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Elastic stability of particular three-dimensional rectangular rigid frames.Chen, Wellington. P. January 1962 (has links)
No description available.
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Clustering-based force-directed algorithms for three-dimensional graph visualizationLu, Jia Wei January 2018 (has links)
University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science
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Advancements in the technique of low fold three dimensional seismic reflection surveying.Evans, Brian J. January 1996 (has links)
Three dimensional (3-D) seismic reflection surveying is accepted as the preferred method for imaging complex geology for proving and developing commercial oil and gas fields. However, the cost of 3-D seismic recording and processing is substantial and often can be as expensive as the cost of production drilling. This is particularly the case for land oil field development, where the cost of 3-D surveying is often unacceptably high. Such high costs also restrict its application in coal exploration, where 2-D seismic methods have long been accepted.During the early 1980's, a low fold technique for recording land 3-D data was devised which offered significant cost savings. The technique was adapted by the author for land 3-D surveying over coal fields. Inherent in the technique was a requirement that the data must have a high signal-to-noise ratio, which is not generally the case in land surveying due to the presence of strong source generated surface wave noise. A further major impediment to the technique was its inability to perform an acceptable stacking velocity analysis because of the low number of seismic traces generated. This thesis defines three data collection and processing advancements in low fold 3-D technology which go some way towards resolving these impediments.The first advancement is a method to enhance the signal-to-noise ratio of the stacked seismic data, and consists of a Radon-based transform which stacks shot domain data along a curved trajectory, thereby attenuating surface waves on swath recorded data. This transform is termed the 'Radial Transform' of 3-D data.The second advancement is a statics method to improve the stacked image from a low number of input traces. The method uses the concept that if both the reflected and refracted waves pass through a weathering layer with very similar travel paths, then static corrections to remove the ++ / effects of weathering variations on the refraction travel times would be very similar to those required for the reflections. This method, which was patented, is used equally for both 2-D and 3-D field data, and is regularly used in high resolution seismic processing for coal at Curtin University.The third advancement resolves the problem of azimuthal variation of stacking velocities. By predicting the true reflector dip and its azimuth, apparent dip can be included in the normal moveout equation, which is named the Generalized Moveout equation. The requirement for an azimuthally dependent stacking velocity is then no longer an impediment in low fold 3-D processing of coal data.After developing these transforms and applying them to synthetic data, they were tested with success on modelled field data. All field data used within this thesis were either recorded in the field by the author, or were produced with a physical modelling system, which was built by the author at the University of Houston and later at Curtin University.Results indicate that the procedures described in this thesis enable the low fold 3-D technique to be used as a viable method for recording seismic data when survey economics are a major issue. Furthermore, all three advancements are suitable for application in conventional two dimensional (2-D) and swath seismic surveying.
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Algorithmic approaches to finding cover in three-dimensional, virtual environments /Morgan, David J. January 2003 (has links) (PDF)
Thesis (M.S. in Modeling, Virtual Environments and Simulation)--Naval Postgraduate School, September 2003. / Thesis advisor(s): Christian J. Darken, Joseph A. Sullivan. Includes bibliographical references (p. 91-92). Also available online.
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A variational approach for viewpoint-based visibility maximizationRocha, Kelvin Raymond January 2008 (has links)
Thesis (Ph.D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Allen R. Tannenbaum; Committee Member: Anthony J. Yezzi; Committee Member: Gregory Turk; Committee Member: Joel R. Jackson; Committee Member: Patricio A. Vela
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Organ volume estimation from magnetic sensor based 3D ultrasound data : application in gastric emptying /Jong, Jing-Ming. January 1997 (has links)
Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (leaves [89]-98).
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Sensitivity comparison evaluation of computer-generated three dimensional surface topography to conventional maxillofacial radiographic imageryHazey, Michael A., January 2006 (has links)
Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains x, 220 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 69-74).
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In line fibre optic laser Doppler velocimeter using Bragg grating interferometric filters as frequency to intensity transducersChehura, Edmon January 2002 (has links)
No description available.
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The fabrication and assessment of three-dimensional photonic crystalsSharp, David Neil January 2001 (has links)
No description available.
