• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.203-216
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.121-132
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• 2019

As the 4th industrial age enters, the number of IoT devices is exploding. Accordingly, the importance of security is also increasing in proportion to the increasing number of security incidents of IoT devices. However, due to the limited performance of IoT devices, there are limitations to applying existing security solutions. Therefore, a new automatic firmware distribution solution is needed to solve this problem. To solve this problem, we propose a new automatic firmware update system that uses a hybrid blockchain that combines a public blockchain and a private blockchain. The public blockchain allows various firmware providers to distribute firmware using a common system. Private blockchain solves the transaction overload problem of the public blockchain and facilitates the management of IoT devices. It also uses distributed file storage to ensure high availability without failing. Therefore, this system is expected to be very effective for improving the security of IoT devices.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.457-462
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• 2006

Coastline has been considered as fundamental geographic information of a nation. Recently, the coastlines of higher resolution and accuracy with less update period ever than before are increasingly required. This requirement cannot be easily satisfied with the most traditional methods based on field survey such as leveling or GPS measurements. The newly developed airborne LIDAR system can be used as a promising alternative since it rapidly acquire numerous three-dimensional points densely sampled from the terrain around the coastline. Hence, in this study we developed a nearly automatic method to extract the coastline from LIDAR data and applied it to real data to verify its performance. From the comparison of the extracted coastlines with those from a digital map, we conclude that the proposed method can provide more accurate and precise lines.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.417-420
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• 2006

기존의 내용기반 비디오 검색 시스템들을 주석기반 검색 또는 특징기반 검색과 같은 단일 방식으로만 검색을 하므로 검색 효율이 낮을 뿐 아니라 완전한 자동 처리가 되지 않아 시스템 관리자나 주석자의 많은 노력을 요구한다. 본 논문에서는 주석기반 검색을 이용하여 대용량의 비디오 데이터에 대한 사용자의 다양한 의미검색을 지원하는 에이전트 기반에서의 자동화되고 통합된 비디오 의미기반 검색 시스템을 제안한다. 사용자의 기본적인 질의를 분석하고 질의에 의해 추출된 키 프레임의 이미지를 사용자가 선택함으로써 인덱싱 에이전트는 추출된 키 프레임의 주석에 대한 의미를 더욱 구체화시킨다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.147-148
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• 2015

대학의 컴퓨터 관련 학과에서 데이터베이스에 대한 SQL(DML)을 학생들에게 숙지시키기 위한 시험(정기 시험, 퀴즈)은 필수이며, 이에 대한 채점을 수작업을 하고 있어 교수들에게 채점의 부담으로 작용하고 있다. 본 논문은 이런 부담을 덜기 위한 SQL 채점 자동화 시스템을 개발함으로써 학생들에게 채점의 부담 없이 시험을 통해 충분한 시험을 실시하도록 하는 시스템을 개발하였다. 대학에서 SQL은 SELECT, UPDATE, INSERT, DELETE 4개의 데이터 조작어로 구분되며, 기본적인 구문의 시험이 대부분이다, 이에 대한 채점 구문분석을 위한 파싱트리(parsing tree)을 만들어 자동 채점 시스템을 구현하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.531-536
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• 2002

In this paper, we have applied Genetic Algorithms(GAs) to Intrusion Detection System(TDS), and then proposed and simulated the misuse detection model firstly. We have implemented with the KBD contest data, and tried to simulated in the same environment. In the experiment, the set of record is regarded as a chromosome, and GAs are used to produce the intrusion patterns. That is, the intrusion rules are generated. We have concentrated on the simulation and analysis of classification among the Data Mining techniques and then the intrusion patterns are produced. The generated rules are represented by intrusion data and classified between abnormal and normal users. The different rules are generated separately from three models "Time Based Traffic Model", "Host Based Traffic Model", and "Content Model". The proposed system has generated the update and adaptive rules automatically and continuously on the misuse detection method which is difficult to update the rule generation. The generated rules are experimented on 430M test data and almost 94.3% of detection rate is shown.3% of detection rate is shown.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1133-1141
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

• Proceedings of the KSRS Conference
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• v.1
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• pp.409-412
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

• Journal of Information Display
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• v.8 no.4
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• pp.27-31
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• 2007

In this paper, we present an efficient tiled stereo display system for tangible meeting. For tangible meeting, it is important to provide immersive display with high resolution image to cover up the field of view and provide to the local user the same environment as that of remote site. To achieve these, a high resolution image needs to be transmitted for reconstruction of remote world, and it should be displayed using a tiled display. However, it is hard to transmit high resolution image in real time due to the limit of network bandwidth, and so we receive multiple images and reconstruct a remote world with received images in advance. Then, we update only a specific area where remote user exists by receiving low resolution image in realtime. We synthesize the transmitted image to the existing environmental map of remote world and display it as a stereo image. For this, we developed a new system which supports GPU based real time warping and blending, automatic feature extraction using machine vision technique.