Collaborative learning is known as an effective learning method and various different kinds of technologies have been developed to support and facilitate collaborative learning. Many of these technologies are used to support the functional activities of a group of learners by enabling students to communicate, share documents and materials, track the work of the group, or distribute and allocate tasks. One factor that influences the success of collaborative groups is the awareness that members have of each others' activities i.e. activity awareness (Gutwin et al., 2004). Limited attention has been paid to promoting activity awareness in the collaborative learning literature. The work that does exist has focused on enhancing activity awareness by capturing and sharing details of the activity (e.g. Ganoe et al., 2003; Carroll et al., 2003). In contrast, there are no technologies that focus on the learners’ attitudes and behaviours with regard to activity awareness without considering the functional aspects of the group's work. This PhD hypothesises that persuasive technologies can offer a novel way of promoting activity awareness by changing learners’ attitudes and behaviours and persuading them to be more aware of fellow group members’ activities. This approach to enhancing activity awareness was investigated by using a persuasive social actor to change the attitudes and behaviours of learners who were working on collaborative learning projects over extended periods of time. Four studies were conducted: a pilot study to explore collaborative learning groups, an exploratory study to understand collaboration and activity awareness, a follow-up study to study activity awareness in depth, and a main study where a persuasive social actor for activity awareness in collaborative learning groups was developed and tested. All of these studies focused on a specific collaborative learning setting, in which small numbers of students (3 to 5) worked together in collaborative groups to complete real learning projects over approximately 6 weeks. This thesis makes four contributions to the fields of HCI and collaborative learning. The main contribution is a novel approach to enhance activity awareness in collaborative learning groups by changing learners’ attitudes and behaviours using a persuasive technology i.e. a persuasive social actor. The second contribution is a new method to evaluate activity awareness in collaborative learning groups. The third contribution is insight into how the Persuasive Systems Design (PSD) model (Oinas-kukkonen & Harjumaa, 2009) can be used in the design and evaluation of a persuasive social actor. The fourth contribution is an analysis of how students collaborate in long-term collaborative learning projects in naturalistic settings.

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this thesis we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 11 experimental phenomena and show that it can provide an adequate account for 9, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSCTD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used.

Mobile user interfaces are becoming increasingly complex due to the expanding range of functionalities that they incorporate, which poses significant difficulties in software development. Formal methods are beneficial for highly complex software systems, as they enable the designed behaviour of a mobile user interface (UI) to be modelled and tested for accuracy before implementation. Indeed, assessing the compatibility between the software specification and user requirements and verifying the implementation in relation to the specification are essential procedures in the development process of any type of UI. To ensure that UIs meet users‘ requirements and competences, approaches that are based on interaction between humans and computers employ a variety of methods to address key issues. The development of underlying system functionality and UIs benefit from formal methods as well as from user-interface design specifications. Therefore, both approaches are incorporated into the software development process in this thesis. However, this integration is not an easy task due to the discrepancies between the two approaches. It also includes a method, which can be applied for both simple and complex UI applications. To overcome the issue of integrating both approaches, the thesis proposes a new formal model called the Formal Model of Mobile User Interface Design (FMMUID). This model is devised to characterise the composition of the UI design based on hierarchical structure and a set theory language. To determine its applicability and validity, the FMMUID is implemented in two real-world case studies: the quiz game iPlayCode and the social media application Social Communication (SC). A comparative analysis is undertaken between two case studies, where each case study has three existing applications with similar functionality in terms of structure and numbers of elements, functions and colours. Furthermore, the case studies are also assessed from a human viewpoint, which reveals that they possess better usability. The assessment supports the viability of the proposed model as a guiding tool for software development. The efficiency of the proposed model is confirmed by the result that the two case studies are less complex than the other UI applications in terms of hierarchical structure and numbers of elements, functions and colours, whilst also presenting acceptable usability in terms of the four examined dimensions: usefulness, information quality, interface quality, and overall satisfaction. Hence, the proposed model can facilitate the development process of mobile UI applications.

