The present study was undertaken to investigate issues concerned with the endurance to muscular loads created by the holding of static postures, without the presence of any other form of muscular effort. Its main aim was to explore the possibilities for the development of models which are expected to account for the capacity to endure such kind of exertion. Upright standing postures, with both arms abducted, were held by young male and female subjects (age 18-24 yr.) for as long as they could, until sensations of physical discomfort, rated on a scale with marks between 0 and 10 (Borg, 1982), became unbearable and forced them to abandon the posture. The study was constituted by two main experimental stages. In the first one, a posture as described above, with arms abducted at 60°, was used to submit to the test a model developed in 1985 by N. P. Milner (Milner's model). Although this model was originally proposed as a means to predict the remaining proportion of the maximum endurance (or 'recovery') left to the subject after a single sequence of work and rest, where work consisted of the holding of a stooped posture, its author affirmed it could be applied to any posture. The results of the testing, performed on six female subjects, demonstrated that Milner's model cannot predict with reasonable accuracy the 'recovery' for the upright standing posture with abduction of both arms. Apparently, the assumptions made by Milner concerning the relationships between the endurance capacity and the length of work and rest in a stooped posture did not apply to the test posture. The second experimental stage had three aims. The first was to test the repeatability of the endurance to standing postures with abduction of both arms. The maximum holding time for postures with arms abducted at 30°, 60° and 90° was measured on three occasions on a sample of five male and five female subjects. The maximum holding time for each of the three postures exhibited a wide variability between subjects, but when compared between the repeated measurements, the average value for the whole sample did not exhibit a significant difference. Also, male subjects had, on average, longer holding times than females, but there was a substantial overlap of the individual values. The second aim was to investigate the pattern of growth of the discomfort ratings over the length of the maximum holding time. This was found to be of a very strong linear nature, evident in all three postures studied and very similar for men and women. The strength and consistency of this relationship suggest that it may be used as a model to predict either the endurance capacity in function of the rate of growth of discomfort ratings, or the degree of discomfort that a certain length of holding will provoke. The third aim was to establish whether pure postural loads will provoke changes in the myoelectric activity which indicate the presence of heavy localised muscular fatigue. Mean power frequency (MPF) and RMS amplitude of the EMG signal were monitored throughout the 90 trials of posture holding. Significant changes were evident, with MPF decreasing and RMS amplitude increasing in most of the trials. This means that the posture, even at the lowest angle did provoke muscular fatigue. Another finding, rarely documented, was the presence of electromyographic changes that went in the reversed direction, i. e., MPF increased whilst RMS amplitude decreased. Finally, no well-defined pattern could be established for the time course of those changes or for their relationship with the discomfort ratings.

This study explores the usage of linear programming (LP) as a tool to optimise the parameters of time series forecasting models. LP is the most well-known tool in the field of operational research and it has been used for a wide range of optimisation problems. Nonetheless, there are very few applications in forecasting and all of them are limited to causal modelling. The rationale behind this study is that time series forecasting problems can be treated as optimisation problems, where the objective is to minimise the forecasting error. The research topic is very interesting from a theoretical and mathematical prospective. LP is a very strong tool but simple to use; hence, an LP-based approach will give to forecasters the opportunity to do accurate forecasts quickly and easily. In addition, the flexibility of LP can help analysts to deal with situations that other methods cannot deal with. The study consists of five parts where the parameters of forecasting models are estimated by using LP to minimise one or more accuracy (error) indices (sum of absolute deviations – SAD, sum of absolute percentage errors – SAPE, maximum absolute deviation – MaxAD, absolute differences between deviations – ADBD and absolute differences between percentage deviations – ADBPD). In order to test the accuracy of the approaches two samples of series from the M3 competition are used and the results are compared with traditional techniques that are found in the literature. In the first part simple LP is used to estimate the parameters of autoregressive based forecasting models by minimising one error index and they are compared with the method of the ordinary least squares (OLS minimises the sum of squared errors, SSE). The experiments show that the decision maker has to choose the best optimisation objective according to the characteristic of the series. In the second part, goal programming (GP) formulations are applied to similar models by minimising a combination of two accuracy indices. The experiments show that goal programming improves the performance of the single objective approaches. In the third part, several constraints to the initial simple LP and GP formulations are added to improve their performance on series with high randomness and their accuracy is compared with techniques that perform well on these series. The additional constraints improve the results and outperform all the other techniques. In the fourth part, simple LP and GP are used to combine forecasts. Eight simple individual techniques are combined and LP is compared with five traditional combination methods. The LP combinations outperform the other methods according to several performance indices. Finally, LP is used to estimate the parameters of autoregressive based models with optimisation objectives to minimise forecasting cost and it is compared them with the OLS. The experiments show that LP approaches perform better in terms of cost. The research shows that LP is a very useful tool that can be used to make accurate time series forecasts, which can outperform the traditional approaches that are found in forecasting literature and in practise.

