• Special Issue of the Society of Naval Architects of Korea
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• 2008.09a
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• pp.90-95
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• 2008

The letters and marks on the hull of vessels are marked by welding bead or steel plate to resist the corrosion environment. It has done by manual work. So, it cause deterioration of welding quality and process delay and so on. The automated welding device for draft mark has developed partially in the field of shipbuilding. But it can be used for draft mark only. And it has caused a few problems about that workablity and movablity are decreased owing to the size and weight of device. So we developed the automated welding device that can be used for most letters and marks on the hull. It designed to 3 axises mobile robot include to ratoation axis and stand alone type controller with multi GUI base on imbedded windows.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.5
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• pp.475-481
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• 2021

The on-board processor of satellite Synthetic Aperture Radar(SAR) digitizes the back-scattered echoes and transmits them to the ground. As satellite SAR image of various operating conditions including broadband and high resolution is required, an enormous amount of SAR data is generated. Decimation filter is used for data compression to improve the transmission efficiency of these data. Decimation filter is implemented with the FIR(Finite Impulse Response) filter and here, the decimation ratio and tap length are constrained by resource requirements of FPGA used for implementation. This paper suggests to use a non-integer ratio decimation filter in order to optimize the data transmission efficiency. Also, it proposes a filter design method that remarkably reduces the resource constraints of the FPGA in-use via applying a polyphase filter structure. The required resources for implementing the proposed filter is analysed in this paper.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.847-855
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• 2018

GMTI (Ground Moving Target Indicator) is a kind of airborne radar function that is used widely in military applications to detect the moving targets on the ground. In this paper, GMTI signal processing technique was presented and its performance was verified using sum and difference channels raw data obtained by the captive flight test.

• Annual Conference of KIPS
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• 2024.05a
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• pp.397-400
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• 2024

2013년 도커가 등장한 이후, 컨테이너 기술을 기반으로 한 프로젝트 및 사업이 지속적으로 활성화되고 있는 추세이다. 도커 컨테이너는 커널을 포함하고 있지 않음에 따라 기존 가상머신에 비해 경량화된 형태로 애플리케이션을 프로비저닝하는데 활용될 수 있다. 또한, 도커에서는 퍼블릭 도커 이미지 레포지토리인 Docker Hub를 통해 개발된 도커 이미지가 공유 및 배포될 수 있도록 하여 개발자들이 자신의 목적에 부합하는 서비스를 구축하는데 많은 도움을 주고 있다. 최근에는 클라우드 네이티브 환경에 대한 수요가 증가하면서 컨테이너 기술이 더욱 각광받고 있는 실정이다. 이에 따라 도커 이미지 및 이를 기반으로 한 도커 컨테이너 환경에 대한 보안을 위한 연구/개발은 다수 이루어지고 있으나, 도커 이미지 라이선스 컴플라이언스 이슈에 대한 논의 및 민감 데이터 보호 방안에 대한 연구/개발은 부재한 상황이다. 이에 본 논문에서는 도커 이미지 라이선스 컴플라이언스 위반 방지 시스템을 제안하여 도커 이미지 업로드시, Docker Hub 내 도커 이미지와 유사도 검사를 수행할 수 있는 방안을 제시하고자 하며, 도커 이미지 내 민감 데이터를 식별하고 이를 보안할 수 있는 방안에 대해 제시하여 신뢰할 수 있는 도커 컨테이너 공급망을 구축할 수 있음을 보인다.

• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.168-180
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• 2011

The accuracy of rainfall data for a hydrological modeling study is important. NEXRAD (Next Generation Radar) rainfall data estimated by WRS-88D (Weather Surveillance Radar - 1988 Doppler) radar system has advantages of its finer spatial and temporal resolution. In this study, NEXRAD rainfall data was tested and compared with conventional weather station data using the previously calibrated SWAT (Soil and Water Assessment Tool) model to identify local storms and to analyze the impacts on hydrology. The previous study used NEXRAD data from the year of 2000 and the NEXRAD data was substituted with weather station data in the model simulation in this study. In a selected watershed and a selected year (2006), rainfall data between two datasets showed discrepancies mainly due to the distance between weather station and study area. The largest difference between two datasets was 94.5 mm (NEXRAD was larger) and 71.6 mm (weather station was larger) respectively. The differences indicate that either recorded rainfalls were occurred mostly out of the study area or local storms only in the study area. The flow output from the study area was also compared with observed data, and modeled flow agreed much better when the simulation used NEXRAD data.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.143-150
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• 2013

