In this study, a novel incremental ring rolling process used in production of rings with various cross sections is examined. A basic type of this process is investigated numerically, using commercial finite element programs / MSC Superform, MSC Marc. The user defined subroutines are also utilized for flexibility in modeling. The aim of modeling is to determine the material flow for geometrical analysis, strain/stress distribution for tool force analysis and residual stresses, in a cost effective way. The process has instabilities and requires large number of incremental stages to complete a full finite element simulation. The full models are reliable but costly hence the numerical studies are focused on reliable simplified models with lower computation time. Different approaches are developed: three-dimensional segment model, improved segment model, velocity coupling model. The results of these models are compared with experimentally verified full models. Numerical parameters such as mesh type, step size, convergence ratio are examined. After verification of the model different applications to of the process is developed and physical parameters affecting the process are discussed / such as the tool path .

The thesis aims to provide a comprehensive experimental analysis of the processing and acquisition of Turkish relative clauses in Turkish monolingual and Turkish-English bilingual children at the ages of 5-8. The study combines of

This thesis proposes an incremental algorithm to discover regional network access patterns from traffic data of a regional network. Because the size of network traffic database is very large, we need to develop a fast algorithm of association rules in order to efficiently generate user access patterns. Attributed relational graph is used to represent user access patterns on the network. The change of relational graph indicates the access pattern of a regional network is changed. In order to keep the network access pattern up to date without spending great computation costs, we propose an incremental procedure to generalize network access patterns from time to time. The results can be used for supporting network administrators to easily keep track of network usage patterns and better manage regional networks

This dissertation presents the development of a semi-supervised incremental learning framework with a multi-view perspective for image concept modeling. For reliable image concept characterization, having a large number of labeled images is crucial. However, the size of the training set is often limited due to the cost required for generating concept labels associated with objects in a large quantity of images. To address this issue, in this research, we propose to incrementally incorporate unlabeled samples into a learning process to enhance concept models originally learned with a small number of labeled samples. To tackle the sub-optimality problem of conventional techniques, the proposed incremental learning framework selects unlabeled samples based on an expected error reduction function that measures contributions of the unlabeled samples based on their ability to increase the modeling accuracy. To improve the convergence property of the proposed incremental learning framework, we further propose a multi-view learning approach that makes use of multiple features such as color, texture, etc., of images when including unlabeled samples. For robustness to mismatches between training and testing conditions, a discriminative learning algorithm, namely a kernelized maximal- figure-of-merit (kMFoM) learning approach is also developed. Combining individual techniques, we conduct a set of experiments on various image concept modeling problems, such as handwritten digit recognition, object recognition, and image spam detection to highlight the effectiveness of the proposed framework.

In this thesis we provide three main contributions to blind source separation methods based on NMF. Our first contribution is a group-sparsity inducing penalty specifically tailored for Itakura-Saito NMF. In many music tracks, there are whole intervals where only one source is active at the same time. The group-sparsity penalty we propose allows to blindly indentify these intervals and learn source specific dictionaries. As a consequence, those learned dictionaries can be used to do source separation in other parts of the track were several sources are active. These two tasks of identification and separation are performed simultaneously in one run of group-sparsity Itakura-Saito NMF. Our second contribution is an online algorithm for Itakura-Saito NMF that allows to learn dictionaries on very large audio tracks. Indeed, the memory complexity of a batch implementation NMF grows linearly with the length of the recordings and becomes prohibitive for signals longer than an hour. In contrast, our online algorithm is able to learn NMF on arbitrarily long signals with limited memory usage. Our third contribution deals user informed NMF. In short mixed signals, blind learning becomes very hard and sparsity do not retrieve interpretable dictionaries. Our contribution is very similar in spirit to inpainting. It relies on the empirical fact that, when observing the spectrogram of a mixture signal, an overwhelming proportion of it consists in regions where only one source is active. We describe an extension of NMF to take into account time-frequency localized information on the absence/presence of each source. We also investigate inferring this information with tools from machine learning.

