The purpose of this work was to investigate the relationship between a number of influential factors, including cognitive style and approach to learning, and students’ processing behaviour during their use of a particular Web-based resource for Electronics and Electrical Engineering undergraduates. This was achieved through the development of a learner profile for each student using Riding’s (1991) Revised Study Process Questionnaire (R-SPQ-2F). The quantitative component of the research was then set against a detailed analysis of students’ processing behaviour using verbal protocol data gathered through individual think-aloud sessions and post-intervention interviews. The results of the quantitative component of the research provided no compelling evidence to suggest that cognitive style was a factor that influenced student performance while using the resource or their perceptions of the package. There was however, some evidence to suggest that the package was more positively received by students who profiled as deep learners than their surface counterparts. The analysis of students’ processing behaviour from their verbal protocols highlighted a number of the resource’s shortcomings, which typically promoted a surface, goal-oriented approach to its content. It also identified problems with the design and structure of the resource, which at times had a deleterious effect on learning. The results also raised questions regarding the efficacy and use of psychometric inventories in this kind of research.

This thesis presents an investigation of a computational model of hierarchical visual behaviours within an active binocular robot vision architecture. The robot vision system is able to localise multiple instances of the same object class, while simultaneously maintaining vergence and directing its gaze to attend and recognise objects within cluttered, complex scenes. This is achieved by implementing all image analysis in an egocentric symbolic space without creating explicit pixel-space maps and without the need for calibration or other knowledge of the camera geometry. One of the important aspects of the active binocular vision paradigm requires that visual features in both camera eyes must be bound together in order to drive visual search to saccade, locate and recognise putative objects or salient locations in the robot's field of view. The system structure is based on the “attentional spotlight” metaphor of biological systems and a collection of abstract and reactive visual behaviours arranged in a hierarchical structure. Several studies have shown that the human brain represents and learns objects for recognition by snapshots of 2-dimensional views of the imaged scene that happens to contain the object of interest during active interaction (exploration) of the environment. Likewise, psychophysical findings specify that the primate’s visual cortex represents common everyday objects by a hierarchical structure of their parts or sub-features and, consequently, recognise by simple but imperfect 2D view object part approximations. This thesis incorporates the above observations into an active visual learning behaviour in the hierarchical active binocular robot vision architecture. By actively exploring the object viewing sphere (as higher mammals do), the robot vision system automatically synthesises and creates its own part-based object representation from multiple observations while a human teacher indicates the object and supplies a classification name. Its is proposed to adopt the computational concepts of a visual learning exploration mechanism that controls the accumulation of visual evidence and directs attention towards the spatial salient object parts. The behavioural structure of the binocular robot vision architecture is loosely modelled by a WHAT and WHERE visual streams. The WHERE stream maintains and binds spatial attention on the object part coordinates that egocentrically characterises the location of the object of interest and extracts spatio-temporal properties of feature coordinates and descriptors. The WHAT stream either determines the identity of an object or triggers a learning behaviour that stores view-invariant feature descriptions of the object part. Therefore, the robot vision is capable to perform a collection of different specific visual tasks such as vergence, detection, discrimination, recognition localisation and multiple same-instance identification. This classification of tasks enables the robot vision system to execute and fulfil specified high-level tasks, e.g. autonomous scene exploration and active object appearance learning.

