A vehicle active suspension system, in comparison with its counterparts, plays a crucial role in adequately guarantee the stability of the vehicle and improve the suspension performances. With a full understanding of the state of the art in vehicle control systems, this thesis identifies key issues in robust control design for active suspension systems with uncertainty, contributes to enhance the suspension performances via handling tradeoffs between ride comfort, road holding and suspension deflection. Priority of this thesis is to emphasize the contributions in handing actuator-related challenges and suspension model parameter uncertainty. The challenges in suspension actuators are identified as time-varying actuator delay and actuator faults. Time-varying delay and its effects in suspension actuators are targeted and analyzed. By removing the assumptions from the state of the art methods, state-feedback and output-feedback controller design methods are proposed to design less conservative state-feedback and output-feedback controller existence conditions. It overcomes the challenges brought by generalized timevarying actuator delay. On the other hand, a novel fault-tolerant controller design algorithm is developed for active suspension systems with uncertainty of actuator faults. A continuous-time homogeneous Markov process is presented for modeling the actuator failure process. The fault-tolerant H∞ controller is designed to guarantee asymptotic the stability, H∞ performance, and the constrained performance with existing possible actuator failures. It is evident that vehicle model parameter uncertainty is a vital factor affecting the performances of suspension control system. Consequently, this thesis presents two robust control solutions to overcome suspension control challenges with nonlinear constraints. A novel fuzzy control design algorithm is presented for active suspension systems with uncertainty. By using the sector nonlinearity method, Takagi-Sugeno (T-S) fuzzy systems are used to model the system. Based on Lyapunov stability theory, a new reliable fuzzy controller is designed to improve suspension performances. A novel adaptive sliding mode controller design approach is also developed for nonlinear uncertain vehicle active suspension systems. An adaptive sliding mode controller is designed to guarantee the stability and improve the suspension performances. In conclusion, novel control design algorithms are proposed for active suspension systems with uncertainty in order to guarantee and improve the suspension performance. Simulation results and comparison with the state of the art methods are provided to evaluate the effectiveness of the research contributions. The thesis shows insights into practical solutions to vehicle active suspension systems, it is expected that these algorithms will have significant potential in industrial applications and electric vehicles industry.

Inspired by Brian Eno's ambient music, which is persistent and supports different levels of engagement, this research explores ambient gameplay in computer, video and pervasive games. Through the creation of original games containing ambient gameplay and looking for ambient gameplay in existing commercial games, this research focuses on gameplay that supports a range of depths of player engagement. This research is not concerned with ambient intelligent environments or other technologies that might support ambience, but focusses on gameplay mechanisms. The definition of ambient music is used as a starting point for developing a tentative set of properties that enable ambient gameplay. A game design research methodology is initially used. Two very different research games, Ambient Quest (using pedometers) and Pirate Moods (using RFID, radio-frequency identification, technology) are analysed. The resulting qualitative ambient gameplay schema contains themes of persistence, discovery, engagement, invention, ambiguity and complexity. In order to confirm the wider applicability of this result a case study of an existing commercial game, Civilization IV, is undertaken. Ambient gameplay properties of engagement, complexity, abstraction, persistence and modelessness identified in Civilization IV, and other commercial games, are combined with the ambient gameplay schema to develop a definition of ambient gameplay. This definition is the basis for a set of investigative lenses (lenses of persistence, attention, locative simultaneity, modelessness, automation and abstraction) for identifying ambient gameplay. This research creates a deeper understanding of computer games and hence gives game designers new ways of developing richer gameplay and gives games researchers new ways of viewing and investigating games.