Purpose: The aim of this study was to determine the influence of 30min. of moderate and heavy intensity aerobic exercise to heart rate during interval incremental exercise. Methods: Eight healthy males (mean SD 23 1yr; 76 4,8 kg; 178 6,6 cm) were tested 3 times. They performed incremental veloergometer exercise test until subjective exhaustion. Pedalling rate was maintained constant at 70 rpm. Test began with 4 min. of cycling at 25 W. Then the workload was increased by 25 W and maintained for 3 min. until participant ,s heart rate (HR) reached 90 % of HRmax (220 - age, year). Between workloads the participants rested for 4 min. Two times exercise was preceded by 30 min. of moderate (equal to lactate threshold), heavy intensity (50 W heavier than lactate threshold) or no warm-up. Capillary blood samples were drawn from finger to measure lactate concentration at rest and 5, 10, 20, 30, min. during work. HR was registered before exercise and every 5 min. during work. Also HR was recorded every 5 s. during interval incremental veloergometer test. The heart rate data were modelled using single exponential models, which included amplitudes, time constants and asimptotics values. Results: Heart rate was more elevated during heavy warm-up compared to the moderate (3 min. – 140 13,7; 13 min. – 158 16,1; 23 min. – 164 13,6; 26 min. - 167 13,7 and 3 min. – 128 8,7; 13 min. – 134 11,2; 23 min. – 140 11,2; 26 min. – 142 10,9 beats/min. respectively). Heavy warm-up resulted... [to full text]

If we don't take care of how people are moving into cities, it will continue happen in the form of slums. This project is an attempt, a start in the search of finding a typeology that we clearly need.

The seismic response of steel monopole wind turbine towers is investigated and their risk is assessed in the Canadian seismic environment. This topic is of concern as wind turbines are increasingly being installed in seismic areas and design codes do not clearly address this aspect of design. An implicit finite element model of a 1.65MW tower was developed and validated. Incremental dynamic analysis was carried out to evaluate its behaviour under seismic excitation, to define several damage states, and to develop a framework for determining its probability of damage. This framework was implemented in two Canadian locations, where the risk was found to be low for the seismic hazard level prescribed for buildings. However, the design of wind turbine towers is subject to change, as is the design spectrum. Thus, a methodology is outlined to thoroughly investigate the probability of reaching predetermined damage states under seismic loading for future considerations.

The seismic response of steel monopole wind turbine towers is investigated and their risk is assessed in the Canadian seismic environment. This topic is of concern as wind turbines are increasingly being installed in seismic areas and design codes do not clearly address this aspect of design. An implicit finite element model of a 1.65MW tower was developed and validated. Incremental dynamic analysis was carried out to evaluate its behaviour under seismic excitation, to define several damage states, and to develop a framework for determining its probability of damage. This framework was implemented in two Canadian locations, where the risk was found to be low for the seismic hazard level prescribed for buildings. However, the design of wind turbine towers is subject to change, as is the design spectrum. Thus, a methodology is outlined to thoroughly investigate the probability of reaching predetermined damage states under seismic loading for future considerations.

Leucodepletion, the removal of leucocytes from blood products improves the safety of blood transfusion by reducing adverse events associated with the incidental non-therapeutic transfusion of leucocytes. Leucodepletion has been shown to have clinical benefit for immuno-suppressed patients who require transfusion. The selective leucodepletion of blood products by bed side filtration for these patients has been widely practiced. This study investigated the economic consequences in Queensland of moving from a policy of selective leucodepletion to one of universal leucodepletion, that is providing all transfused patients with blood products leucodepleted during the manufacturing process. Using an analytic decision model a cost-effectiveness analysis was conducted. An ICER of $16.3M per life year gained was derived. Sensitivity analysis found this result to be robust to uncertainty in the parameters used in the model. This result argues against moving to a policy of universal leucodepletion. However during the course of the study the policy decision for universal leucodepletion was made and implemented in Queensland in October 2008. This study has concluded that cost-effectiveness is not an influential factor in policy decisions regarding quality and safety initiatives in the Australian blood sector.