In an age where computers challenge the smartest human beings in cognitive tasks, the conspicuous discrepancy between robot and animal locomotion appears paradoxical. While animals can move around autonomously in complex environments, today’s robots struggle to independently operate in such surroundings. There are many reasons for robots’ inferior performance, but arguably the most important one is our missing understanding of complexity. This thesis introduces the notion of discrete actuation for the study of locomotion in robots and animals. The actuation of a system with discrete actuation is restricted to be applied at a finite number of instants in time and is impulsive. We find that, despite their simplicity, such systems can predict various experimental observations and inspire novel technologies for robot design and control. We further find that, through the study of discrete actuation, causal relationships between actuation and resulting behaviour are revealed and become quantifiable, which relates the findings presented in this thesis to the broader concepts of complexity, self-organisation, and self-stability. We present four case studies in Chapters 3-6 which demonstrate how the concept of discrete actuation can be employed to understand the physics of locomotion and to facilitate novel robot technologies. We first introduce the impulsive eccentric wheel model which is a discretely actuated system for the study of hopping locomotion. We find that the model predicts robot hopping trajectories and animal related hopping characteristics by reducing the dynamics of hopping–usually described by hybrid differential equations–to analytic maps. The reduction of complexity of the model equations reveals the underlying physics of the locomotion process, and we identify the importance of robot shape and mass distribution for the locomotion performance. As a concrete application of the model, we compare the energetics of hopping and rolling locomotion in environments with obstacles and find when it is better to hop than to roll, based on the fundamental physical principles we discover in the model analysis. The theoretical insights of this modelling approach enable new actuation techniques and design for robots which we display in Robbit; a robot that uses strictly convex foot shapes and rotational impulses to induce hopping locomotion. We show that such systems outperform hopping with non-strictly convex shapes in terms of energy effective and robust locomotion. A system with discrete actuation motivates the exploitation of shape and the environment to improve locomotion dynamics, which reveals advantageous effect of inelastic impacts between the robot foot and the environment. We support this idea with experimental results from the robot CaneBot which can change its foot shape to induce timed impacts with the environment. Even though inelastic impacts are commonly considered detrimental for locomotion dynamics, we show that their appropriate control improves the locomotion speed considerably. The findings presented in this thesis show that discrete actuation for locomotion inspires novel ways to appreciate locomotion dynamics and facilitates unique control and design technologies for robots. Furthermore, discrete actuation emphasises the definition of causality in complex systems which we believe will bring robots closer to the locomotion behaviour of animals, enabling more agile and energy effective robots.

An autonomous robot able to navigate inside an unknown environment and reconstruct full 3D scene models using monocular video has been a long term goal in the field of Machine Vision. A key component of such a system is the reconstruction of surface models from estimated scene structure. Sparse 3D measurements of real scenes are readily estimated from N-view image sequences using structure-from-motion techniques. In this thesis we present a geometric theory for reconstruction of surface models from sparse 3D data captured from N camera views. Based on this theory we introduce a general N-view algorithm for reconstruction of 3D models of arbitrary scenes from sparse data. Using a hypothesise and verify strategy this algorithm reconstructs a surface model which interpolates the sparse data and is guaranteed to be consistent with the feature visibility in the N-views. To achieve efficient reconstruction independent of the number of views a simplified incremental algorithm is developed which integrates the feature visibility independently for each view. This approach is shown to converge to an approximation of the real scene structure and have a computational cost which is linear in the number of views. Surface hypothesis are generated based on a new incremental planar constrained Delaunay triangulation algorithm. We present a statistical geometric framework to explicitly consider noise inherent in estimates of 3D scene structure from any real vision system. This approach ensures that the reconstruction is reliable in the presence of noise and missing data. Results are presented for reconstruction of both real and synthetic scenes together with an evaluation of the reconstruction performance in the presence of noise.

