The key objective of this multi-disciplinary research was to seek for feasible solutions to avoid effluent from livestock trucks spilling onto roads. Stock effluent spillage mainly poses road safety hazards and environmental damage, and also causes offence to road users and tourists. This task required reviewing previous institutional actions, assessing the power of the existing legislation, and evaluating the interests and attitudes of the stakeholder groups involved in the overall livestock supply chain. It was also necessary to consider politics, administration, public policy and economics, gaining the willing cooperation and confidence of the stakeholder groups through application of 'Soft Systems Methodology' (SSM). A key component was the creation of a 13 minute video and its associated brochure as a primary tool for a stakeholder educational awareness programme. It was necessary to analyse the complex relationships between livestock preparation prior to transport; effluent produced in-transit; and end product quality factors. Detailed information pertaining to the nature of livestock shipments by truck in the South Island of New Zealand had to be collected and verified. All the above information were fed into the calculation of an ideal network of in-transit effluent discharge sites on State Highways in the South Island of New Zealand. Assuming the adoption of best practice throughout the supply chain, it was possible to recommend sustainable solutions. The problem is amenable to solution. Adoption of a strong Industry Code of Practice, coupled with the construction of a strategic network of dump sites will enable the industry to avoid the heavy-handed legal consequences of allowing the status quo to continue.

Lors de cette thèse, je me suis intéressée à la modélisation du métabolisme des micro-organismes. Nous nous sommes focalisé sur le métabolisme des petites molécules qui ne prend pas en compte les réactions associées aux macromolécules, telle que la synthèse des protéines.Nous avons ainsi utilisé différents formalismes de modélisation.Tout d'abord, nous avons développé TOTORO où les réseaux métaboliques sont représentés par des hypergraphes dirigés et qui permet d'identifier les réactions ayant participé à une transition métabolique. TOTORO a été utilisé sur un jeu de données sur la levure en présence de cadmium. Nous avons pu montrer que nous retrouvons les mécanismes connus de désintoxication.Ensuite, en utilisant une méthode de modélisation par contraintes, nous discutons d'un développement en cours, KOTOURA, qui propose d'utiliser les connaissances actuelles de concentrations de métabolites entre différentes conditions pour inférer de manière quantitative les possibles asynchronies des réactions lors du passage d'un état stable à un autre. Nous avons testé son implémentation sur des données simulées.Enfin, nous proposons MULTIPUS, une méthode d'extraction d'(hyper)-arbres de Steiner dirigés qui permet de sélectionner les voies métaboliques pour la production de composés au sein d'une communauté bactérienne. Les réseaux métaboliques sont modélisés en utilisant des hypergraphes dirigés et pondérés. Nous proposons un algorithme de programmation dynamique paramétré ainsi qu'une formulation utilisant la programmation par ensemble réponse. Ces deux propositions sont ensuite comparées dans deux cas d'applications / In this PhD work, we proposed to model metabolism. Our focus was to develop generic models, that are not specific to one organism or condition, but are instead based on general assumptions that we tried to validate using data from the literature.We first present TOTORO that uses a qualitative measurement of concentrations in two steady-states to infer the reaction changes that lead to differences in metabolite pools in both conditions.TOTORO enumerates all sub-(hyper)graphs that represent a sufficient explanation for the observed differences in concentrations. We exploit a dataset of Yeast (Saccharomyces cerevisiae) exposed to cadmium and show that we manage to retrieve the known pathways used by the organisms. We then address the same issue, but using a constraint-based programming framework, called KOTOURA, that allows to infer more quantitatively the reaction changes during the perturbed state. We use in this case exact concentration measurements and the stoichiometric matrix, and show on simulated datasets that the overall variations of reaction fluxes can be captured by our formulation.Finally, we propose MULTIPUS, a method to infer microbial communities and metabolic roads to produce specific target compounds from a set of defined substrates. We use in this case a weighted directed hypergraph. We apply MULTIPUS to the production of antibiotics using a consortium composed of an archae and an actinobacteria and show hat their metabolic capacities are complementary. We then infer for another community the excretion of an inhibitory product (acetate) by a 1,3-propanediol (PDO) producer and its consumption by a methanogene archae

