6 resultados para Objective lenses
em Brock University, Canada
Resumo:
Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.
Resumo:
Studies that have used mostly self-reported height have found that men with a same-sex orientation and women with an other-sex orientation are shorter, on average, than men with an other-sex orientation and women with a same-sex orientation, respectively. This thesis examined whether an objective height difference exists or whether a psychosocial account (e.g., distortion of self-reports) may explain these putative height differences. Also, this thesis examined whether certain individual differences (e.g, gender roles and socially desirable responding) predict height distortion. Eight hundred and thirteen participants, recruited at Brock University, the Niagara Community and through surrounding LGBT events, completed self-reported height, measures of gender roles and socially desirable responding, and had their height measured. Using hierarchical linear regressions, it was found that Same-Sex/Both-Sex Oriented men were shorter, on average, than predominantly Other-Sex Oriented men; however, there was no difference in objective height between Same-Sex/Both-Sex Oriented women and predominantly Other-Sex Oriented women. These findings contribute to existing biological theories of men's sexual orientation development and do not contribute to biological theories of women's sexual orientation development. Height distortion was not related to sexual orientation and only marginally related to sex. Predictors of height distortion were Impression Management, in both men and women, and Unmitigated Agency, in men. These findings highlight the complexity of sexual orientation development in men and women. These findings also highlight the role of certain psychosocial factors in how people perceive their bodies and/or how they want their bodies to be perceived by others.
Resumo:
Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.
Resumo:
Converging evidence has demonstrated learning advantages when an individual is instructed to focus their attention externally. However, many of the motor tasks utilized in past research had clear external objectives (i.e., putting accuracy), creating a compatible relationship between an external focus of attention (i.e., outcome) and an external task objective (i.e., putting accuracy). The present study examined whether or not the consistency of instructions and task objective would differentially impact the acquisition of a golf putting task. Participants performed a putting task in a control condition or in one of four experimental conditions resulting from the factorial interaction of task instructions (internal or external) and task objective (internal or external). The retention and transfer data revealed that participants who received an external task objective demonstrated superior outcome scores. Participants who received technique information paired with outcome information demonstrated superior technique scores.
Resumo:
This research study explored a support system for children with learning disabilities. The Learning Disabilities Association of Niagara Region (LDANR) recently expanded its Better Emotional and Social Times (B.E.S.T.) program to incorporate an innovative, character education initiative called the “Who is NOBODY?” program. The objective of this qualitative case study was two-fold. First, the study aimed to support the LDANR in assessing the efficacy of the “Who is NOBODY?” program, providing the LDANR with empirical support for their programs. Second, the study enabled a more in-depth understanding of how to best support children with LD in regards to their social and emotional well-being. The study explored the “Who is NOBODY?” program through three lenses: design, implementation, and experiences of participating children. Three primary themes emerged from these three data lenses: positive character traits, prosocial behaviour, and strong self-efficacy – leading to the promotion of strong character development and self-esteem. Taken together, the “Who is NOBODY?” program was shown to be a successful remediation program for supporting vulnerable children with LD.
Resumo:
Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or three objectives. Unfortunately, when tasked with solving MOPs with four or more objectives, referred to as many-objective problems (MaOPs), a large majority of optimizers experience significant performance degradation. The downfall of these optimizers is that simultaneously maintaining a well-spread set of solutions along with appropriate selection pressure to converge becomes difficult as the number of objectives increase. This difficulty is further compounded for large-scale MaOPs, i.e., MaOPs possessing large amounts of decision variables. In this thesis, we explore the challenges of many-objective optimization and propose three new promising algorithms designed to efficiently solve MaOPs. Experimental results demonstrate the proposed optimizers to perform very well, often outperforming state-of-the-art many-objective algorithms.