Online services such as e-marketplaces, social networking sites, online gaming environments etc have grown in popularity in the recent years. These services represent situation where participants do not get to negotiate face to face before interaction and most of the time parties to transaction remain anonymous. It is thus necessary to have a system that rightly assesses trustworthiness of the other party in order to maintain quality assurance in such systems. Recent works on Trust and Reputation in online communities have focused on identifying probable defaulters, but less effort has been put to come up with system that make cooperation attractive over defection in order to achieve cooperation without enforcement. Our work in this regard concerns design and investigation of trust assessment systems that not only filter defaulters but also promote evolution of cooperativeness in player society. Based on the concept of game theory and prisoner¿s dilemma, we model business games and design incentive method, compensation method, acquaintance based assessment method and decision theoretic assessment method as mechanisms to assure trustworthiness in online business environments. Effectiveness of each of these methods in promoting the evolution of cooperation in player society has been investigated. Our results show that these methods contribute positively in promoting cooperative evolution. We have further extended our trust assessment model to suit the needs of a mobile ad-hoc network setting. The effectiveness of this model has been tested against its capability to reduce packet drop rate and energy conservation. In both of these the results show promise. / EU Asia-link project TH/Asia Link/004(91712) East-West and its local host Kantipur Engineering College in Nepal, and Kathmandu University.

The aim of this thesis is to improve our understanding of the neural systems involved in schizophrenia by suggesting possible avenues for future computational modelling in an attempt to make sense of the vast number of studies relating to the symptoms and cognitive deficits relating to the disorder. This multidisciplinary research has covered three different levels of analysis: abnormalities in the microscopic brain structure, dopamine dysfunction at a neurochemical level, and interactions between cortical and subcortical brain areas, connected by cortico-basal ganglia circuit loops; and has culminated in the production of five models that provide useful clarification in this difficult field. My thesis comprises three major relevant modelling themes. Firstly, in Chapter 3 I looked at an existing neural network model addressing the Neurodevelopmental Hypothesis of Schizophrenia by Hoffman and McGlashan (1997). However, it soon became clear that such models were overly simplistic and brittle when it came to replication. While they focused on hallucinations and connectivity in the frontal lobes they ignored other symptoms and the evidence of reductions in volume of the temporal lobes in schizophrenia. No mention was made of the considerable evidence of dysfunction of the dopamine system and associated areas, such as the basal ganglia. This led to my second line of reasoning: dopamine dysfunction. Initially I helped create a novel model of dopamine neuron firing based on the Computational Substrate for Incentive Salience by McClure, Daw and Montague (2003), incorporating temporal difference (TD) reward prediction errors (Chapter 5). I adapted this model in Chapter 6 to address the ongoing debate as to whether or not dopamine encodes uncertainty in the delay period between presentation of a conditioned stimulus and receipt of a reward, as demonstrated by sustained activation seen in single dopamine neuron recordings (Fiorillo, Tobler & Schultz 2003). An answer to this question could result in a better understanding of the nature of dopamine signaling, with implications for the psychopathology of cognitive disorders, like schizophrenia, for which dopamine is commonly regarded as having a primary role. Computational modelling enabled me to suggest that while sustained activation is common in single trials, there is the possibility that it increases with increasing probability, in which case dopamine may not be encoding uncertainty in this manner. Importantly, these predictions can be tested and verified by experimental data. My third modelling theme arose as a result of the limitations to using TD alone to account for a reinforcement learning account of action control in the brain. In Chapter 8 I introduce a dual weighted artificial neural network, originally designed by Hinton and Plaut (1987) to address the problem of catastrophic forgetting in multilayer artificial neural networks. I suggest an alternative use for a model with fast and slow weights to address the problem of arbitration between two systems of control. This novel approach is capable of combining the benefits of model free and model based learning in one simple model, without need for a homunculus and may have important implications in addressing how both goal directed and stimulus response learning may coexist. Modelling cortical-subcortical loops offers the potential of incorporating both the symptoms and cognitive deficits associated with schizophrenia by taking into account the interactions between midbrain/striatum and cortical areas.

