• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.881-891
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• 2020

Recently, the Ministry of Land, Infrastructure and Transport and the Ministry of Science and ICT are developing the Land Observation Satellite (CAS-500) to meet increased demand for high-resolution satellite images. Expected image products of CAS-500 includes precision orthoimage, Digital Surface Model (DSM), change detection map, etc. The quality of these products is determined based on the geometric accuracy of satellite images. Therefore, it is important to make precision geometric corrections of CAS-500 images to produce high-quality products. Geometric correction requires the Ground Control Point (GCP), which is usually extracted manually using orthoimages and digital map. This requires a lot of time to acquire GCPs. Therefore, it is necessary to automatically extract GCPs and reduce the time required for GCP extraction and orthoimage generation. To this end, the Precision Image Processing (PIP) System was developed for CAS-500 images to minimize user intervention in GCP extraction. This paper explains the products, processing steps and the function modules and Database of the PIP System. The performance of the System in terms of processing speed, is also presented. It is expected that through the developed System, precise orthoimages can be generated from all CAS-500 images over the Korean peninsula promptly. As future studies, we need to extend the System to handle automated orthoimage generation for overseas regions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.629-635
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• 2019

In Deep Learning models derivative is implemented by error back-propagation which enables the model to learn the error and update parameters. It can find the global (or local) optimal points of parameters even in the complex models taking advantage of a huge improvement in computing power. However, deliberately generated data points can 'fool' models and degrade the performance such as prediction accuracy. Not only these adversarial examples reduce the performance but also these examples are not easily detectable with human's eyes. In this work, we propose the method to detect adversarial datasets with random noise addition. We exploit the fact that when random noise is added, prediction accuracy of non-adversarial dataset remains almost unchanged, but that of adversarial dataset changes. We set attack methods (FGSM, Saliency Map) and noise level (0-19 with max pixel value 255) as independent variables and difference of prediction accuracy when noise was added as dependent variable in a simulation experiment. We have succeeded in extracting the threshold that separates non-adversarial and adversarial dataset. We detected the adversarial dataset using this threshold.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.392-399
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• 2013

Due to the development of IT technology and the information age, a dependency of the network over the most of our lives have grown to a greater extent. Although it provides us to get various useful information and service, it also has negative effectiveness that can provide network intruder with vulnerable roots. In other words, we need to urgently cope with theses serious security problem causing service disableness or system connected to network obstacle with exploiting various packet information. Many experts in a field of security are making an effort to develop the various security solutions to respond against these threats, but existing solutions have a lot of problems such as lack of storage capacity and performance degradation along with the massive increase of packet data volume. Therefore we propose the packet analysis model to apply issuing Big Data technology in the field of security. That is, we used NoSQL which is technology of massive data storage to collect the packet data growing massive and implemented the packet analysis model based on K-means clustering using MapReudce which is distributed programming framework, and then we have shown its high performance by experimenting.

• Journal of the Korean Society of Radiology
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• v.8 no.5
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• pp.217-223
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• 2014

The aim of this study is evaluation of dose distribution on radiation therapy planning system with the CT image of high-density material inserted phantom. Gammex 467 Tissue Characterization Phantom is used to acquire an image similar to the human tissues and insert a Titanium to generate metal artifact. The acquired images were reconstructed with Metal Artifact Reduction for Orthopedic Implants (O-MAR). By using the treatment planning system, the volume was analyzed and dose distribution was extracted. Photon dose distribution in linear accelerator was measured by the $MapCHECK^{TM}$ and compared with planned and measured dose distributions. In result of the comparative analysis, when artifact is generated by Titanium, The volume applied O-MAR was increased 6.8% to BR-12 Breast and 40.2% to LV 1 Liver. After O-MAR was used, Dose distribution was higher 1.4 to 1.6% than before. Consequently, The artifact caused by metal objects should be removed if possible, and after that used in the radiotherapy treatment plan can be considered to reduce errors.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.375-383
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• 2012

