Biofilm systems such as the moving bed biofilm reactor (MBBR) are finding increased application in wastewater treatment. One important process that governs MBBRs and yet is poorly understood is the rate of biofilm detachment. The detachment of cells from biofilm surfaces controls both the accumulation of biofilm and the quantity of biomass that is suspended in the bulk liquid phase. This changing balance of attached and suspended cells, in this thesis named the biosolids dynamics, can impact the efficacy of MBBRs. The goal of this research was to investigate how the biosolids dynamics are influenced by process changes relevant to applied wastewater treatment systems and suggest new routes to reactor design and optimization. To achieve this goal, the work addresses three separate but interconnected lines of inquiry. First, multivariate analysis (Principal Component Analysis, Partial Least Squares) was used to examine 2 years of historical data from an MBBR operating at a Canadian pulp mill in order to identify key process variables, perform process diagnostics, and act as a predictive tool. Secondly, the effect of calcium concentration on biofilm structure, microbiology and reactor performance was investigated in four laboratory-scale MBBRs operated at a range of calcium concentrations (1 to 300 mg/L Ca2+). It was found that above a threshold calcium concentration between 1-50 mg/L, MBBR biofilms were observed to be thicker with greater density, contain larger anoxic regions adjacent to the carrier substratum, have more proteinaceous EPS, and have altered microbial community structure. The results suggest an important role for calcium that should be considered in the design and operation of MBBRs. In the final line of inquiry, a diffusion-reaction biofilm model was adapted to represent the key processes of the MBBR. The model was found to simulate average trends observed in the lab-scale experiments allowing for quantification of the detachment rate. Transient periods of reactor starvation were also simulated by introducing a novel metabolic state function to account for down-regulation of metabolism as a result of starvation. This approach was found to accurately simulate starvation response when coupled with detachment expressions that were growth-dependant.

Pedestrian protection performance becomes more and more in focus for the car manufactures and systems to reduce injury risk are under development. A wider understanding of both the present and the future windscreen performance in free moving headform testing is needed to optimize these systems. The purpose of this thesis was therefore to learn and understand windscreen behaviour when subjected to head impact and to gain knowledge of CAE status for head impact in windscreens from a pedestrian point of view. A literature review concluded that there are different ways to model a windscreen. It was found that the computer material models for laminated windscreen glass were not capable of fully representing the behaviour of this material under all impact conditions, particularly the non-linear behaviour after fracture or failure. Experimental testing on three different windscreen models, with a free moving headform in a horizontal impactor, has been performed. Test set up was according to Euro NCAP pedestrian testing protocol and three different windscreen angles were tested. The parameter investigated was curvature and HIC and deformation depth on the windscreen were used as evaluation tools. Deformation was measured with a laser positioned behind the windscreen at impact. Film analysis and integration of headform accelerations were used as comparison. The testing concludes that different curvature alone will not have a big influence on HIC and deformation.   Keywords: PVB laminated windscreen, pedestrian, impact, free moving headform

The objective of this thesis is to detect and identify moving objects in a video sequence. The currently available techniques for motion estimation can be broadly categorized into two main classes: block matching methods and optical flow methods.<p>This thesis investigates the different motion estimation algorithms used for video processing applications. Among the available motion estimation methods, the Lucas Kanade Optical Flow Algorithm has been used in this thesis for detection of moving objects in a video sequence. Derivatives of image brightness with respect to x-direction, y-direction and time t are calculated to solve the Optical Flow Constraint Equation. The algorithm produces results in the form of horizontal and vertical components of optical flow velocity, u and v respectively. This optical flow velocity is measured in the form of vectors and has been used to segment the moving objects from the video sequence. The algorithm has been applied to different sets of synthetic and real video sequences.<p>This method has been modified to include parameters such as neighborhood size and Gaussian pyramid filtering which improve the motion estimation process. The concept of Gaussian pyramids has been used to simplify the complex video sequences and the optical flow algorithm has been applied to different levels of pyramids. The estimated motion derived from the difference in the optical flow vectors for moving objects and stationary background has been used to segment the moving objects in the video sequences. A combination of erosion and dilation techniques is then used to improve the quality of already segmented content.<p>The Lucas Kanade Optical Flow Algorithm along with other considered parameters produces encouraging motion estimation and segmentation results. The consistency of the algorithm has been tested by the usage of different types of motion and video sequences. Other contributions of this thesis also include a comparative analysis of the optical flow algorithm with other existing motion estimation and segmentation techniques. The comparison shows that there is need to achieve a balance between accuracy and computational speed for the implementation of any motion estimation algorithm in real time for video surveillance.