The purpose of this study is to suggest the methodology to develop variable-scale network model, which is able to induce large-scale road network in detailed level corresponding to small-scale linear objects with various abstraction in higher level. For this purpose, the definition of terms, the benefits and the specific procedures related with a variable-scale model were examined. Second, representation level and the components of layer to design the variable-scale map were presented. In addition, rule-based data generating method and indexing structure for higher LoD were defined. Finally, the implementation and verification of the model were performed to road network in study area (Jeju -do) so that the proposed algorithm can be practical. That is, generated variable scale road network were saved and managed in spatial database (Oracle Spatial) and performance analysis were carried out for the effectiveness and feasibility of the model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.144-150
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• 2017

Recently, deep learning is used for intelligent processing and accuracy improvement of data. It is formed calculation model composed of multi data processing layer that train the data representation through an abstraction of the various levels. A category of deep learning, convolution neural network is utilized in various research fields, which are human pose estimation, face recognition, image classification, speech recognition. When using the deep layer and lots of class, CNN that show a good performance on image classification obtain higher classification rate but occur the overfitting problem, when using a few data. So, we design the training network based on convolution neural network and trained our image data set for object classification in few class problem. The experiment show the higher classification rate of 7.06% in average than the previous networks designed to classify the object in 1000 class problem.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.67-74
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• 1998

This paper performed terrain analysis using DTM(digital terrain model) with TIN/ GRID structure on PC environment. Contour layer from 1:5,000 scale map was used to produce DTM. DTHs were produced with and without considering breakline for each data structure. Processing time, file size, mean elevation and standard variation were analyzed for each DTM. slope map, aspect map were analyzed for grid structure with consideration of TEX>$5\times{5m},\;l0\times{10m},\;15\times{15m},\;l0\times{30m},\;45\times{45m},\;60\times{60m}$ cell size respectively. The results suggest following; The incorporation of breakline does improve mapping accuracy for highly disturbed landscape, Mean elevation doesn't increase as the grid size increases, while processing time, storage room is significantly lessened. Thus, the optimal grid size must be determined in advance for efficient application. slope decreases, while aspect increases as grid size is increasing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.291-292
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• 2014

High-speed video transmission modes of master bridge IC are implemented, which supports MIPI (Mobile Industry Processor Interface) DSI (Display Serial Interface) standard. MIPI DSI master bridge IC sends RGB data and various commands to display module (slave) in order to test it. The master bridge IC consists of buffers storing video data of two lines, packet generation block, and D-PHY layer that distributes packets to data lanes and transmits them to slave. In addition, it supports four bpp (bit per pixel) formats and three transmission modes including Burst and Non-Burst (Sync Events, Sync Pulses types). The designed bridge IC is verified by RTL simulations showing that it functions correctly for various operating parameters.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.909-914
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• 2024

This study suggests a quantitative evaluation of transfer learning, which is widely used in various AI fields, including image recognition for robot vision. Quantitative and qualitative analyses of results applying transfer learning are presented, but transfer learning itself is not discussed. Therefore, this study proposes a quantitative evaluation of transfer learning itself based on MNIST, a handwritten digit database. For the reference network, the change in recognition accuracy according to the depth of the transfer learning frozen layer and the ratio of transfer learning data and pre-training data is tracked. It is observed that when freezing up to the first layer and the ratio of transfer learning data is more than 3%, the recognition accuracy of more than 90% can be stably maintained. The transfer learning quantitative evaluation method of this study can be used to implement transfer learning optimized according to the network structure and type of data in the future, and will expand the scope of the use of robot vision and image analysis AI in various environments.