published_or_final_version / Computer Science and Information Systems / Master / Master of Philosophy

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As the importance of natural gas as a resource increases, the importance of volumetric dry gas reservoirs with mobile water as the dominant gas reservoir types will also increase. This research developed an efficient, user-friendly simulation program specifically designed to model two-phase flow of gas and water in these reservoirs. Since fluid compression and viscous forces are the dominant parameters that control fluid movement in a dry gas reservoir, we used the Implicit Pressure and Explicit Saturation (IMPES) formulation of flow equations in which neither gravity nor capillary pressure terms are pertinent. Therefore, the IMPES approach showed greater stability for all cases considered in this work. The developed simulator is a Visual Basic Application (VBA) code for which the users can obsereve the results in a pertinent Microsoft Excel file. This program allows users to study the depletion behavior of volumetric dry gas reservoirs with mobile water as efficiently and accurately as is now possible in more expensive commercially available reservoir simulators. The program was validated by comparing the results with a well-recognized commercial reservoir simulator (CMG). The results of a battery of tests of this simulator matched very well with results of the commercial reservoir simulator for all tested schemes including different simulation plans; reservoir, grid and fluid data; and well configurations. The observed applicability of the program suggests when dealing with volumetric dry gas reservoirs with mobile water there is no need to employ more expensive commercial reservoir simulators, as the program can reliably be used for any simulation scheme of this case. Furthermore, the program can later be applied in a more robust reservoir simulator as the part that handles dry gas cases.

We study the application of network coding in periodic safety broadcasting in Vehicular Ad hoc Networks. We design a sub-layer in the application layer of the WAVE architecture. Our design uses rebroadcasting of network coded safety messages, which considerably improves the overall reliability. It also tackles the synchronized collision problem stated in the IEEE 1609.4 standard as well as congestion problem and vehicle-to-vehicle channel loss. We study how massage repetition can be used to optimize the reliability in combination with a simple congestion control algorithm. We analytically evaluate the application of network coding using a sequence of discrete phase-type distributions. Based on this model, a tight safety message loss probability upper bound is derived. Completion delay is defined as the delay that a node receives the messages of its neighbour nodes. We provide asymptotic delay analysis and prove a general and a restricted tighter asymptotic upper bound for the completion delay of random linear network coding. For some safety applications, average vehicle to vehicle reception delay is of interest. An instantly decodable network coding based on heuristics of index coding problem is proposed. Each node at each transmission opportunity tries to XOR some of its received original messages. The decision is made in a greedy manner and based on the side information provided by the feedback matrix. A distributed feedback mechanism is also introduced to piggyback the side information in the safety messages. We also construct a Tanner graph based on the feedback information and use the Belief Propagation algorithm as an efficient heuristic similar to LDPC decoding. Layered BP is shown to be an effective algorithm for our application. Lastly, we present a simple experimental framework to evaluate the performance of repetition based MAC protocols. We conduct an experiment to compare the POC-based MAC protocol with a random repetition-based MAC.

We study the application of network coding in periodic safety broadcasting in Vehicular Ad hoc Networks. We design a sub-layer in the application layer of the WAVE architecture. Our design uses rebroadcasting of network coded safety messages, which considerably improves the overall reliability. It also tackles the synchronized collision problem stated in the IEEE 1609.4 standard as well as congestion problem and vehicle-to-vehicle channel loss. We study how massage repetition can be used to optimize the reliability in combination with a simple congestion control algorithm. We analytically evaluate the application of network coding using a sequence of discrete phase-type distributions. Based on this model, a tight safety message loss probability upper bound is derived. Completion delay is defined as the delay that a node receives the messages of its neighbour nodes. We provide asymptotic delay analysis and prove a general and a restricted tighter asymptotic upper bound for the completion delay of random linear network coding. For some safety applications, average vehicle to vehicle reception delay is of interest. An instantly decodable network coding based on heuristics of index coding problem is proposed. Each node at each transmission opportunity tries to XOR some of its received original messages. The decision is made in a greedy manner and based on the side information provided by the feedback matrix. A distributed feedback mechanism is also introduced to piggyback the side information in the safety messages. We also construct a Tanner graph based on the feedback information and use the Belief Propagation algorithm as an efficient heuristic similar to LDPC decoding. Layered BP is shown to be an effective algorithm for our application. Lastly, we present a simple experimental framework to evaluate the performance of repetition based MAC protocols. We conduct an experiment to compare the POC-based MAC protocol with a random repetition-based MAC.

