The accurate determination of gender of biological samples has valuable applications in medical and forensic investigations. Gender determination based on length variations in the X-Y homologous amelogenin gene, is part of most commercial multiplex DNA profiling kits. The first report of a failure of the amelogenin sex test was in 1998 when two normal males were typed as female. Subsequently, several amelogenin Y (AMELY) negative males have been reported. This study represents the first report of this phenomenon in the black South African population. This study determined the size of the Y-chromosome deletion that resulted in the failure of the amelogenin sex test in two black South African AMELY-negative males by typing specific DNA markers surrounding the amelogenin locus. Through deletion size and Y-chromosome microsatellite haplotypes, the relationship between the samples was investigated. The samples were sequenced at the amelogenin gene and typed for thirteen sites on the short arm of the Y-chromosome. In order to determine the Y-chromosome haplotypes, eleven Y-chromosome microsatellite markers were typed. These samples had the same size deletion of approximately 3 Mb. The Y-chromosome haplotypes indicated that these were probably independent events. The frequency of AMELY-negative males is rare in this population sample of 8,344 individuals, with a frequency of 0.065% in the black South African sample population. Notwithstanding, tests performed for detecting the presence of male DNA based on the presence of the amelogenin gene alone should be reconsidered, as this study confirms that these deletions do occur in the African population. The impact of the results generated in this study on the medical and forensic practise of DNA testing is significant. / Thesis (Ph.D. (Biochemistry))--North-West University, Potchefstroom Campus, 2011.

There are many practical decision problems that fall into the category of network flow problems: numerous examples of applications can be found in areas such as telecommunications, logistics, distributions, engineering, computer science and so on. One of the most popular and valuable tools to solve network flow problems of a topological nature is the use of linear programming models. An important extension of these models is that of integer programming models that deal with problems where some, or all, of the variables are required to assume integer variables. A significant application in this class of problems is the knapsack problem that arises in different contexts such as loading containers in aircraft or satisfying the demand for various lengths of cloth which must be cut from fixed length bolts of fabric. In this study, the feasibility of representing a network flow model in a tree network model and subsequently solving it using a tree knapsack approach is investigated. To compare and validate the proposed technique, a specific case study was chosen from the literature that can be used as a basis for the research project. The said study was an oil pipeline design problem, addressed by Brimberg et al. (2003). This focuses on the optimal design of an oil pipeline network for the South Gabon oil field in Africa. The objective was to reduce oil transportation costs to a major port. Following an overview of different network flow and knapsack models, an overview of the said matter is presented. A description of the proposed tree knapsack approach and the application of this approach to the given problem is given. Results have indicated that it is feasible to apply a tree knapsack approach to solve network flow problems. / Thesis (M.Sc. (Computer Science))--North-West University, Potchefstroom Campus, 2011.

Made available in DSpace on 2016-06-02T19:51:34Z (GMT). No. of bitstreams: 1 1660.pdf: 940693 bytes, checksum: d22e5083ad9e958c15a2bb99a5a7056e (MD5) Previous issue date: 2007-12-18 / Cash flow management is a financial problem that involves the efficient management of cash, short-term investments and short-term loans. In this study, we formulate the cash flow problem encountered in a typical agro-industrial company as a network optimization problem. Two examples using a linear programming model were studied: in the first example, the original model were used to support operational cash flow decisions, in the second example, the model were extended to a tactical planning of loan payments. The mathematic models are resolved in the solver tool that is an add-in of Microsoft Excel. Spreadsheets are of wide applicability for analytical work in business. The model has the potential of being flexible and to maximize the cash return from the final planning period in real-life situations / Neste estudo, temos como objetivo otimizar o processo de gerenciamento financeiro do fluxo de caixa num horizonte de planejamento multi-período e finito, presente em uma empresa típica do setor agroindustrial. Procuramos maximizar o conjunto de recursos monetários ao final do período estudado. Para isso, contamos com uma abordagem simultânea dos parâmetros envolvidos no procedimento, possibilitada pelos recursos oferecidos pela Pesquisa Operacional. Como método de otimização para auxiliar as decisões do processo de fluxo de caixa, utilizamos a programação matemática linear. Avaliamos a aplicação de um modelo de gerenciamento do fluxo de caixa, baseado na teoria de fluxo em redes, que contempla os propósitos de ganhos de fluxo de dinheiro e considera os parâmetros mais importantes para a solução. Dois exemplos são estudados: no primeiro, aplicamos o modelo original para apoiar decisões operacionais na gestão do caixa da empresa; no segundo, adaptamos o modelo para abranger o planejamento tático de amortizações de financiamentos na gestão do caixa. Os dois exemplos são testados em situações reais e resolvidos por meio da ferramenta solver do Excel, amplamente utilizada nos ambientes de gestão financeira das empresas. A flexibilidade do modelo de otimização em atender mais de um tipo de situação e a capacidade de gerar soluções melhores que as praticadas na empresa, no período estudado, são evidenciadas por meio de exemplos numéricos

