Characterizing Dynamic Optimization Benchmarks for the Comparison of Multi-Modal Tracking Algorithms

Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.

The landscape of work engagement in brain injury rehabilitation /

This study examined work engagement among brain injury rehabilitation professionals with specific attention to how they engage with their work (the extent to which they experience vigor, dedication, and absorption while working) and how they engage with people (the degree to which they are welcoming towards others and demonstrate integrity, responsibility, transparency). This study also tested a theoretical model of work engagement that predicted a relationship between engagement and personal, interpersonal, and organizational capacity. Eighty-one staff employed in a hospital-based brain injury program participated in the study. A quantitative self-report survey was used to measure participants' levels of capacity and engagement and a qualitative question was included to identify initiatives that could be introduced to enhance job performance. As predicted by the model, there were statistically significant positive correlations among all three capacity variables and engagement with work and statistically significant positive correlations between ethical engagement and personal and interpersonal capacity. The results of the qualitative data analysis revealed three broad categories of recommendations for improving job performance (more learning opportunities, more resources to support professional development, and the need to build greater team cohesion). These findings provide initial support for a theoretical model that emphasizes the link between capacity and engagement, which could be used to guide theory-driven interventions aimed at improving the work environment.

Landscape geochemical investigations in the vicinity of a lead deposit near Snertingdal, southern Norway

Landscape geochemical investigations were conducted upon portions of a natural uniform landscape in southern Norway. This consisted of sampling both soil profile samples and spruce tree twigs for the analysis of twelve chemical elements. These elements were cobalt, copper, nickel, lead, zinc, manganese, magnesium, iron, calcium, sodium, potassium and aluminum which were determined by atomic absorption analysis on standardized extraction techniques for both organic and inorganic materials. Two "landscape traverses" were chosen for a comparative study of the effects of varying landscape parameters upon the trace element distribution patterns throughout the landscape traverses. The object of this study was to test this method of investigation and the concept of an ideal uniform landscape under Norwegian conditions. A "control traverse" was established to represent uniform landscape conditions typical of the study area and was used to determine "normal" or average trace element distribution patterns. A "signal traverse" was selected nearby over an area of lead mineralization where the depth to bedrock is very small. The signal traverse provided an area of similar landscape conditions to those of the control traverse with significant differences in the bedrock configuration and composition. This study was also to determine the effect of the bedrock mineralization upon the distribution patterns of the twelve chemical elements within the major components of the two landscape traverses (i.e. soil profiles and tree branches). The lead distribution within the soils of the signal traverse showed localized accumulations of lead within the overburden with maximum values occurring within the organic A horizon of soil profile #10. Above average concentrations of lead were common within the signal traverse, however, the other elements studied were not significantly different from those averages determined throughout the soils of the control traverse. The spruce twig samples did not have corresponding accumulations of lead near the soil lead anomaly. This is attributable to the very localized nature of the lead dispersion pattern within the soils. This approach to the study of the geochemistry of a natural landscape was effective in establishing: a) average or "normal" trace element distribution patterns b) local variations in the landscape morphology and c) the effect of unusually high lead concentrations upon the geochemistry of the landscape (i.e. within the soil profiles and tree branches). This type of study provides the basis for further more intensive studies and serves only as a first approximation of the behaviour of elements within a natural landscape.