Centrifugal pumps play an important role in engineering applications since they are commonly used in industrial and residential systems, covering wide range of flow rates. Improving the performance of turbomachines such as the centrifugal pumps can be difficult to achieve, since the flow is turbulent with unsteady behaviour and cavitation. Cavitation is a complex phenomenon that is commonly considered as one of the main causes of deterioration in pump performance. Diagnosing cavitation and detecting its level of severity are essential for maintaining the pump’s reliability. Continuous condition monitoring of the pump is important to increase its operational life, decrease maintenance costs and hence, enhance the reliability of the pump. Early detection of cavitation can also improve the pump’s life expectancy by adopting various preventative actions. In this research, the first technique used for detecting cavitation is Computational Fluid Dynamics because it can provide suitable visualisation and reasonably accurate information, regarding the behaviour of fluid flow in the pump. In this work, both qualitative and quantitative analyses were carried out through a wide range of operating conditions and different geometrical configurations of a centrifugal pump under single-phase and cavitation conditions. Both, global and local flow field characteristics were investigated for better understanding. For qualitatively analysis, contours of static pressure and velocity magnitude under single-phase conditions and vapour volume fractions contour under cavitation conditions were adopted. On the other hand, the head and pressure variation in both time and frequency domains were analysed for qualitative analysis. The results showed that, as the pump rotational speed, number of impeller blades, and the outlet impeller diameter increase the head of the pump increases as well as the occurrence of cavitation. Based on the extensive numerical investigations for variety of operational and geometrical parameters, novel semi-empirical correlations under single-phase and cavitation conditions for the pump head and power coefficients were developed. Developments of aforementioned relations were carried out using multiple regression analysis technique. The second and third research areas consist of an extensive experimental analysis on the effects of operating conditions on the pump performance to predict cavitation using vibration and acoustic signature analyses. Detailed experimental investigations were carried out for the detection and diagnosis of cavitation, with the aid of sophisticated equipment and sensors. The condition monitoring was experimentally carried out in both, time and frequency domains analyses. Time domain method was applied to analyse the vibration and acoustic signals in time waveform analysis (TWFA). These signatures were analysed using different statistical parameters such as peak, root mean square (RMS), peak-to-peak and variance. In addition, transforming and analysing these signals in frequency domain was made by using Fast Fourier Transform technique. Analyses of these signals in frequency domain were also carried out using different statistical parameters such as mean and RMS features under wide various frequency ranges. The results revealed that using cavitation detection index (CDI) was a powerful technique, which can be used in both time and frequency domains for detecting cavitation and comparing the sensitivity of the vibration and acoustic techniques in estimating earlier stage of cavitation. Moreover, vibration technique was more sensitive to detect different levels of cavitation, especially inception of cavitation as compared to acoustic technique. This research has also found that the range of frequency between 0Hz to 15kHz was more sensitive to detect cavitation in the pump at the early stages. However, further investigation indicated that a frequency range of 1Hz to 2kHz was also effective on predicting the cavitation. Based on these findings, it can be suggested to use low range of frequency sensors (accelerometer and microphone) to capture the cavitation phenomenon instead of higher range of frequency, which are more expensive. In addition, it was found that all three techniques adopted in this investigation such as; CFD, vibration and acoustic techniques are well capable to analyse cavitation behaviours under different operating conditions. Moreover, it was observed that the numerical results and vibration technique can detect the inception of cavitation within a pump earlier than the acoustic technique. The results also revealed that, the combined use of these techniques (numerical and experimental) could increase the reliability. The combined method can be a considered to be a robust method, which can provide detailed information about the performance of the pump and detection/diagnosis of cavitation within a centrifugal pump. Hence, this will assist in prolonging the life of the pump and protect the system from emergency shutdown.