Manufacturing companies must invest in new technologies and processes to succeed in a rapidly changing global environment. Managers have the difficulty of justifying capital investment in adopting new, state-of-the-art technology. Technology investment accounts for a large part of capital spending and is a key form of improving competitive advantage. Typical approaches focus on the expected return of investment and financial reward gained from the implementation of such equipment. With an increasingly dynamic market environment and global economic model, forecasting of financial payback can be argued to become increasingly less accurate. Subsequently, less quantifiable factors are becoming increasingly important. For example, the alignment of a technology with an organisations objective to fulfil future potential and gain competitive advantage is becoming as crucial as economic evaluation. In addition, the impact on human operators and skill level required must be considered. This research was motivated by the lack of decision methodologies that understand why a technology is more successful within an environment rather than re-examining the underlying performance attributes of a technology. The aim is to create a common approach where both experts and non-experts can use historical decision information to support the evaluation and selection of an optimal manufacturing technology. This form of approach is based on the logic in which a decision maker would irrationally recall previous decisions to identify relationships with new problem cases. The work investigates data mining and machine learning techniques to discover the underlying influences to improve technology selection under a set of dynamic factors. The approach initially discovers the practices to which an expert would conduct the selection of a manufacturing technology within industry. A defined understanding of the problem and techniques was subsequently concluded. This led to an understanding of the structure by which historical decision information is recalled by an expert to support new selection problems. The key attributes in the representation of a case were apparent and a form of characterising tangible and intangible variables was justified. This led to the development of a novel, experience-based manufacturing technology selection framework using fuzzy-decision-trees. The methodology is an iterative approach of learning from previously implemented technology cases. Rules and underlying knowledge of the relationships in past cases predicts the outcome of new decision problems. The link of information from a multitude of historical cases may identify those technologies with technical characteristics that perform optimally for projects with unique requirements. This also indicates the likeliness of technologies performing successfully based on the project requirements. Historical decision cases are represented through original project objectives, technical performance attributes of the chosen technology and judged project performance. The framework was shown to provide a comprehensive foundation for decision support that reduces the uncertainty and subjective influence within the selection process. The model was developed with industrial guidance to represent the actions of a manufacturing expert. The performance of the tool was measured by industrial experts. The approach was found to represent well the decision logic of a human expert based on their developed experience through cases. The application to an industrial decision case study demonstrated encouraging results and use by decision makers feasible. The model reduces the subjectivity in the process by using case information that is formed from multiple experts of a prior decision case. The model is applied in a shorter time period than existing practices and the ranking of potential solutions is well aligned to the understanding of a decision maker. To summarise, this research highlights the importance of focusing on less quantifiable factors and the performance of a technology to a specific problem/environment. The arrangement of case information thus represents the experience an expert would acquire and recall as part of the decision process.

Intelligent virtual characters are becoming increasingly popular in en­ tertainment, educational and simulation software. A virtual charac­ ter is the creation or re-creation of a human being in an image, using computer-generated imagery. It must act and react in the environment, drawing on the disciplines of automated reasoning and planning. Creating characters with human-like behaviours that respond interactively to a real person in a video, is still a serious challenge. There are several major reasons for this. First, human motion is very complex, which makes it particularly difficult to simulate. Second, the human form is also not straightforward to design due to the large number of degrees of freedom of the motion. Third, creating novel contextual movements for virtual characters in real time is a new research area.

