No description available.

A thesis submitted to the Faculty of Science University of the Witwatersrand in fulfillment of the requirements for the degree of Doctor of Philosophy. Johannesburg, 1998. / Conformational analysis of portions of functionally-active and functionally-inactive signal peptides (incorporating the wild-type and mutants thereof) has been performed using a variety of computational prediction techniques based on both statistics and molecular mechanics. Molecular mechanics conformational studies are generally plagued by the problem of combinatorial explosion; this problem was addressed with a systematic searching procedure as well as a recently developed genetic algorithm, both utilising tile ECEPP/3 force field. The genetic algorithm, in combination with a gradient minimiser, proved to be successful in finding low-energy conformations for each peptide sequence studied. Analysis was performed in both simulated hydrophobic and hydrophilic environments, under distance-constraints. The molecular mechanics results and statistical predictions generated from the study were compared With existing experimental observations. The reliability of statistical predictions proved to be dependent on prediction method; the more consistent predictions were produced by methods based on membrane proteins, as opposed to those based on globular proteins. The physical property of hydrophobicity of signal peptide sequences, explored in these statistical predictions, was determined to be an important factor in relating sequence to functional activity. Molecular mechanics calculations produced either interrupted or non interrupted a-helical secondary structures both for functionally-efficient and for functionally-inefficient signal peptides, indicating that cc-helixformation alone cannot be correlated with protein export competence. It was concluded from our overall results that both a-helicity and hydrophobicity are required for the efficient functioning of signal peptides. / AC2017

Surface tiling, as well as its counterpart in 3D, i.e. volume tiling, is a fundamental research problem in the subject of computer graphics and geometric modeling, which has found applications in numerous areas, such as computer-aided design (CAD), physical simulation, realtime rendering and architectural modeling. The objective of surface tiling is to compute discrete mesh representations for given surfaces which are often required to possess some desirable geometric properties. Likewise, volume tiling focuses on the study of discretizing a given 3D volume with complex boundary into a set of high-quality volumetric elements. This thesis starts with the study of computing optimal sampling for parametric surfaces, that is, decompose the surface into quad patches such that 1) each quad patch should have their sides with equal length; and 2) the shapes and sizes of all the quad patches should be the same as much as possible. Then, the similar idea is applied to the discrete case, i.e. optimizing the face elements of a quad mesh surface with the goal of making it possess, as much as possible, face elements of desired shapes and sizes. This thesis further studies the computation of hexagonal tiling on free-form surfaces, where the planarity of the faces is more concerned. Free-form meshes with planar hexagonal faces, to be called P-Hex meshes, provide a useful surface representation in discrete differential geometry and are demanded in architectural design for representing surfaces built with planar glass/metal panels. We study the geometry of P-Hex meshes and present an algorithm for computing a free-form P-Hex mesh of a specified shape. Lastly, this thesis progresses to 3D volume case and proposes an automatic method for generating boundary-aligned all-hexahedron meshes with high quality, which possess nice numerical properties, such as a reduced number of elements and high approximation accuracy in physical simulation and mechanical engineering. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