Este trabalho apresenta um algoritmo determinístico para o planejamento da operação de sistemas hidrotérmicos de potência com representação individualizada das usinas hidroelétricas. Este problema caracteriza-se por ser não-linear, não diferenciável e de grande porte. O modelo de otimização foi baseado em algoritmos de fluxo em rede não-linear e foi utilizado o método do gradiente reduzido para se encontrar a direção ótima e o método da razão áurea para a busca do tamanho do passo ótimo. A estrutura da rede hidráulica formada pelas equações de balanço de água foi explorada através da definição da base na matriz defluência básica. Testes no programa foram realizados em diversos sistemas compostos por usinas reais pertencentes ao sistema sudeste brasileiro. Esses estudos foram realizados visando apresentar os princípios básicos que regem a operação ótima dos reservatórios e validar o algoritmo implementado. / This work presents a deterministic algorithm for the operational planning of hydrothermal power systems where each plant is represented individually. This problem is characterized by non-linear, non-diferenciable and large scale. The optimization model was based in non-linear network flow algorithm and it was used the reduced gradient method to find the optimal direction and the golden ratio method to find the best step size. The structure of hydraulic network formed by the water balance equation was exploited through the definition of the base in the basic flow matrix. Many tests were done with some system composed by real plants located on brazilian southeast. This studies was done to show the basics principles that rule the optimal operation of reservoirs and to validate the algorithm implemented.

