• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.37-58
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• 2011

In general, testing DB applications is much more difficult than testing other types of software. The fact that the DB states as much as the input data influence and determine the procedures and results of program testing is one of the decisive reasons for the difficulties. In order to create and maintain proper DB states for testing, it not only takes a lot of time and efforts, but also requires extensive IT expertise and business knowledge. Despite the difficulties, there are not enough research and tools for the needed help. This article reports the result of research on automatic creation and maintenance of DB states for testing DB applications. As its core, this investigation develops an automation tool which collects relevant information from a variety of sources such as log, schema, tables and messages, combines collected information intelligently, and creates pre- and post-Images of database tables proper for application tests. The proposed procedures and tool are expected to be greatly helpful for overcoming inefficiencies and difficulties in not just unit and integration tests but including regression tests. Practically, the tool and procedures proposed in this research allows developers to improve their productivity by reducing time and effort required for creating and maintaining appropriate DB sates, and enhances the quality of DB applications since they are conducive to a wider variety of test cases and support regression tests. Academically, this research deepens our understanding and introduces new approach to testing enterprise systems by analyzing patterns of SQL usages and defining a grammar to express and process the patterns.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.545-559
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• 2020

In this paper, we propose a content creation framework that enables users without programming experience to easily create interactive media content that responds to user gestures. In the proposed framework, users define the gestures they use and the media effects that respond to them by numbers, and link them in a text-based configuration file. In the proposed framework, the interactive media content that responds to the user's gesture is linked with the dynamic projection mapping module to track the user's location and project the media effects onto the user. To reduce the processing speed and memory burden of the gesture recognition, the user's movement is expressed as a gray scale motion history image. We designed a convolutional neural network model for gesture recognition using motion history images as input data. The number of network layers and hyperparameters of the convolutional neural network model were determined through experiments that recognize five gestures, and applied to the proposed framework. In the gesture recognition experiment, we obtained a recognition accuracy of 97.96% and a processing speed of 12.04 FPS. In the experiment connected with the three media effects, we confirmed that the intended media effect was appropriately displayed in real-time according to the user's gesture.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.1-12
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• 2003

Recently, there have been many indexing schemes for multimedia data such as image, video data. But recent database applications, for example data mining and multimedia database, are required to support multi-user environment. In order for indexing schemes to be useful in multi-user environment, a concurrency control algorithm is required to handle it. So we propose a concurrency control algorithm that can be applied to CBF (cell-based filtering method), which uses the signature of the cell for alleviating the dimensional curse problem. In addition, we extend the SHORE storage system of Wisconsin university in order to handle high-dimensional data. This extended SHORE storage system provides conventional storage manager functions, guarantees the integrity of high-dimensional data and is flexible to the large scale of feature vectors for preventing the usage of large main memory. Finally, we implement the web-based image retrieval system by using the extended SHORE storage system. The key feature of this system is platform-independent access to the high-dimensional data as well as functionality of efficient content-based queries. Lastly. We evaluate an average response time of point query, range query and k-nearest query in terms of the number of threads.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.634-642
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• 2020

With the proliferation of Internet of Things (IoT) devices, using the Linux operating system in various architectures has increased. Also, security threats against Linux-based IoT devices are increasing, and malware variants based on existing malware are constantly appearing. In this paper, we propose a system where the binary data of a visualized Executable and Linkable Format (ELF) file is applied to Local Binary Pattern (LBP) image processing techniques and a median filter to classify malware in a Convolutional Neural Network (CNN). As a result, the original image showed the highest accuracy and F1-score at 98.77%, and reproducibility also showed the highest score at 98.55%. For the median filter, the highest precision was 99.19%, and the lowest false positive rate was 0.008%. Using the LBP technique confirmed that the overall result was lower than putting the original ELF file through the median filter. When the results of putting the original file through image processing techniques were classified by majority, it was confirmed that the accuracy, precision, F1-score, and false positive rate were better than putting the original file through the median filter. In the future, the proposed system will be used to classify malware families or add other image processing techniques to improve the accuracy of majority vote classification. Or maybe we mean "the use of Linux O/S distributions for various architectures has increased" instead? If not, please rephrase as intended.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.31-35
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• 2004