Abstract The thesis is addressing the inventory valuation method called moving average and how this inventory method handles exchange rate differences. Intentions of the study is also to highlight differences and similarities between the two methods standard cost and moving average. This study fills an existing gap in science regarding pros and cons with the moving average method which made the topic very interesting.  It also has strong practical contribution regarding possible benefits and problems of relevance to companies that have intentions of implementing moving average on their inventory. The relationships between foreign exchange rate risks and inventory leads to the formulated research question for this thesis: What are the effects of currency movements in the cost of goods sold from an inventory valued at moving average method? Based on the technical problem statement was a constructive approach and interpretive standpoint considered best suited for the study. The gathering of data was conducted by using a qualitative research strategy. Three different topics are used in the theoretical frame; inventory valuation, exchange rates and hedging. The theoretical frame describes the accounting standards behind inventory valuation and exchange rates, as well as the theories addressed. Third and final topic hedging is about how to manage exchange rate exposures using different hedging techniques. The in-depth investigation was made for four business units with inventories valued according to the moving average method. Sampling was divided into two parts one for the companies and another choosing respondents. Selection of companies was a convenient sample within the non-probability samples used and the respondents were selected using a snowball sample. Semi-structured interviews were conducted with nine respondents. Both the empirical- and analysis chapter follows the same three topics as the theory structure and the empirical answers are divided into companies to facilitate the comparison. A short summary of the analysis is that moving average is most suitable for inventories with; high inventory turnovers, sales from shelf and stable costs. There is a need to identify input costs to manage exchange rate differences correctly. The final part about hedging showed that different exposures need different hedging techniques. Forward contracts were the most common financial instrument used for hedging transaction exposures. Input risks also identified as an economic risk is one of the hardest to manage. This study has showed that effects from exchange rate fluctuations affect the moving average inventory value different than other inventory models. The input currencies need to be identified and separated from the sales currencies otherwise there is a potential risk to make wrong decisions.

The purpose of this study is to explore the possibilities of the retirees or future retirees group who currently reside in the urban areas to migrate in-island Taiwan. Utilizing Andersen¡¦s ¡§Behavior Model of Health Service Utilization¡¨ as structure, this research aims to explore the factors influencing moving intention and the accompanying geographic attribute selection in order to understand the feasibility of the development of the retiree inland migrant group. On April, 2012, using purposive and snowball sampling, this research carried out a questionnaire targeting retirees or future retirees aged between 50 to 70 years old in five cities: Taipei City, New Taipei City, pre-county-city consolidated cities of Taichung City (including Fengyuan City), Tainan City and Kaoshiung City (including Fongshan City). A total of 1,110 questionnaires were given out, 722 retrieved, 691 were valid with an effective rate of 62.82%. The results of this study show a fairly low 23.20% moving intention of retirees or future retirees from the urban areas. As to geographic attribute selection, the majority show an inclination to choosing to live in the urban outskirts (45.90%) and the urban areas (32.40%). According to the Chi-square analysis, components influencing moving intention and geographic attribute selection include: the predisposing components of gender, current residency, place of residency before 15 years old, number of children and lifestyle; the enabling components of average monthly disposable income, living pattern, residential burden status and the need component of regional characteristic demand have a significant difference with moving intention. Furthermore, the predisposing components of level of education and lifestyle, the enabling component of average monthly disposable income and the need components which include one of the activities planning of refresher¡¦s course participation and regional characteristic demand have a significant difference with geographic attribute selection. Additionally, the majority among those with a moving intention are inclined to choose to live in rural areas. Thus, it is reasonable to conclude that current residents in urban areas will tend to migrate to rural environments rather than other urban areas or outskirts after retiring. According to the above analysis, recommendation is given to areas where retirees have migrated in order to better understand the retirees or future retirees group and the development of the local industry in Taiwan.