Condition monitoring (CM) of gear transmission has attracted extensive research in recent years. In particular, the detection and diagnosis of its faults in their early stages to minimise cost by maximising time available for planned maintenance and giving greater opportunity for avoiding a system breakdown. However, the diagnostic results obtained from monitored signals are often unsatisfactory because mainstream technologies using vibration response do not sufficiently account for the effect of friction and lubrication. To develop a more advanced and accurate diagnosis, this research has focused on investigating the nonlinearities of vibration generation and transmission with the viscoelastic properties of lubrication, to provide an in-depth understanding of vibration generating mechanisms and hence develop more effective signal processing methods for early detection and accurate diagnosis of gear incipient faults. A comprehensive dynamic model has been developed to study the dynamic responses of a multistage helical gear transmission system. It includes not only time-varying stiffness but also tooth friction forces based on an elastohydrodynamic lubrication (EHL) model. In addition, the progression of a light wear process is modelled by reducing stiffness function profile, in which the 2nd and 3rd harmonics of the meshing frequency (and their sidebands) show significant alteration that support fault diagnostic at early stages. Numerical and experimental results show that the friction and progressive wear induced vibration excitations will change slightly the amplitudes of the spectral peaks at both the mesh frequency and its sideband components at different orders, which provides theoretical supports for extracting reliable diagnostic signatures. As such changes in vibrations are extremely small and submerged in noise, it is clear that effective techniques for enhancing the signal-to-noise ratio, such as time synchronous averaging (TSA) and modulation signal bispectrum (MSB) are required to reveal such changes. MSB is preferred as it allows small amplitude sidebands to be accurately characterised in a nonlinear way without information loss and does not impose any addition demands regarding angular displacement measurement as does TSA. With the successful diagnosis of slight wear in helical gears, the research progressed to validate the capability of MSB based methods to diagnose four common gear faults relating to gear tribological conditions; lubrication shortfall, changes in lubrication viscosity, water in oil, and increased bearing clearances. The results show that MSB signatures allows accurate differentiation between these small changes, confirming the model and signal processing proposed in this thesis.

Extensible Markup Language (XML) has become a dominant technology for transferring data through the worldwide web. The XML labelling schemes play a key role in handling XML data efficiently and robustly. Thus, many labelling schemes have been proposed. However, these labelling schemes have limitations and shortcomings. Thus, the aim of this research was to investigate the existing XML labelling schemes and their limitations in order to address the issue of efficiency of XML query performance. This thesis investigated the existing labelling schemes and classified them into three categories based on certain criteria, in order to identify the limitations and challenges of these labelling schemes. Based on the outcomes of this investigation, this thesis proposed a state-of-theart labelling scheme, called clustering-based labelling scheme, to resolve or improve the key limitations such as the efficiency of the XML query processing, labelling XML nodes, and XML updates cost. This thesis argued that using certain existing labelling schemes to label nodes, and using the clustering-based techniques can improve query and labelling nodes efficiency. Theoretically, the proposed scheme is based on dividing the nodes of an XML document into clusters. Two existing labelling schemes, which are the Dewey and LLS labelling schemes, were selected for labelling these clusters and their nodes. Subsequently, the proposed scheme was designed and implemented. In addition, the Dewey and LLS labelling scheme were implemented for the purpose of evaluating the proposed scheme. Subsequently, four experiments were designed in order to test the proposed scheme against the Dewey and LLS labelling schemes. The results of these experiments suggest that the proposed scheme achieved better results than the Dewey and LLS schemes. Consequently, the research hypothesis was accepted overall with few exceptions, and the proposed scheme showed an improvement in the performance and all the targeted features and aspects.

