Power saving for extending session lifetime is an important research subject in wireless sensor networks (WSNs). Recognizing the fact that Quality of Service can be deteriorated by insufficient transmit power, this work studies how to minimize power consumption while achieve a satisfactory QoS of data streams in WSNs. A cross-layer routing scheme is proposed to maximize session lifetime by adjusting individual transmit power on intermediate nodes. The thesis is divided into two major parts for analyzing our proposition. In the first part, we propose an efficient routing scheme with optimal power management and on-demand quality control for WSNs. When source node issues a QoS provision for route discovery, an adjustment of transmit power is computed for each pass-by node by taking into its individual wireless link account. Then, an optimal route associated with lowest power consumption and consistent QoS can be selected among all of the candidate routes. In the second part, by following the definition of QoS criterion in the first part, we further consider the problem of how to balance the needs on constraining end-to-end quality and prolonging lifetime in an established route. The problem can be interpreted as a non-linear optimization paradigm, which is then shown to be a max-min composite formulation. To solve the problem, we propose two methods, (1) route-associated power management (RAPM), and (2) link-associated power management (LAPM). Considering computation-restricted sensor nodes, the RAPM scheme is two-fold simplification; not only it can reduce power computation, but it also quickly determines the longest lifetime and proper transmit power for nodes. On the other hand, if computational cost is not a major concern in a sink node, the LAPM algorithm is more suitable than RAPM to solve the lifetime maximization problem, in terms of accuracy. Finally, we analyze the performance of these two methods. The results demonstrate that the LAPM scheme is very comparable to a heuristic approach.

Wireless sensor network has applications in environmental surveillance, healthcare, and military operations. Because the energy of sensor nodes is limited and nodes are unable to supply energy in real time, the purpose of many researches is to prolong lifetime of sensor network. Lifetime is times that the sink can collect data from all sensor nodes. When a user proposes a query, then the sink gathers data from all sensor nodes. The problem defined in the previous research is given a sensor network and residual energy of each node, and the energy consumption of transmitting a unit message between two nodes. Then this problem is to find a directed tree that maximize minimum residual energy. In this thesis, we define a new problem that given a sensor network and residual energy of each node, and the energy consumption of transmitting a unit message between two nodes. Then our problem is to find a path of each node, which maximize minimum residual energy. We prove this problem is NP-complete. We propose a heuristic algorithm and a similar heuristic algorithm for this problem.

No description available.

