. The behavior of uranium is only weakly related to that of radon (correlation coefficient = 0.15). There are also weak correlations between radionuclides and the main chemical components, pH, EC, Eh, and well depth. Of note, the correlation coefficient between radon and $SiO_2$ is 0.68, and that between radon and $HCO_3$ is -0.48. Factor analysis shows that radionuclides behave somewhat independently of each other because there are no significant factors that control the behavior of chemical components as well as radionuclides. The detailed concentration maps during this study will be used to establish useful database of radionuclide distribution and geological properties throughout Korea.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.4
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• pp.303-313
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• 2020

Rice grain shape is one of the key components of grain yield and market value. An understanding of the genetic basis of the variation in grain shape could be used to improve grain shape. In this study, we developed a total of 265 F₂ individuals derived from a cross between japonica cultivars (Josaeng-jado and Langi) and used this population for quantitative trait locus (QLT) analysis. Correlation analysis was performed to identify relationships between grain traits (GL: grain length, GW: grain width, L/W: ratio of length to width, TGW: 1,000 grain weight). The grain shape was positively correlated with GL and TGW, and negatively correlated with GW. In QTL analysis associated with grain shape, one QTL for GL, qGL5, detected on chromosome 5, explained 20.3% of the phenotypic variation (PV), while two QTLs, qGW5 (PV=36.1) and qGW7 (PV=26.1), for GW were identified on chromosomes 5 and 7, respectively. Evaluation of the effects of each of the QTLs on the grain shape in the population showed a significant difference in the grain size in positive lines compared with the lines without the QTLs. According to the QTL combination of the allelic-types, the grain shape of the tested lines varied from semi-round type to long spindle-shaped type. The results of this study extend our knowledge about the genetic pool governing the diversity of grain shape in japonica cultivars and could be used to improve the grain shape of this species through marker-assisted selective breeding in Korea.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.2
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• pp.87-97
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• 2020

The compositions of the phenocrystic feldspars of the Sanbangsan trachyte range from labradorite(An_53.6) to andesine(An_35.4), and of the microphenocrysts and laths range from andesine(An_31.2) to oligoclase(An_18.7). Mantled feldspar which forms a thin rim around the phenocrysts and microphenocrysts, is anorthoclase(Or_20.5An_9.4) to sanidine(Or_49.2An_1.4). Phenocrystic plagioclase, which shows a distinct zonal structure, represents an oscillatory zoning in which the An content of the zone repeatedly increases or decreases between andesine (An_39.3) and labradorite (An_51.3) from the core toward the rim, and the rim of the phenocrysts is surrounded by alkali feldspar(Or_31.9-39.4Ab_63.2-57.0An_4.9-3.7), showing the antirapakivi texture. Microphenocryst which does not represent the antirapakivi texture, shows the normal zoning with a decreasing An content (An_36.4→An_25.6) as it moves outward from the center of a crystal. As a result of X-ray mapping of K, Ca, and Na elements for the feldspar phenocrysts representing the typical zonal structure, shows the oscillatory zoning that six zones show the distinctive compositional differences, and the rims are mantled by alkali feldspar to indicate the antirapakivi texture. The groundmass is composed of K-enriched, Ca-poor alkali feldspar. The antirapakivi texture of feldspar which appears in Sanbangsan trachyte, may have been formed in mixing systems as a result of the juxtaposition of near liquidus melt, rich in alkali feldspar components(trachytic magma), with plagioclase phenocrysts and microphenocrysts already crystallized in a more mafic system.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.6
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• pp.522-528
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• 2009

This study focused on establishing prediction models using visible-near infrared spectrum to simultaneously detect multiple components of soils and enhancing the performance quality by suitably transformed input spectra and classification of soil spectral types for prediction model input. The continuum-removed spectra showed significant result for all cases in terms of soil properties and classified or bulk predictions. The prediction model using classified soil spectra at an absorption peak area around 500nm and 950nm efficiently indicating soil color showed slightly better performance. Especially, Ca and CEC were well estimated by the classified prediction model at $R^{2}$ > 0.8. For organic carbon, both classified and bulk prediction model had a good performance with $R^{2}$ > 0.8 and RPD> 2. This prediction model may be applied in global soil mapping, soil classification, and remote sensing data analysis.