This PhD examines the historical making and interpretation of West-German official labour statistics in the period 1950-1973: how did official statistics come to be inscribed in state and administrative attempts to intervene into the labour market with respect to (un-)employment? Rather than considering statistics as a resource for state action and scientific investigation, this thesis is concerned with statistics as a contested topic comprising different techniques and ideas, styles of reasoning, practices, technologies and institutional contexts. Drawing on archival material from the Ministry of Labour and Social Affairs, the Federal Labour Office, the Federal Statistical Office, the Organisation for Economic Corporation and Development (OECD), and other sources, the thesis examines debates over the abolition of the federal labour office’s labour statistics 1950–1963, and the establishment of a new statistical infrastructure in the following decade. In bridging work in economic and social history, and the history and geography of official statistics and technology, this thesis shows how debate on the employment files – generated in 1935 and reestablished in 1950 – as the basis of quarterly official statistics was centred on the question of which statistics for which polity. This involved different ‘statistical gazes’ at different scales among labour administrators, bureaucratic officials, and statisticians. In studying the scientific-administrative issues of how and where statistics were produced and made credible, the analysis shows how authoritarian conceptions inscribed onto the files gave way, first, to more economical conceptions of data capturing (i.e. representative samples) and, from the late 1960s, to a statistical infrastructure based on electronic data processing. In examining the different rationalities – statistical-technical and political – the thesis shows how transformations in labour statistics were affected by dynamics between: federal state space and locality; technological dreams of labour administrators and statistical requirements; mathematisation and mechanisation of the statistical discourse; trust and credibility; public critique and legitimacy.

The subject of this case study is the Vermont Agricultural Resilience in a Changing Climate initiative, a transdisciplinary research team at UVM that has maintained success in meeting research and outreach objectives despite collaborating in a way that does not follow any particular ideal-type transdisciplinary process. In following recent science and technology (STS) studies' accounts of cross-disciplinary collaboration, the hypothesis pursued is that the transdisciplinary study of messy or "wicked" problems like climate change brings forth an array of responses from researchers whose disciplinary backgrounds already position them to pursue their research differently, particularly when they involve outside stakeholders in a participatory action research agenda. When not addressed explicitly through the transdisciplinary research framework, these differences are likely to result in more subterranean or affective responses, such as ambivalence and equivocation, which may permeate the collaborative group process. Through a qualitative ethnographic approach, I show that transdisciplinary work is complex and situational, due to the topic itself in agricultural resilience and climate change, the affective nature of the collaborative process, the differences in disciplinary perspectives, the researchers' subjectivities, and the influence of outside actors in the initiative. I argue that transdisciplinary work must necessarily be challenging given the variety of heterogeneous forces at play, and that deeper attention to the situation elucidates underlying dynamics that are not addressed in the normal research process. This research contributes insights into the literature on transdisciplinary research on messy problems.

There is a growing interest towards self configuring/tuning automated general-purpose reusable heuristic approaches for combinatorial optimisation, such as, hyper-heuristics. Hyper-heuristics are search methodologies which explore the space of heuristics rather than the solutions to solve a broad range of hard computational problems without requiring any expert intervention. There are two common types of hyper-heuristics in the literature: selection and generation methodologies. This work focuses on the former type of hyper-heuristics. Almost all selection hyper-heuristics perform a single point based iterative search over the space of heuristics by selecting and applying a suitable heuristic to the solution in hand at each decision point. Then the newly generated solution is either accepted or rejected using an acceptance method. This improvement process is repeated starting from an initial solution until a set of termination criteria is satisfied. The number of studies on the design of hyper-heuristic methodologies has been rapidly increasing and currently, we already have a variety of approaches, each with their own strengths and weaknesses. It has been observed that different hyper-heuristics perform differently on a given subset of problem instances and more importantly, a hyper-heuristic performs differently as the set of low level heuristics vary. This thesis introduces a general "multi-stage" hyper-heuristic framework enabling the use and exploitation of multiple selection hyper-heuristics at different stages during the search process. The goal is designing an approach utilising multiple hyper-heuristics for a more effective and efficient overall performance when compared to the performance of each constituent selection hyper-heuristic. The level of generality that a hyper-heuristic can achieve has always been of interest to the hyper-heuristic researchers. Hence, a variety of multi-stage hyper-heuristics based on the framework are not only applied to the real-world combinatorial optimisation problems of high school timetabling, multi-mode resource-constrained multi-project scheduling and construction of magic squares, but also tested on the well known hyper-heuristic benchmark of CHeSC 2011. The empirical results show that the multi-stage hyper-heuristics designed based on the proposed framework are still inherently general, easy-to-implement, adaptive and reusable. They can be extremely effective solvers considering their success in the competitions of ITC 2011 and MISTA 2013. Moreover, a particular multi-stage hyper-heuristic outperformed the state-of-the-art selection hyper-heuristic from CHeSC 2011.

