• Title/Summary/Keyword: 3-D visualization program

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Study on Installed Performance Simulation of Aircraft Gas-Turbine Engine Considering Inlet and Exhaust Losses (흡배기구 손실예측 및 이를 고려한 항공기 가스터빈의 장착 성능모사 연구)

  • Kong, Chang-Duk;Owino, George.Omollo.
    • Journal of the Korean Society of Propulsion Engineers
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    • v.10 no.4
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    • pp.100-108
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    • 2006
  • Experimental study has been a general way to evaluate inlet and exhaust duct performances, but this is not only costly but also time consuming. Computational simulation is hence replacing experimental study and consequently time and cost saving. This paper therefore aims to investigate typical component performance of the intake and exhaust ducts using 3D representation. In this study a specific inlet and exhaust was modeled and analyzed to estimate its losses and flow field using computational fluid dynamic program with flow visualization capabilities. A process that requires geometry data to be modeled. That allowed for possibility of design trade off in designing phase. Installed performance of a specific turbo shaft engine was finally evaluated with the estimated inlet, exhaust and other accessories losses.

Development of an Automatic 3D Coregistration Technique of Brain PET and MR Images (뇌 PET과 MR 영상의 자동화된 3차원적 합성기법 개발)

  • Lee, Jae-Sung;Kwark, Cheol-Eun;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul;Park, Kwang-Suk
    • The Korean Journal of Nuclear Medicine
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    • v.32 no.5
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    • pp.414-424
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    • 1998
  • Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

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Research Trends of Studies Related to the Geological Fieldwork Using Semantic Network Analysis: Focused on the Last 21 Years(2000-2020) (언어 네트워크를 이용한 야외지질답사 관련 연구 동향 분석: 최근 21년(2000~2020년)을 중심으로)

  • Jeong, Dong-Gwon
    • Journal of the Korean Society of Earth Science Education
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    • v.14 no.2
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    • pp.173-192
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    • 2021
  • The purpose of this study is to analyze the previous research on geological fieldwork from 2000 to 2020, examine the tasks that have been focused on, and suggest directions and implications for future geological fieldwork research. The data was conducted for the thesis searched on ScienceON and RISS in relation to geological fieldwork and journals listed in the Korean Citation Index(KCI), and the study title was analyzed using the semantic network analysis. For analysis, the data that had been pre-processed was visualized as a network by semantic network analysis, and frequency and centrality were analyzed. The centrality analysis was based on degree centrality and eigenvector centrality, and all analyzes were performed by dividing the entire study period into four periods: 2000-2005, 2006-2010, 2011-2015, and 2016-2020. As a result, research on geological fieldwork focused more on the development of geological field courses, and in particular, jeju island was actively discussed as a learning site. Also, the study was conducted on students rather than teachers, and among them, high school students showed high frequency and centrality. In addition, it can be seen that studies on the educational effect of geological fieldwork were discussed, either in connection with programs such as STEAM, free-semester program, or indirect geological fieldwork methods such as web, flash panorama, and 3D. This study is meaningful in that it suggests the direction of future research by looking back on the research on geological fieldwork that has been done so far.

A Topographical Classifier Development Support System Cooperating with Data Mining Tool WEKA from Airborne LiDAR Data (항공 라이다 데이터로부터 데이터마이닝 도구 WEKA를 이용한 지형 분류기 제작 지원 시스템)

  • Lee, Sung-Gyu;Lee, Ho-Jun;Sung, Chul-Woong;Park, Chang-Hoo;Cho, Woo-Sug;Kim, Yoo-Sung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.133-142
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    • 2010
  • To monitor composition and change of the national land, intelligent topographical classifier which enables accurate classification of land-cover types from airborne LiDAR data is highly required. We developed a topographical classifier development support system cooperating with da1a mining tool WEKA to help users to construct accurate topographical classification systems. The topographical classifier development support system has the following functions; superposing LiDAR data upon corresponding aerial images, dividing LiDAR data into tiles for efficient processing, 3D visualization of partial LiDAR data, feature from tiles, automatic WEKA input generation, and automatic C++ program generation from the classification rule set. In addition, with dam mining tool WEKA, we can choose highly distinguishable features by attribute selection function and choose the best classification model as the result topographical classifier. Therefore, users can easily develop intelligent topographical classifier which is well fitted to the developing objectives by using the topographical classifier development support system.