Computer Science
http://hdl.handle.net/10468/227
Sat, 02 Aug 2014 06:55:15 GMT2014-08-02T06:55:15ZModular smoothed analysis of median-of-three Quicksort
http://hdl.handle.net/10468/1367
Modular smoothed analysis of median-of-three Quicksort
Hennessy, Aoife; Schellekens, Michel P.
Spielman’s smoothed complexity - a hybrid between worst and average case complexity measures - relies on perturbations of input instances to determine where average-case behavior turns to worst-case. This approach simplifies the smoothed analysis and achieves greater precession in the expression of the smoothed complexity, where a recurrence equation is obtained as opposed to bounds. Moreover, the approach addresses, in this context, the formation of input instances–an open problem in smoothed complexity. In [23], we proposed a method supporting modular smoothed analysis and illustrated the method by determining the modular smoothed complexity of Quicksort. Here, we use the modular approach to calculate the median of three variant and compare these results with those in [23].
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10468/13672014-01-01T00:00:00ZModular smoothed analysis
http://hdl.handle.net/10468/1368
Modular smoothed analysis
Schellekens, Michel P.; Hennessy, Aoife; Shi, Bichen
Spielman’s smoothed complexity - a hybrid between worst and average case complexity measures - relies on perturbations of input instances to determine where average-case behavior turns to worst-case. The paper proposes a method supporting modular smoothed analysis. The method, involving a novel permutation model, is developed for the discrete case, focusing on randomness preserving algorithms. This approach simplifies the smoothed analysis and achieves greater precession in the expression of the smoothed complexity, where a recurrence equation is obtained as opposed to bounds. Moreover, the approach addresses, in this context, the formation of input instances–an open problem in smoothed complexity. To illustrate the method, we determine the modular smoothed complexity of Quicksort.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10468/13682014-01-01T00:00:00ZUncertainty visualization in 3D scalar data
http://hdl.handle.net/10468/1535
Uncertainty visualization in 3D scalar data
Ma, Ji
One problem in most three-dimensional (3D) scalar data visualization techniques is that they often overlook to depict uncertainty that comes with the 3D scalar data and thus fail to faithfully present the 3D scalar data and have risks which may mislead users’ interpretations, conclusions or even decisions. Therefore this thesis focuses on the study of uncertainty visualization in 3D scalar data and we seek to create better uncertainty visualization techniques, as well as to find out the advantages/disadvantages of those state-of-the-art uncertainty visualization techniques. To do this, we address three specific hypotheses: (1) the proposed Texture uncertainty visualization technique enables users to better identify scalar/error data, and provides reduced visual overload and more appropriate brightness than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (2) The proposed Linked Views and Interactive Specification (LVIS) uncertainty visualization technique enables users to better search max/min scalar and error data than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (3) The proposed Probabilistic Query uncertainty visualization technique, in comparison to traditional Direct Volume Rendering (DVR) methods, enables radiologists/physicians to better identify possible alternative renderings relevant to a diagnosis and the classification probabilities associated to the materials appeared on these renderings; this leads to improved decision support for diagnosis, as demonstrated in the domain of medical imaging. For each hypothesis, we test it by following/implementing a unified framework that consists of three main steps: the first main step is uncertainty data modeling, which clearly defines and generates certainty types of uncertainty associated to given 3D scalar data. The second main step is uncertainty visualization, which transforms the 3D scalar data and their associated uncertainty generated from the first main step into two-dimensional (2D) images for insight, interpretation or communication. The third main step is evaluation, which transforms the 2D images generated from the second main step into quantitative scores according to specific user tasks, and statistically analyzes the scores. As a result, the quality of each uncertainty visualization technique is determined.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10468/15352014-01-01T00:00:00ZRepairing wireless sensor network connectivity in damaged environments
http://hdl.handle.net/10468/1494
Repairing wireless sensor network connectivity in damaged environments
Truong, Thuy T.
A wireless sensor network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. In addition, minimising the number of relay nodes might lead to long routing paths to the sink, which may cause problems of data latency. This data latency is extremely important in wireless sensor network applications such as battlefield surveillance, intrusion detection, disaster rescue, highway traffic coordination, etc. where they must not violate the real-time constraints. Therefore, we also consider the problem of deploying multiple sinks in order to improve the network performance. Previous research has only parts of this problem in isolation, and has not properly considered the problems of moving through a constrained environment or discovering changes to that environment during the repair or network quality after the restoration. In this thesis, we firstly consider a base problem in which we assume the exploration tasks have already been completed, and so our aim is to optimise our use of resources in the static fully observed problem. In the real world, we would not know the radio and physical environments after damage, and this creates a dynamic problem where damage must be discovered. Therefore, we extend to the dynamic problem in which the network repair problem considers both exploration and restoration. We then add a hop-count constraint for network quality in which the desired locations can talk to a sink within a hop count limit after the network is restored. For each new problem of the network repair, we have proposed different solutions (heuristics and/or complete algorithms) which prioritise different objectives. We evaluate our solutions based on simulation, assessing the quality of solutions (node cost, movement cost, computation time, and total restoration time) by varying the problem types and the capability of the agent that makes the repair. We show that the relative importance of the objectives influences the choice of algorithm, and different speeds of movement for the repairing agent have a significant impact on performance, and must be taken into account when selecting the algorithm. In particular, the node-based approaches are the best in the node cost, and the path-based approaches are the best in the mobility cost. For the total restoration time, the node-based approaches are the best with a fast moving agent while the path-based approaches are the best with a slow moving agent. For a medium speed moving agent, the total restoration time of the node-based approaches and that of the path-based approaches are almost balanced.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10468/14942014-01-01T00:00:00Z