The reduction in feed intake and growth rate that occurs following weaning is of major economic consequence to the pig industry. Currently, a range of antimicrobial products can be used to minimise the impact of weaning on piglet health and subsequent performance. However, the use of these products in pig diets is subject to increasing restriction worldwide because of perceived risks to public health and to the environment. Thus, alternative methods are required to mitigate the growth check that almost invariably occurs after weaning in most production systems. Piglets produced outdoors are claimed to experience less of a growth check at weaning and to be able to thrive in relatively unsophisticated weaner accommodation. However, these claims have not been substantiated under Western Australian conditions, nor a scientific basis for these claims established. Consequently, a series of experiments was designed to test the general hypothesis for this thesis – ‘the gut structure and function, and lifetime performance of the weaned pig are affected by its pre- and post-weaning rearing environments’. Experiment 1 was conducted in two parts to quantify differences in the growth performance, health and gut structure of weaner pigs produced indoors or outdoors and reared in conventional or deep-litter pens. The weaner diet in the first part of the experiment contained 100 ppm of olaquindox and 3,000 ppm of zinc oxide (Exp1a). This experiment was repeated without using dietary antimicrobial products (Exp1b). Experiment 2 was conducted in conventional buildings to examine the effect of exposing piglets in lactation to similar substrates to those available to outdoor piglets used in Exp1a and Exp1b in the absence of other differences in the outdoor production milieu. Pre-weaning environments in Exp1a (indoor production (IP) and outdoor production (OP)) appeared to have little effect on gut structure and overall growth rate but significantly affected carcass composition, whereas post-weaning environments (conventional (C) or deep-litter (DL)) affected both overall growth rate and carcass composition. Although feed disappearance was similar, OP pigs grew faster than IP pigs in the first 47 d after weaning in Exp1a but not in Exp1b. Lifetime growth rate (GR), P2 backfat, feed disappearance and feed conversion ratio (FCR) were not significantly affected by the production environment in Exp1a whereas OP pigs grew slower with higher P2 backfat and FCR in Exp1b. Interestingly, OP pigs had heavier carcass weights and higher dressing percentages than IP pigs in both parts of the experiment. The effects of post-weaning environment were more consistent as DL pigs grew faster, were fatter, and had higher carcass weights and dressing percentages than C pigs. Villus height and crypt depth of IP and OP pigs were not different at 21 (weaning) or 28 d, but villus height decreased and crypt depth increased in the week after weaning. Pigs reared in C pens had greater faecal concentrations of volatile fatty acids than pigs in DL, indicating that the latter ingested sufficient straw to alter fermentation characteristics. In Experiment 2, there were no differences in gut structure or pre-weaning and lifetime GR of pigs offered no creep feed (NC), a commercial creep feed (CF) or an ‘outdoor’ mix (OM) comprising of 1 part straw, 5 parts sow feed and 25 parts of soil taken from paddocks in which OP pigs used in Exp1a and Exp1b were farrowed. However, NC pigs grew slower in the week after weaning than the other two treatments. Backfat and feed disappearance were similar for all treatments but pigs on the OM treatment had higher carcass weights and dressing percentages than pigs on the NC and CF treatments. Villus height and crypt depth were not different between treatments and, although the piglets were weaned at 28 d, villus height decreased and crypt depth increased in the week after weaning to an extent similar to that experienced by piglets weaned at 21 d in Experiment 1. Although all piglets received intramuscular injections of 200 mg iron (Fe) dextran when 1 to 2 days old, piglets offered the OM during lactation had higher serum iron and blood haemoglobin (Hb) levels than those offered NC or CF. Furthermore, half the piglets offered NC or CF had Hb levels indicative of chronic Fe deficiency anaemia. The average parity of sows used in this experiment was 6.3 litters, suggesting that piglets may have been born with low Fe stores, possibly because of low Fe stores in their dams due to sub-optimal mineral nutrition over successive parities. In summary, the findings from these experiments partly supported the general hypothesis for this thesis. Under the conditions of these experiments, access to outdoor substrates in lactation had little effect on gut structure and lifetime growth rate but increased both carcass weight and dressing percentage, whereas rearing in DL pens increased feed intake, FCR, growth rate, P2 backfat, carcass weight and dressing percentage.

No description available.

No description available.

Motor drives represent electric equipment used for speed control of electric motors. Varieties of industrial applications, such as assembly, pumps, fans etc., require motors and they consume huge amount of electric energy. Compared with traditional motor drives, which can only send energy from grid to motor, a regenerative motor drive can achieve bi-directional power flow control between motors and utility grid. Regenerative motor drives are excellent candidates for reducing power loss in motor-related applications. One of the most essential parts of a regenerative motor drive power cell is dc-link capacitors. They create suitable dc-link voltages and smooth the voltage waveforms. Reliability, or lifetime of dc-link capacitors highly affect power cell lifetime, and power loss in dc-link capacitor is also another issue that worth noticing. This thesis focuses on the lifetime modeling and lifetime improvement of dc-link capacitors in a regenerative cascaded H-bridge medium-voltage motor drive. The lifetime modeling bases itself on the mechanisms of dominant lifetime stresses in practical operations. A proposed method is used to reduce a dominant current harmonic component in dc-link capacitors. With the proposed lifetime model and harmonic-reduction method, dc-link capacitor lifetime improvement can be anticipated in this motor drive model. Less power losses in those dc-link capacitor banks can also be achieved. / Thesis / Master of Applied Science (MASc)