Unconstrained human hand motions consisting of grasp motion and inhand manipulation lead to a fundamental challenge that many recognition algorithms have to face, in both theoretical and practical development, mainly due to the complexity and dexterity of the human hand. The main contribution of this thesis is a novel fuzzy framework of three proposed recognition algorithms. This consists of extended Time Clustering (TC), Fuzzy Gaussian Mixture Model (FGMM) and Fuzzy Empirical Copula (FEC), using numerical values, Gaussian pattern and data dependency structure respectively in the context of optimal real-time human hand motion recognition. First of all, a fuzzy time-modeling approach, TC, is proposed based on fuzzy clustering and Takagi-Sugeno modeling with a numerical value as output. The extended TC is not only capable of learning repeated motions from the same subject but also can effectively model similar motions from various subjects. The recognition algorithm itself can identify the start point and end point of the testing motion. It is applicable to motion planning directly transfered from the recognition result. Secondly, FGMMis developed to effectively extract abstract Gaussian patterns to represent components of hand gestures with a fast convergence. The dissimilarity function in fuzzy C-means, which maintains the exponential relationship between membership and distance, is refined for FGMM with a degree of fuzziness in terms of the membership grades. Not only does it possess non-linearity but it also offers the characteristic of computationally inexpensive convergence. It is applicable to applications which have a small model storage space and require a method to generate the desired trajectory. Thirdly, FEC is proposed by integrating the fuzzy clustering by local approximation of memberships with Empirical Copula (EC). To save the computational cost, fuzzy clustering reduces the required sampling data and maintains the interrelations before data dependence structure estimation takes over. FEC utilizes the dependence structure among the finger joint angles to recognize the motion type. It is capable of effectively recognizing human handmotions for both single subject andmultiple subjects with a few training samples. It can be used in applications requiring high recognition rate and no desired trajectory with limited training samples. All the proposed algorithms have been evaluated on a wide range of scenarios of human hand recognition: a) datasets including 13 grasps and 10 in-hand manipulations; b) single subject and multiple subjects. c) varying training samples. The experimental results have demonstrated that all the proposed methods in the framework outperform Hidden Markov Model (HMM) and Gaussian Mixture Model (GMM) in terms of both effectiveness and efficiency criteria.

Enormous uncertainties in unconstrained human motions lead to a fundamental challenge that many recognising algorithms have to face in practice: efficient and correct motion recognition is a demanding task, especially when human kinematic motions are subject to variations of execution in the spatial and temporal domains, heavily overlap with each other,and are occluded. Due to the lack of a good solution to these problems, many existing methods tend to be either effective but computationally intensive or efficient but vulnerable to misclassification. This thesis presents a novel inference engine for recognising occluded 3D human motion assisted by the recognition context. First, uncertainties are wrapped into a fuzzy membership function via a novel method called Fuzzy Quantile Generation which employs metrics derived from the probabilistic quantile function. Then, time-dependent and context-aware rules are produced via a genetic programming to smooth the qualitative outputs represented by fuzzy membership functions. Finally, occlusion in motion recognition is taken care of by introducing new procedures for feature selection and feature reconstruction. Experimental results demonstrate the effectiveness of the proposed framework on motion capture data from real boxers in terms of fuzzy membership generation, context-aware rule generation, and motion occlusion. Future work might involve the extension of Fuzzy Quantile Generation in order to automate the choice of a probability distribution, the enhancement of temporal pattern recognition with probabilistic paradigms, the optimisation of the occlusion module, and the adaptation of the present framework to different application domains.

The derivation of margins for use in external beam radiotherapy involves a complex balance between ensuring adequate tumour dose coverage that will lead to cure of the cancer whilst sufficiently sparing the surrounding organs at risk (OARs). The treatment of cancer using ionising radiation is currently witnessing unprecedented levels of new treatment techniques and equipment being introduced. These new treatment strategies, with improved imaging during treatment, are aimed at improved radiation dose conformity to dynamic targets and better sparing of the healthy tissues. However, with the adoption of these new techniques for radiotherapy, the validity of the continued use of recommended statistical model based margin formulations to calculate the treatment margins is now being questioned more than ever before. To derive margins for use in treatment planning which address present shortcomings, this study utilised novel applications of fuzzy logic and neural network techniques to the PTV margin problem. As an extension of this work a new hybrid fuzzy network technique was also adopted for use in margin derivation, a novel application of this technique which required new rule formulations and rule base manipulations. The new margin models developed in this study utilised a novel combination of the radiotherapy errors and their radiobiological effects which was previously difficult to establish using mathematical methods. This was achieved using fuzzy rules and neural network input layers. An advantage of the neural network procedure was that fewer computational steps were needed to calculate the final result whereas the fuzzy based techniques required a significant number of iterative computational steps including the definition of the fuzzy rules and membership functions prior to computation of the final result. An advantage of the fuzzy techniques was their ability to use fewer data points to deduce the relationship between the output and input parameters. In contrast the neural network model requires a large amount of training data. The previously stated limitations of currently recommended statistical techniques were addressed by application of the fuzzy and neural network models. A major advantage of the computational intelligence methods from this study is that they allow the calculation of patient-specific margins. Radiotherapy planning currently relies on the use of ‘one size fits all’ class solutions for margins for each tumour site and with the large variability in patient physiology these margins may not be suitable for use in some cases. The models from this study can be applied to other treatment sites, including brain, lung and gastric tumours.

