The Web has become an ubiquitous environment for human interaction, communication, and data sharing. As a result, large amounts of data are produced. This data can be utilised by building predictive models of user behaviour in order to support business decisions. However, the fast pace of modern businesses is creating the pressure on industry to provide faster and better decisions. This thesis addresses this challenge by proposing a novel methodology for an effcient prediction of user behaviour. The problems concerned are: (i) modelling user behaviour on the Web, (ii) choosing and extracting features from data generated by user behaviour, and (iii) choosing a Machine Learning (ML) set-up for an effcient prediction. First, a novel Time-Varying Attributed Graph (TVAG) is introduced and then a TVAG-based model for modelling user behaviour on the Web is proposed. TVAGs capture temporal properties of user behaviour by their time varying component of features of the graph nodes and edges. Second, the proposed model allows to extract features for further ML predictions. However, extracting the features and building the model may be unacceptably hard and long process. Thus, a guideline for an effcient feature extraction from the TVAG-based model is proposed. Third, a method for choosing a ML set-up to build an accurate and fast predictive model is proposed and evaluated. Finally, a deep learning architecture for predicting user behaviour on the Web is proposed and evaluated. To sum up, the main contribution to knowledge of this work is in developing the methodology for fast and effcient predictions of user behaviour on the Web. The methodology is evaluated on datasets from a few Web platforms, namely Stack Exchange, Twitter, and Facebook.

In our research context, sustainable procurement can be seen as a process to reduce damage to the environment by integrating certain aspects into making procurement decisions, such as value for money throughout the whole life cycle and being of benefit to society and the economy. This research has found more than one way of interpreting the ‘sustainable system’, for example, ‘green-friendly’ versus remaining effective in the long term. Sustainable procurement requires specific information to support the procurement process. The study reported in this thesis aimed to investigate the type of information needed in order for organisations to make correct sustainable procurement decisions. From these findings, information architecture for sustainable procurement in UK universities has been derived. While the initial focus has been on the information needed to make informed decisions in purchasing sustainable information technology (IT) equipment, it is believed that the framework would also be more widely applicable to other types of purchases. To ensure that these findings would support the university aspiration in terms of sustainability practices, a goal-context modelling technique called VMOST/B-SCP was chosen to analyse the sustainable procurement strategy in order to evaluate the alignment of IT strategy and its business strategy. A goal-context model using VMOST/B-SCP was produced to evaluate the procurement strategy, with this validated by procurement staff. This research helps to improve the way that goals and context are identified by integrating another technique, namely, social network analysis (SNA) to produce actor network diagrams. The VMOST/B-SCP technique is transferrable to the mapping of action strategies. The findings from goal-context modelling show that a goal-context model is not static: it changes as external circumstances and organisational priorities change. Most changes to the strategy occurred where external entities on which the change programme depended did not act as planned. The actor networks produced in our version of VMOST/B-SCP can be used to identify such risks. This research was pioneering in its use of VMOST/B-SCP in examining a business change while it was actually taking place rather than after it had been completed (and thus needed to accommodate changes in objectives and strategies). In addition, the research analysed a system with some IT support but where human-operated procedures predominated. The original B-SCP framework used Jackson’s problem frames which focus on possible software components: in our scenario, SNA-inspired actor diagrams were found to be more appropriate.

Unmanned Ground Vehicles (UGVs) are becoming more widespread in their deployment. Advances in technology have improved not only their reliability but also their ability to perform complex tasks. UGVs are particularly attractive for operations that are considered unsuitable for human operatives. These include dangerous operations such as explosive ordnance disarmament, as well as situations where human access is limited including planetary exploration or search and rescue missions involving physically small spaces. As technology advances, UGVs are gaining increased capabilities and consummate increased complexity, allowing them to participate in increasingly wide range of scenarios. UGVs have limited power reserves that can restrict a UGV’s mission duration and also the range of capabilities that it can deploy. As UGVs tend towards increased capabilities and complexity, extra burden is placed on the already stretched power resources. Electric drives and an increasing array of processors, sensors and effectors, all need sufficient power to operate. Accurate prediction of mission power requirements is therefore of utmost importance, especially in safety critical scenarios where the UGV must complete an atomic task or risk the creation of an unsafe environment due to failure caused by depleted power. Live energy prediction for vehicles that traverse typical road surfaces is a wellresearched topic. However, this is not sufficient for modern UGVs as they are required to traverse a wide variety of terrains that may change considerably with prevailing environmental conditions. This thesis addresses the gap by presenting a novel approach to both off and on-line energy prediction that considers the effects of weather conditions on a wide variety of terrains. The prediction is based upon nonlinear polynomial regression using live sensor data to improve upon the accuracy provided by current methods. The new approach is evaluated and compared to existing algorithms using a custom ‘UGV mission power’ simulation tool. The tool allows the user to test the accuracy of various mission energy prediction algorithms over a specified mission routes that include a variety of terrains and prevailing weather conditions. A series of experiments that test and record the ‘real world’ power use of a typical small electric drive UGV are also performed. The tests are conducted for a variety of terrains and weather conditions and the empirical results are used to validate the results of the simulation tool. The new algorithm showed a significant improvement compared with current methods, which will allow for UGVs deployed in real world scenarios where they must contend with a variety of terrains and changeable weather conditions to make accurate energy use predictions. This enables more capabilities to be deployed with a known impact on remaining mission power requirement, more efficient mission durations through avoiding the need to maintain excessive estimated power reserves and increased safety through reduced risk of aborting atomic operations in safety critical scenarios. As supplementary contribution, this work created a power resource usage and prediction test bed UGV and resulting data-sets as well as a novel simulation tool for UGV mission energy prediction. The tool implements a UGV model with accurate power use characteristics, confirmed by an empirical test series. The tool can be used to test a wide variety of scenarios and power prediction algorithms and could be used for the development of further mission energy prediction technology or be used as a mission energy planning tool.

