• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.307-314
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• 2008

This paper presents a new robust watermarking method for curves that uses informed-detection. To embed watermarks, the presented algorithm parameterizes a curve using the B-spline model and acquires the control points of the B-spline model. For these control points, 2D mesh are created by applying Delaunay triangulation and then the mesh spectral analysis is performed to calculate the mesh spectral coefficients where watermark messages are embedded in a spread spectrum way. The watermarked coefficients are inversely transformed to the coordinates of the control points and the watermarked curve is reconstructed by calculating B-spline model with the control points. To detect the embedded watermark, we apply curve matching algorithm using inflection points of curve. After curve registration, we calculate the difference between the original and watermarked mesh spectral coefficients with the same process for embedding. By calculating correlation coefficients between the detected and candidate watermark, we decide which watermark was embedded. The experimental results prove the proposed scheme is more robust than previous watermarking schemes against print-scan process as well as geometrical distortions.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.34-44
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• 2006

Simulation models allow researchers to model large hydrological catchment for comprehensive management of the water resources and explication of the diffuse pollution processes, such as land-use changes by development plan of the region. Recently, there have been reported many researches that examine water body quality using Geographic Information System (GIS) and dynamic watershed models such as AGNPS, HSPF, SWAT that necessitate handling large amounts of data. The aim of this study is to develop a watershed based water quality estimation system for the impact assessment on stream water quality. KBASIN-HSPF, proposed in this study, provides easy data compiling for HSPF by facilitating the setup and simulation process. It also assists the spatial interpretation of point and non-point pollutant information and thiessen rainfall creation and pre and post processing for large environmental data An integration methodology of GIS and water quality model for the preprocessing geo-morphologic data was designed by coupling the data model KBASIN-HSPF interface comprises four modules: registration and modification of basic environmental information, watershed delineation generator, watershed geo-morphologic index calculator and model input file processor. KBASIN-HSPF was applied to simulate the water quality impact by variation of subbasin pollution discharge structure.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.194-198
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• 2008

Significant soil erosion and water quality degradation issues are occurring at highland agricultural areas of Kangwon province because of agronomic and topographical specialities of the region. Thus spatial and temporal modeling techniques are often utilized to analyze soil erosion and sediment behaviors at watershed scale. The Soil and Water Assessment Tool (SWAT) model is one of the watershed scale models that have been widely used for these ends in Korea. In most cases, the SWAT users tend to use the readily available input dataset, such as the Ministry of Environment (MOE) land cover data ignoring temporal and spatial changes in land cover. Spatial and temporal resolutions of the MOE land cover data are not good enough to reflect field condition for accurate assesment of soil erosion and sediment behaviors. Especially accelerated soil erosion is occurring from agricultural fields, which is sometimes not possible to identify with low-resolution MOD land cover data. Thus new land cover data is prepared with cadastral map and high spatial resolution images of the Doam-dam watershed. The SWAT model was calibrated and validated with this land cover data. The EI values were 0.79 and 0.85 for streamflow calibration and validation, respectively. The EI were 0.79 and 0.86 for sediment calibration and validation, respectively. These EI values were greater than those with MOE land cover data. With newly prepared land cover dataset for the Doam-dam watershed, the SWAT model better predicts hydrologic and sediment behaviors. The number of HRUs with new land cover data increased by 70.2% compared with that with the MOE land cover, indicating better representation of small-sized agricultural field boundaries. The SWAT estimated annual average sediment yield with the MOE land cover data was 61.8 ton/ha/year for the Doam-dam watershed, while 36.2 ton/ha/year (70.7% difference) of annual sediment yield with new land cover data. Especially the most significant difference in estimated sediment yield was 548.0% for the subwatershed #2 (165.9 ton/ha/year with the MOE land cover data and 25.6 ton/ha/year with new land cover data developed in this study). The results obtained in this study implies that the use of MOE land cover data in SWAT sediment simulation for the Doam-dam watershed could results in 70.7% differences in overall sediment estimation and incorrect identification of sediment hot spot areas (such as subwatershed #2) for effective sediment management. Therefore it is recommended that one needs to carefully validate land cover for the study watershed for accurate hydrologic and sediment simulation with the SWAT model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.421-430
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• 2010