The H.264/MPEG-4 Advanced Video Coding (AVC) standard is a high efficiency and flexible video coding standard compared to previous standards. The high efficiency is achieved by utilizing a comprehensive full search motion estimation method. Although the H.264 standard improves the visual quality at low bitrates, it enormously increases the computational complexity. The research described in this thesis focuses on optimization of the computational complexity on H.264 scalable and multiview video coding. Nowadays, video application areas range from multimedia messaging and mobile to high definition television, and they use different type of transmission systems. The Scalable Video Coding (SVC) extension of the H.264/AVC standard is able to scale the video stream in order to adapt to a variety of devices with different capabilities. Furthermore, a rate control scheme is utilized to improve the visual quality under the constraints of capability and channel bandwidth. However, the computational complexity is increased. A simplified rate control scheme is proposed to reduce the computational complexity. In the proposed scheme, the quantisation parameter can be computed directly instead of using the exhaustive Rate-Quantization model. The linear Mean Absolute Distortion (MAD) prediction model is used to predict the scene change, and the quantisation parameter will be increased directly by a threshold when the scene changes abruptly; otherwise, the comprehensive Rate-Quantisation model will be used. Results show that the optimized rate control scheme is efficient on time saving. Multiview Video Coding (MVC) is efficient on reducing the huge amount of data in multiple-view video coding. The inter-view reference frames from the adjacent views are exploited for prediction in addition to the temporal prediction. However, due to the increase in the number of reference frames, the computational complexity is also increased. In order to manage the reference frame efficiently, a phase correlation algorithm is utilized to remove the inefficient inter-view reference frame from the reference list. The dependency between the inter-view reference frame and current frame is decided based on the phase correlation coefficients. If the inter-view reference frame is highly related to the current frame, it is still enabled in the reference list; otherwise, it will be disabled. The experimental results show that the proposed scheme is efficient on time saving and without loss in visual quality and increase in bitrate. The proposed optimization algorithms are efficient in reducing the computational complexity on H.264/AVC extension. The low computational complexity algorithm is useful in the design of future video coding standards, especially on low power handheld devices.

This study analyses the processes of agricultural and rural restructuring that have characterised rural economies since the end of the Second World War, leading to a reorientation from productivist to more entrepreneurial models of farming. In particular, the transition from the conventional role of the farmer as price taker, which requires appropriate technical and managerial competency, towards that of price maker, which calls for broader entrepreneurial competencies is highlighted. This transition is explored in the context of farm tourism, identified as a diversification strategy to promote a more sustainable rural economy and to protect farm incomes against market fluctuation. To date, the literature on farm tourism has overlooked many of these processes and whilst conceptualising the farmer as an entrepreneur, has not sufficiently engaged with key theories of entrepreneurship or indeed emergent frameworks of entrepreneurial skill and competency. The research draws on a mixed-method’s approach, which includes two distinct research phases conducted in the North West of England. In the initial phase, a survey of 118 diversified farm tourism businesses identifies that whilst the primary motivation to diversify is to provide additional household income, these farmers value business and management competencies at the expense of entrepreneurial competency. Thus, this initial phase, challenges the extent to which farmers are currently entrepreneurial in the context of the rural and agricultural restructuring highlighted. At the second research phase, utilising Q Methodology, a technique designed for the systematic study of subjectivity, a 42-item instrument developed from the extant literature on entrepreneurial competence was administered to 15 farm tourism entrepreneurs. The Q analysis identifies three distinct perspectives on entrepreneurial skill and competency which farmers identify as necessary for successful diversification, termed: the Reflective Leader, the Opportunity Aware Organiser and the Opportunity Driven Innovator. The main characteristics of these groups are discussed and provide the basis for a taxonomy of the farmer as a rural tourism entrepreneur. Moreover, the results reveal the heterogeneity of diversified farmers in the study region, which encapsulates a wide range of perspectives from the risk averse to the opportunity aware, from the managerial to the entrepreneurial The thesis concludes by presenting a conceptual model of entrepreneurial competency, as well an additional taxonomy which classifies the farmer as a rural entrepreneur within a broad landscape of farming identity. The work thus provides a better understanding of farm tourism and a valuable insight into the complexity of rural and farm tourism entrepreneurship. As well as suggestions for future research, the findings will be of interest to academics and policy actors, with the conclusions providing a foundation to better understand farm diversification. Insights that may better inform rural business support, training and advisory services and foster critical policy discussion and debate.