A relevância da infraestrutura de transporte para incrementos em produtividade, induzindo ao desenvolvimento socioeconômico de determinada região é amplamente reconhecida. O Brasil, no entanto, apresenta sérias deficiências em relação à sua infraestrutura de transporte, oriundas de seu desenvolvimento histórico e da redução de níveis de investimentos públicos no setor nas últimas décadas. Estas deficiências traduzem-se em grande concentração no modal rodoviário para o transporte de cargas, menos eficiente do que os modais ferroviário e hidroviário, resultando em reduzida competitividade das organizações nacionais. Neste contexto, objetivou-se no presente trabalho a proposição de um modelo para avaliação e seleção de investimentos em infraestrutura de transporte de cargas, considerando-se seu caráter multidimensional. Para isso, foi proposta metodologia integrando os conceitos de análise de decisão multicritério e de programação matemática, representados pela teoria de utilidade multiatributo (Multi-Attribute Utility Theory - MAUT) e por problema de otimização de fluxos em rede (Minimum Cost Network Flow Problem - MCNFP), respectivamente. No desenvolvimento do modelo foram contemplados critérios de avaliação referentes às dimensões de análise financeira, operacional e ambiental. Posteriormente, foi considerada a aplicação de versões do modelo proposto com diferentes números de períodos de análise em caso ilustrativo, representativo da rede de transporte disponível e planejada da região Norte do Brasil. A aplicação das diversas versões do modelo proposto, de forma geral, apresentou resultados compatíveis com as teorias relacionadas à avaliação deste problema de decisão, incluindo indução à multimodalidade. Algumas versões do modelo apresentaram violações em algumas de suas restrições. Estes resultados adversos não foram plenamente eliminados, devido a limitações das ferramentas adotadas para aplicação. No entanto, foi possível a correção manual destas violações, resultando em soluções viáveis que, apesar de não serem consideradas ótimas, são mais completas do que soluções obtidas por meio de metodologias unidimensionais de análise. Por fim, foram apresentadas recomendações para condução de trabalhos futuros visando eliminação dos resultados adversos do modelo proposto e complementação de sua análise. / The role of transport infrastructure in productivity increases leading to regional social-economic development is widely recognized. Brazil, however, has serious deficiencies in its transport infrastructure, rooted in the country\'s historical development and in the recent decades\' reduction of public investment in the sector. These deficiencies can be observed in Brazil\'s strong focus on roads for cargo transportation, which besides being less efficient than rail and waterways, results in reduced competitiveness of national enterprises. In this context, the aim of this work was to propose a model for evaluating and selecting investments in freight\'s transportation infrastructure, considering its multidimensional character. It was proposed a methodology integrating the concepts of multi-criteria decision analysis and mathematical programming, represented by the Multi-Attribute Utility Theory (MAUT) along with the Minimum Cost Network Flow Problem (MCNFP). The developed model included financial, operational and environmental analysis evaluation criteria. Subsequently, this study applied the proposed model into a case study of the transportation network, available and planned, of the Northern region of Brazil. Overall, the application of various versions of the proposed model yielded results consistent with related evaluation and decision making theories, including induction of multimodality. Some versions of the model presented some violations of its restrictions. These adverse results were not fully eliminated due to the limitations of the application tools utilized. It was possible, however, to manually correct these violations and obtain viable solutions that, while cannot be considered optimal, are more complete than those obtained by single dimension analysis. Finally, recommendations were made for future studies aiming at eliminating the proposed model\'s adverse outcomes, and complementing its analysis.

Nous considérons dans ce travail, des problèmes d’optimisation dans des graphes de flot multi-agent. Trois types d’agents sont considérés : les agents producteurs, transporteurs et usagers et différentes variétés de topologies de réseaux sont abordées. Chaque agent transporteur contrôle la capacité d’un ensemble de routes élémentaires (arcs), ayant chacun une capacité qui peut être augmenté jusqu’à une valeur maximale moyennant un coût fixe. Les autres agents (i.e., usagers/producteurs) sont intéressés par la maximisation du flot qu’ils reçoivent. Dans ce but, ces derniers offrent une récompense aux agents transporteurs, cette récompense est proportionnelle à la valeur du flot reçu. Ce contexte multi-agent particulier est appelé jeu expansion de réseau multi-agent. La stratégie d’un agent transporteur consiste à décider de la capacité de ses arcs sachant qu’un coût supplémentaire est encouru pour toute expansion unitaire de capacité. Il reçoit en contrepartie une part de la récompense. Il est intéressé par la maximisation de son profit et se comporte en conséquence. En outre, la stratégie d’un agent producteur/usager consiste à décider de la politique de partage de sa récompense afin de maximiser le flot qu’il reçoit. Le flot total réalisé dépend finalement des stratégies de tous les agents. Dans ces jeux d’expansion de réseau multi-agent, nous nous intéressons à caractériser des stratégies stables (i.e., Equilibre de Nash) selon diverses hypothèses. En se basant sur cette caractérisation, différents cas sont définis et étudiés. L’analyse de la complexité de quelques problèmes de décision est présentée dans ce manuscrit. Nous nous intéressons particulièrement au problème de recherche d’un équilibre de Nash qui maximise la valeur du flot total circulant dans le réseau. Nous montrons que ce problème est NP-difficile au sens fort et nous montrons comment une telle stratégie peut être caractérisée par des chemins spécifiques dans des graphes résiduels. Nous proposons également un programme linéaire à variables mixtes (PLM) qui résout le problème dans le cas d’un seul agent producteur/usager et un ensemble d’agents transporteurs. Des résultats expérimentaux sont fournis pour prouver l’efficacité de notre approche. / In this work, multi-agent network flow problems are addressed. Three types of agentsare considered, namely the producer, transportation and customer agents and various network topologies are tackled. Every transportation agent controls the capacities of a set of elementary routes (arcs), each one having a capacity that can be increased up to a certain point at a given cost. The other agents (i.e., customers/producers) are interesting in maximizing their flow of products. For that aim, we assume that they offer to the transportation agents a reward that is proportional to the realized flow value. This particular multi-agent framework is referred to as a multi-agent network expansion game. The transportation agent’s strategy consists in deciding upon the capacity of its arcs, an extra-cost being incurred for any capacity expansion. It receives in return a part of the total reward. It is interested in the maximization of its profit and behaves accordingly. Beside that, the producers/customers’ strategies consist in deciding the sharing policy for their reward for maximizing their own flow of products. The total network flow value eventually depends on all agents’ strategies. We take interest in characterizing and finding particular stable strategies (i.e., Nash Equilibria) that are of interest for this game under various assumptions. Based on this characterization, several cases are defined and studied. The analysis of the complexity of some decision problems is made. We particularly focus on the problem of finding a Nash Equilibrium that maximizes the value of the total flow. We prove that this problem is NP-hard in the strong sense and show how such a strategy can be characterized considering paths in specific reduced agent-networks. We also provide a mixed integer linear programming (MILP) formulation that solves the problem in the case of a single producer/customer agent and a set of transportation agents. Computational experiments are provided to prove the effectiveness of our approach