This thesis develops an ecological perspective devoted to the question of what, if anything, it means to speak of music ‘itself’. As such it seeks to enrich and further develop music-centred perspectives in the sociology of music. To this end, the thesis uses and develops a sociology of mediations designed to specify empirically the constituents of localized, emergent and performed configurations of “music” within the ‘classical’ music world. An ethnographically informed and practice-driven case study of viola and viola playing is used as a means to gain insight into the avant-garde of viola playing today and to follow the ways in which different protagonists constitute viola aesthetics. Considering the viola’s identity historically, in terms of both reproduction and change (specifically, the instrument’s shift from a marginal status to a position nearer the centre within ‘classical’ music), the study addresses instrument materiality and technologies, sound playing techniques, as well as, more globally, viola identities in relation to the instrument’s sonic features, repertoire, psycho-cultural and affective associations and meaning making in interpretation and performance. It is also shown how musicians deal with and ‘erase’ ‘limitations’ formerly attributed to the viola and make the instrument ‘work’ (through technological calibration in collaboration with instrument-makers as well as playing techniques) and thus correspond the requirements of contemporary music performance. Aiming to be a useful resource for violists, this thesis traces change but also identifies potential constraints produced by the past history of the viola upon the ways the instrument is seen, used and explored. The data for this study was collected through audio/video-recorded interviews with eight widely recognized highly-skilled violists, video-recorded performance and observations of viola lessons, and documentary analysis. This thesis highlights the importance of intermediate mediations that, situated in-between score and performance, affect how music comes to sound when played. It also outlines a grounded theory of the affordances of couplings made between players and instruments, so as to develop a performative idiom that considers representations, discourses and social construction, but also materiality, bodies and minds, internalization processes, practices. The thesis concludes by suggesting that a ‘strong’ cultural and musical sociology requires a relational and transdiciplinary approach and that this approach in turn helps to articulate an eclectic and hybrid sociology of imbrications, one that challenges intra-disciplinary divides.

Many systems in the world can be represented as models of complex networks and subsequently be analysed fruitfully. One fundamental property of the real-world networks is that they usually exhibit inhomogeneity in which the network tends to organise according to an underlying modular structure, commonly referred to as community structure or clustering. Analysing such communities in large networks can help people better understand the structural makeup of the networks. For example, it can be used in mobile ad-hoc and sensor networks to improve the energy consumption and communication tasks. Thus, community detection in networks has become an important research area within many application fields such as computer science, physical sciences, mathematics and biology. Driven by the recent emergence of big data, clustering of real-world networks using traditional methods and algorithms is almost impossible to be processed in a single machine. The existing methods are limited by their computational requirements and most of them cannot be directly parallelised. Furthermore, in many cases the data set is very big and does not fit into the main memory of a single machine, therefore needs to be distributed among several machines. The main topic of this thesis is about network community detection within these big data networks. More specifically, in this thesis, a novel approach, namely Decentralized Iterative Community Clustering Approach (DICCA) for clustering large and undirected networks is introduced. An important property of this approach is its ability to cluster the entire network without the global knowledge of the network topology. Moreover, an extension of the DICCA called Parallel Decentralized Iterative Community Clustering approach (PDICCA) is proposed for efficiently processing data distributed across several machines. PDICCA is based on MapReduce computing platform to work efficiently in distributed and parallel fashion. In addition, the real-world networks are usually noisy and imperfect with missing and false edges. These imperfections are often difficult to eliminate and highly affect the quality and accuracy of conventional methods used to find the community structure in the network. However, in real-world networks, node attribute information is also available in addition to topology information. Considering more than one source of information for community detection could produce meaningful clusters and improve the robustness of the network. Therefore, a pre-processing approach that considers attribute information, shared neighbours and connectivity information aspects of the network for community detection is presented in this thesis as part of my research. Finally, a set of real-world mobile phone usage data obtained from Cambridge Laboratories (Device Analyzer) has been analysed as an exploratory step for viability to apply the algorithms developed in this thesis. All the proposed approaches have been evaluated and verified for feasibility using real-world large data set. The evaluation results of these experimentations prove very promising for the type of large data networks considered.