Multiple description coding (MDC) has received a lot of attention recently, and has been studied widely and extended to many demanding applications such as speech and video. MDC is a coding technique that generates correlated descriptions of the source stream for transmitting over a diversity system with several channels. The objective of this diversity system is to overcome channel impairments and provide more reliability. In the context of lossy source coding and quantization, a multiple description quantization system usually consists of multiple channels, side encoders to quantize the source samples and send over different channels, and side and central decoders to reconstruct the source. We propose two multiple description quantization schemes in order to design the codebooks and partitions of side and central quantizers of a multiple description system with two channels. The applied framework originated in the multiple description quantization via Gram-Schmidt orthogonalization approach. The basic idea of our proposed schemes is to minimize a Lagrangian cost function by an iterative technique which jointly designs side codebooks and partitions. Our proposed methods perform very closely to the optimum MD quantizer with considerably less complexity. We also propose a multiple description video coding technique motivated by human visual perception. We employ two simple parameters as a measure of the perceptual tolerance of discrete cosine transform (DCT) blocks against visual distortion. We duplicate the essential information such as motion vectors and some low-frequency DCT coefficients of prediction errors into each description, and split the remaining high-frequency DCT coefficients according to the calculated perceptual tolerance parameter. Our proposed technique has very low complexity and achieves superior performance compared to other similar techniques which do not consider perceptual distortion in the design problem. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-08-19 03:33:10.451

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The combined appearance model is a linear, parameterized and flexible model which has emerged as a powerful tool for representing, interpreting, and synthesizing the complex, non-rigid structure of the human face. The inherent strength of this model arises from the utilization of a representative training set which provides a-priori knowledge of the allowable appearance variation of the face. The model was introduced by Edwards et al in 1998 as part of the Active Appearance Model framework, a template alignment algorithm which used the model to automatically locate deformable objects within images. Since this debut, the model has been utilized within a plethora of applications relating to facial image processing. In essence, the ap pearance model combines individual statistical models of shape and texture variation in order to produce a single model of correlations between both shape and texture. In the context of facial modelling, this approach produces a model which is flexible in that it can accommodate the range of variation found in the face, specific in that it is restricted to only facial instances, and compact in that a new facial instance may be synthesized using a small set of parameters. It is additionally this compactness which makes it a candidate for model based video coding. Methods used in the past to model faces are reviewed and the capabilities of the statistical model in general are investigated. Various approaches to building the intermediate linear Point Distribution Models (PDMs) and grey-level models are outlined and an approach decided upon for implementation. The respective statistical models for the Informatics and Modelling (IMM) and Extended Multi-Model Verification for Teleservices and Secu- rities (XM2VTS) facial databases are built using MATLAB in an approach incorporating Procrustes Analysis, Affine Transform Warping and Principal Components Analysis. The MATLAB implementation's integrity was validated against a similar approach encoun tered in literature and found to produce results within 0.59%, 0.69% and 0.69% of those published for the shape, texture and combined models respectively. The models are consequently assessed with regard to their flexibility, specificity and compactness. The results demonstrate the model's ability to be successfully constrained to the synthesis of "legal" faces, to successfully parameterize and re-synthesize new unseen images from outside the training sets and to significantly reduce the high dimensionality of input facial images to produce a powerful, compact model. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2007

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