Kan Yeuk Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Objectives --- p.2 / Chapter 1.3 --- Report Organization --- p.3 / Chapter 2. --- RETROSPECT OF NON-MANIFOLD SOLID MODELING --- p.5 / Chapter 2.1 --- Geometric Modeling --- p.5 / Chapter 2.2 --- Euclidean Space and Topological Space --- p.6 / Chapter 2.3 --- Domains of Solid and Non-Manifold Geometric Modeling --- p.8 / Chapter 2.3.1 --- r-set Domain --- p.8 / Chapter 2.3.2 --- Manifold Domain --- p.9 / Chapter 2.3.3 --- Adjacency Form of Topology --- p.11 / Chapter 2.3.4 --- Cell Complex --- p.13 / Chapter 2.4 --- Representation Schemes of Solid and Non-Manifold Geometric Modeling --- p.14 / Chapter 2.4.1 --- Spatial Decomposition --- p.14 / Chapter 2.4.2 --- Constructive Solid Geometry (CSG) --- p.15 / Chapter 2.4.3 --- Boundary Representations (B-rep) --- p.17 / Chapter 2.5 --- Summary --- p.20 / Chapter 3. --- BOOSTING UP THE SPEED OF BOOLEAN OPERATIONS --- p.21 / Chapter 3.1 --- Solid Modeling with Specialized Hardware --- p.22 / Chapter 3.1.1 --- Modeling with a 4x4 Determinant Processor --- p.22 / Chapter 3.1.2 --- Ray Casting Engine --- p.24 / Chapter 3.2 --- Solid Modeling with General Purposed Parallel Computer --- p.25 / Chapter 3.2.1 --- Modeling with Shared Memory Parallel Computer --- p.27 / Chapter 3.2.2 --- Modeling with SIMD Massively Parallel Computer --- p.27 / Chapter 3.2.3 --- Modeling with MIMD Distributed Memory Parallel Computer --- p.30 / Chapter 3.3 --- Summary --- p.33 / Chapter 4. --- OVERVIEW OF DECmpp 12000/Sx/8K --- p.34 / Chapter 4.1 --- System Architecture --- p.34 / Chapter 4.1.1 --- DECmpp Sx Front End --- p.34 / Chapter 4.1.2 --- DECmpp Sx Data Parallel Unit --- p.35 / Chapter 4.1.2.1 --- Array Control Unit --- p.35 / Chapter 4.1.2.2 --- Processor Element Array --- p.35 / Chapter 4.1.2.3 --- Processor Element Communication Mechanism --- p.36 / Chapter 4.2 --- DECmpp Sx Programming Language --- p.37 / Chapter 4.2.1 --- Variable Declarations --- p.37 / Chapter 4.2.2 --- Plural Pointers --- p.38 / Chapter 4.2.3 --- Processor Selection by Conditional Expressions --- p.39 / Chapter 4.2.4 --- Processor Element Communications --- p.39 / Chapter 4.3 --- Summary --- p.40 / Chapter 5. --- ARCHITECTURE OF THE NON-MANIFOLD GEOMETRIC MODELER --- p.41 / Chapter 6. --- SEQUENTIAL MODELER --- p.43 / Chapter 6.1 --- Sequential Half-Wedge structures (SHW) --- p.43 / Chapter 6.2 --- Incremental Topological Operators --- p.51 / Chapter 6.3 --- Sequential Boolean Operations --- p.58 / Chapter 6.3.1 --- Complementing the subtracted model --- p.59 / Chapter 6.3.2 --- Computing intersection of geometric entities --- p.59 / Chapter 6.3.3 --- Construction of sub-faces --- p.53 / Chapter 6.3.4 --- Extraction of resultant topological entities --- p.64 / Chapter 6.4 --- Summary --- p.67 / Chapter 7. --- PARALLEL MODELER --- p.68 / Chapter 7.1 --- Parallel Half-Wedge Structure (PHW) --- p.68 / Chapter 7.1.1 --- Pmodel structure --- p.69 / Chapter 7.1.1.1 --- Phwedge structure --- p.69 / Chapter 7.1.1.2 --- Psurface structure --- p.71 / Chapter 7.1.1.3 --- Pedge structure --- p.72 / Chapter 7.1.2 --- Pmav structure --- p.73 / Chapter 7.2 --- Parallel Boolean Operations --- p.74 / Chapter 7.2.1 --- Complementing the subtracted model --- p.75 / Chapter 7.2.2 --- Intersection computation --- p.79 / Chapter 7.2.2.1 --- Distributing geometric entities --- p.80 / Chapter 7.2.2.2 --- Vertex-Vertex intersection --- p.89 / Chapter 7.2.2.3 --- Vertex-Edge intersection --- p.89 / Chapter 7.2.2.4 --- Edge-Edge intersection --- p.89 / Chapter 7.2.2.5 --- Vertex-Face intersection --- p.90 / Chapter 7.2.2.6 --- Edge-Face intersection --- p.92 / Chapter 7.2.2.7 --- Face-Face intersection --- p.93 / Chapter 7.2.3 --- Constructing sub-faces --- p.98 / Chapter 7.2.4 --- Extraction and construction of resultant topological entities --- p.100 / Chapter 7.3 --- Summary --- p.106 / Chapter 8. --- THE PERFORMANCE OF PARALLEL HALF-WEDGE MODELER --- p.108 / Chapter 8.1 --- The performance of converting sequential to parallel structure --- p.111 / Chapter 8.2 --- The overall performance of parallel Boolean operations --- p.112 / Chapter 8.3 --- The percentage of execution time for individual stages of parallel Boolean operations --- p.119 / Chapter 8.4 --- The effect of inbalance loading to the performance of parallel Boolean operations --- p.121 / Chapter 8.5 --- Summary --- p.125 / Chapter 9. --- CONCLUSIONS AND SUGGESTIONS FOR FURTHER WORK --- p.126 / Chapter 9.1 --- Conclusions --- p.126 / Chapter 9.2 --- Suggestions for further work --- p.127 / APPENDIX / Chapter A. --- SEQUENTIAL HALF-WEDGE STRUCTURE --- p.A-1 / Chapter B. --- COMPUTATION SCHEME IN CHECKING A FACE LOCATING INSIDE THE FACES OF A SOLID --- p.A-3 / Chapter C. --- ALGORITHM IN FINDING A HALF-WEDGE WITH A DIRECTION CLOSEST FROM A REFERENCE HALF-WEDGE --- p.A-5 / Chapter D. --- PARALLEL HALF-WEDGE STRUCTURE --- p.A-7 / REFERENCES --- p.A-10