정보통신 기술의 발달과 디지털 방송의 시작, 뉴미디어의 출현으로 인한 통신과 방송의 융합은 가속화되고 있다. 또한 2010년까지 광대역통신망 BcN과 홈네트워크 구축을 위한 정부정책이 실행 중에 있다. 100Mbps의 전송속도를 구현해야 하는 광대역 통신망(BcN)을 위해 기존 인터넷 백본 1)망은 잘 구축이 되어 있으나 가입자까지의 망 구조에 많은 문제점을 앉고 있다. 기존 전화국을 이용한 XDSL과 지역 SO를 활용한 Cable Modem의 경우 병목현상과 이론상 속도 또한 BcN과 통방통합이 요구하는 50-100Mhz의 전송속도를 만족하지 못한다. 새로운 망 구조를 구축하기 위해 많은 비용과 시간의 소요가 예상된다 가입자 망 구축에 따른 많은 방법과 이론이 제시되고 있다. 똔 논문에선 지역 SO를 활용하여 가입자까지 망을 통방통합과 BcN에 적합한 가입자 망을 새롭게 구성하는 것을 목표로 한다. 먼저 지역 50의 망을 활용하기 위해선 기존 KT와 파워콤의 COF(Glass Optical Fiber)망과 지역 케이블 SO의 HFC 망을 이용하기에는 동축케이블 망의 물리적 특성에 따른 한계로 통방통합과 BcN에 부적합하다. Tree And Branch 구조의 HFC망 대신 $SMF^{2)}$의 기존 SO의 자가망을 새롭게 설계하고 광분배망 기술인 $E-PON^{3)}$방식을 접목시켜 최대한 동축망을 사용하지 않고 굴곡 특성에 약한 $FOG^{4)}$의 특성을 극복하기 위해 $POF^{5)}$망을 이용하여 댁내 홈게이트웨이까지 연결하는 방식으로 지역 SO를 거점으로 활용하여 댁내까지 FHHT와 홈 네트워크까지의 가입자 망을 새롭게 구성하고자 한다. 저장의 효율성을 위해 이진 포멧인 IPMP화된 MP4 파일을 생성할 수 있다.으로써, 에러 이미지가 가지고 있는 엔트로피에 좀 근접하게 코딩을 할 수 있게 되었다. 이 방법은 실제로 Arithmetic Coder를 이용하는 다른 압축 방법에 그리고 적용할 수 있다. 실험 결과 압축효율은 JPEG-LS보다 약 $5\%$의 압축 성능 개선이 있었으며, CALIC과는 대등한 압축률을 보이며, 부호화/복호화 속도는 CALIC보다 우수한 것으로 나타났다.우 $23.87\%$($18.00\~30.91\%$), 갑폭 $23.99\%$($17.82\~30.48\%$), 체중 $91.51\%$($58.86\~129.14\%$)이였으며 성장율은 사육 온도구간별 차는 없었다.20 km 까지의 지점들(지점 2에서 지점 6)에서 매우 높은 값을 보이며 이는 조석작용으로 해수와 담수가 강제혼합되면서 표층퇴적물이 재부유하기 때문이라고 판단된다. 영양염류는 월별로 다소의 차이는 있으나, 대체적으로 지점 1과 2에서 가장 낮고, 상류로 갈수록 점차 증가하며 지점 7 상류역이 하류역에 비해 높은 농도이다. 월별로는 7월에 규산염, 용존무기태질소 및 암모니아의 농도가 가장 높은 반면에 용존산소포화도는 가장 낮다. 그러나 지점 14 상류역에서는 5월에 측정한 용존무기태질소, 암모니아, 인산염 및 COD 값이 7월보다 다소 높거나 비슷하다. 한편 영양염류와 COD값은 대체적으로 8월에 가장 낮으나 용존산소포화도는 가장 높다.출조건은 $100^{\circ}C$에서 1분간의 고온단시간 추출이 적합하였다. 증가를 나타내었는데

• Journal of Engineering Education Research
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• v.8 no.1
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• pp.71-83
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• 2005

This paper presents an internet-based self-learning educational system which can be enhancing efficiency in the learning process of Java language. The proposed self-learning educational system is called Java Web Player(JWP), which is a Java application program and is executable through Java Web Start technologies. Also, three important sequential learning processes : concept learning process, programming practice process and assessment process are integrated in the proposed JWP using Java Web Start technologies. This JWP enables the learners to achieve efficient and interesting self-learning since the learning process is designed to enhance the multimedia capabilities on the basis of various educational technologies. Furthermore, internet-based on-line voice presentation and its related texts together with moving images are synchronized for efficient language learning process. Also, a simple and useful Java compiler is included in the JWP for providing language practice environment such as coding, editing, executing and debugging Java source files. Finally, repeated practice can make the learners to understand easily the key concepts of Java language. Simple multiple choices are given suddenly to the learners while they are studying through the JWP and the test results are displayed on the message box. This assessment process is very essential to increase the learner's academic capability.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.239-249
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• 2010

