• Geophysics and Geophysical Exploration
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• v.17 no.2
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• pp.49-57
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• 2014

3D magnetic inversion, based on the assemblage of 2D forward modeling and inversion as a practical technique to reflect the a priori information, was conducted to investigate the spatial distribution features of black-shale related and pyrometamorphic uranium deposit and several lithological units of Ogcheon Super Group in an area of Geumsan. By using the 3D visualization technique with suitable susceptibility interval and horizontal slice map, the spatial distribution of magnetic susceptibility corresponded to the black shale related uranium bearing lithological units, Black Slate member was well coincided with a information of uranium deposit. Also, even though it is indirect indicator for the detetction of uranium deposits interbedded in Gray Hornfels member, spatial susceptibility distribution which shows the south-east magnetic linearment corresponding to the Majeon-ri formation and Dark Gray Slate were matched well. From this investigation, we inferred that maximum depth extension which Black Slate member can be separately recognized with respect to adjacent Dark Gray Slate with strong magnetic susceptibility anomaly is about 150m with reference elevation level of 306m. In addition, Majeon-ri formation located south of Black Slate member revels relatively high magnetic susceptibility range but shows high spatial susceptibility fluctation. And, as an intrusive rocks, Jurassic Biotite Granite shows relatively low magnetic susceptibility characteristics. On the contrary, Cretaceous granite distributed in soutthern part of the study area shows the relatively high susceptibility distribution.

• Steel and Composite Structures
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• v.48 no.1
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• pp.43-57
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• 2023

The impacts of waste tire rubber (WTR) on the bending conduct of reinforced concrete beams (RCBs) are investigated in visualization of experimental tests and 3D finite element model (FEM) using both ANSYS and SAP2000. Several WTR rates are used in total 4 various full scale RCBs to observe the impact of WTR rate on the rupture and bending conduct of RCBs. For this purpose, the volumetric ratios (Vf) of WTR were chosen to change to 0%, 2.5%, 5% and 7.5% in the whole concrete. In relation to experimental test consequences, bending and rupture behaviors of the RCBs are observed. The best performance among the beams was observed in the beams with 2.5% WTR. Furthermore, as stated by test consequences, it is noticed that while WTR rate in the RCBs is improved, max. bending in the RCBs rises. For test consequences, it is clearly recognized as WTR rate in the RCB mixture is improved from 0% to 2.5%, deformation value in the RCB remarkably rises from 3.89 cm to 7.69 cm. This consequence is markedly recognized that WTR rates have a favorable result on deformation values in the RCBs. Furthermore, experimental tests are compared to 3D FEM consequences via using ANSYS software. In the ANSYS, special element types are formed and nonlinear multilinear misses plasticity material model and bilinear misses plasticity material model are chosen for concrete and compression and tension elements. As a consequence, it is noticed that each WTR rates in the RCBs mixture have dissimilar bending and rupture impacts on the RCBs. Then, to observe the impacts of WTR rate on the constructions under near-fault ground motions, a reinforced-concrete building was modelled via using SAP2000 software using 3-D model of the construction to complete nonlinear static analysis. Beam, column, steel haunch elements are modeled as nonlinear frame elements. Consequently, the seismic impacts of WTR rate on the lateral motions of each floor are obviously investigated particularly. Considering reduction in weight of structure and capacity of the members with using waste tire rubber, 2.5% of WTR resulted in the best performance while the construction is subjected to near fault earthquakes. Moreover, it is noticeably recognized that WTR rate has opposing influences on the seismic displacement behavior of the RC constructions.

• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Journal of the Korean Geographical Society
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• v.41 no.2 s.113
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• pp.212-226
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• 2006

Surface data generally represent continuous distribution of geographical or social phenomena of a region in urban analysis. Instances include distribution of temperature, population of region, and various distributions related to human activities. When spatial data are given in the form of surface, surface comparison is required as a way of comprehending the surface change or the relationship between two surfaces. As for previous approaches of surface comparison, there are visualization, quantitative methods and qualitative method. All those approaches, however, show the difference between two surfaces in a limited way. Especially, they are not able to distinguish spatial difference between two surfaces. To overcome such problem, this paper proposes a method of comparing two surfaces in terms of their spatial structure. Main concept of the method comes from earth moving problem and the method is named minimum surface transformation, here. When a surface is transformed into another, total surface volume moved in the process of transformation should be the minimum. Both quantitative and spatial differences between two surfaces are evaluted by total surface volume moved and the distribution of moved surface volume of each cell respectively. The method is applied to hypothetical and actual data. From the former, it is understood that the method explains how two surfaces are quantitatively and spatially different. The result of the latter shows that moved total surface volume decreases as time goes by which fits the actual situation that population change rate gets smaller. Concerning the other measure of surface difference, the distribution of $X_{ij}$ describes detailed flow of surface volume than that of simply subtracting surface volume by indicating to what direction the population change occurs.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.803-811
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• 2021

In this study, the exposure amount of IASCC test worker was evaluated by applying the process simulation technology. Using DELMIA Version 5, a commercial process simulation code, IASCC test facility, hot cells, and workers were prepared, and IASCC test activities were implemented, and the cumulative exposure of workers passing through the dose-distributed space could be evaluated through user coding. In order to simulate behavior of workers, human manikins with a degree of freedom of 200 or more imitating the human musculoskeletal system were applied. In order to calculate the worker's exposure, the coordinates, start time, and retention period for each posture were extracted by accessing the sub-information of the human manikin task, and the cumulative exposure was calculated by multiplying the spatial dose value by the posture retention time. The spatial dose for the exposure evaluation was calculated using MCNP6 Version 1.0, and the calculated spatial dose was embedded into the process simulation domain. As a result of comparing and analyzing the results of exposure evaluation by process simulation and typical exposure evaluation, the annual exposure to daily test work in the regular entrance was predicted at similar levels, 0.388 mSv/year and 1.334 mSv/year, respectively. Exposure assessment was also performed on special tasks performed in areas with high spatial doses, and tasks with high exposure could be easily identified, and work improvement plans could be derived intuitively through human manikin posture and spatial dose visualization of the tasks.