The long-term preservation of digital objects has become increasingly relevant. Libraries, public institutions and museums, but also companies are requesting solutions to store their digital files with all relevant contents and attributes for the future. This master thesis makes two contributions to the research in digital preservation.The first attempt is the creation of a testbed which stores many files in different file formats. These files can be used to evaluate the impact of preservation solutions. In this paper an environment for storing and describing files is being suggested and implemented.The second contribution is made by presenting a framework which is based on Utility Analysis for evaluating different preservation solutions. The application of a detailed hierarchy of objectives, considering the individual requirements of the user, will allow a reasonable and clear decision for a specific preservation solution, which can be supported with arguments. The theoretic framework is evaluated in two casestudies. For the first one the whole process is being realized, for the second example only the major part of the analysis, the objective tree, is treated in detail.

There is a growing interest in combining different levels of detail of biological phenomena into unique multi-scale models that represent both biochemical details and higher order structures such as cells, tissues or organs. The state of the art of multi-scale models presents a variety of approaches often tailored around specific problems and composed of a combination of mathematical techniques. As a result, these models are difficult to build, compose, compare and analyse. In this thesis we identify process algebra as an ideal formalism to multi-scale modelling of biological systems. Building on an investigation of existing process algebras, we define process algebra with hooks (PAH), designed to be a middle-out approach to multi-scale modelling. The distinctive features of PAH are: the presence of two synchronisation operators, distinguishing interactions within and between scales, and composed actions, representing events that occur at multiple scales. A stochastic semantics is provided, based on functional rates derived from kinetic laws. A parametric version of the algebra ensures that a model description is compact. This new formalism allows for: unambiguous definition of scales as processes and interactions within and between scales as actions, compositionality between scales using a novel vertical cooperation operator and compositionality within scales using a traditional cooperation operator, and relating models and their behaviour using equivalence relations that can focus on specified scales. Finally, we apply PAH to define, compose and relate models of pattern formation and tissue growth, highlighting the benefits of the approach.

Understanding how listeners relate and compare pieces of music is a fundamental challenge in music research as well as for commercial applications: Today’s large-scale applications for music recommendation and exploration utilise various models for similarity prediction to satisfy users’ expectations. Perceived similarity is specific to the individual and influenced by a number of factors such as cultural background and age. Thus, adapting a generic model to human similarity data is useful for personalisation and can help to better understand such differences. This thesis presents new and state-of-the-art machine learning techniques for modelling music similarity and their first evaluation on relative music similarity data. We expand the scope for future research with methods for similarity data collection and a new dataset. In particular, our models are evaluated on their ability to “spot the odd song out” of three given songs. While a few methods are readily available, others had to be adapted for their first application to such data. We explore the potential for learning generalisable similarity measures, presenting algorithms for metrics and neural networks. A generic modelling workflow is presented and implemented. We report the first evaluation of the methods on the MagnaTagATune dataset showing learning is possible and pointing out particularities of algorithms and feature types. The best results with up to 74% performance on test sets were achieved with a combination of acoustic and cultural features, but model training proved most powerful when only acoustic information is available. To assess the generalisability of the findings, we provide a first systematic analysis of the dataset itself. We also identify a bias in standard sampling methods for cross-validation with similarity data and present a new method for unbiased evaluation, providing use cases for the different validation strategies. Furthermore, we present an online game that collects a new similarity dataset, including participant attributes such as age, location, language and music background. It is based on our extensible framework which manages storage of participant input, context information as well as selection of presented samples. The collected data enables a more specific adaptation of music similarity by including user attributes into similarity models. Distinct similarity models are learnt from geographically defined user groups in a first experiment towards the more complex task of culture-aware similarity modelling. In order to improve training of the specific models on small datasets, we implement the concept of transfer learning for music similarity models.