Single molecule studies on CdSe quantum dots functionalized with oligo-phenylene vinylene ligands (CdSe-OPV) provide evidence of strong electronic communication that facilitate charge and energy transport between the OPV ligands and the CdSe quantum dot core. This electronic interaction greatly modify, the photoluminescence properties of both bulk and single CdSe-OPV nanostructure thin film samples. Size-correlated wide-field fluorescence imaging show that blinking suppression in single CdSe-OPV is linked to the degree of OPV coverage (inferred from AFM height scans) on the quantum dot surface. The effect of the complex electronic environment presented by photoexcited OPV ligands on the excited state property of CdSe-OPV is measured with single photon counting and photon-pair correlation spectroscopy techniques. Time-tagged-time-resolved (TTTR) single photon counting measurements from individual CdSe-OPV nanostructures, show excited state lifetimes an order of magnitude shorter relative to conventional ZnS/CdSe quantum dots. Second-order intensity correlation measurements g(2)(τ) from individual CdSe-OPV nanostructures point to a weak multi-excitonic character with a strong wavelength dependent modulation depth. By tuning in and out of the absorption of the OPV ligands we observe changes in modulation depth from g(2)(0) ≈ 0.2 to 0.05 under 405 and 514 nm excitation respectively. Defocused images and polarization anisotropy measurements also reveal a well-defined linear dipole emission pattern in single CdSe-OPV nanostructures. These results provide new insights into to the mechanism behind the electronic interactions in composite quantum dot/conjugated organic composite systems at the single molecule level. The observed intensity flickering, blinking suppression and associated lifetime/count rate and antibunching behaviour is well explained by a Stark interaction model. Charge transfer from photo-excitation of the OPV ligands to the surface of the CdSe quantum dot core, mixes electron/holes states and lifts the degeneracy in the band edge bright exciton state, which induces a well define linear dipole behaviour in single CdSe-OPV nanostructures. The shift in the electron energies also affects Auger assisted hole trapping rates, suppress access to dark states and reduce the excited state lifetime.

The purpose of this thesis was to develop an approach that could evaluate the burden of unhealthy behaviours over a lifetime through linked population-based health surveys. The Canadian Community Health Survey (CCHS) is one such cross-sectional survey that is routinely administered to the household population and has been linked to a multitude of administrative healthcare databases. Utilizing the linked CCHS to evaluate the burden of unhealthy behaviours over a lifetime is challenging. Health behaviours naturally change over a lifetime due to many factors, and the burden of unhealthy behaviours has many different dimensions (e.g., mortality, disability, and healthcare costs) that are interconnected with each other. The degree to which lifetime disability and healthcare costs vary in relation to differences in life expectancy remains an area of debate. It is unclear whether individuals with healthy behaviours actually experience less lifetime disability and healthcare costs than individuals with unhealthy behaviours since they typically live much longer. Through several studies, this thesis developed various components that can be potentially combined into a lifetime approach which incorporates multivariable transitions. The first two studies assessed the burden of unhealthy behaviours on period life expectancy and period lifetime healthcare costs. In the first study, CCHS-based multivariable risk algorithms were constructed to provide estimates of the causal associations between each unhealthy behavior (smoking history, leisure physical inactivity, non-active transport, leisure sedentary activity, and poor diet) and mortality. The burden of unhealthy behaviours on period life expectancy was estimated to be 7.5 (6.5-8.3) life years in 2000-2004 and 6.7 (5.8-7.4) life years in 2010-2014. The largest burdens were attributed to non-active transport and smoking. In the second study, CCHS-based multivariable risk algorithms were constructed to provide estimates of the causal associations between each unhealthy behavior and healthcare costs within different phases of life (i.e., defined by proximity to death). Unhealthy behaviours were attributed with 10.2% (2.5%-17.7%) of the period lifetime healthcare costs in 2000-2004, and 12.9% (5.6%-19.8%) in 2010-2014. Leisure sedentary activity and non-active transport were responsible for almost this entire burden, while the other unhealthy behaviours appeared to actually reduce period lifetime healthcare costs. The degree to which these estimates are accurate is unclear given the limitations of period life tables and the potential for unhealthy behaviours relating to physical activity to be a product of aging and prior illness. The third study focused on developing methods by which to derive CCHS-based multivariable transition risk algorithms, which would allow for the creation of cohort life tables rather than period life tables. Novel methods involving multiple imputation models were utilized to create quasi-longitudinal CCHS cohorts from multiple cycles of the CCHS. These quasi-longitudinal cohorts were leveraged to develop multivariable risk algorithms for transitions towards different levels of immobility, an exposure that had been included in the prior algorithms for mortality and healthcare costs. Transitions towards moderate immobility were predicted by all unhealthy behaviours except poor diet, and transitions towards severe immobility were predicted by all unhealthy behaviours except sedentary activity. This approach can also be utilized to develop multivariable transitions for the unhealthy behaviours, which were simultaneously allowed to transition in the quasi-longitudinal CCHS cohorts. Such multivariable transition algorithms could potentially be combined with the previously derived algorithms for mortality and healthcare costs to generate more realistic estimates of life expectancy and lifetime healthcare costs. Large variability in the imputed quasi-longitudinal CCHS cohorts requires further examination, and may be reduced by including comorbidities, healthcare costs, and other information from linked administrative healthcare databases. The last two studies evaluated the representativeness of linked CCHS respondents for population-based studies. Response and consent (to linkage) rates in the CCHS have been declining since its introduction raising concerns surrounding the comparability of CCHS samples over time. Similar to other population-based surveys, survey weights are provided that are designed address biases that may arise from non-response and non-consent to linkage. Unfortunately, these survey weights are not necessarily appropriate for many linked health outcomes that are rare. As a result, CCHS-based multivariable health risk algorithms are frequently derived from pooled unweighted CCHS samples. Fortunately, relative to wider sampling frames, unweighted linked CCHS samples were observed to be comparable over time. Nevertheless, linked CCHS respondents were observed to be healthier than comparable individuals in the community-dwelling and general populations at older ages, where they demonstrated lower risks of mortality, long-term care admission, and healthcare costs. This was not unexpected given that important segments of the population (e.g., residents of retirement homes and long-term care care) are excluded from the CCHS sampling frame. These studies highlighted the difficulties of estimating life expectancy and corresponding lifetime healthcare costs from the household population, and the necessity to ensure that such estimates realistically incorporate the time individuals may live outside of the household population over a lifetime. These series of studies therefore resulted in mortality, healthcare cost, and transition risk algorithms that could potentially be combined to generate lifetime estimates of life expectancy, disability, and healthcare costs for a CCHS respondent. The development of transition risk algorithms requires further research. Once these methods are optimized and transition risk algorithms for all exposures of interest are generated, all the components required for this framework will be complete. At that point, explicit methods by which to combine the algorithms and validate projections will be required. This framework will enable a cause-deleted approach to be applied that simultaneously considers the impact of unhealthy behaviours on mortality, disability, transitions, and healthcare costs. This thesis represents an initial first step towards creating a framework that has the potential to generate lifetime estimates, as well as counterfactual estimates, which better reflect the complex nature of lifetime trajectories.