Now a days, as a communications network is being broadband, IPTV(Internet Protocol Television) service which provides various two-way TV service is increasing. But as the data which is transmitted between IPTV set-top box and smart card is almost transmitted to set-top box, the illegal user who gets legal authority by approaching to the context of contents illegally using McComac Hack Attack is not prevented perfectly. In this paper, set-top box access security model is proposed which is for the protection from McComac Hack Attack that tries to get permission for access of IPTV service illegally making data line which is connected from smart card to set-top box by using same kind of other set-top box which illegal user uses. The proposed model reports the result of test which tests the user who wants to get permission illegally by registration the information of a condition of smart card which is usable in set-top box in certification server so that it prevents illegal user. Specially, the proposed model strengthen the security about set-top box by adapting public key which is used for establishing neighbor link and inter-certification process though secret value and random number which is created by Pseudo random function.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.705-714
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• 2001

The computing systems of today expanded business trade and distributed business process Internet. More and more systems are developed from components with exactly reusability, independency, and portability. Component based development is focused on advanced concepts rater than passive manipulation or source code in class library. The primary component construction in CBD. However, lead to an additional cost for reconstructing the new component with CBD model. It also difficult to serve component information with rapidly and exactly, which normalization model are not established, frequency user logging in Web caused overload. A lot of difficult issues and aspects of Component Based Development have to be investigated to develop good component-based products. There is no established normalization model which will guarantee a proper treatment of components. This paper elaborates on some of those aspects of web application to adapt user requirement with exactly and rapidly. Distributed components in this paper are used in the most tiny size on network and suggest the network-addressable interface based on business domain. We also discuss the internal and external specifications for grasping component internal and external relations of user requirements to be analyzed. The specifications are stored on Servlets after dividing the information between session and entity as an EJB (Enterprise JavaBeans) that are reusable unit size in business domain. The reusable units are used in business component through query to get business component. As a major contribution, we propose a systems model for registration, auto-arrange, search, test, and download component, which covers component reusability and component customization.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.103-110
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• 2022

Online transactions are more familiar in various fields due to the development of the ICT and the increase in trading platforms. In particular, the amount of transactions is increasing due to the increase in used transaction platforms and users, and reliability is very important due to the nature of used transactions. Among them, the used car market is very active because automobiles are operated over a long period of time. However, used car transactions are a representative market to which information asymmetry is applied. In this paper presents a DID-based transaction model that guarantees reliability to solve problems with false advertisements and false sales in used car transactions. In the used car transaction model, sellers only register data issued by the issuing agency to prevent false sales at the time of initial sales registration. It is authenticated with DID Auth in the issuance process, it is safe from attacks such as sniping and middleman attacks. In the presented transaction model, integrity is verified with VP's Proof item to increase reliability and solve information asymmetry. Also, through direct transactions between buyers and sellers, there is no third-party intervention, which has the effect of reducing fees.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.597-608
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• 2022

Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.

• Journal of the Korean Regional Science Association
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• v.36 no.1
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• pp.51-67
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• 2020

The purpose of this study is to estimate the housing area per capita for verifying if the public Big Data, of the building ledger and resident registration ledger, can be used as well as the National Census and Housing Survey. The Mankiw and Weil (MW) model was constructed by extracting samples of general detached houses and flat houses from the public big data, and compared with the result from traditional survey method. Then, the MW models of 25 municipalities in Seoul was established. As a result, it can be confirmed that it is possible to establish MW models comparable to regular surveys using public big data, and to establish a model for each basic localities which was difficult to use as a regular survey method. Public Big Data has the advantage of expanding the knowledge frontier, but there are some limitations because it uses data generated for other original purposes. Also, the difficult process of accessing personal information is a burden to carry out analysis. It is expected that continuing research should be needed on how public Big Data would be processed to complement or replace traditional statistical surveys.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.65-76
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• 2015

The Clean Development Mechanism (CDM) is the multi-lateral 'cap and trade' system endorsed by the Kyoto Protocol. CDM allows developed (Annex I) countries to buy CER credits from New and Renewable (NE) projects of non-Annex countries, to meet their carbon reduction requirements. This in effect subsidizes and promotes NE projects in developing countries, ultimately reducing global greenhouse gases (GHG). To be registered as a CDM project, the project must prove 'additionality,' which depends on numerous factors including the adopted technology, baseline methodology, emission reductions, and the project's internal rate of return. This makes it difficult to determine ex ante a project's acceptance as a CDM approved project, and entails sunk costs and even project cancellation to its project stakeholders. Focusing on hydro power projects and employing UNFCCC public data, this research developed a prediction model using logistic regression and CART to determine the likelihood of approval as a CDM project. The AUC for the logistic regression and CART model was 0.7674 and 0.7231 respectively, which proves the model's prediction accuracy. More importantly, results indicate that the emission reduction amount, MW per hour, investment/Emission as crucial variables, whereas the baseline methodology and technology types were insignificant. This demonstrates that at least for hydro power projects, the specific technology is not as important as the amount of emission reductions and relatively small scale projects and investment to carbon reduction ratios.