實體造型在各種設計和生產項目中起著關鍵的作用。他們作為虛擬雕刻，微結構設計和快速成型等等這些常常需要處理複雜形狀和拓撲模型的應用的基礎。隨著愈來愈複雜性的工業模型和需要執行重複性的操作，我們必須要有一個有效率的處理系統。然而，因為許多基本的幾何運算是計算密集型的，一般商用的幾何內核（例如Parasolid和ACIS），尤其是對自由曲面和高度詳細複雜的模型，計算成本的要求是非常高，甚至有時不能使用。本研究的目的是開發一個以自由曲面模型為對象能夠完全在GPU 上運行的實體建模，這將大大提高建模的效率。 / 引致操作中高計算強度的一個關鍵原因是因為他們使用了邊界表示法（B-REP）。我們引入了一個新的表述 - 名為多層深度法向圖像（LDNI）來直接在GPU 上描述對象。LDNI 能夠滿足一定的幾何和拓撲的要求，同時保持簡單和易於並行實現，提供了一個比邊界表示法更可行的形式。 / 在基於B-REP 的建模核心內執行基本操作（如布爾運算，閔可夫斯基和等）往往是耗時和容易出現偶爾失敗。我們已經開發出一些GPU 加速算法，包括布爾和一般閔可夫斯基和，它們的執行速度遠遠超過傳統的方法並且沒有顯著的穩定性問題出現。這些算法是基於圖像表示法來進行的，可以讓特定的任務在每個像素上獨立運行。 / 我們還開發了在GPU 上由B-REP 轉換成LDNI 和由LDNI 轉換成B-REP 的算法。我們為了高效率而使用光栅化來獲得圖像並利用GPGPU 庫來將圖像轉換成B-REP。有了這些算法，我們的建模框架可以與其他常見的CAD 內核進行交換操作。這框架還支持模型的局部細化網格，這有助減少內存消耗，並同時保持曲面G¹ 連續性。 / 最後，本研究的目的是提供一個全面處理複雜形狀的建模問題的框架。我們展示幾個使用了以GPU 為基礎的實體建模應用例子，相比現有的以B-REP 為基礎的系統，我們的框架在效率上得到極大的改善。 / Solid modeling plays a key role in a variety of design and manufacturing activities. They serve as the foundation for applications like virtual sculpting, microstructure design and rapid prototyping, which usually deal with complex shape and topology model. The fast growing complexity of industrial models and the need to perform some operations repeatedly thereby necessitate an efficient processing system. However, since many fundamental geometric operations are compute-intensive, most commercial geometric kernels (e.g. Parasolid and ACIS), especially for freeform and highly-detailed complex models, require very high computational cost and do not work on such complex models. The purpose of this research is to exploit a solid modeler for freeform objects completely running on GPUs, which will greatly improve the efficiency of shape modeling. / A critical reason for such high computing intensity in operations is because they are performed on Boundary Representation (B-Rep). A new representation named Layered Depth Normal Images (LDNI) is introduced in this thesis to describe an object directly on GPU. LDNI is an extension of ray-representation which inherits the good properties of Boolean simplicity, localization, domain decoupling and the ease of parallel implementation, therefore provides a more feasible form than usual boundary representations. / Performing fundamental operations (such as Boolean operations, Minkowski sum, etc) are often time-consuming and prone to numerical problems when being applied on B-Rep model. This work develops several GPU-accelerated algorithms, including Boolean and general Minkowski sum. Our algorithms are carried out on image-based representation and thus are able to perform much faster than conventional approaches without arise any significant instability or robustness issues. / Algorithms have also been developed for converting B-Rep to LDNI and vice versa on GPU. Our sampling method makes use of rasterization to get the images for high efficiency and GPGPU libraries to convert them back to B-Rep. With these algorithms, the representations of models can be converted between this framework and other common CAD kernels. The framework also supports local refinement of coarse mesh, which is useful for reducing memory consumption while maintaining G¹ continuity. / Finally, the objective of this research is to provide a comprehensive framework for complex shape modeling problem. Several applications are demonstrated in using the GPU-based solid modeler, which shows great improvement in the efficiency compared with existing B-rep based systems. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Leung, Yuen Shan. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 148-159). