• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.267-273
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• 2024

Using a cloud-based vertex AI platform that can develop an artificial intelligence learning model without coding, this study easily developed an artificial intelligence learning model by the non-professional general public and confirmed its clinical applicability. Nine dental diseases and 2,999 root disease X-ray images released on the Kaggle site were used for the learning data, and learning, verification, and test data images were randomly classified. Image classification and multi-label learning were performed through hyper-parameter tuning work using a learning pipeline in vertex AI's basic learning model workflow. As a result of performing AutoML(Automated Machine Learning), AUC(Area Under Curve) was found to be 0.967, precision was 95.6%, and reproduction rate was 95.2%. It was confirmed that the learned artificial intelligence model was sufficient for clinical diagnosis.

• Journal of Astronomy and Space Sciences
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• v.22 no.2
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• pp.125-138
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• 2005

S152 is a small bright emission nebula located in the Perseus arm. Its optical diameter corresponds to 1.5 pc for an adopted distance 3.5 kpc. However, S152 is a part of a giant molecular cloud complex, which consists of several dense cores, containing active star-forming sites, and well aligned arm-like features. We analyzed the FCRAO $^{12}CO(J=\;1{\to}0)$ Outer Galaxy Survey data in this region to study the kinematical structure of this region, which resembles a big "scorpion". We found that there exist three different velocity components, about -54.5, -50.4, -48.8 km $s^{-1}$, depending on the position of the "scorpion". There also exist velocity gradients of 0.21 km $s^{-1}pc^{-1}$ and 0.16 km $s^{-1}pc^{-1}$ through the whole extent of the "scorpion". Interestingly, these two velocity gradients show an opposite direction with each other. It is likely that the velocity structure of this region may result from the mergence of different gas clouds, and the interaction with the SNR 109.1-1.0 occurred later, mostly at the region around the "head of the scorpion" only.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.229-240
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• 2019

3D geo-spatial model have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, the demand for high quality 3D spatial information such as precise road map construction has explosively increased, MMS and UAV techniques have been actively used to acquire them more easily and conveniently in surveying and geo-spatial field. However, in order to perform 3D modeling by integrating the two data set from MMS and UAV, its so needed an proper registration method is required to efficiently correct the difference between the raw data acquisition sensor, the point cloud data generation method, and the observation accuracy occurred when the two techniques are applied. In this study, we obtained UAV point colud data in Yeouido area as the study area in order to determine the automatic registration performance between MMS and UAV point cloud data using ICP(Iterative Closet Point) method. MMS observations was then performed in the study area by dividing 4 zones according to the level of overlap ratio and observation noise with based on UAV data. After we manually registered the MMS data to the UAV data, then compared the results which automatic registered using ICP method. In conclusion, the higher the overlap ratio and the lower the noise level, can bring the more accurate results in the automatic registration using ICP method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.67-77
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• 2018

This paper suggests that LOD establishes its own link policy and publishes it to LOD cloud to provide identity among entities in different LODs. For specifying the link policy, we proposed vocabulary set founded on RDF model as well. We implemented Policy based In-depth Searching and Cleansing(PISC for short) system that proceeds in-depth searching across LODs by referencing the link policies. PISC has been published on Github. LODs have participated voluntarily to LOD cloud so that degree of the entity identity needs to be evaluated. PISC, therefore, evaluates the identities and cleanses the searched entities to confine them to that exceed user's criterion of entity identity level. As for searching results, PISC provides entity's detailed contents which have been collected from diverse LODs and ontology customized to the content. Simulation of PISC has been performed on DBpedia's 5 LODs. We found that similarity of 0.9 of source and target RDF triples' objects provided appropriate expansion ratio and inclusion ratio of searching result. For sufficient identity of searched entities, 3 or more target LODs are required to be specified in link policy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.133-142
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• 2014

Landsat is one of the popular satellites for observing land surface that is used in various areas including monitoring, detecting and classifying changes in land surface. However, shades, which cloud itself and its shadow, interrupted often clear observation and analysis of ground surface. For this reason, the process of removing shades and restoring original ground surfaces are critical for geospatial users. This study is planned to recommend a methodology for more accurate and clear images of Landsat-8 sensor, which provided two additional bands of costal/aerosol and cirrus. In fact, those bands are known as functioned effectively in detecting and restoring shades. Otsu's thresholding technique to detect clouds, we replaced those detective shades by using experimental and reference images. In accurate assessment, the overall accuracy and kappa coefficients were about 85% and 0.7128, respectively. This indicates that the proposed technique is effective for recovering the original land surface.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.795-807
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• 2014