This thesis aimed to understand the relationship between the Apple brand and Apple consumers. It presents an historical semiotic analysis of a selection of the Apple brand from 1978 to 2009 and in-depth interviews with Apple consumers. The interviews were then analysed thematically, looking at the ways participants employed Apple in the construction of identity. The thesis extends theoretical critical approaches to branding with the inclusion of participant interviews. Approaches to branding consider the role of consumers in brand production and ownership, but this thesis moves focus beyond abstraction to interrogate how much of consumer participation is predetermined by the brand. This was achieved by actually examining the ways in which brand consumers articulate the brand. In doing so findings showed that Apple consumers distinguish themselves from non-Apple consumers, but significantly they made a second distinction. For the first distinction, Apple consumers articulated emotional investment, superior aesthetic taste, and feelings of being part of an exclusive community. The second distinction is an articulation of uniqueness within the Apple community. This is achieved through creating a sense of critical distance from consumption via individual lifestyle and taste.

This thesis explores and develops the potential of interactive television (iTV) technology for language learning. Through a modified form of the socio-cognitive engineering approach (Sharpies et al., 2002a), a range of learner centred design activities were carried out and a system developed to provide cross platform support, blending iTV and mobile phones, for adult language learners.

The research reported in this thesis investigates preschoolers‟ interactions with interactive television applications. The study involved the development of an electronic programme guide prototype and the empirical evaluation thereof. There were three main aims. The first aim was to analyse children‟s interactions and illustrate them in a framework to further understanding of the way preschoolers interact with the television. The second aim was to contribute design principles for preschool interactive television and the third aim was to refine methods and add to the knowledge of design and evaluation techniques involving young children.

The research reported in this thesis explores issues of information design for mobile devices, in particular those relating to selection and presentation of on-screen information and interactive functionality for users of mobile phones. The example domain is that of mobile tour guides for tourists, local people, students and families. Central to the research is the issue of multimodality, particularly the graphic and interaction design issues involved in viewing video, in combination with other media, on a mobile device, in an outdoor context. The study produced three main results: 1. An analytical framework for user-experience concerns in cultural heritage settings, 2. Design recommendations for outdoor mobile multimedia guides and 4. Refinements in methods for collecting and analysing data from fieldwork with visitors in cultural heritage settings. Those results were formulated for the use of mobile guide designers. The methodology used to inform and structure the work was Design Research, involving literature review and empirical work, including user trials of a prototype tourist guide developed in the project. The literature review covered areas of tourism, multimedia design, mobile HCI and existing mobile guides. Outdoor fieldwork exercises were carried out with three different cultural information sources - human tour guide, paper based guide and mobile guide app - in order to identify any problems that visitors might have and to gather requirements for the development of a mobile cultural guide. Qualitative analysis was applied to analyse the video observations and questionnaires completed during the tours. Requirements were grouped and analysed to give substantial information for a conceptual design. Personas and scenarios were created based on real participants and situations that occurred on the tours. A mobile guide prototype was developed and evaluated in the field with visitors. Qualitative analysis and descriptive statistics were used to analyse the data. Visitors were asked about their preferences among various multimedia design elements and answered a questionnaire on their experience. The elements that affect the user experience with outdoor mobile guides were categorised and organised into a framework. It became apparent that users' experience of technology (in this case the mobile tourist guide) and environment are affected by context, content and look and feel elements. This framework of user experience generated a design toolkit with a collection of recommendations for designers of such systems. The recommendations are described in context of usage and have a rating system with strength of evidence and confidence based on how often they appeared in the field works and solutions tested.