Nonlinear estimation techniques play an important role for process monitoring since some states and most of the parameters cannot be directly measured. There are many techniques available for nonlinear state and parameter estimation, i.e., extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filtering (PF) and moving horizon estimation (MHE) etc. However, many issues related to the available techniques are to be solved. This dissertation discusses three important techniques in nonlinear estimation, which are the application of unscented Kalman filters, improvement of moving horizon estimation via computation of the arrival cost and different implementations of extended Kalman filters. First the use of several estimation algorithms such as linearized Kalman filter (LKF), extended Kalman filter (EKF), unscented Kalman filter (UKF) and moving horizon estimation (MHE) are investigated for nonlinear systems with special emphasis on UKF as it is a relatively new technique. Detailed case studies show that UKF has advantages over EKF for highly nonlinear unconstrained estimation problems while MHE performs better for systems with constraints. Moving horizon estimation alleviates the computational burden of solving a full information estimation problem by considering a finite horizon of the measurement data; however, it is non-trivial to determine the arrival cost. A commonly used approach for computing the arrival cost is to use a first order Taylor series approximation of the nonlinear model and then apply an extended Kalman filter. The second contribution of this dissertation is that an approach to compute the arrival cost for moving horizon estimation based on an unscented Kalman filter is proposed. It is found that such a moving horizon estimator performs better in some cases than if one based on an extended Kalman filter. It is a promising alternative for approximating the arrival cost for MHE. Many comparative studies, often based upon simulation results, between extended Kalman filters (EKF) and other estimation methodologies such as moving horizon estimation, unscented Kalman filter, or particle filtering have been published over the last few years. However, the results returned by the extended Kalman filter are affected by the algorithm used for its implementation and some implementations of EKF may lead to inaccurate results. In order to address this point, this dissertation investigates several different algorithms for implementing extended Kalman filters. Advantages and drawbacks of different EKF implementations are discussed in detail and illustrated in some comparative simulation studies. Continuously predicting covariance matrix for EKF results in an accurate implementation. Evaluating covariance matrix at discrete times can also be applied. Good performance can be expected if covariance matrix is obtained from integrating the continuous-time equation or if the sensitivity equation is used for computing the Jacobian matrix.

In this study, an attempt is made to obtain convergent and stable solutions of the K-E turbulence model equations for non-reacting turbulent flows over an isothermal solid surface in regression. A physics based mathematical model is used to describe the flow and temperature field over the moving surface. The flow is assumed to be two-dimensional, unsteady, incompressible with boundary layer approximations. Parabolized form of the standard K-E equations is adopted to simulate turbulence in the flow. Regression of the solid surface causes the bounds of the solution domain to change with time, therefore a coordinate transformation is used in the vertical direction. The computational domain with fixed boundaries is discretized using an orthogonal grid system where a coordinate stretching is used in the vertical direction. A second order accurate, explicit finite difference technique is used for discretization of the governing equations. The final set of discretized equations is then solved using a solution algorithm specifically developed for this study. The verification of the solution algorithm includes a grid independence study, time increment study, and a comparison of the steady state results for the laminar and the turbulent flow cases. Finally, a parametric study is conducted using the proposed solution algorithm to test the stability of the numerical results for different Reynolds numbers, regression rates, and surface temperatures. It is concluded that the proposed numerical solution algorithm is capable of providing convergent and stable solutions of the two-equation turbulence model.