Um dos grandes problemas relacionados a modelagem de workflow consiste na utilização de técnicas de modelagem conceitual especificas a cada sistema de workflow, não havendo, dessa forma, urn modelo aceito consensualmente. Esta situação, decorrência do ambiente competitivo neste mercado, leva a não inclusão de muitas características conceitualmente importantes relacionadas a modelagem nos técnicas geralmente utilizadas. Um importante aspecto a ser tratado nos modelos conceituais e a questão da modelagem formal do workflow e que constitui o terra central deste trabalho. Esta dissertação apresenta uma técnica de modelagem de workflow utilizando como modelo de dados referencial o TF-ORM (Temporal Functionality in Objects with Roles Model). Esta técnica desenvolve uma especificação rigorosa de workflow em um nível conceitual, formalizando com a utilização de um modelo técnico seu comportamento interno (cooperação e interação entre tarefas) e seu relacionamento para o ambiente (designação de tarefas de trabalho para executores). Neste modelo, construções são apresentadas para representar, de forma eficiente, a modularização e o paralelismo. Uma linguagem textual de definição de workflow e apresentada. Adicionalmente é apresentada a utilização de descrições formais do workflow para gerar o esquema de dados do workflow e o conjunto de regras para seu gerenciamento. Em adição, o paradigma de regras oferece um formalismo conveniente para expressar computações reativas influenciadas por eventos externos, gerados fora do WFMS (Workflow Manager System). Finalmente é realizada uma analise sobre algumas ferramentas comerciais, procurando validar a praticidade dos modelos conceituais desenvolvidos. Os principais conceitos envolvidos em workflow são descritos e classificados de forma a possibilitar, a validação tanto dos conceitos quanto da modelagem através de um estudo de caso e a utilização de um sistema comercial. / One of the greatest problems in workflow modelling is the use of specific conceptual modelling techniques associated to each workflow system; there is not a consensual accepted model. This situation, a consequence of the strong competitive environment in this market, leads to the non-inclusion of many important conceptual characteristics. This restriction is a consequence of the restricted modelling techniques closely related with implementation models. An important aspect to be considered, and the central subject of this work, is the formal workflow modelling. A modelling technique using the TF-ORM (Temporary Functionality in Objects with Rolls Model) data model is here presented. The modelling technique develops a rigorous specification of workflow at the conceptual level, formalising in one model its internal behaviour (the co-operation and interaction among tasks) and its relationship with the environment (the designation of tasks). In this model, constructions where developed to represent, in an efficient form, the modularity and the parallelism of the activities. A formal language for the workflow definition is presented. Additionally, the use of formal workflow description is used to generate the data flow and rules set for its management. In addition, the rules paradigm offers a convenient formalism to express reactive computations influenced by external events generated outside the Workflow Manager System. Finally a case study is accomplished using some commercial modelling tools, to validate the developed conceptual models practicality.

Expanding cell populations extracted from patients or animals is essential to the process of tissue engineering and is commonly performed in laboratory incubation devices known as bioreactors. Bioreactors provide a means of controlling the chemical and mechanical environment experienced by cells to ensure growth of a functional population. However, maximising this growth requires detailed knowledge of how cell proliferation is affected by bioreactor operating conditions, such as the flow rate of culture medium into the bioreactor, and by the initial cell seeding distribution in the bioreactor. Mathematical modelling can provide insight into the effects of these factors on cell expansion by describing the chemical and physical processes that affect growth and how they interact over different length- and time-scales. In this thesis we develop models to investigate how cell expansion in bioreactors is affected by fluid flow, solute transport and cell seeding. For this purpose, a perfused single-fibre hollow fibre bioreactor is used as a model system. We start by developing a model of the growth of a homogeneous cell layer on the outer surface of the hollow fibre in response to local nutrient and waste product concentrations and fluid shear stress. We use the model to simulate the cell layer growth with different flow configurations and operating conditions for cell types with different nutrient demands and responses to fluid shear stress. We then develop a 2D continuum model to investigate the influence of oxygen delivery, fluid shear stress and cell seeding on cell aggregate growth along the outer surface of the fibre. Using the model we predict operating conditions and initial aggregate distributions that maximise the rate of growth to confluence over the fibre surface for different cell types. A potential limitation of these models is that they do not explicitly consider individual cell interaction, movement and growth. To address this, we conclude the thesis by assessing the suitability of a hybrid framework for modelling bioreactor cell aggregate growth, with a discrete cell model coupled to a continuum nutrient transport model. We consider a simple set-up with a 1D cell aggregate growing along the base of a 2D nutrient bath. Motivated by trying to reduce the high computational cost of simulating large numbers of cells with a cell-based model, and to assess the validity of our previous continuum description of cell aggregate growth, we derive a continuum approximation of the discrete model in the large cell number limit and determine whether it agrees with the discrete model via numerical simulations.

