Particle Swarm Optimization with Spatially Meaningful Neighbours

Neighbourhood topologies in particle swarm optimization (PSO) are typically random in terms of the spatial positions of connected neighbours. This study explores the use of spatially meaningful neighbours for PSO. An approach is designed which uses heuristics to leverage the natural neighbours computed with Delaunay triangulation. The approach is compared to standard PSO sociometries and fitness distance ratio approaches. Although intrinsic properties of Delaunay triangulation limit the practical application of this approach to low dimensions results show that it is a successful particle swarm optimizer

A Comparison of Linear Skinning Techniques for Character Animation

Character animation is the task of moving a complex, artificial character in a life-like manner. A widely used method for character animation involves embedding a simple skeleton within a character model and then animating the character by moving the underlying skeleton. The character's skin is required to move and deform along with the skeleton. Research into this problem has resulted in a number of skinning frameworks. There has, however, been no objective attempt to compare these methods. We compare three linear skinning frameworks that are computationally efficient enough to be used for real-time animation: Skeletal Subspace Deformation, Animation Space and Multi-Weight Enveloping. These create a correspondence between the points on a character's skin and the underlying skeleton by means of a number of weights, with more weights providing greater flexibility. The quality of each of the three frameworks is tested by generating the skins for a number of poses for which the ideal skin is known. These generated skin meshes are then compared to the ideal skins using various mesh comparison techniques and human studies are used to determine the effect of any temporal artefacts introduced. We found that SSD lacks flexibility while Multi-Weight Enveloping is prone to overfitting. Animation Space consistently outperforms the other two frameworks

DOCKside - A Tool for Docking Atomic Molecular Structures into Low-Resolution Electron Microscopy Graphs

The process of cryo-electron microscopy allows scientists to view the complex structures of proteins as they bind and interact with one another. This process however, outputs low resolution noisy density maps which in their initial form are of little use. Through a process called docking, high resolution models of each of the interacting components can be fitted into these low resolution maps so that further study can occur. DOCKside allows users to interact with 3D representations of the proteins and of the electron density maps. Design was an initial concern. Related work was studied to better create a efficient solution to the problem. Different techniques for visualising the various components are implemented and discussed. Docking can also be performed manually using interactive graphics or automatically using a range of mathematically intensive algorithms. These too are detailed and discussed. Through user testing, a review is made as to how efficient the docking process is in producing meaningful and accurate data when compared to the automatically docked solutions

Compression of Dense and Regular Point Clouds

We present a simple technique for single-rate compression of point clouds sampled from a surface, based on a spanning tree of the points. Unlike previous methods, we predict future vertices using both a linear predictor, which uses the previous edge as a predictor for the current edge, and lateral predictors that rotate the previous edge 90 degrees left or right about an estimated normal. By careful construction of the spanning tree and choice of prediction rules, our method improves upon existing compression rates when applied to regularly sampled point sets, such as those produced by laser range scanning or uniform tesselation of higherorder surfaces. For less regular sets of points, the compression rate is still generally within 1.5 bits per point of other compression algorithms

Techniques for visualization of carbohydrate molecules

Standard molecular visualizations, such as the classic ball-and-stick model, are not suitable for large, complex molecules because the overall molecular structure is obscured by the atomic detail. For proteins, the more abstract ribbon and cartoon representations are instead used to reveal large scale molecular conformation and connectivity. However, there is currently no accepted convention for simplifying oligo- and polysaccharide structures. We introduce two novel visualization algorithms for carbohydrates, incorporated into a visualization package, CarboHydra. Both algorithms highlight the sugar rings and backbone conformation of the carbohydrate chain, ignoring ring substituents. The first algorithm, termed PaperChain, emphasizes the type and conformation of the carbohydrate rings. The second, Twister, emphasizes the relative orientation of the rings. We further include two rendering enhancements to augment these visualizations: silhouettes edges and a translucent overlay of the ball-and-stick atomic representation. To demonstrate their utility, the algorithms and visualization enhancements are here applied to a variety of carbohydrate molecules. User evaluations indicate that they present a more useful view of carbohydrate structure than the standard ball-and-stick representation. The algorithms were found to be complementary, with PaperChain particularly effective for smaller carbohydrates and Twister useful at larger scales for highlighting the backbone twist of polysaccharides

A Spatial Awareness Framework for Enhancing Game Agent Behaviour

We describe a framework for providing game agents with awareness of the intrinsic spatial qualities of the virtual worlds that they inhabit. We develop a novel data structure based on a modified medial axis, which establishes a mapping between the medial axis and world structures. This data structure can be used to perform queries about the width, curvature and connectivity of a space within a virtual world. Additional information, such as sampled visibility can also be integrated with this framework. An agent-based crowd simulation is adapted to make use of the sensory information provided by this data structure and the success of using this information within two game scenarios is evaluated