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L'objectif de l'étude est de valider une approche basée sur l'orientation des segments des membres supérieurs et du dos et des forces mesurées aux mains pour estimer les chargements lombaires. Plusieurs méthodes d'estimation des chargements au bas du dos ont été documentées par la recherche avec des tâches simples et dans un environnement controlé de laboratoire. Cependant, aucune méthode n'a encore été proposée pour l'estimation de ces chargements dans un environnement réel de travail avec des manutentions plus complexes et sur des durées prolongées. C'est avec cet objectif à long terme qu'un modèle exploitant l'orientation des segments, plutôt que leurs position et orientation, mérite d'être validé. Ces orientations pourraient éventuellement être mesurées par des senseurs inertiels ambulatoires. Six femmes et 5 hommes ont manutentionné des charges de 7,7 kg et de 15,6 kg dans une série de levers et d'abaissements asymétriques et à 2 vitesses : une choisie et une de 25% plus rapide. Un modèle à segments liés du haut du corps a été utilisé pour calculer les chargements 3D à L5/S1. Ce modèle n'utilise que l'orientation des segments et les forces aux mains sont mesurées avec une caisse dynamométrique. Le modèle critère, quant à lui, utilise la cinématique du bas du corps avec l'orientation et la position des segments. Les forces au sol sont mesurées par 3 plateformes de forces formant une grande surface de travail. La validité du modèle a été quantifiée en calculant l'erreur quadratique moyenne (eRMS), les coefficients de détermination (r²), les erreurs maximales et les ratioshaut/bas (moment maximum du modele a valider divise par le moment maximum du modele critere, multiplie par 100). L'eRMS entre les 2 modeles sur le moment resultant a L5/S1 se situe entre 9,9 Nm et 25,4 Nm, le coefficient de determination entre 0,80 et 0,98, l'erreur maximale entre 29 Nm et 142 Nm et les ratios haut/bas sont en moyenne autour de 100%. De plus, l'augmentation de la vitesse moyenne de 22% augmente l'eRMS entre les 2 modèles de 12,7%. L'erreur de ce modèle du haut du corps n'utilisant que l'orientation des segments et les forces aux mains est tout à fait acceptable dans le cadre d'une future utilisation terrain. Dans le cadre d'étude requérant un niveau de précision supérieur, des modifications relativement simples mériteraient d'être investiguées afin d'améliorer la performance du modèle. Dans sa forme actuelle, sa polyvalence pourrait très certainement en faire un excellent outil d'évaluation clinique. Grâce à cette étude, il peut maintenant être envisagé d'estimer les chargements au dos à l'aide de senseurs inertiels pour mesurer les orientations des segments du corps, et donc de faire l'estimation des chargements au dos dans des environnements de travail variés et plus réels.

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PET (positron emission tomography) scans are still in the experimental phase, as one of the newest breast cancer diagnostic techniques. It is becoming the new standard in neurology, oncology and cardiology. PET, like other nuclear medicine diagnostic and treatment techniques, involves the use of radiation. Because of the negative impact of radioactivity to our bodies the radiation doses in PET should be small. The existing computing algorithms for calculating PET images can be divided into two broad categories: analytical and iterative methods. In the analytical approach the relation between the picture and its projections is expressed by a set of integral equations which are then solved analytically. The Fourier backprojection (FBP) algorithm is a numerical approximation of this analytical solution. Iterative approaches use deterministic (ART = Algebraic Reconstructed Technique) or stochastic (EM = Expectation Maximization) algorithms. My proposed kernel density estimation (KDE) algorithm also falls also into the category of iterative methods. However, in this approach each coincidence event is considered individually. The estimate location of the annihilation event that caused each coincidence event is based on the previously assigned location of events processed earlier. To accomplish this, we construct a probability distribution along each coincidence line. This is generated from previous annihilation points by density estimation. It is shown that this density estimation approach to PET can reconstruct an image of an existing tumor using significantly less data than the standard CT algorithms, such as FBP. Therefore, it might be very promising technique allowing reduced radiation dose for patients, while retaining or improving image quality.

Whilst considerable research has found that people tend to underestimate their task completion times (e.g., Buehler et al., 1994), factors that might influence the accuracy of temporal predictions have received little empirical treatment. The research presented in this thesis identified two distinct factors that mediated time estimation accuracy and bias. One factor was task duration, whereas the other factor was the person’s prior experience of the task. There was evidence that having prior experience of performing all or a substantial part of the same task enabled participants to more accurately estimate its duration. Additionally, predictions were more accurate when participants viewed tasks before making time estimates. Contrary to the theory of the planning fallacy (Kahneman & Tversky, 1979), these findings suggest that people do take account of their previous task performance, and use such distributional information to good effect. However, there was evidence of time prediction bias when unrelated tasks were completed beforehand, suggesting that erroneous information about previous task performance was used when making a subsequent estimate. The directional nature of time estimation bias was also highlighted in the present research. In general, there was some evidence of temporal overestimation on tasks with a duration of up to four or five minutes, whereas participants tended to underestimate their completion times on tasks that took between eight and 16 minutes to complete. These findings indicate that task duration influences the direction in which time estimates are biased (i.e., under or overestimation), with the temporal underestimation indicative of the planning fallacy occurring on tasks of at least eight minutes' duration. The present research has potential implications for task duration estimation in everyday life, and outlines conditions under which prediction bias can be reduced. The present findings are discussed in relation to the theory of the planning fallacy and the potential role of cognitive judgemental heuristics in determining temporal misestimation.

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This thesis presents methodology to analyse repeated ordered categorical data (repeated ordinal data), under the assumption that measurements arise as discrete realisations of an underlying (latent) continuous distribution. Two sets of estimation equations, called quasiestimation equations or QEEs, are presented to estimate the mean structure and the cutoff points which define boundaries between different categories. A series of simulation studies are employed to examine the quality of the estimation processes and of the estimation of the underlying latent correlation structure. Graphical studies and theoretical considerations are also utilised to explore the asymptotic properties of the correlation, mean and cutoff parameter estimates. One important aspect of repeated analysis is the structure of the correlation and simulation studies are used to look at the effect of correlation misspecification, both on the consistency of estimates and their asymptotical stability. To compare the QEEs with current methodology, simulations studies are used to analyse the simple case where the data are binary, so that generalised estimation equations (GEEs) can also be applied to model the latent trend. Again the effect of correlation misspecification will be considered. QEEs are applied to a data set consisting of the pain runners feel in their legs after a long race. Both ordinal and continuous responses are measured and comparisons between QEEs and continuous counterparts are made. Finally, this methodology is extended to the case when there are multivariate repeated ordinal measurements, giving rise to inter-time and intra-time correlations.