No description available.

This thesis offers an explanation of the statistical modelling of corporate financial indicators in the context where the life of a company is terminated. Whilst it is natural for companies to fail or close down, an excess of failure causes a reduction in the activity of the economy as a whole. Therefore, studies on business failure identification leading to models which may provide early warnings of impending financial crisis may make some contribution to improving economic welfare. This study considers a number of bankruptcy prediction models such as multiple discriminant analysis and logit, and then introduces survival analysis as a means of modelling corporate failure. Then, with a data set of UK companies which failed, or were taken over, or were still operating when the information was collected, we provide estimates of failure probabilities as a function of survival time, and we specify the significance of financial characteristics which are covariates of survival. Three innovative statistical methods are introduced. First, a likelihood solution is provided to the problem of takeovers and mergers in order to incorporate such events into the dichotomous outcome of failure and survival. Second, we move away from the more conventional matched pairs sampling framework to one that reflects the prior probabilities of failure and construct a sample of observations which are randomly censored, using stratified sampling to reflect the structure of the group of failed companies. The third innovation concerns the specification of survival models, which relate the hazard function to the length of survival time and to a set of financial ratios as predictors. These models also provide estimates of the rate of failure and of the parameters of the survival function. The overall adequacy of these models has been assessed using residual analysis and it has been found that the Weibull regression model fitted the data better than other parametric models. The proportional hazard model also fitted the data adequately and appears to provide a promising approach to the prediction of financial distress. Finally, the empirical analysis reported in this thesis suggests that survival models have lower classification error than discriminant and logit models.

No description available.

Novel techniques, mainly three-dimensional (3D) reconstructions from image stacks and finite element analysis (FEA), were combined to study the oxygen transport mechanism in the human placenta and its relationship to placental structure. Initial research relates to the development of a platform suitable for realistic computational simulations. The work shows how the 3D architecture of a terminal villus can be accurately reconstructed from confocal laser scanning microscopic (CLSM) images. By combining the resultant 3D structures of terminal villi with finite element analysis, the diffusion of oxygen from the maternal bloodstream towards the fetal blood across the villous membrane is assessed. The results correlate with theoretical studies demonstrating that image-based computational modelling is a robust platform to explore the structure-function relationship in the placenta. Following work deals with the study of blood flow through the fetal capillary network, with particular interest in its role on the oxygen transport capacity of the terminal villi. The computational models are corroborated by a particle image velocimetry (PIV) experiment. The study shows that the variation in capillary diameter is key for effective oxygen uptake by the fetus. The fetus invests minimum energy needed for the blood to travel fast enough in order to provide oxygenated blood, but at the same time slow enough to allow for good oxygenation. This is achieved by the combination of narrow and dilated segments. Additionally, the results demonstrate that there is no vortical flow or whirling. In the subsequent work, the effect of blood properties is investigated. The calculated oxygen flux is 75 times higher than in the previous study (blood flow models), highlighting the importance of haemoglobin molecules in transporting oxygen. Fetal blood affinity is shown to improve fetal oxygen uptake by 11.5%. However, when accounting for haemoglobin concentration the data suggest that the different villous structures have a constant oxygen transport capacity. The methodology developed herein helps to elucidate the structure-function relationship in the human placenta. Additionally, 3D image-based multi-physics computational modelling is demonstrated to be a powerful tool to investigate in detail the mechanics of transport in the human placenta. This technique has the potential to enlighten on the development of pregnancy complications and serve as an in vivo diagnostic tool.