The object of inquiry of this thesis is synthetic biology. In this thesis I ask what is this ‘thing’ that is synthetic biology (Latour, 2005) and what might it mean for synthetic biology to inhabit the world and to inhabit it well? Synthetic biology’s coming into being has been accompanied by a considerable amount of ‘hype’ and ‘hyperbole’ (Marris and Rose, 2012) – by what the philosopher Annemarie Mol (1999) would describe as a noisy ‘perspectivalism.’ My aim in this thesis is to contribute to the telling of different kinds of less-perspectival and less-technologically-deterministic stories about the development of this burgeoning approach to biological engineering. In drawing on a combination of empirical material from over 30 1-2 hour interviews with leading synthetic biologists and ethnographic materials generated from working alongside the UK’s Health and Safety Executive (the UK regulatory authority responsible for overseeing the development of synthetic biology), I aim to multiply outwards registers for understanding what synthetic biology is and what it might become. I highlight, for example, how synthetic biology is not simply a hubristic endeavour (Lewens, 2013) but is also about processes of learning and apprehension. What’s more, depending on how synthetic biology takes shape(s) in different practices, ‘time’ also becomes aleatory and freed from its modernist shackles (Serres, 2008). I use the lens of regulation as a means of addressing the question of what it might mean for synthetic biology to inhabit the world well. Synthetic biology’s regulatory provocations have been largely underexplored within STS and human geography literatures. The thesis is informed by and builds upon, theoretical notions of multiplicity (Mol, 2002) and of syncretisms (Law and Mol, 2013). The thesis contributes to a broader shift in social theory from critique towards compositionism and concludes by arguing for the development of a modest geography of novel biologies.

It is widely accepted that public policies have an important role in driving science, technology and innovation (STI) initiatives in order to achieve socio-economic and development objectives. Nevertheless, previous research reveals that developing countries still face difficulties in formulating policies to support and promote STI. A possible reason for this is found in the apparent lack of capabilities for policymaking. Capabilities are "a precondition for effective policy formulation in developing countries" (UNIDO, 2005, p.16). However, our knowledge and understanding of what these capabilities are, remain limited. In this thesis I examine the roles that capabilities play in formulating STI policies, the development of these capabilities and their evolution over the years. I group policy capabilities into organisational capabilities – which refers to policy processes and routines – and individual capabilities – which refers to the skills of individual policymakers (Nelson and Winter, 1982; Dosi et al., 2000; Feldman and Pentland, 2003). In order to address the identified gaps in literature, I use the Nigerian Federal Ministry of Science and Technology (FMST) – which in 2012 completed the formulation of a new national STI policy – as an illustrative case for the investigation of these issues. To achieve the aim of the thesis, I address three research questions: (1) What roles do capabilities play in formulating STI policies at FMST and why? (2) How did policy formulation capabilities originally emerge at FMST and why? (3) How have policy formulation capabilities evolved (i.e. changed over the years, from 1986 to 2012) at FMST and why? To collect data, I interviewed key staff at FMST and stakeholder organisations (who participated in the STI policy formulation exercise), in addition to secondary data from relevant policy documents. The data analysis was based on the “explanation-building” technique (Yin, 2009). The findings reveal the various roles that policy capabilities (processes, routines and skills) play in policy formulation; how and why policy capabilities were developed and their evolution over the years at FMST. The results address the aforementioned gaps. The findings should be useful to policymakers, decision-makers and practitioners involved in STI policymaking, research and capability management.

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