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Chinese Abstract --- p.iii / Acknowledgements --- p.iv / List of Figures --- p.ix / List of Tables --- p.xi / List of Publications --- p.xii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Contribution --- p.3 / Chapter 1.3 --- Organization --- p.4 / Chapter 2 --- Literature Review --- p.6 / Chapter 2.1 --- Exact Solid Modeling --- p.6 / Chapter 2.1.1 --- Solid Modeling Based on B-rep --- p.6 / Chapter 2.1.1.1 --- Data Structure --- p.7 / Chapter 2.1.1.2 --- Boolean Operation --- p.10 / Chapter 2.1.1.3 --- Problems --- p.11 / Chapter 2.1.2 --- Solid Modeling based on CSG --- p.11 / Chapter 2.1.2.1 --- Operations --- p.12 / Chapter 2.1.2.2 --- Comparison --- p.13 / Chapter 2.1.3 --- Boundary Space Partition Trees --- p.14 / Chapter 2.2 --- Approximate Solid Modeling --- p.16 / Chapter 2.2.1 --- Voxel representation --- p.16 / Chapter 2.2.2 --- Oct-tree representation --- p.18 / Chapter 2.2.3 --- Distance-Field --- p.20 / Chapter 2.2.4 --- Unorganized Point-Cloud --- p.22 / Chapter 2.3 --- Computational Intensive Operations --- p.23 / Chapter 2.3.1 --- Minkowski Sum --- p.23 / Chapter 2.3.2 --- Offset --- p.26 / Chapter 2.3.3 --- Sweeping --- p.29 / Chapter 2.4 --- Volumetric Representation to B-Rep Conversion --- p.32 / Chapter 2.5 --- Curved B-rep Generation on GPU --- p.33 / Chapter 3 --- Data Structure of Solid Modeling on GPU --- p.36 / Chapter 3.1 --- Layered Depth Normal Images --- p.36 / Chapter 3.2 --- Data Structure on GPU --- p.39 / Chapter 3.2.1 --- Encode Normal Vector --- p.41 / Chapter 3.2.2 --- Compactly Stored Data Structure --- p.42 / Chapter 4 --- Model Sampling in Image Space --- p.46 / Chapter 4.1 --- Introduction --- p.46 / Chapter 4.2 --- Prior Sampling Approaches --- p.48 / Chapter 4.2.1 --- Stencil Buffer --- p.50 / Chapter 4.2.2 --- Freepipe --- p.52 / Chapter 4.3 --- GPU-Accelerated Conservative Sampling --- p.53 / Chapter 4.3.1 --- Algorithm Overview --- p.54 / Chapter 4.3.2 --- Voxel Classification --- p.57 / Chapter 4.3.3 --- Fast Bit Checking --- p.60 / Chapter 4.3.4 --- MAX Blending for Depth Value Retrieval --- p.61 / Chapter 4.3.5 --- Implementation Detail --- p.62 / Chapter 4.4 --- Results and Discussion --- p.64 / Chapter 4.5 --- Applications --- p.67 / Chapter 5 --- Boolean Operations in Images Space --- p.69 / Chapter 5.1 --- Introduction --- p.69 / Chapter 5.2 --- GPU-Accelerated Boolean Operations --- p.70 / Chapter 5.2.1 --- Boolean Operations on shader --- p.70 / Chapter 5.2.2 --- Boolean Operations on CUDA --- p.71 / Chapter 5.3 --- Results and Discussion --- p.75 / Chapter 6 --- Minkowski Sum in Image Space --- p.77 / Chapter 6.1 --- Introduction --- p.77 / Chapter 6.2 --- Algorithm Based on Exterior Boundary Extraction --- p.78 / Chapter 6.3 --- GPU-Accelerated Minkowski Sum --- p.79 / Chapter 6.3.1 --- Minkowski Sums in Image Space Without Voids --- p.79 / Chapter 6.3.1.1 --- Algorithm Overview --- p.79 / Chapter 6.3.1.2 --- Implementation Issue --- p.80 / Chapter 6.3.1.3 --- Results and Performance --- p.81 / Chapter 6.3.2 --- Minkowski Sums with Inner Voids --- p.82 / Chapter 6.3.2.1 --- Algorithm Overview --- p.83 / Chapter 6.3.2.2 --- Convex Decomposition --- p.83 / Chapter 6.3.2.3 --- Pairwise Minkowski Sum --- p.85 / Chapter 6.3.2.4 --- Super-union in Image Space --- p.86 / Chapter 6.3.2.5 --- Results and Discussion --- p.90 / Chapter 6.3.2.6 --- Application --- p.93 / Chapter 7 --- Localized Construction of Curved Surfaces --- p.96 / Chapter 7.1 --- Local Construction of Curved Polygon --- p.98 / Chapter 7.1.1 --- Basic Construction Scheme --- p.98 / Chapter 7.1.1.1 --- Gregory Patch Interpolation --- p.98 / Chapter 7.1.1.2 --- Silhouette Curve Interpolation --- p.100 / Chapter 