Measurement of the velocity profile of water continuous multiphase flows is important because it can enable production optimisation and avoidance of unwanted flow assurance issues in both mining and oil and gas industries. However, accurate measurement of the velocity profile of the continuous phase in multiphase flows when they are time dependent or transient is still a challenge in such industries. Many available commercial multiphase flow meters, which are not able to directly measure the velocity profile of the continuous phase, use radioactive measurement techniques. Radioactive measurement techniques have many safety issues involving exposure to radiation, which is very harmful and is a known cause of cancer in humans. This thesis describes the development of a non-radioactive based flow meter, which relies on the measurement principle of a multi-electrode electromagnetic flow meter. This flow meter is capable of measuring the velocity profile of the conducting continuous phase in both single and multiphase flows tens (or potentially even hundreds) of times every second. The images of velocity profile of the conducting continuous phase in both single and multiphase flows were reconstructed using inductive flow tomography technique (IFT) from flow induced potential difference measurements obtained from a flush mounted array of electrodes on the wall of the flow meter. The designed and developed IFT system presented in this thesis consists of (i) a flow meter body, which has coils for generating magnetic fields and an array of 16-electrodes to enable sensing of flow induced potential differences; (ii) analogue electronic circuits for coil excitation and for signal conditioning of flow induced potential difference measurements and (iii) a computer unit for controlling system hardware and data acquisition and processing (which includes the mathematical algorithm for reconstructing the velocity profile of the continuous phase). Performance of the IFT system was tested in vertical single-phase ‘water only’ flows and in both vertical and inclined two-phase air-in-water and solids-in-water flows. The velocity profile measurements from the IFT system were in good agreement with reference measurements and were consistent with previous work cited in the literature. In addition, the IFT system was tested in both single-phase ‘water only’ and air-in-water transient vertical flows, for which the velocity profiles were measured with improved accuracy and temporal resolution.

One of the most significant drawbacks of modelling complex machine structures and drives using numerical models (discreet or hybrid Finite Element Analysis (FEAs)) is the difficulty of obtaining accurate modal parameters, such as stiffness and damping values of the mechanical parts as well as the accuracy of the models. Although the FEA is one of the numerical methods that are used to speed up the simulation/calculations, the dynamics of the machine tool/drives are expected to change under machining conditions, which makes numerical models inconvenient. Using Operational Modal Analysis (OMA), on-line parameters identification, can overcome the static state deviations and give more accurate results to represent the mechanical system. Thus, the project will introduce a new systematic procedure to carry out OMA on ball-screw drives. Firstly, the identification techniques are evaluated by means of simulated models and applied to identify the dynamics of the ball-screw drive using two different modelling approaches. Furthermore, this project tends to investigate the dynamics of the ball-screw driver using a novel measurement procedure to conduct OMA. The ball-screw driver of the machine is excited using Idle running to reform impulsive inertial sequences. The vibration measurements of the system were measured using a Laser Interferometer using displacement travels of the ball-screw drive. Also, the identified modal parameters of the system were compared to those captured by mounting accelerometers on the top level of the table structure using random, impulsive and cutting force excitations. The modal parameters identification was carried out by means of the improved subspace identification, which uses the auto and cross correlation of the segmented vibration signals as an input to the classical covariance subspace identification. The proposed methodology presented the ability to perform under high-sampling rates and noise suppressions. The identified results of the feed-drive system using Laser Interferometer were obtained using different feed-rates and mass weight loads to highlight the most sensitive vibration modes due to the machining process.

The process of converting natural language specifications into conceptual models requires detailed analysis of natural language text, and designers frequently make mistakes when undertaking this transformation manually. Although many approaches have been used to help designers translate natural language text into conceptual models, each approach has its limitations. One of the main limitations is the lack of a domain-independent ontology that can be used as a repository for entities and relationships, thus guiding the transition from natural language processing into a conceptual model. Such an ontology is not currently available because it would be very difficult and time consuming to produce. In this thesis, a semi-automated system for mapping natural language text into conceptual models is proposed. The model, which is called SACMES, combines a linguistic approach with an ontological approach and human intervention to achieve the task. The model learns from the natural language specifications that it processes, and stores the information that is learnt in a conceptual model ontology and a user history knowledge database. It then uses the stored information to improve performance and reduce the need for human intervention. The evaluation conducted on SACMES demonstrates that (1) designers’ creation of conceptual models is improved when using the system comparing with not using any system, and that (2) the performance of the system is improved by processing more natural language requirements, and thus, the need for human intervention has decreased. However, these advantages may be improved further through development of the learning and retrieval techniques used by the system.