Soil erosion has been emphasized as serious environmental problem affecting water quality in the receiving waterbodies. Recently, Best Management Practices (BMPs) have been applied at a field to reduce soil erosion and its effectiveness in soil erosion reduction has been monitored with various methods. Although monitoring at fields/watershed outlets would be accurate way for these ends, it is not possible at some fields/watersheds due to various limitations in direct monitoring. Thus modeling has been suggested as an alternative way to evaluate effects of the BMPs. Most models, which have been used in evaluating hydrology and water quality at a watershed, could not reflect rainfall intensity in runoff generation and soil erosion processes. In addition, source codes of these models are not always public for modification/enhancement. Thus, runoff-sediment evaluation system using hourly rainfall data and vegetated filter strip (VFS) evaluation module at field level were developed using open source MapWindow GIS component in this study. This evaluation system was applied to Bangdongri, Chuncheonsi to evaluate its prediction ability and VFS module in this study. The NSE and $R^2$ values for runoff estimation were 0.86 and 0.91, respectively, and measured and simulated sediment yield were 15.2 kg and 16.5 kg indicating this system, developed in this study, can be used to simulate runoff and sediment yield with acceptable accuracies. Nine VFS scenarios were evaluated for effectiveness of soil erosion reduction. Reduction efficiency of the VFS was high when sediment inflow was small. As shown in this study, this evaluation system can be used for evaluation BMPs with local rainfall intensity and variations considered with ease-of-use GIS interface.

• Economic and Environmental Geology
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• v.37 no.2
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• pp.207-223
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• 2004

The purpose of this study is to reveal spatial relationships between landslide and geospatial data set, to map the landslide susceptibility using the relationship and to verify the landslide susceptibility using the landslide occurrence data in Boun area in 1998. Landslide locations were detected from aerial photography and field survey, and then topography, soil, forest, and land cover data set were constructed as a spatial database using GIS. Various spatial parameters were used as the landslide occurrence factors. They are slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil. type, age, diameter and density of wood, lithology, distance from lineament and land cover. To calculate the relationship between landslides and geospatial database, Bayesian probability methods, weight of evidence. were applied and the contrast value that is >$W^{+}$->$W^{-}$ were calculated. The landslide susceptibility index was calculated by summation of the contrast value and the landslide susceptibility maps were generated using the index. The landslide susceptibility map can be used to reduce associated hazards, and to plan land cover and construction.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.43-51
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• 2011

The recent development of the technology for wireless mobile computing and applied technology for location-based services has made it possible to support query processing faster than that in the past. However, some technological limitations on hardware and software still exist. The most critical aspects of query processing are accuracy and speed. For improving the accuracy, it is required that detailed information on the data involved in query processing be saved. In this case, the amount of information on the data increases, which decreases the speed. On the other hand, for increasing the speed, it is necessary to reduce the broadcast cycle, which enables rapid data acquisition as desired. In this case, because of insufficient index information, the listen time for the client increases, which may cause unnecessary energy consumption. Therefore, a trade-off occurs between the accuracy and speed. This paper proposes a hierarchical bitmap-based spatial index (HBI) as a solution for the aforementioned problems. HBI describes an object with 0 and 1 on the Hilbert curve map. It reduces the broadcast cycle by decreasing the index size on the basis of bit information and tree structure. Therefore, it is able to shorten the listen time and query processing time. In addition, HBI enables the detection of the locations of all the objects so that it is possible selectively listen to a broadcast. A performance evaluation of the proposed technique demonstrates that it is excellent.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.251-258
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• 1998