The development of essential medicines is being slowed by a lack of efficiency in drug development as ninety per cent of drugs fail at some stage during clinical evaluation. This attrition in drug development is seen not because of a reduction in pharmaceutical research expenditure nor is it caused by a declining understanding of biology, if anything, these are both increasing. Instead, drugs are failing because we are unable to effectively predict how they will work before they are given to patients. This is due to limitations of the current methods used to evaluate a drug's toxicity and efficacy prior to its development. Quite simply, these methods do not account for the full complexity of biology in humans. Systems pharmacology models are a likely candidate for increasing the efficiency of drug discovery as they seek to comprehensively model the fundamental biology of disease mechanisms in a quantit- ative manner. They are computational models, designed and hailed as a strategy for making well-informed and cost effective decisions on drug viability and target druggability and therefore attempt to reduce this time-consuming and costly attrition. Using text mining and text classification I present a growing landscape of systems pharmacology models in literature growing from humble roots because of step-wise increases in our understanding of biology. Furthermore, I develop a case for the capability of systems pharmacology models in making predictions by constructing a model of interleukin-6 signalling for rheumatoid arthritis. This model shows that druggable target selection is not necessarily an intuitive task as it results in an emergent but unanswered hypothesis for safety concerns in a monoclonal antibody. Finally, I show that predictive classification models can also be used to explore gene expression data in a novel work flow by attempting to predict patient response classes to an influenza vaccine.

There have been a number of computational modelling studies that aim to replicate the cerebellar Purkinje cell, though these typically use the morphology of rodent cells. While many species, including rodents, display intricate dendritic branching, it is not a universal feature among Purkinje cells. This study uses morphological reconstructions of 24 Purkinje cells from seven species to explore the changes that occur to the cell through evolution and examine whether this has an effect on the processing capacity of the cell. This is achieved by combining several modes of study in order to gain a comprehensive overview of the variations between the cells in both morphology and behaviour. Passive and active computational models of the cells were created, using the same electrophysiological parameters and ion channels for all models, to characterise the voltage attenuation and electrophysiological behaviour of the cells. These results and several measures of branching and size were then used to look for clusters in the data set using machine learning techniques. They were also used to visualise the differences within each species group. Information theory methods were also employed to compare the estimated information transfer from input to output across each cell. Along with a literature review into what is known about Purkinje cells and the cerebellum across the phylogenetic tree, these results show that while there are some obvious differences in morphology, the variation within species groups in electrophysiological behaviour is often as high as between them. This suggests that morphological changes may occur in order to conserve behaviour in the face of other changes to the cerebellum.

Furnaces that heat metal parts (blooms) prior to hot-working processes such as rolling or forging are called pre-forming reheat furnaces. In these furnaces, the fundamental idea is to heat the blooms to a prescribed temperature without very large temperature gradients in them. This is to ensure correct performance of the metal parts subsequent to reheating. Due to the elevated temperature in the furnace chamber, radiation is the dominant mode of heat transfer from the furnace to the bloom. In addition, there is convection heat transfer from the hot gases to the bloom. The heat transfer within the bloom is by conduction. In order to design a new furnace or to improve the performance of existing ones, the heat transfer analysis has to be done accurately. Given the complex geometry and large number of parameters encountered in the furnace, an analytical solution is difficult, and hence numerical modeling has to be resorted to. In the present work, a numerical technique for modelling the steady-state and transient heat transfer in a reheat furnace is developed. The work mainly involves the development of a radiation heat transfer analysis code for a reheat furnace, since a major part of the heat transfer in the furnace chamber is due to radiation from the roof and combustion gases. The code is modified from an existing finite volume method (FVM) based radiation heat transfer solver, The existing solver is a general purpose radiation heat transfer solver for enclosures and incorporates the following features: surface-to-surface radiation, gray absorbing-emitting medium in the enclosure, multiple reflections off the bounding walls, shadowing effects due to obstructions in the enclosure, diffuse reflection and enclosures with irregular geometry. As a part of the present work, it has now been extended to include the following features that characterise radiation heat transfer in the furnace chamber · Combination of specular and diffuse reflection as is the case with most real surfaces · Participating non-gray media, as the combustion gases in the furnace chamber exhibit highly spectral radiative characteristics Transient 2D conduction heat transfer within the metal part is then modelled using a FVM-based code. Radiation heat flux from the radiation model and convection heat flux calculated using existing correlations act as boundary conditions for the conduction model. A global iteration involving the radiation model and the conduction model is carried out for the overall solution. For the study, two types of reheat furnaces were chosen; the pusher-type furnace and the walking beam furnace. The difference in the heating process of the two furnaces implies that they have to be modelled differently. In the pusher-type furnace, the heating of the blooms is only from the hot roof and the gas. In the walking beam furnace, the heating is also from the hearth and the blooms adjacent to any given bloom. The model can predict the bloom residence time for any particular combination of furnace conditions and load dimensions. The effects of variations of emissivities of the load, thickness of the load and the residence time of billet in the furnaces were studied.

Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / As técnicas inversas têm sido usadas na determinação de parâmetros importantes envolvidos na concepção e desempenho de muitos processos industriais. A aplicação de métodos estocásticos tem aumentado nos últimos anos, demonstrando seu potencial no estudo e análise dos diferentes sistemas em aplicações de engenharia. As rotinas estocásticas são capazes de otimizar a solução em uma ampla gama de variáveis do domínio, sendo possível a determinação dos parâmetros de interesse simultaneamente. Neste trabalho foram adotados os métodos estocásticos Luus-Jaakola (LJ) e Random Restricted Window (R2W) na obtenção dos ótimos dos parâmetros cinéticos de adsorção no sistema de cromatografia em batelada, tendo por objetivo verificar qual método forneceria o melhor ajuste entre os resultados obtidos nas simulações computacionais e os dados experimentais. Este modelo foi resolvido empregando o método de Runge- Kutta de 4 ordem para a solução de equações diferenciais ordinárias. / The inverse techniques have been used in the determination of parameters involved in design and performance of many industrial processes. The application of stochastic methods has increased in recent years, demonstrating their potential in study and analysis of different systems in engineering applications. Stochastic routines are able to optimize the solution in a wide range of variables, it is possible to determine the parameters of interest simultaneously. In this work two adopted the stochastic methods, Luus-Jaakola (LJ) and Restricted Random Window (R2W), to obtain the optimum parameters for adsorption kinetics in batch chromatography system, aiming to determine which method would provide the best fit between the results obtained in computer simulations and experimental data. This model was solved using the Runge-Kutta 4th order for ordinary differential equations solution.

Cette thèse porte sur une réflexion autour de la composition musicale arabe et les nouvelles technologies, avec comme élément central, les particularités idiosyncratiques inhérentes au langage musical.La rencontre avec les nouvelles technologies soulève plusieurs interrogations sous-jacentes. L’approche proposée consiste en la détermination d’un cadre formel avec un ensemble de structures idiomatiques selon un angle pluridisciplinaire musicologique et ethnomusicologique, mais aussi historico-acoustique et théorico-empirique à la fois.Le modèle musicologique dégagé permet de souligner : l’importance des cellules mélodiques primaires, une quantification acoustique des systèmes intervalliques, les aspects de monodie et d’hétérophonie selon le niveau individuel et collectif, une instabilité des degrés, et des aspects liés à l’interprétation musicale. Des approches originales sont envisagées concernant l’étude des mécanismes d’ornementations et trois catégories sont baptisées.La confrontation de ce modèle musicologique avec la rencontre des nouvelles technologies est établie et les conséquences de celle-ci sont soulignées. Les notions de simulation et d’émulation mettent en évidence la centralité du timbre et le recours à des échantillons audiovisuels permet d’identifier le domaine implicite de l’expérimentation. Une comparaison avec le modèle expérimental sur le plan de la musique électronique en général et l’informatique musicale en particulier est alors réalisée.Enfin, un essai de modélisation informatique dans l’environnement Csound est proposé et retrace les éléments idiosyncratiques identifiés. Des compositions électroacoustiques sont citées et une pièce est analysée. / This thesis focuses on Arabic musical composition and new technologies, with the idiosyncratic characteristics inherent in the musical language as central element.The encounter with new technologies raises several underlying questions.The approach suggested consists of a formal frame with a set of idiomatic structures according to a pluridisciplinary angle musicological and ethnomusicological, but also historical-acoustical and theorico-empirical at the same time.The musicological model revealed underlines: the importance of primary melodic cells, acoustic quantification of interval systems, monody and heterophony aspects according to individual and collective level, instability of degrees, and aspects related to musical interpretation.Original approaches are envisaged concerning the study of the mechanisms of ornamentations and three categories are baptized.The confrontation of this musicological model with new technologies’ encounter is established and the consequences of this one are underlined.Simulation and emulation concepts highlight the centrality of timbre and the use of audio-visual samples allows the identification of the implicit domain of experimentation.A comparison with the experimental model of electronic music in general and computer music in particular is therefore made.Finally, a computational modelling test in the Csound environment is proposed and traces the idiosyncratic elements identified. Electroacoustic compositions are cited and a musical work is analysed.