In this thesis we present a comprehensive approach for applying model checking to Agent-Based Learning (ABL) systems. Model checking faces a unique challenge with ABL systems, as the modelling of learning is thought to be outwith its scope. The practical work performed to model these systems is presented in the incremental stages by which it was carried out. This allows for a clearer understanding of the problems faced and of the progress made on traditional ABL system analysis. Our focus is on applying model checking to a specific type of system. It involves a biologically-inspired robot that uses Input Correlation learning to help it navigate environments. We present a highly detailed PROMELA model of this system, using embedded C code to avoid losing accuracy when modelling it. We also propose an abstraction method for this type of system: Agent-centric abstraction. Our abstraction is the main contribution of this thesis. It is defined in detail, and we provide a proof of its soundness in the form of a simulation relation. In addition to this, we use it to generate an abstract model of the system. We give a comparison between our models and traditional system analysis, specifically simulation. A strong case for using model checking to aid ABL system analysis is made by our comparison and the verification results we obtain from our models. Overall, we present a framework for analysing ABL systems that differs from the more common approach of simulation. We define this framework in detail, and provide results from practical work coupled with a discussion about drawbacks and future enhancements.

Ubiquitous computing is becoming an increasingly prevalent part of our everyday lives. The reliance of society upon such devices as mobile phones, coupled with the increasing complexity of those devices is an example of how our everyday human-human interaction is affected by this phenomenon. Social scientists studying human-human interaction must now take into account the effects of these technologies not just on the interaction itself, but also on the approach required to study it. User evaluation is a challenging topic in ubiquitous computing. It is generally considered to be difficult, certainly more so than in previous computational settings. Heterogeneity in design, distributed and mobile users, invisible sensing systems and so on, all add up to render traditional methods of observation and evaluation insufficient to construct a complete view of interactional activity. These challenges necessitate the development of new observational technologies. This thesis explores some of those challenges and demonstrates that system logs, with suitable methods of synchronising, filtering and visualising them for use in conjunction with more traditional observational approaches such as video, can be used to overcome many of these issues. Through a review of both the literature of the field, and the state of the art of computer aided qualitative data analysis software (CAQDAS), a series of guidelines are constructed showing what would be required of a software toolkit to meet the challenges of studying ubiquitous computing systems. It outlines the design and implementation of two such software packages, \textit{Replayer} and \textit{Digital Replay System}, which approach the problem from different angles, the former being focussed on visualising and exploring the data in system logs and the latter focussing on supporting the methods used by social scientists to perform qualitative analyses. The thesis shows through case studies how this technique can be applied to add significant value to the qualitative analysis of ubiquitous computing systems: how the coordination of system logs and other media can help us find information in the data that would otherwise be inaccessible; an ability to perform studies in locations/settings that would otherwise be impossible, or at least very difficult; and how creating accessible qualitative data analysis tools allows people to study particular settings or technologies who could not have studied them before. This software aims to demonstrate the direction in which other CAQDAS packages may have to move in order to support the study of the characteristics of human-computer and human-human interaction in a world increasingly reliant upon ubiquitous computing technology.

The human mitral valve (MV) consists of a large anterior-medial leaflet and a smaller posterior lateral leaflet, which are both connected to the left ventricular papillary muscles via multiple fibrous chordae tendineae. An understanding of mitral valve bio-mechanics is pivotal for optimization of surgical procedures aimed at restoring normal mitral valve function in pathological subjects. Computational models can realistically capture the anatomical and functional features of the MV and hence can provide detailed spatial and temporal data that may not be easily obtained clinically or experimentally. This thesis therefore aims at developing a framework for the fluid-structure interaction modeling of the mitral valve using immersed boundary method. First, we model the dynamics of a prosthetic mitral valve under a realistic pressure load using a staggered grid version of a formally second-order accurate immersed boundary method. In this study, we demonstrate that when bending rigidity are included in both the mitral leaflets and chordae, the computational results has better agreements with experimental measurements. In addition, non-physical oscillations that occur upon valve closure are greatly reduced when bending forces are included in the model. These findings highlight the importance of accounting for the bending stiffness in the dynamic simulation of the mitral valve prosthesis. Furthermore, an in-vivo human mitral valve geometry model is derived from magnetic resonance imaging (MRI) data, and then is analysed using the immersed boundary method under a physiological left-atrium-ventricle pressure loading. An initial validation of the model is provided by comparing the computed opening shape and flow rates to clinical measurements from the volunteer who provided the anatomical data for constructing the mitral valve. The convex (with respect to the left ventricle) shape near annulus and concave shape near free edge of valve are observed in our simulation during diastole and systole when assigning physiological thickness to the anterior leaflet and posterior leaflet, which match perfectly with clinical observations. These results suggest that differences in the thickness of the leaflets play an important role in maintaining the physiological curvature of the mitral valve. These features bring out a question that is the relatively simple isotropic material fibre model sufficient to describe the mitral valve leaflets. The real valve is anisotropic, with collagen fibres distributed along the circumferential direction. To this end, the further improved in-vivo human mitral valve geometry model, which incorporating spatial annulus ring, is then simulated under a physiological pressure loading with a finite element version of the immersed boundary method that is able to incorporate experimentally oriented constitutive laws for elasticity models. A hypo-elastic transversely isotropic material constitutive law is used to characterize the mechanical behaviour of the mitral valve tissue based on recent biaxial tests on healthy human leaflets. Simulation results exhibit better agreement and reduced oscillations in flow rate compared with experiment measurements and previous simulation and show that the maximum principal stress and strain is carried by the collagen fibres in the mitral leaflets in deep systole. These results show that the methodology in this study could generate a patient-specific finite element mitral valve model that closely replicated the in vivo mitral valve dynamic motion during diastole and systole. This model may be further developed to study mitral valve mechanics and disease to bring more insight of diagnosis, treatment, and prevention of patient valvular heart diseases.

