Particle swarm optimization for two-connected networks with bounded rings

The Two-Connected Network with Bounded Ring (2CNBR) problem is a network design problem addressing the connection of servers to create a survivable network with limited redirections in the event of failures. Particle Swarm Optimization (PSO) is a stochastic population-based optimization technique modeled on the social behaviour of flocking birds or schooling fish. This thesis applies PSO to the 2CNBR problem. As PSO is originally designed to handle a continuous solution space, modification of the algorithm was necessary in order to adapt it for such a highly constrained discrete combinatorial optimization problem. Presented are an indirect transcription scheme for applying PSO to such discrete optimization problems and an oscillating mechanism for averting stagnation.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.

Benefits of Using Target Activities to Assist in Improvement of Striking in Striking and Fielding Games for Individuals with Autism: A Comparative Case Study

The purpose of the research study was to increase understanding about the potential benefits of combining target activities with striking-fielding games for individuals with high functioning autism spectrum disorder. A comparative case study was conducted to understand if target activities can assist in improving the skills of striking and throwing, aid the learning of tactics and add to current understanding of how certain teaching skills might be linked to the transfer between target and striking-fielding games. Data was collected through observations, student journals and interviews and were analyzed using both inductive and deductive methods. Results show an appearance of improvement in throwing, striking, bowling and badminton for overall skill levels. In regards to teaching skills, appropriate and effective teaching techniques, appropriate and effective equipment, dynamic of participants and student-instructors and consistency of attendance are vital. Future research should further look at the transferability to outdoor settings and interview the participants.

Modeling Metal Protein Complexes from Experimental Extended X-ray Absorption Fine Structure using Computational Intelligence

Experimental Extended X-ray Absorption Fine Structure (EXAFS) spectra carry information about the chemical structure of metal protein complexes. However, pre- dicting the structure of such complexes from EXAFS spectra is not a simple task. Currently methods such as Monte Carlo optimization or simulated annealing are used in structure refinement of EXAFS. These methods have proven somewhat successful in structure refinement but have not been successful in finding the global minima. Multiple population based algorithms, including a genetic algorithm, a restarting ge- netic algorithm, differential evolution, and particle swarm optimization, are studied for their effectiveness in structure refinement of EXAFS. The oxygen-evolving com- plex in S1 is used as a benchmark for comparing the algorithms. These algorithms were successful in finding new atomic structures that produced improved calculated EXAFS spectra over atomic structures previously found.

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.

Destigmatizing Child and Adolescent Mental Health through Group Chat: A Workshop to Support the Emotional and Social Needs of Youth

The purpose of this project was to raise awareness surrounding child and adolescent mental health in an effort to reduce preconceived stigmas in relation to this specialized field. This project presented a literature review of the current state of child and adolescent mental health in Canada today, including the prevalence and several treatment options for young people confronting mental health challenges. Consideration of the powerful role of the education system upon youth with mental health issues became evident, specifically regarding early identification and prevention. A needs assessment was conducted to gather feedback from the clinical practitioners of a Section 23 classroom within a Southern Ontario hospital. This assessment was used to develop an informational and pedagogical workshop resource to extend practitioner understanding of this pertinent issue and support the social and emotional needs of young people confronting mental heath challenges. Results of the assessment indicated the significant need for such a workshop resource, and these responses were used to guide the development of Group Chat: A Workshop to Support the Emotional and Social Needs of Youth. The latter was subsequently presented to participants, whereby evaluative questionnaires indicated the efficacy and usefulness of this workshop resource to both practitioners and students alike.

INFLUENCE OF INCREASED EXTRACELLULAR LEUCINE ON THE PROTEIN METABOLIC RESPONSES DURING OSMOTIC STRESS IN SKELETAL MUSCLE

The purpose of this study was to examine the effects of increased extracellular leucine concentration on protein metabolism in skeletal muscle cells when exposed to 3 different osmotic stresses. L6 skeletal muscle cells were incubated in either a normal or supplemental leucine (1.5mM) medium set to hypo-osmotic (230 ± 10 Osm), iso-osmotic (330 ± 10 Osm) or hyper-osmotic (440 ± 10 Osm) conditions. 3H-tyrosine was used to quantify protein synthesis. Western blotting analysis was performed to determine the activation of mTOR, p70S6k, ubiquitin, actin, and μ-calpain. Hypo-osmotic stress resulted in the greatest increase in protein synthesis rate under the normal-leucine condition while iso-osmotic stress has the greatest increase under the elevated-leucine condition. Elevated-leucine condition had a decreased rate in protein degradation over the normal condition within the ubiquitin proteasome pathway (p<0.05). Leucine and hypo-osmotic stress therefore creates a favourable environment for anabolic events to occur.