In recent years, diesel engines with reduced emissions and low fuel consumption have been developed worldwide for the purpose of environmental protection and energy conservation. Turbochargers are playing an important role in these modern engines by providing power boost to the engine. A turbocharger comprises of three major parts i.e. the turbine stage, the bearing housing and the compressor stage. Turbocharger designers are continuously seeking for compact stage designs, while maintaining the stage performance. A turbocharger’s compressor stage comprises of various parts i.e. inlet, impeller, diffuser and volute. The diffuser is an important section of the turbocharger compressor stage that plays a key role in increasing the isentropic efficiency of the stage. The diffuser converts the kinetic energy imparted to the flow by the impeller, into static pressure rise, which inturn increases the isentropic efficiency of the stage. The shape of a diffuser is conventionally simple in design. Modifications to the diffuser geometry can lead to higher efficiencies and compact designs of the compressor stage. The present study focuses on the use of advanced computational techniques, such as Computational Fluid Dynamics (CFD), to analyse the effects of diffuser modifications on the local flow features, and the global performance parameters. A baseline diffuser configuration, consisting of a parallel wall diffuser, is numerically analysed to establish the accuracy of CFD based predictions. Various diffusers’ geometrical configurations have been analysed in the present study, both qualitatively and quantitatively. These geometrical configurations cover a wide range, such as diverging, tilting and curving of the diffuser walls. These parametric investigations aid to improve the compressor stage performance and make it more compact. The first aim of the study is to quantify the increase in the stage performance by diverging the straight wall vaneless diffuser passage. This is carried out by diverging the shroud wall (i.e. increasing the outlet-to-inlet width ratio) and varying the location of the divergence point on the shroud wall. The results obtained depict that the effect of increasing the diffuser’s outlet-to-inlet width ratio is dominant in comparison with the location of the wall divergence point. Moreover, increase in diffuser’s outlet-to-inlet width ratio increases the downstream area ratio of the diffuser, causing the flow to separate and creating flow recirculation near the hub wall. This creates restriction to the flow and causes air blockage. Furthermore, shifting the wall divergence point towards the outlet of the diffuser relocates the flow separation point closer to the diffuser exit. The second aim of this study is to analyse the effects of tilted diffuser walls on the flow variables within the compressor stage of the turbocharger. Tilting diffuser walls provides an increased streamwise length to the flow. Furthermore, divergence is applied to the diffuser hub wall in order to increase the outlet-to-inlet width ratio. This makes the turbocharger compressor stage compact in design, while maintaining the stage performance, which is the current requirement of the automotive sector. Design of Experiments, using Taguchi method, has been incorporated in this study to define the scope of the numerical work. The results obtained show that the diffuser with both titled and diverged walls together, performs optimally as compared to the other configurations considered. The third aim of this study is to use curved diffuser walls in order to make the design more compact. Divergence to the hub wall is also applied to enhance the performance of the compressor stage. Various configurations of curvilinear diffuser walls have been considered for numerical analysis. The local flow field analysis has been carried out, quantifying the effects of the geometrical parameters on the stage performance. The results depict that a curved diffuser model reduces the losses within the diffuser passage, but there is negligible effect on the stage efficiency. However, when the divergence is applied to the hub wall of the curved diffuser, there is significant increase in the stage efficiency. Based on these investigations, a turbocharger’s compressor stage can be designed for a compact design and optimal efficiency.