This thesis explores possible approaches to detecting robotic activity of botnets on network. Initially, the detection based on full packet analysis in consideration of DNS, HTTP and IRC communication, is described. However, this detection is found inapplicable for technical and ethical reasons. Then it focuses on the analysis based on network flow metadata, compiling them to be processable in machine learning. It creates detection models using different machine learning methods, to compare them with each other. Bayes net method is found to be acceptable for detecting robotic activity of botnets. The Bayesian model is only able to identify the botnet that already executes the commands sent by its C&C server. "Sleeping" botnets are not reliably detectable by this model.

This master's thesis deals with optimization of traffic networks. There are discussed modeling methods for traffic and simplifications used in these models. Introductory part is focused on mathematical theory used to buid presented model. Main focus of this thesis was creation and optimization of the model which describes real world traffic network with traffic lights. Model was tested on both artificial and real data gathered in city Zlín. It was necessary to create generator which can produce suitable input data for model.

This thesis focuses on development of web application for the visualization of waste transportation according to calculated data from optimization methods in GAMS application. Visualization shows the nodes and edges on Google Maps where it is possible to show more detailed information including diagrams and tables. The application provides filtering edges by their type, highlighting edges with dynamic setting, several different ways for user access and other features. Based on developed application there will be presented some recommendations applicable in future using of the model.

The focus of this thesis is to find, visualize and analyze the optimal flow of autonomous electric vehicles with charge constraints in urban traffic with respect to energy consumption. The traffic has been formulated as a static multi-commodity network flow problem, for which two different models have been implemented to handle the charge constraints. The first model uses a recursive algorithm to find the optimal solution fulfilling the charge constraints, while the second model discretizes the commodities’ battery to predetermined battery levels. An implementation of both methods is provided through simulations on scenarios of three different sizes. The results show that both methods are capable of representing the traffic flow with charge constraints, with limitations given by the size of the problem. In particular, the recursive model has the advantage of considering the charge as a continuous quantity. On the other hand the discretization of battery levels allows to handle charge constraint setups with higher complexity, that is when longer detours are needed to fulfill the charge constraints.