• The Korean Journal of Ecology
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• v.26 no.5
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• pp.237-246
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• 2003

A mountain village is defined as that which is autogenously formed over at least 100 years and supported by agricultural yields and forest products and forest area portion of which is over 70% in Guidelines for the Comprehensive Development Planning of Mountain Village. Recently, concerns about management planning of the Green and Eco-Village causes researches related to the Mountain Village's economics, tourism attractiveness, experience programming and investigation of the ecosystem and environment based on the village area. This kind of eco-village project should be supported by ecological evaluation of its spatial structure. But there is rare research of the village spatial structure studied from the ecological viewpoint originally. The purpose of this study is to interpret the spatial structure of Korean mountain village on the landscape ecological paradigm. The paradigm components are patches, corridors, networks, and matrix which explain the land and spatial structure at landscape scale. For this purpose, we selected two case study areas- Sansu and Ajick villages in Gimje city, Jeonlabukdo. We interpreted and evaluated the spatial structure by three steps: (1) to clarify the existing land mosaic pattern by land use mapping (2) to estimate the pore size as development area in matrix (3) to investigate the funnel effect of patch shape. These landscape ecological steps and frameworks could be applied for the proper methodology as fundamentals of eco-village planning and design.

• 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:Databases
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• v.34 no.6
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• pp.528-545
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• 2007

Recently ontology has been an attractive technology along with the business strategy of providing a plenty of more intelligent services. The essential problem in application domains using ontology is that all members, agents, and application programs in the domains must share the same ontology concepts. However, a variety of mobile devices, sensing devices, and network components manufactured by various companies, a variety of common carriers, and a variety of contents providers make multiple heterogeneous ontologies more likely to coexist. We can see many past researches fallen into resolving this semantic interoperability. Such methods can be broadly classified into by-mapping, by-merging, and by-translation. In this research, we focus on by-translation among them which uses a translation rule directly made between two heterogeneous ontology data like OntoMorph. However, the manual composition of the direct translation rule is not convenient by itself and if there are N ontologies, the direct method has the rule composition complexity of $O(N^2)$ in the worst case. Therefore, in this paper we introduce the cascade composition of translation rules based on web openness in order to improve the complexity. The research result made us recognize some important factors in an ontology translation system, that is speediness of translation, and conveniency of translation rule composition, and some experiments and comparing analysis with existing methods showed that our cascade method has more conveniency with insuring the speediness and the correctness.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.12
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• pp.543-548
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• 2017

In recent years, the importance of the safety of medical device software has been emphasized because of the function and role of the software among components of the medical device, and because the operation of the medical device software is directly related to the life and safety of the user. To this end, various standards have been set up that provide activities that can effectively ensure the safety of medical devices and provide their respective requirements. The activities that standards provide to ensure the safety of medical device software are largely divided into the development life cycle of medical device software and the risk management process. These two activities should be concurrent with the development process, but there is a limitation that the risk management requirements to be performed at each stage of the medical device software development life cycle are not classified. As a result, developers must analyze the association of standards directly to develop risk management activities during the development of medical devices. Therefore, in this paper, we analyze the relationship between medical device software development life cycle and risk management process, and extract risk management requirement items. It enables efficient and systematic risk management during the development of medical device software by mapping the extracted risk management requirement items to the development life cycle based on the analyzed associations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.81-88
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• 2014

The researcher of this study applied PCA on aerial hyper-spectral sensor and selectively combined bands which contain high amount of information, creating five types of PCA images. By applying Spectral Angle Mapping-supervised classification technique on each type of image, classification process was carried out and accuracy was evaluated. The test result showed that the amount of information contained in the first band of PCA-transformation image was 76.74% and the second accumulated band contained 98.40%, suggesting that most of information were contained in the first and the second PCA components. Quantitative classification accuracy evaluation of each type of image showed that total accuracy, producer's accuracy and user's accuracy had similar patterns. What drew the researcher's attention was the fact that the first and the second bands of the PCA-transformation image had the highest accuracy according to the classification accuracy although it was believed that more than four bands of PCA-transformation image should be contained in order to secure accuracy when doing the qualitative classification accuracy.