Um dos grandes problemas relacionados a modelagem de workflow consiste na utilização de técnicas de modelagem conceitual especificas a cada sistema de workflow, não havendo, dessa forma, urn modelo aceito consensualmente. Esta situação, decorrência do ambiente competitivo neste mercado, leva a não inclusão de muitas características conceitualmente importantes relacionadas a modelagem nos técnicas geralmente utilizadas. Um importante aspecto a ser tratado nos modelos conceituais e a questão da modelagem formal do workflow e que constitui o terra central deste trabalho. Esta dissertação apresenta uma técnica de modelagem de workflow utilizando como modelo de dados referencial o TF-ORM (Temporal Functionality in Objects with Roles Model). Esta técnica desenvolve uma especificação rigorosa de workflow em um nível conceitual, formalizando com a utilização de um modelo técnico seu comportamento interno (cooperação e interação entre tarefas) e seu relacionamento para o ambiente (designação de tarefas de trabalho para executores). Neste modelo, construções são apresentadas para representar, de forma eficiente, a modularização e o paralelismo. Uma linguagem textual de definição de workflow e apresentada. Adicionalmente é apresentada a utilização de descrições formais do workflow para gerar o esquema de dados do workflow e o conjunto de regras para seu gerenciamento. Em adição, o paradigma de regras oferece um formalismo conveniente para expressar computações reativas influenciadas por eventos externos, gerados fora do WFMS (Workflow Manager System). Finalmente é realizada uma analise sobre algumas ferramentas comerciais, procurando validar a praticidade dos modelos conceituais desenvolvidos. Os principais conceitos envolvidos em workflow são descritos e classificados de forma a possibilitar, a validação tanto dos conceitos quanto da modelagem através de um estudo de caso e a utilização de um sistema comercial. / One of the greatest problems in workflow modelling is the use of specific conceptual modelling techniques associated to each workflow system; there is not a consensual accepted model. This situation, a consequence of the strong competitive environment in this market, leads to the non-inclusion of many important conceptual characteristics. This restriction is a consequence of the restricted modelling techniques closely related with implementation models. An important aspect to be considered, and the central subject of this work, is the formal workflow modelling. A modelling technique using the TF-ORM (Temporary Functionality in Objects with Rolls Model) data model is here presented. The modelling technique develops a rigorous specification of workflow at the conceptual level, formalising in one model its internal behaviour (the co-operation and interaction among tasks) and its relationship with the environment (the designation of tasks). In this model, constructions where developed to represent, in an efficient form, the modularity and the parallelism of the activities. A formal language for the workflow definition is presented. Additionally, the use of formal workflow description is used to generate the data flow and rules set for its management. In addition, the rules paradigm offers a convenient formalism to express reactive computations influenced by external events generated outside the Workflow Manager System. Finally a case study is accomplished using some commercial modelling tools, to validate the developed conceptual models practicality.

Computational modelling is playing an increasing role in neuroscience research by providing not only theoretical frameworks for describing the activity of the brain and the nervous system, but also by providing a set of tools and techniques for better understanding data obtained using various recording techniques. The focus of this thesis was on the latter - using computational modelling to assist with analyzing measurement results and the underlying mechanisms behind them. The first study described in this thesis is an example of the use of a computational model in the case of intracellular in vivo recordings. Intracellular recordings of neurons in vivo are becoming routine, yielding insights into the rich sub-threshold neural dynamics and the integration of information by neurons under realistic situations. In particular, these methods have been used to estimate the global excitatory and inhibitory synaptic conductances experienced by the soma. I first present a method to estimate the effective somatic excitatory and inhibitory conductances as well as their rate and event size from the intracellular in vivo recordings. The method was applied to intracellular recordings from primary motor cortex of awake behaving mice. Next, I studied how dendritic filtering leads to misestimation of the global excitatory and inhibitory conductances. Using analytical treatment of a simplified model and numerical simulations of a detailed compartmental model, I show how much both the mean, as well as the variation of the synaptic conductances are underestimated by the methods based on recordings at the soma. The influence of the synaptic distance from the soma on the estimation for both excitatory as well as inhibitory inputs for different realistic neuronal morphologies is discussed. The last study was an attempt to classify the synaptic location region based on the measurements of the excitatory postsynaptic potential at two different locations on the dendritic tree. The measurements were obtained from the in vitro intercellular recordings in slices of the somatosensory cortex of rats when exposed to glutamate uncaging stimulation. The models were used to train the classifier and to demonstrate the extent to which the automatic classification agrees with manual classification performed by the experimenter.