This dissertation investigates the development of new Global system for mobile communications (GSM) improvement algorithms used to solve the nondeterministic polynomial-time hard (NP-hard) problem of assigning cells to switches. The departure of this project from previous projects is in the area of the GSM network being optimised. Most previous projects tried minimising the signalling load on the network. The main aim in this project is to reduce the operational expenditure as much as possible while still adhering to network element constraints. This is achieved by generating new network configurations with a reduced transmission cost. Since assigning cells to switches in cellular mobile networks is a NP-hard problem, exact methods cannot be used to solve it for real-size networks. In this context, heuristic approaches, evolutionary search algorithms and clustering techniques can, however, be used. This dissertation presents a comprehensive and comparative study of the above-mentioned categories of search techniques adopted specifically for GSM network improvement. The evolutionary search technique evaluated is a genetic algorithm (GA) while the unsupervised learning technique is a Gaussian mixture model (GMM). A number of custom-developed heuristic search techniques with differing goals were also experimented with. The implementation of these algorithms was tested in order to measure the quality of the solutions. Results obtained confirmed the ability of the search techniques to produce network configurations with a reduced operational expenditure while still adhering to network element constraints. The best results found were using the Gaussian mixture model where savings of up to 17% were achieved. The heuristic searches produced promising results in the form of the characteristics they portray, for example, load-balancing. Due to the massive problem space and a suboptimal chromosome representation, the genetic algorithm struggled to find high quality viable solutions. The objective of reducing network cost was achieved by performing cell-to-switch optimisation taking traffic distributions, transmission costs and network element constraints into account. These criteria cannot be divorced from each other since they are all interdependent, omitting any one of them will lead to inefficient and infeasible configurations. Results obtained further indicated that the search space consists out of two components namely, traffic and transmission cost. When optimising, it is very important to consider both components simultaneously, if not, infeasible or suboptimum solutions are generated. It was also found that pre-processing has a major impact on the cluster-forming ability of the GMM. Depending on how the pre-processing technique is set up, it is possible to bias the cluster-formation process in such a way that either transmission cost savings or a reduction in inter base station controller/switching centre traffic volume is given preference. Two of the difficult questions to answer when performing network capacity expansions are where to install the remote base station controllers (BSCs) and how to alter the existing BSC boundaries to accommodate the new BSCs being introduced. Using the techniques developed in this dissertation, these questions can now be answered with confidence. / Dissertation (MEng)--University of Pretoria, 2008. / Electrical, Electronic and Computer Engineering / unrestricted

En vue de contrôler les émissions de gaz à effet de serre, il est envisagé d’injecter du CO2 dans des réservoirs géologiques. Or le CO2 n'est pas un gaz inerte. En modifiant la composition chimique de l'eau in situ, il est à l'origine d'interactions roche/fluide. Ces réactions géochimiques impactent les propriétés d'écoulement. Aussi, pour s'assurer de la viabilité et de la pérennité du stockage, les opérateurs ont besoin de simulations tenant compte de ces écoulements réactifs. Cependant les paramètres de l'équation macroscopique de transport utilisée sont affectés par les réactions surfaciques. Or, ces spécificités dues au transfert de masse ne sont pas prises en compte actuellement. De même, la loi perméabilité-porosité (K-F) n’est estimée que semi-empiriquement. Le but de cette thèse a été de développer une méthode pour obtenir les coefficients macroscopiques précédents et les relations K-F, en résolvant les équations gouvernant les phénomènes à l'échelle du pore. Pour ce faire, nous avons utilisé l'approche réseau de pores. L'avantage du modèle réseau est qu'il prend en compte explicitement la structure tout en conceptualisant cette dernière à un ensemble de pores et de canaux à la morphologie simplifiée (sphères, cylindres). L'étude est basée sur deux changements d'échelles successifs : du local au pore, puis du pore à la carotte. Le problème de transport réactif est résolu pour des éléments basiques, analytiquement ou numériquement. Puis, en faisant appel aux solutions précédemment trouvées, le transport réactif est traité sur l'ensemble du réseau. Notre model fut validé par des observations sur micromodèles, puis à l'aide d'une expérience d'altération acide / The geological storage of CO2 is considered as an attractive option to reduce the greenhouse gas emissions in the atmosphere. CO2 is not an inert gas, however. Its dissolution in brine forms a weak acid that has the potential to react with the host rock formation. The induced pores structure modification impacts the flow properties. Thus, to ensure the viability and sustainability of CO2 storage, operators need simulations that take into account the specificities of reactive transport. However, the macroscopic coefficients of the reactive transport equation are modified from the values of an inert tracer by surface reactions. These specificities due to mass transfer are currently not considered. Similarly, the permeability-porosity (K-F) relationship is only estimated semi-empirically. The aim of this thesis was to develop a method to obtain the macroscopic coefficients and the K-F laws, by solving the equations governing the pore-scale phenomena. To do this, we used the Pore Network Modelling approach (PNM). The advantage of the PNM is that it explicitly takes into account the pore structure, while conceptualizing the latter to a set of pores and throats whose morphology is simplified into spheres or cylinders for instance. The study is based into two successive upscalings: from local-scale to pore-scale, then from pore-scale to core-scale. The reactive transport problem is solved for basic elements, analytically or numerically. Then, using the solutions previously found at the pore scale, the reactive transport phenomena are treated throughout the network. Our model was validated by observations on micromodels and by a comparison with an acid-induced alteration experiment

The forecasting of Eskom transmission electrical network demands is a complex task. The lack of historical data on some of the network components complicates this task even further. In this dissertation a model is suggested which will address all the requirements of the transmission system expansion engineers in terms of future loads and market trends. Suggestions are made with respect to ways of overcoming the lack of historical data, especially on the point loads, which is a key factor in modelling the electrical networks. A brief overview of the transmission electrical network layout is included to provide a better understanding of what is required from such a forecast. Lastly, some theory on multiple regression, neural networks and qualitative forecasting techniques is included, which will be of value for further model developments. / Computing / M. Sc. (Operations Research)

The forecasting of Eskom transmission electrical network demands is a complex task. The lack of historical data on some of the network components complicates this task even further. In this dissertation a model is suggested which will address all the requirements of the transmission system expansion engineers in terms of future loads and market trends. Suggestions are made with respect to ways of overcoming the lack of historical data, especially on the point loads, which is a key factor in modelling the electrical networks. A brief overview of the transmission electrical network layout is included to provide a better understanding of what is required from such a forecast. Lastly, some theory on multiple regression, neural networks and qualitative forecasting techniques is included, which will be of value for further model developments. / Computing / M. Sc. (Operations Research)