This thesis investigates the usability and security of recognition-based graphical authentication schemes in which users provide simple images. These images can either be drawn on paper and scanned into the computer, or alternatively, they can be created with a computer paint program. In our first study, looked at how culture and gender might affect the types of images drawn. A large number of simple drawings were provided by Libyan, Scottish and Nigerian participants and then divided into categories. Our research found that many doodles (perhaps as many as 20%) contained clues about the participants’ own culture or gender. This figure could be reduced by providing simple guidelines on the types of drawings which should be avoided. Our second study continued this theme and asked the participants to try to guess the culture of the person who provided the image. This provided examples of easily guessable and harder to guess images. Our third study we built a system to automatically register simple images provided by users. This involved creating a website where the users could register their images and which they could later login to. Image analysis software was also written which corrected any mistakes the user might make when scanning in their images or using the Paint program. This research showed that it was possible to build an automatic registration system, and that users preferred using a paint tool rather than drawing on paper and then scanning in the drawing. This study also exposed poor security in some user habits, since many users kept their drawings or image files. This research represents one of the first studies of interference effects where users have to choose two different graphical passwords. Around half of the users provided very similar set of drawings. The last study conducted an experiment to find the best way of avoiding ‘shoulder surfing’ attacks to security when selecting simple images during the login stage. Pairs of participants played the parts of the observer and the user logging in. The most secure approaches were selecting using a single keystroke and selecting rows and columns with two key strokes.

This dissertation describes an authoring environment, called IWE, which allows a teacher to develop computer-based interactive worked examples without bespoke programming. The focus is on worked examples that involve transforming one representation into another using judgments not algorithms or rules. The worked examples created are all drawn from Computing Science; for example, transforming a requirements specification into an entity-relationship diagram. Teachers model the problem-solving process as a sequence of steps demonstrating how the problem is translated step-by-step into a solution, explaining the decision-making in each step. They can incorporate questions within the examples to increase student engagement and encourage students to do active thinking. Students interact with the transformation process at their own pace to obtain experience of problem-solving. Teachers are able to evolve the examples based on feedback from students and usage data from the system. A review of educational literature identified the best practice guidelines for designing and presenting effective worked examples for novices and faded worked examples for intermediate learners. These guidelines informed the essential requirements of IWE. A prototype authoring environment was designed, implemented and evaluated. Educational literature also recommends using worked examples combined with practice of problem solving. A field study was conducted applying these recommendations to evaluate the usability of IWE. Evaluations were carried out with teachers to assess their ability to create and modify interactive worked examples while the teaching of their courses was in progress. Evaluations were also carried out with students to assess the usability of IWE. The main conclusion of this research, based on analysis of the evaluations, is that the prototype of IWE is useable by both teachers and students. It allows teachers to create interactive worked examples following best practice and evolve existing examples on the basis of feedback. It allows students to use interactive worked examples independently following best practice. Finally, the dissertation identifies some possibilities for widening the scope of this research.