The Geostationary Ocean Color Imager (GOCI) data-processing system (GDPS), which is a software system for satellite data processing and analysis of the first geostationary ocean color observation satellite, has been developed concurrently with the development of th satellite. The GDPS has functions to generate level 2 and 3 oceanographic analytical data, from level 1B data that comprise the total radiance information, by programming a specialized atmospheric algorithm and oceanic analytical algorithms to the software module. The GDPS will be a multiversion system not only as a standard Korea Ocean Satellite Center(KOSC) operational system, but also as a basic GOCI data-processing system for researchers and other users. Additionally, the GDPS will be used to make the GOCI images available for distribution by satellite network, to calculate the lookup table for radiometric calibration coefficients, to divide/mosaic several region images, to analyze time-series satellite data. the developed GDPS system has satisfied the user requirement to complete data production within 30 minutes. This system is expected to be able to be an excellent tool for monitoring both long-term and short-term changes of ocean environmental characteristics.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.27 no.2
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• pp.82-96
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• 2018

3D printing is a process of producing 3d object from a digital file in STL format by joining, bonding, sintering or polymerizing small volume elements by layer. The various type of 3d printing is classified according to the additive manufacturing strategies. Among the types of 3D printer, SLA(StereoLithography Apparatus) and DLP(Digital Light Processing) 3D printer which use polymerization by light source are widely used in dental office. In the previous study, a full-arch scale 3d printed model is less precise than a conventional stone model. However, in scale of quadrant arch, a 3d printed model is significantly precise than a five-axis milled model. Using $3^{rd}$ Party dental CAD program, full denture, provisional crowns and diagnostic wax-up model are fabricated by 3d printer in dental office. In Orthodontics, based on virtual setup model, indirect bracket bonding tray can be generated by 3d printer. And thermoforming clear aligner can be fabricated on the 3d printed model. 3D printed individual drilling guide enable the clinician to place the dental implant on the proper position. The development of layer additive technology enhance the quality of 3d printing object and shorten the operating time of 3D printing. In the near future, traditional dental laboratory process such as casting, denture curing will be replaced by digital 3D printing.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.119-129
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• 2021

The process of constructing the DB in the current geotechnical information DB system needs a lot of human and time resource consumption. In addition, it causes accuracy problems frequently because the current input method is a person viewing the PDF and directly inputting the results. Therefore, this study proposes building an automatic digital DB using AI (artificial intelligence) of boring logs. In order to automatically construct DB for various boring log formats without exception, the boring log forms were classified using the deep learning model ResNet 34 for a total of 6 boring log forms. As a result, the overall accuracy was 99.7, and the ROC_AUC score was 1.0, which separated the boring log forms with very high performance. After that, the text in the PDF is automatically read using the robotic processing automation technique fine-tuned for each form. Furthermore, the general information, strata information, and standard penetration test information were extracted, separated, and saved in the same format provided by the geotechnical information DB system. Finally, the information in the boring log was automatically converted into a DB at a speed of 140 pages per second.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.11
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• pp.403-410
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• 2022

Non-Fungible Tokens (NFTs) created on the basis of blockchain have their own unique value, so they cannot be forged or exchanged with other tokens or coins. Using these characteristics, NFTs can be issued to digital assets such as images, videos, artworks, game characters, and items to claim ownership of digital assets among many users and objects in cyberspace, as well as proving the original. However, interest in NFTs exploded from the beginning of 2020, causing a lot of load on the blockchain network, and as a result, users are experiencing problems such as delays in computational processing or very large fees in the mining process. Additionally, all actions of users are stored in the blockchain, and digital assets are stored in a blockchain-based distributed file storage system, which may unnecessarily expose the personal information of users who do not want to identify themselves on the Internet. In this paper, we propose an NFT platform using cloud computing, access gate, conversion table, and cloud ID to improve usability and privacy problems that occur in existing system. For performance comparison between local and cloud systems, we measured the gas used for smart contract deployment and NFT-issued transaction. As a result, even though the cloud system used the same experimental environment and parameters, it saved about 3.75% of gas for smart contract deployment and about 4.6% for NFT-generated transaction, confirming that the cloud system can handle computations more efficiently than the local system.