The underlying causes of variability in the electrical activity of hearts from individuals of the same species are not well understood. Understanding this variability is important to enable prediction of the response of individual hearts to diseases and therapies. Current experimental and computational methods for investigating the behaviour of the heart do not incorporate biological variation between individuals. In experimental studies, experimental results are averaged together to control errors and determine the average behaviour of the studied organism. In computational studies, averaged experimental data is usually used to develop models, and these models therefore represent a 'typical' organism, with all information on variability within the species having been lost. In this thesis we develop a methodology for modelling variability between individuals of the same species in cardiac cellular electrophysiology, motivated by the inability of traditional computational modelling approaches to capture experimental variability. A first study is conducted using traditional modelling approaches to investigate potentially pro-arrhythmic abnormalities in rabbit Purkinje fibres. A comparison with experimental recordings highlights their wide variability and the inability of existing computer modelling approaches to capture it. This leads to the development of a novel methodology that integrates the variability observed in experimental data with computational modelling and simulation, by building experimentally-calibrated populations of computational models, that collectively span the variability seen in experimental data. We apply this methodology to construct a population of rabbit Purkinje cell models. We show that our population of models can quantitatively predict the range of responses, not just the average response, to application of the potassium channel blocking drug dofetilide. This demonstrates an important potential application of our methodology, for predicting pro-arrhythmic drug effects in safety pharmacology. We then analyse a data set of experimental recordings from human ventricular tissue preparations, and use this data to develop a population of human ventricular cell models. We apply this population to study how variability between individuals alters the susceptibility of cardiac cells to developing drug-induced repolarisation abnormalities. These abnormalities can increase the chance of fatal arrhythmias, but the mechanisms that determine individual susceptibility are not well-understood.

Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / As técnicas inversas têm sido usadas na determinação de parâmetros importantes envolvidos na concepção e desempenho de muitos processos industriais. A aplicação de métodos estocásticos tem aumentado nos últimos anos, demonstrando seu potencial no estudo e análise dos diferentes sistemas em aplicações de engenharia. As rotinas estocásticas são capazes de otimizar a solução em uma ampla gama de variáveis do domínio, sendo possível a determinação dos parâmetros de interesse simultaneamente. Neste trabalho foram adotados os métodos estocásticos Luus-Jaakola (LJ) e Random Restricted Window (R2W) na obtenção dos ótimos dos parâmetros cinéticos de adsorção no sistema de cromatografia em batelada, tendo por objetivo verificar qual método forneceria o melhor ajuste entre os resultados obtidos nas simulações computacionais e os dados experimentais. Este modelo foi resolvido empregando o método de Runge- Kutta de 4 ordem para a solução de equações diferenciais ordinárias. / The inverse techniques have been used in the determination of parameters involved in design and performance of many industrial processes. The application of stochastic methods has increased in recent years, demonstrating their potential in study and analysis of different systems in engineering applications. Stochastic routines are able to optimize the solution in a wide range of variables, it is possible to determine the parameters of interest simultaneously. In this work two adopted the stochastic methods, Luus-Jaakola (LJ) and Restricted Random Window (R2W), to obtain the optimum parameters for adsorption kinetics in batch chromatography system, aiming to determine which method would provide the best fit between the results obtained in computer simulations and experimental data. This model was solved using the Runge-Kutta 4th order for ordinary differential equations solution.