Vehicular Ad hoc Network (VANET) has gone through a rich amount of research and currently is making its way towards the deployment. However, surprisingly it evolved to rather more applications and services-rich breed referred to as VANET-based clouds due to the advancements in the automobile and communication technologies. Security and privacy have always been the challenges for the think tanks to deploy this technology on mass scale. It is even worse that some security issues are orthogonally related to each other such as privacy, revocation and route tracing. In this paper, we aim at a specific VANET-based clouds framework proposed by Hussain et al. namely VANET using Clouds (VuC) where VANET and cloud infrastructure cooperate with each other in order to provide VANET users (more precisely subscribers) with services. We specifically target the aforementioned conflicted privacy, route tracing, and revocation problem in VANET-based clouds environment. We propose a multiple pseudonymous approach for privacy reasons and leverage the beacons stored in the cloud infrastructure for both route tracing and revocation. In the proposed scheme, revocation authorities after colluding, can trace the path taken by the target node for a specified timespan and can also revoke the identity if needed. Our proposed scheme is secure, conditional privacy preserved, and is computationally less expensive than the previously proposed schemes.

• Cross-Cultural Studies
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• v.52
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• pp.371-392
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• 2018

Beginning with ethical nature inherent in the novel, this paper argues that ethical responsibility of $21^{st}$ century global fiction lies in its invitation to readers to rethink the status quo in a globalized world. While David Mitchell's Cloud Atlas and Min-gyu Park's Dinner with Buffett use international settings, these works exemplify how global fiction fails at, or succeeds in, the ethical task of challenging the contemporary world, respectively. This is because Mitchell's 500-page novel, although a felicitous embodiment of globalization and hybridity, does not challenge dominant ideologies and instead ends up reproducing a conventional humanist ideology against the backdrop of exotic places and diverting literary pastiches. In contrast, Dinner with Buffett, a novella about a Korean average Joe who wins a charity meal with tycoon Warren Buffett, perplexes the reader with counterintuitive turns and, in doing so, uncovers what we believe to be common sense today that serves global capitalism.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.10-24
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• 2021

Rock mass classification for construction of underground facilities is essential to secure their stabilities. Therefore, the reliable values for rock mass classification from the precise information on rock discontinuities are most important factors, because rock mass discontinuities can affect exclusively on the physical and mechanical properties of rock mass. The conventional classification operation for rock mass has been usually performed by hand mapping. However, there have been many issues for its precision and reliability; for instance, in large-scale survey area for regional geological survey, or rock mass classification operation by non-professional engineers. For these reasons, automated rock mass classification using LiDAR becomes popular for obtaining the quick and precise information. But there are several suggested algorithms for analyzing the rock mass discontinuities from point cloud data by LiDAR scanning, and it is known that the different algorithm gives usually different solution. Also, it is not simple to obtain the exact same value to hand mapping. In this paper, several discontinuity extract algorithms have been explained, and their processes for extracting rock mass discontinuities have been simulated for real rock bench. The application process for several algorithms is anticipated to be a good reference for future researches on extracting rock mass discontinuities from digital point cloud data by laser scanner, such as LiDAR.

• Conservation Science in Museum
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• v.25
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• pp.63-84
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• 2021

In order to investigate the diverse physicochemical changes that occurred in traditional Korean pottery during its production, including before and after firing, this study produced six replicas of a celadon maebyeong inlaid with cloud-and-crane designs, respectively corresponding to the process of shaping, carving, inlaying designs, first firing, glazing and second firing, respectively. It then conducted a scientific study of these six replicas and analyzed their images through high-resolution three-dimensional transmission imaging. The materials used for the replicas show different mineral phases and even colors depending on the components of each material. For example, black inlay with a high content of iron oxide (Fe₂O₃) shows dark colors and white inlay with a high alumina (Al₂O₃) content appears white. Physicochemical properties such as chromaticity and magnetic susceptibility and major components of the replicas were confirmed by the differences in the density in the computed tomography (CT) images. The characteristics of fired products such as fine structure, absorption ratio, apparent porosity, and other characteristics of the major mineral components were identified by the presence of pores and the formation of cracks inside the replicas in the image analysis.