In this thesis, we consider the problem of long-term persistence in ecological and epidemiological systems. This is important in conservation biology for protecting species at risk of extinction and in epidemiology for reducing disease prevalence and working towards elimination. Understanding how to predict and control persistence is critical for these aims. In Chapter 2, we discuss existing ways of characterising persistence and their relationship with the modelling paradigms employed in ecology and epidemiology. We note that data are often limited to information on the state of particular patches or populations and are modelled using a metapopulation approach. In Chapter 3, we define persistence in relation to a pre-specified time horizon in stochastic single-species and two-species competition models, comparing results between discrete and continuous time simulations. We find that discrete and continuous time simulations can result in different persistence predictions, especially in the case of inter-specific competition. The study also serves to illustrate the shortcomings of defining persistence in relation to a specific time horizon. A more mathematically rigorous interpretation of persistence in stochastic models can be found by considering the quasi-stationary distribution (QSD) and the associated measure of mean time to extinction from quasi-stationarity. In Chapter 4, we investigate the contribution of individual patches to extinction times and metapopulation size, and provide predictors of patch value that can be calculated easily from readily available data. In Chapter 5, we focus directly on the QSD of heterogeneous systems. Through simulation, we investigate possible compressions of the QSD that could be used when standard numerical approaches fail due to high system dimensionality, and provide guidance on appropriate compression choices for different purposes. In Chapter 6, we consider deterministic models and investigate the effect of introducing additional patch states on the persistence threshold. We suggest a possible model that might be appropriate for making predictions that extend to stochastic systems. By considering a family of models as limiting cases of a more general model, we demonstrate a novel approach for deriving quantities of interest for linked models that should help guide modelling decisions. Finally, in Chapter 7, we draw out implications for conservation biology and disease control, as well as for future work on biological persistence.

This thesis investigates the use of the acoustic emission (AE) monitoring technique for use in identifying the damage mechanisms present in paper associated with its production process. The microscopic structure of paper consists of a random mesh of paper fibres connected by hydrogen bonds. This implies the existence of the two damage mechanisms of interest, the failure of a fibre/fibre bond and the failure of a fibre. The majority of this work focuses on the development of a novel hybrid mathematical model which couples the mechanics of the mass/spring model to the acoustic wave propagation model for use in generating the acoustic signal emitted by complex structures of paper fibres under strain. A discussion of the coupling method is presented and the model is then analysed using a simple plucked fibre as a test case with a comparison between the numerical and experimental results. The hybrid mathematical model is then used to simulate small fibre networks aimed at providing information on the acoustic response of each damage mechanism. To do this the mass/spring model must successfully simulate the response of the fibre structure when undergoing a fibre/fibre bond failure or a fibre failure. This can be achieved by dynamically manipulating the mass and spring elements of the fibre structure. The simulated AEs from the two damage mechanisms are then analysed using a Continuous Wavelet Transform (CWT) to provide a two dimensional time/frequency representation of the signal. From the CWT certain features of the AEs can be attributed to each damage mechanism and as such a criteria for the time and frequency properties of each damage mechanism can be formulated. This criterion provides the basis for identifying the damage mechanisms present in the experimental data. The final contribution of this thesis is the investigation of training an intelligent classifier which can dynamically identify the AEs from the two damage mechanisms. This is achieved by converting the time and frequency criteria for each damage mechanisms into a set of features for the training of a Self-Organising Map (SOM). The significant step in this analysis is the method for the extraction of the features from the CWT of the AE. This work successfully combines four different scientific areas, paper physics, acoustic emission technology, data analysis and computational modelling to provide an insight into the micro-mechanics of paper. The most significant contribution of this work is the development of the hybrid model which has the ability to generate the acoustic response of a paper fibre structure undergoing two different damage processes. This alone has provided a significant insight into the micro-mechanics of paper to allow for the identification of the two damage mechanisms when the AEs are analysed with the CWT. Other contributions include the method used for the extraction of relevant features from the CWT to enable the training of a SOM for identifying the type of damage mechanism the AE originated from.