7.1.1.3 --- Cross-Tangent Function --- p.101 / Chapter 7.1.2 --- Property Analysis --- p.103 / Chapter 7.1.3 --- Discussions --- p.106 / Chapter 7.1.4 --- Algorithm for Generating N-Sided Polygons --- p.109 / Chapter 7.2 --- Flexible Shape Control --- p.111 / Chapter 7.2.1 --- Possibility of Extending the Basic Scheme --- p.111 / Chapter 7.2.2 --- Reorienting Silhouette Curve (Extended Scheme 1) --- p.111 / Chapter 7.2.3 --- Straight Silhouette (Extended Scheme 2) --- p.112 / Chapter 7.2.4 --- Crease (Extended Scheme 3) --- p.113 / Chapter 7.2.5 --- Silhouette Adjacent to Crease (Extended Scheme 4) --- p.113 / Chapter 7.2.6 --- Smooth Patch Bulging (Extended Scheme 5) --- p.114 / Chapter 7.2.7 --- Flat Surface (Extended Scheme 6) --- p.115 / Chapter 7.3 --- Implementation Details on GPU --- p.115 / Chapter 7.3.1 --- Refinement --- p.116 / Chapter 7.3.2 --- Position Mapping --- p.118 / Chapter 7.3.3 --- Normal Computation for Shading --- p.118 / Chapter 7.4 --- Results and Comparison --- p.119 / Chapter 8 --- B-rep Reconstruction on GPU --- p.124 / Chapter 8.1 --- Introduction --- p.124 / Chapter 8.2 --- B-rep Representation by Dual-Contouring --- p.125 / Chapter 8.3 --- GPU-Accelerated Dual-Contouring --- p.126 / Chapter 8.3.1 --- Algorithm Overview --- p.126 / Chapter 8.3.2 --- Implementation Issue --- p.129 / Chapter 8.4 --- Results and Discussion --- p.130 / Chapter 9 --- Applications --- p.133 / Chapter 9.1 --- Bone Graft --- p.133 / Chapter 9.2 --- Personalized Medical Treatment --- p.137 / Chapter 10 --- Conclusion --- p.139 / Chapter 10.1 --- Summary --- p.139 / Chapter 10.2 --- Future Work --- p.141 / Chapter A --- Appendix A: Examples and Results --- p.143 / Bibliography --- p.148

published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

No description available.

Drought is the most costly hazard among all natural disasters. Despite the significant improvements in drought modeling over the last decade, accurate provisions of drought conditions in a timely manner is still one of the major research challenges. In order to improve the current drought monitoring and forecasting skills, this study presents a hybrid system with a combination of remotely sensed data assimilation based on particle filtering and a probabilistic drought forecasting model. Besides the proposed drought monitoring system through land data assimilation, another novel aspect of this dissertation is to seek the use of data assimilation to quantify land initial condition uncertainty rather than relying entirely on the hydrologic model or the land surface model to generate a single deterministic initial condition. Monthly to seasonal drought forecasting products are generated using the updated initial conditions. The computational complexity of the distributed data assimilation system required a modular parallel particle filtering framework which was developed and allowed for a large ensemble size in particle filtering implementation. The application of the proposed system is demonstrated with two case studies at the regional (Columbia River Basin) and the Conterminous United States. Results from both synthetic and real case studies suggest that the land data assimilation system significantly improves drought monitoring and forecasting skills. These results also show how sensitive the seasonal drought forecasting skill is to the initial conditions, which can lead to better facilitation of the state/federal drought preparation and response actions.

No description available.

Chan, Pui Lam. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 72-75). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.