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3D reconstruction of building site. / 建築物埸景的三維重建 / 3D reconstruction of building site. / Jian zhu wu yi jing de san wei zhong jianJanuary 2004 (has links)
Tsui Ping Tim = 建築物埸景的三維重建 / 徐秉添. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 82-85). / Text in English; abstracts in English and Chinese. / Tsui Ping Tim = Jian zhu wu yi jing de san wei zhong jian / Xu Bingtian. / Acknowledgement --- p.ii / Abstract --- p.iii / Table of Content --- p.v / Chapter Chapter 1. --- Introduction --- p.1 / Chapter 1.1. --- A Brief Review on 3D Site Reconstruction --- p.1 / Chapter 1.2. --- Approach of the Project --- p.3 / Chapter 1.3. --- Organization of the Thesis --- p.4 / Chapter 1.3.1 --- The 3D Site Reconstruction --- p.4 / Chapter 1.3.2 --- The Conformal Point Theory --- p.5 / Chapter 1.4. --- Notations --- p.6 / Chapter Chapter 2. --- General System Overview --- p.7 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Ground Reconstruction --- p.8 / Chapter 2.2.1 --- Planar Homography --- p.9 / Chapter 2.2.2 --- Determination of the Planar Homography --- p.10 / Chapter 2.3 --- Buildings and Cliff Reconstruction --- p.13 / Chapter 2.3.1 --- Correspondence Extraction --- p.14 / Chapter 2.3.2 --- Self-Calibration --- p.17 / Chapter 2.3.3 --- Extrinsic Parameters Estimation --- p.17 / Chapter 2.3.4 --- Scene Point Coordinates Computation --- p.18 / Chapter 2.3.5 --- Bundle Adjustment --- p.19 / Chapter 2.4 --- Object Assimilation --- p.19 / Chapter 2.5 --- Summary --- p.21 / Chapter Chapter 3. --- Camera Calibration --- p.22 / Chapter 3.1 --- Introduction --- p.22 / Chapter 3.2 --- Chapter Organization --- p.22 / Chapter 3.3 --- Brief Review of Camera Calibration --- p.23 / Chapter 3.4 --- Camera Intrinsic Parameters --- p.23 / Chapter 3.5 --- Difficulty of the Calibration Problem --- p.25 / Chapter 3.6 --- Non-automatic Calibration --- p.26 / Chapter 3.6.1 --- DLT --- p.26 / Chapter 3.6.2 --- Vanishing Points Approach --- p.26 / Chapter 3.6.3 --- Homography Approach --- p.28 / Chapter 3.7 --- Auto-Calibration --- p.29 / Chapter 3.7.1 --- Square Pixel with Known Principal Points --- p.30 / Chapter 3.7.2 --- Constant Camera Matrices --- p.31 / Chapter 3.8 --- Experiment --- p.33 / Chapter 3.8.1 --- Experimental Measurement --- p.33 / Chapter 3.8.2 --- Experimental Results --- p.34 / Chapter 3.9 --- Conclusion --- p.37 / Chapter Chapter 4. --- Bundle Adjustment --- p.38 / Chapter 4.1 --- Introduction --- p.38 / Chapter 4.2 --- Descent Direction and Gradient Method --- p.39 / Chapter 4.3 --- Problem Implementation --- p.40 / Chapter 4.4 --- Newton Method --- p.40 / Chapter 4.5 --- Gauss-Newton and Levenberg-Marquardt Method --- p.41 / Chapter 4.6 --- Linear Line Search --- p.43 / Chapter 4.7 --- Golden Section [38] --- p.44 / Chapter 4.8 --- Experiment --- p.47 / Chapter 4.9 --- Summary --- p.50 / Chapter Chapter 5. --- Site Reconstruction Review --- p.51 / Chapter 5.1. --- Introduction --- p.51 / Chapter 5.2. --- Chapter Organization --- p.51 / Chapter 5.3. --- Road Reconstruction --- p.51 / Chapter 5.4. --- Cliff Reconstruction --- p.54 / Chapter 5.5. --- Building Reconstruction --- p.56 / Chapter 5.6. --- Object Assimilation --- p.60 / Chapter 5.7. --- Gallery --- p.61 / Chapter 5.8. --- Application --- p.64 / Chapter Chapter 6. --- Conformal Point Theory --- p.65 / Chapter 6.1. --- Introduction --- p.65 / Chapter 6.2. --- Chapter Organization --- p.65 / Chapter 6.3. --- Hartley Conformal Point Theory --- p.66 / Chapter 6.3.1 --- Angle Measurement Making Use of the Conformal Point --- p.66 / Chapter 6.3.2 --- Position of the Conformal Point --- p.66 / Chapter 6.3.3 --- Proof of the Metric Measurement with the Conformal Point --- p.67 / Chapter 6.3.4 --- Limitation of Hartley's Theory --- p.69 / Chapter 6.4. --- The Discovery of Vanishing Line from 2 or More Images --- p.69 / Chapter 6.4.1 --- Parallax and Plane Stabilization --- p.70 / Chapter 6.4.2 --- Recovery of Vanishing Point by Ideal Plane Stabilization --- p.71 / Chapter 6.5 --- Determining the Infinite Homography and Angle Measurement --- p.73 / Chapter 6.5.1 --- "Four Corresponding Vanishing Points, 3 of which are of Orthogonal Directions" --- p.73 / Chapter 6.5.2 --- "Three Corresponding Orthogonal Point Pairs, and Known Epipoles" --- p.74 / Chapter 6.5.3 --- Known camera matrix and Four Distant Points --- p.74 / Chapter 6.6 --- Applications --- p.77 / Chapter 6.7 --- Conclusion --- p.77 / Chapter 6.8 --- Notes on Publication --- p.78 / Chapter Chapter 7. --- Conclusions --- p.79 / Chapter 7.1 --- Summary --- p.79 / Chapter 7.2 --- Conclusion and Future Work --- p.80 / Appendix A. References --- p.82 / Appendix B. Experiment Dataset --- p.86 / Chapter B.1. --- Introduction --- p.86 / Chapter B.2. --- Synthetic Dataset 1 (S1) --- p.87 / Chapter B.3. --- Synthetic Dataset 2 (S2) --- p.89 / Chapter B.4. --- Real Dataset 1 (Rl) --- p.91 / Chapter B.5. --- Real Dataset 2 (R2) --- p.92 / Chapter B.6. --- Real Dataset 3 (R3) --- p.93 / Appendix C. Mathematical Proof of Vanishing Line Detection by Infinite Plane Stabilization --- p.94
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