To the best of the author’s knowledge, this is one of the first times that a large quantity of flight data has been studied in order to improve safety. A two phase novelty detection approach to locating abnormalities in the descent phase of aircraft flight data is presented. It has the ability to model normal time series data by analysing snapshots at chosen heights in the descent, weight individual abnormalities and quantitatively assess the overall level of abnormality of a flight during the descent. The approach expands on a recommendation by the UK Air Accident Investigation Branch to the UK Civil Aviation Authority. The first phase identifies and quantifies abnormalities at certain heights in a flight. The second phase ranks all flights to identify the most abnormal; each phase using a one class classifier. For both the first and second phases, the Support Vector Machine (SVM), the Mixture of Gaussians and the K-means one class classifiers are compared. The method is tested using a dataset containing manually labelled abnormal flights. The results show that the SVM provides the best detection rates and that the approach identifies unseen abnormalities with a high rate of accuracy. Furthermore, the method outperforms the event based approach currently in use. The feature selection tool F-score is used to identify differences between the abnormal and normal datasets. It identifies the heights where the discrimination between the two sets is largest and the aircraft parameters most responsible for these variations.

The phenomenon of pervasive games is a relatively new and unexplored area of games research. These are games that, unlike card, computer, or board games, incorporate elements from outside the perceived boundaries of play, in order to blur the line between reality and fiction and make the game feel more ‘real’. This thesis investigates the player experience of pervasive games, using a novel approach that is informed by the methodology of Glaserian Grounded Theory (Glaser 1978; 1998) in order to clarify understanding and explore issues that players of pervasive games would be likely to encounter. Following a discussion of various themes such as player interpretation, creative play, ambiguity in games and the ‘magic circle of play’, and guided by the preparatory work of the researcher, SF0 (www.sf0.org) is identified as a particularly suitable example of a pervasive game to use for an in-depth study. 24 players of SF0 are interviewed about the gameplay process, and their responses are analysed using the methods implied by Grounded Theory. A theory evolves regarding their experiences, namely that SF0 is providing the means and motive to take part in everyday activities that they somehow could not, or might not, have done before. In particular, SF0 is helping players to be artistic, outgoing and wise. Informed by the methodology, no formal literature review is conducted prior to the main study, therefore the literature is mainly consulted after theory generation in order to more widely situate the results in the context of games literature. Real-world benefit, such as that promoted by ‘serious games’, appears to be emerging from the gameplay in SF0, despite SF0 not appearing to be marketed as a serious game. This unexpected outcome is discussed in terms of implicit rules (Salen & Zimmerman, 2004), player satisfaction, knowledge transfer, and emergence (Johnson, 2001). It is suggested that one explanation for this outcome is the positive attitude SF0 holds towards contradictions in implicit rules which occur from player-to-player. It is recommended that the future study of emergent benefit in games should not be limited to the games overtly labelled as serious games.

Shoulder dysfunction is common and accounts for around four million days of sick leave in the UK each year. Treatment approaches aim to reduce pain, and improve range of motion (ROM). However, patient adherence to therapeutic regimes is poor, partly due to pain avoidance behaviour and lack of engaging therapeutic exercises. Virtual rehabilitation is an area of healthcare which combines physical therapy with virtual reality (VR). It has been shown to facilitate patient engagement and reduce pain perception. Reaching and grasping tasks are well suited to VR applications, and there are a number of studies using VR to explore upper limb motion. However, current approaches for evaluating active shoulder rotation are problematic. A functional test known as Apley’s scratch test could potentially be adapted with magnetic motion tracking, to provide an objective proxy rotation measure to assess changes in ROM in a VR context. An empirical study demonstrated that active rotational movements of the shoulder could be successfully tracked in VR, and that there was evidence of pain suppression during the motion tasks. In addition, head tracking for patients with shoulder and neck pain, was addressed using a novel eye-hand tracking approach. In addition, observations of participants revealed aberrant motion patterns that could compromise rehabilitation outcomes. Despite providing depth cues in the VE itself, analysis suggested that a number of participants remained unsure of the spatial location of the target object which would lead to suboptimal movement behaviour. It was hypothesised that target object geometry may have a particular role in distance judgments, such that a simple icosahedron would provide richer cues with lower computational demand than commonly used spheres or detailed realistic modelled geometry. It was also proposed that providing a proximity cue using exaggerated brightness changes might improve the ability to locate and grasp the object in virtual space. Empirical studies demonstrated that the sphere had a significantly higher duration of time-to-target required in the terminal phase of reaching. Furthermore they demonstrated that a simple icosahedron was more effectively located in virtual space than the sphere object, and performed as well as a more computationally complex “realistic” model. The introduction of richer visual cues only in the terminal phase of reaching was ineffective as was the use of brightness as a proximity cue demonstrating that the use of richer geometry cues throughout was more influential. Nevertheless whilst target object geometry can facilitate spatial perception and influence reaching and grasping task performance, it was not associated with a reduction in arm elevation rigid system behaviour, suggesting other factors still warrant further investigation. This thesis demonstrates that the visual properties of the VE component of a VR system, and specifically the target objects within it, should be taken into consideration when designing spatial perception or reaching tasks in VR, especially within a rehabilitation context.