Made available in DSpace on 2014-12-17T14:10:23Z (GMT). No. of bitstreams: 1 BrunoGS_DISSERT_partes autorizadas.pdf: 2090858 bytes, checksum: 96c920960475d5970880d27da7b95ada (MD5) Previous issue date: 2011-05-23 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / Knowledge of the native prokaryotes in hazardous locations favors the application of biotechnology for bioremediation. Independent strategies for cultivation and metagenomics contribute to further microbiological knowledge, enabling studies with non-cultivable about the "native microbiological status and its potential role in bioremediation, for example, of polycyclic aromatic hydrocarbons (HPA's). Considering the biome mangrove interface fragile and critical bordering the ocean, this study characterizes the native microbiota mangrove potential biodegradability of HPA's using a biomarker for molecular detection and assessment of bacterial diversity by PCR in areas under the influence of oil companies in the Basin Petroleum Geology Potiguar (BPP). We chose PcaF, a metabolic enzyme, to be the molecular biomarker in a PCR-DGGE detection of prokaryotes that degrade HPA s. The PCR-DGGE fingerprints obtained from Paracuru-CE, Fortim-CE and Areia Branca-RN samples revealed the occurrence of fluctuations of microbial communities according to the sampling periods and in response to the impact of oil. In the analysis of microbial communities interference of the oil industry, in Areia Branca-RN and Paracuru-CE was observed that oil is a determinant of microbial diversity. Fortim-CE probably has no direct influence with the oil activity. In order to obtain data for better understanding the transport and biodegradation of HPA's, there were conducted in silico studies with modeling and simulation from obtaining 3-D models of proteins involved in the degradation of phenanthrene in the transport of HPA's and also getting the 3-D model of the enzyme PcaF used as molecular marker in this study. Were realized docking studies with substrates and products to a better understanding about the transport mechanism and catalysis of HPA s / O conhecimento sobre os procariotos nativos em locais de risco favorece a aplica??o de biotecnologias para biorremedia??o. Estrat?gias independentes de cultivo, como metagen?mica, contribuem para aprofundar o conhecimento microbiol?gico, possibilitando estudos com organismos n?o cultiv?veis acerca do status microbiol?gico nativo e seu potencial papel na biodegrada??o de, por exemplo, Hidrocarbonetos Arom?ticos Polic?clicos (HAP s). Considerando o bioma de mangue uma interface fr?gil e cr?tica de fronteira com o oceano, este trabalho caracteriza a microbiota nativa de mangue com potencial biodegradador de HAP s utilizando um biomarcador molecular para detec??o e avalia??o da diversidade bacteriana em ?reas sob influ?ncia de ind?strias petrol?feras atrav?s da PCR-DGGE na Bacia Petrol?fera Potiguar (BPP). Foi escolhido um biomarcador molecular metab?lico, enzima PcaF, para detec??o de procariotos degradadores de HAP s. Com o biomarcador, fingerprints foram obtidos de amostras de Paracuru-CE, Fortim-CE e Areia Branca-RN, revelando a ocorr?ncia de flutua??es das comunidades microbianas de acordo com os per?odos de amostragem e em resposta ao impacto por petr?leo. Atrav?s da an?lise das comunidades microbianas frente ? interfer?ncia da ind?stria do petr?leo, em Areia Branca-RN e Paracuru-CE foi observado que o petr?leo ? determinante para a diversidade microbiana. Fortim-CE provavelmente n?o tem influ?ncia direta da atividade petrol?fera. No intuito de obter dados para o melhor entendimento do transporte e biodegrada??o de HAP s, foram desenvolvidos estudos in silico de modelagem e simula??o computacional a partir da obten??o de modelos 3-D de prote?nas envolvidas na degrada??o do fenantreno, no transporte de HAP s e tamb?m a obten??o do modelo 3-D da enzima PcaF. Estudos de dockings com substratos e produtos forneceram dados para o melhor entendimento sobre o mecanismo de transporte e cat?lise de HAP s