The cost of pretreatment process for saccharification from biomass and the cost of dilute ethanol purification are significant components of the overall cost for fuel grade ethanol production through fermentation or other biological routes. This work focuses on developing optimal designs of dilute ethanol purification process and the new acid hydrolysis technology for the production of fermentable sugars from biomass where the overarching goal is to reduce the cost of ethanol production from biomass. In this thesis, the ethanol separation process with the reverse osmosis membrane pretreatment is developed to reduce separation cost and energy consumption especially when the feed is dilute. In addition, the new solid phase reactive separation system for biomass saccharification via acid hydrolysis is proposed. This new process is applied for both dilute and concentrated acid hydrolysis where the goal is to increase sugar yield and to reduce byproduct formation. The reaction kinetics of the concentrated acid hydrolysis is investigated through batch experiment. All of these use optimization approaches for seeking the best process designs and for parameter estimations.

Quantifying the drilling or recompletion potential in producing gas basins is often a challenging problem, because of large variability in rock quality, well spacing, and well completion practices, and the large number of wells involved. Complete integrated reservoir studies to determine infill potential are often too time-consuming and costly for many producing gas basins. In this work we evaluate the accuracy of a statistical moving-window technique that has been used in tight-gas formations to assess infill and recompletion potential. The primary advantages of the technique are its speed and its reliance upon well location and production data only. We used the statistical method to analyze simulated low-permeability, 100-well production data sets, then compared the moving-window infill-well predictions to those from reservoir simulation. Results indicate that moving-window infill predictions for individual wells can be off by more than 50%; however, the technique accurately predicts the combined infill-production estimate from a group of infill candidates, often to within 10%. We found that the accuracy of predicted infill performance decreases as heterogeneity increases and increases as the number of wells in the project increases. The cases evaluated in this study included real-world well spacing and production rates and a significant amount of depletion at the infill locations. Because of its speed, accuracy and reliance upon readily available data, the moving window technique can be a useful screening tool for large infill development projects.

During field observations of professional movers, it was noticed that some experienced movers carried loads posterior to their pelvis. The purpose of this study was two-fold: (1) to assess the biomechanical differences between hand-held load carriage anterior (AC) and posterior (PC) to the pelvis; and, (2) to determine if an assistive load carriage device could reduce muscle effort while carrying loads either anterior or posterior to the pelvis. In the first laboratory study, an electromyographic (EMG) analysis was conducted while participants carried a load on a treadmill using AC and PC techniques. The subjects conducted three trials of AC and PC techniques while EMG data were being collected. All trial data were normalized to their respective iMVE values. An amplitude probability distribution function (APDF) was used to compare EMG amplitudes between carrying techniques. Results indicated that PC reduced EMG activity of the erector spinae (>50% reduction), trapezius, and anterior deltoid (p<0.05) as well as increasing EMG activity in the posterior deltoid (p<0.05). Eighty percent of the subjects reported that the PC method felt awkward. Due to its awkwardness, many individuals may not use the PC technique; thus, the second purpose of the study was to design an assistive movers’ pack to aid in AC and PC techniques and make the PC method easier to perform. In the second study, subjects were asked to walk unloaded while EMG was recorded. The subjects then performed the AC and PC methods with and without the assistive device. All EMG signals were normalized to unloaded gait followed by EMG APDF analyses. Findings from the first study were confirmed, in that PC, compared to AC significantly reduced erector spinae activity (p<0.05) and focused shoulder activity to the posterior deltoid. Secondly, the assistive device effectively reduced flexor digitorum activity (>40% reduction, p<0.03) and anterior deltoid activity (>75% reduction, p=0.5) in both AC and PC. Erector spinae EMG remained similar to their respective unassisted conditions. The assistive load carriage device may be an effective ergonomic tool in both AC and PC techniques. Subjective surveys indicate that the assistive device decreased the awkwardness in performing the PC technique. / Thesis (Master, Kinesiology & Health Studies) -- Queen's University, 2008-09-29 16:58:19.305