This thesis provides an analysis of youth television, digital content and Channel 4-as-public service broadcaster and has three primary aims. Firstly, the thesis aims to provide a series of "forgotten histories", offering a corrective to pre-existing narratives surrounding Channel 4, extensively utilising untapped resources (the Channel 4 Press Packs), along with a collection of digital archive materials. This is done in order to re-evaluate the broadcaster's purpose, strategies and programming at a vital moment in its history, using these neglected moments to interrogate Channel 4's current relationship with youth audiences and content. Secondly, the thesis aims to reframe Channel 4's history through the lens of its youth provision, as the targeting of this demographic was seen as the "least worst" way of balancing its role as public service publisher and commercial corporation. This choice is discussed regarding the long-term impact upon Channel 4's identity and strategy, whilst offering a nuanced conceptualisation of what constitutes “youth” and how Channel 4 addressed it. Lastly, I aim to introduce a series of original conceptual frameworks in order to illustrate Channel 4's longstanding lack of consistency in terms of commissioning, promotion and organisational strategy, culminating in the use of the term spray. Spray encapsulates both the post-broadcast fluidity within British broadcasting, as well as Channel 4's chaotic and transitory strategic choices as it grapples with its historical identity and purpose. This thesis highlights the contradictory nature of Channel 4, with its opposing remit obligations of public service innovation and commercial viability, with the disparity between its promotional rhetoric and the production reality being pronounced. Through discussion of critically ignored content and programming strands, “forgotten histories” are produced in order to understand contemporary broadcasting, whilst extrapolating its future direction. The thesis also articulates the uneven and variable impact of new media consumption practices, promotional strategies and technological innovation upon both Channel 4 and its current (and future) audiences through the deployment of original conceptual frameworks and extensive analysis of Channel 4's multiplatform/digital policy.

Virtual Environments have demonstrated effectiveness for social task training such as medical training (Anolli, Vescovo, Agliati, Mantovani, & Zurloni, 2006). These types of Virtual Environments have used emotional animated characters. Even though emotions have a strong influence on human-human interactions (Gratch, Mao, & Marsella, 2006), typical system evaluation does not assess whether human and animated emotional displays are perceived similarly by observers. Moreover, the Uncanny Valley, which is a drop in believability as characters become more realistic, threatens the assumption that emotions displayed by an animated character and a human would be interpreted similarly. Thus, it is not known how appropriate the perception to a realistic emotional animated character is. This issue is especially important for social task training which require animated characters to be perceived as social and emotional partners so that trainees would be confronted with situations comparable to real life ones. Using an approach similar to the one proposed by Nass & Moon (2000) in their work on the Media Equation, this thesis investigates how emotional body language displayed by animated characters is interpreted. A psychological experiment was conducted to investigate if emotional body language would be an appropriate way for animated characters to display emotion. This was done by comparing the interpretation of emotional body language displayed by animated characters with that by real actors. The results showed that animated body language can be accurately interpreted. However, the videos of the actor were found to be more emotional, more believable and more natural than the animated characters, whilst displaying the same emotional body language. Moreover, there was a significant difference in the number of correctly interpreted negative emotions displayed. Although, there was not a difference for positive emotions. This could be due to the physical appearance of the animated character or to the loss of micro-gestures inherent to Motion Capture technology. Thus, a second comparative study was conducted to investigate the potential causes for this drop in believability and recognition. It investigated the effect of changing the level of physical realism of the animation as well as deteriorating the quality of the emotional body language itself. Whilst no effect was found regarding the deterioration of the emotional body language, the results show that the videos of the Actor were found to be more emotional, more believable and more natural than the two animated characters. These findings have strong implications for the use of Virtual Environments for social task training.