The power electronics market is valued at $23.25 billion in 2019 and is projected to reach $ 36.64 billion by 2027. Power electronic systems (PES) have been extensively used in a wide range of critical applications, including automotive, renewable energy, industrial variable-frequency drive, etc. Thus, the PESs' reliability and robustness are immensely important for the smooth operation of mission-critical applications. Power semiconductor switches are one of the most vulnerable components in the PES. The vulnerability of these switches impacts the reliability and robustness of the PES. Thus, switch-health monitoring and prognosis are critical for avoiding unexpected shutdowns and preventing catastrophic failures. The importance of the prognosis study increases dramatically with the growing popularity of the next-generation power semiconductor switches, wide bandgap switches. These switches show immense promise in the high-power high-frequency operations due to their higher breakdown voltage and lower switch loss. But their wide adaptation is limited by the inadequate reliability study. A thorough prognosis study comprising switch degradation modeling, remaining useful life (RUL) estimation, and degradation-aware controller development, is important to enhance the PESs' robustness, especially with wide bandgap switches. In this dissertation, three studies are conducted to achieve these objectives- 1) Insulated Gate Bipolar Transistor (IGBT) degradation modeling and RUL estimation, 2) cascode Gallium Nitride (GaN) Field-Effect Transistor (FET) degradation modeling and RUL estimation, and 3) Degradation-aware controller design for a PES, solid-state transformer (SST). The first two studies have addressed the significant variation in RUL estimation and proposed degradation identification methods for IGBT and cascode GaN FET. In the third study, a system-level integration of the switch degradation model is implemented in the SST. The insight into the switch's degradation pattern from the first two studies is integrated into developing a degradation-aware controller for the SST. State-of-the-art controllers do not consider the switch degradation that results in premature system failure. The proposed low-complexity degradation-aware and adaptive SST controller ensures optimal degradation-aware power transfer and robust operation over the lifetime.