Spider diagrams are a recently developed visual logic that make statements about relationships between sets, their members and their cardinalities. By contrast, the study of regular languages is one of the oldest active branches of computer science research. The work in this thesis examines the previously unstudied relationship between spider diagrams and regular languages. In this thesis, the existing spider diagram logic and the underlying semantic theory is extended to allow direct comparison of spider diagrams and star-free regular languages. Thus it is established that each spider diagram defines a commutative star-free regular language. Moreover, we establish that every com- mutative star-free regular language is definable by a spider diagram. From the study of relationships between spider diagrams and commutative star-free regular languages, an extension of spider diagrams is provided. This logic, called spider diagrams of order, increases the expressiveness of spider di- agrams such that the language of every spider diagram of order is star-free and regular, but not-necessarily commutative. Further results concerning the expres- sive power of spider diagrams of order are gained through the use of a normal form for the diagrams. Sound reasoning rules which take a spider diagram of order and produce a semantically equivalent diagram in the normal form are pro- vided. A proof that spider diagrams of order define precisely the star-free regular languages is subsequently presented. Further insight into the structure and use of spider diagrams of order is demonstrated by restricting the syntax of the logic. Specifically, we remove spiders from spider diagrams of order. We compare the expressiveness of this restricted fragment of spider diagrams of order with the unrestricted logic.

A spark ignition (SI) engine operating with a lean burn has the potential for higher thermal efficiency, and lower nitrogen oxide emissions than that of stoichiometric operation. However, a lean or highly diluted mixture leads to poor combustion stability impacting detrimentally upon engine performance. An experimental investigation was carried out, on a 4-valve single cylinder gasoline engine with a split intake tract and two identical production port-fuel injectors installed, allowing independent fuel delivery to each intake valve. The main objective of the study was to extend the limit of lean combustion through the introduction of charge stratification. Novel port fuel injection strategies such as, dual split injection, multiple injections and phased injection, were developed to achieve this goal. In parallel, a model of the engine was developed in the Ricardo WAVE software. The model was used to calculate parameters such as in-cylinder residual gas, for different test points. Combustion stability was improved for the engine conditions tested. At 1000 rpm and 1.0 bar gross indicated mean effective pressure (GIMEP), the lean combustion limit was extended from a 14:1 air-to-fuel ratio (AFR) to 17.5:1. At 1500 rpm and 1.5 bar GIMEP the lean combustion limit was extended from 17.5:1 to approximately 21:1 AFR. Finally for 1800 rpm and 1.8 bar GIMEP, lean combustion was improved from 21: 1 AFR to 22: 1 An experimental spark plug, with an infrared detector, was used to measure the variation in fuel distribution at the spark plug gap. It showed that the different fuel injection strategies generated different levels of fuel concentration. It was identified that injections in a single port created fuel stratification in the spark plug area but were more prone to cycle to cycle variations in fuel concentration. These variations did not correlate with combustion stability or flame speed propagation at the speeds and loads tested. The most important parameter to influence the flame propagation speed was found to be the variation in local lambda with crank angle just after the ignition timing. It was shown that the fastest flame propagation speeds did not necessarily result in the lowest CoV in GIMEP. Finally the fuel injection strategies were investigated for highly dilute conditions, achieved by means of internal residual gas trapping, with the aim of promoting (spark-assisted) compression ignition combustion conditions.

This thesis analyses the structure of natural language queries to document repositories, with the aim of finding better methods for information retrieval. The exponential increase of information on the Web and in other large document repositories during recent decades motivates research on facilitating the process of finding relevant information to meet end users' information needs. A shared problem among several related research areas, such as information retrieval, text summarisation and question answering, is to derive concise textual expressions to describe what a document is about, to function as the bridge between queries and the document content. In current approaches, such textual expressions are typically generated by shallow features, for example, by simply selecting a few most-frequently- occurring key words. However, such approaches are inadequate to generate expressions that truly resemble user queries. The study of what a document is about is closely related to the widely discussed notion of topic, which is defined in many different ways in theoretical linguistics as well as in practical natural language processing research. We compare these different definitions and analyse how they differ from user queries. The main function of a query is that it defines which facts are relevant in some underlying knowledge base. We show that, to serve this purpose, queries are typically formulated by first (a) specifying a focused entity and then (b) defining a perspective from which the entity is approached. For example, in the query 'history of Britain', 'Britain' is the focused entity and 'history' is the perspective. Existing theories of topic often focus on (a) and leave out (b). We develop a theory of extended topic to formalise this distinction. We demonstrate the distinction in experiments with real life topic expressions, such as WH-questions and phrases describing plans of academic papers. The theory of extended topic could be applied to help various application areas, including knowledge organisation and generating titles, etc. We focus on applying the theory to the problem of information retrieval from a document repository. Currently typical information retrieval systems retrieve relevant documents to a query by counting numbers of key word matches between a document and the query. This approach is better suited to retrieving the focused entities than the perspectives. We aim to improve the performance of information retrieval by providing better support for perspectives. To do so, we further subdivide the perspectives into different types and present different approaches to addressing each type. We illustrate our approaches with three example perspectives: 'cause', 'procedure' and 'biography'. Experiments on retrieving causal, procedural and biographical questions achieve better results than the traditional key-word-matching-based approach.