The purpose of this study is to develop the District-level Planning Support System (DPSS) by using GIS. The district-level planning which is related for district-level control of city, needs the various parcel-level information which is composing the urban physical environment. The information has to be stored and analyzed for recognizing the study area, then the district-level planning will be efficiently managed. The use of GIS in the process of district-level planning is restricted for the creation of thematic map. GIS is not used for the analysis of spatial patterns and planning process. This study evaluates the characteristics of current district-level planning and the basic components of urban physical environment. And the database model is built. The topology among components is defined by using the spatial relationship. Then the spatial query machine for district-level planing is developed by using ArcView 3.1, Avenue and Dialog Extension. This spatial query machine is applied for case study. This study shows 1) the possibility of the district-level planning support system for analyzing spatial relationship, 2) the needs of the up-to-date topographic map showing current building's footlines and the complete integration with cadastral maps, it will reduce the uncertainty in the spatial decision making process, 3) the methodology for the construction of spatial decision making rules, 4) the further study for the using of raster, network, image and three dimension data.

• The Journal of Korean Medicine
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• v.29 no.5
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• pp.29-40
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• 2008

Objectives : It has been reported that Sophorae Subprostratae Radix (SSR) has a neuroprotective effect on cerebral ischemia in animals. In the present study, the authors investigated the neuroprotective effect of SSR on glutamate excitotoxicity. Glutamate excitotoxicity was induced by using NMDA, AMPA, and KA in PC12 cells and in organotypic hippocampal slice cultures. Methods :Methanolic extract of SSR was added at 0.5, 5, and 50 ${\mu}$g/ml to culture media for 24 hours. The effects of SSR were evaluated by measuring of cell viability, PI-stained neuronal cell death, TUNEL-positive cells, and MAP-2 immunoreactivity. Results : SSR increased PC12 cell viabilities significantly against AMPA-induced excitotoxicity, but not against NMDA-induced or KA-induced excitotoxicity. In organotypic hippocampal slice cultures damaged by NMDA-induced excitotoxicity, SSR attenuated neuronal cell death significantly in the CA1, CA3, and DG hippocampal regions and reduced TUNEL-positive cells significantly in CA1 and DG regions. In organotypic hippocampal slice cultures damaged by AMPA-induced excitotoxicity, SSR attenuated neuronal cell death and reduced TUNEL-positive cell numbers significantly in the CA1 and DG regions. In organotypic hippocampal slice cultures damaged by KA-induced excitotoxicity, SSR attenuated neuronal cell death significantly in CA3, but did not reduce TUNEL-positive cell numbers in CA1, CA3 or DG. In organotypic hippocampal slice cultures damaged by NMDA-induced excitotoxicity, SSR attenuated pyramidal neuron neurite retraction and degeneration in CA1. Conclusions : These results suggest that the neuroprotective effects of SSR are related to antagonistic effects on the NMDA and AMPA receptors of neuronal cells damaged by excitotoxicity and ischemia.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.9
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• pp.836-841
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• 2016

An indoor positioning system using Wi-Fi is essential to produce a radio map that combines the indoor space of two or more dimensions, the information of node positions, and etc. in processing for constructing the radio map, the measurement of the received signal strength indicator(RSSI) and the confirmation of node placement information counsume substantial time. Especially, when the installed wireless environment is changed or a new space is created, easy installation of the node and fast indoor radio mapping are needed to provide indoor location-based services. In this paper, to reduce the time consumption, we propose an algorithm to distinguish the straight and curve lines of a corridor section by RSSI visualization and Sobel filter-based edge detection that enable accurate node deployment and space analysis using cable-type Wi-Fi node installed at a 3 m interval. Because the cable type Wi-Fi is connected by a same power line, it has an advantage that the installation order of nodes at regular intervals could be confirmed accurately. To be able to analyze specific sections in space based on this advantage, the distribution of the signal was confirmed and analyzed by Sobel filter based edge detection and total RSSI distribution(TRD) computation through a visualization process based on the measured RSSI. As a result to compare the raw data with the performance of the proposed algorithm, the signal intensity of proposed algorithm is improved by 13.73 % in the curve section. Besides, the characteristics of the straight and the curve line were enhanced as the signal intensity of the straight line decreased by an average of 34.16 %.