The games industry has developed online multiplayer three-dimensional game worlds that allow players from different geographical locations to engage in competitive and cooperative gameplay together. This has enabled players from different cultures to inhabit the same virtual game world, bypassing any geographical or cultural boundaries found in the real world. These 3D game worlds ask the player to use the basic principles of spatial awareness and movement from the real world, and are often virtual representations of real world environments. These spaces are designed for players from all nationalities to inhabit concurrently. There is now a need to determine design considerations for these multicultural multiplayer game worlds but any investigation must consider the historical evidence from the games industry of cultural differences in gameplay preferences. This thesis discusses the effect of cultural knowledge on the spatial design and interpretation of three-dimensional game environments that are based on real world affordances. A new methodology for the comparative analysis of the design of three-dimensional game environments is established using Space Syntax metrics. This facilitates the discussion of cultural models applied to design thinking for the implementation and interpretation of game environments. Through spatial metrics the analysis of the intelligibility underlying three-dimensional game environments is correlated to the imageability of the projected two-dimensional screen image. The application of this methodology to internationally popular, and culturally specific, game environments establishes new knowledge on tacit cultural influences within game design processes. The analysed intelligibility of the environments indicates cognitive differences between Eastern and Western cultures, already recognised in the interpretation of two-dimensional imagery, also exist within the design and interpretation of three-dimensional game spaces. This study establishes a new methodology through the analysis of intelligibility for design research into game environments. The resulting evaluation of tacit cultural influences within the design of the environments establishes new cultural differences and commonalities. These design characteristics can inform future game design methodologies within industry for the design and implementation of multicultural game environments.

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The development of the nonlinear version of the Continuous-time Generalised Predictive Control (NCGPC) is presented. Unlike the linear version, the nonlinear version is developed in state-space form and shown to include Nonlinear Generalised Minimum Variance (NGMV), and a new algorithm, Nonlinear Predictive Generalised Minimum Variance (NPGMV), as special cases. Through simulations, it is demonstrated that NCGPC can deal with nonlinear systems whose relative degree is not well defined and nonlinear systems with unstable zero dynamics. Geometric approaches, such as exact linearisation, are shown to be included in the NCGPC as special cases.

Although human sustained control movements are continuous in nature there is still controversy on the mechanisms underlying such physiological systems. A popular topic of debate is whether human motor control mechanisms could be modelled as engineering control systems, and if so, what control algorithm is most appropriate. Since the early years of modelling sustained control tasks in human motor control the servomechanism has been an adequate model to describe human tracking tasks. Another continuous-time system model that is often used to model sustained control tasks is the predictive controller which is based on internal models and includes prediction and optimisation. On the other hand, studies have suggested intermittent behaviour of the ``human controller'' in sustained motor control tasks. This thesis investigated whether intermittent control is a suitable approach to describe sustained human motor control. It was investigated how well an intermittent control system model could approximate both the deterministic and non-deterministic parts of experimental data, from a visual-manual compensatory tracking task. Finally, a preliminary study was conducted to explore issues associated with the practical implementation of the intermittent control model. To fit the deterministic part of experimental data, a frequency domain identification method was used. Identification results obtained with an intermittent controller were compared against the results using continuous-time non-predictive and predictive controllers. The results show that the identified frequency response functions of the intermittent control model not only fit the frequency response functions derived from the experimental data well, but most importantly resulted in identified controller parameters which are similar to those identified using a predictive controller, and whose parameter values appear to be physiologically meaningful. A novel way to explain human variability, as represented by the non-deterministic part of the experimental data (the \emph{remnant}), was developed, based on an intermittent control model with variable intermittent interval. This model was compared against the established paradigm, in which variability is explained by a predictive controller with added noise, either signal dependent control signal noise, or observation noise. The study has shown that the intermittent controller with a variable intermittent interval could model the non-deterministic experimental data as well as the predictive controller model with added noise. This provides a new explanation for the source of remnant in human control as inherent to the controller structure, rather than as a noise signal, and enables a new interpretation for the physiological basis for human variability. Finally, the theoretical intermittent control model was implemented in real-time in the context of the physiological control mechanism of human standing balance. An experimental method was developed to apply automatic artificial balance of an inverted pendulum in the context of human standing, via functions electrical stimulation control of the lower leg muscles of a healthy subject. The significance of this study is, firstly, that frequency domain identification was applied for the first time with intermittent control, and it could be shown that both intermittent and predictive control models can model deterministic experimental data from manual tracking tasks equally well. Secondly, for the first time the inherent variability, which is represented by the remnant signal, in human motor control tasks could be modelled as part of the structure of the intermittent controller rather than as an added noise model. Although, the experimental method to apply automatic artificial balance of an inverted pendulum in the context of human standing was not successful, the intermittent controller was implemented for the first time in real-time and combined with electrical muscle stimulation to control a physiological mechanism.