Winâ Foy : functional object-oriented programming language

This thesis will introduce a new strongly typed programming language utilizing Self types, named Win--*Foy, along with a suitable user interface designed specifically to highlight language features. The need for such a programming language is based on deficiencies found in programming languages that support both Self types and subtyping. Subtyping is a concept that is taken for granted by most software engineers programming in object-oriented languages. Subtyping supports subsumption but it does not support the inheritance of binary methods. Binary methods contain an argument of type Self, the same type as the object itself, in a contravariant position, i.e. as a parameter. There are several arguments in favour of introducing Self types into a programming language (11. This rationale led to the development of a relation that has become known as matching [4, 5). The matching relation does not support subsumption, however, it does support the inheritance of binary methods. Two forms of matching have been proposed (lJ. Specifically, these relations are known as higher-order matching and I-bound matching. Previous research on these relations indicates that the higher-order matching relation is both reflexive and transitive whereas the f-bound matching is reflexive but not transitive (7]. The higher-order matching relation provides significant flexibility regarding inheritance of methods that utilize or return values of the same type. This flexibility, in certain situations, can restrict the programmer from defining specific classes and methods which are based on constant values [21J. For this reason, the type This is used as a second reference to the type of the object that cannot, contrary to Self, be specialized in subclasses. F-bound matching allows a programmer to define a function that will work for all types of A', a subtype of an upper bound function of type A, with the result type being dependent on A'. The use of parametric polymorphism in f-bound matching provides a connection to subtyping in object-oriented languages. This thesis will contain two main sections. Firstly, significant details concerning deficiencies of the subtype relation and the need to introduce higher-order and f-bound matching relations into programming languages will be explored. Secondly, a new programming language named Win--*Foy Functional Object-Oriented Programming Language has been created, along with a suitable user interface, in order to facilitate experimentation by programmers regarding the matching relation. The construction of the programming language and the user interface will be explained in detail.

Effects of age on learning a spatial motor task in younger and older adults individualizing their knowledge of results schedule

Self-controlled KR practice has revealed that providing participants the opportunity to control their KR is superior for motor learning compared to participants replicating the KR schedule of a self-control participant, without the choice (e.g., yoked). The purpose of the present experiment was two-fold. First, to examine the utility of a self-controlled KR schedule for learning a spatial motor task in younger and older adults and second, to determine whether a self-controlled KR schedule facilitates an increased ability to estimate one’s performance in retention and transfer. Twenty younger adults and 20 older adults practiced in either the self-control or yoked condition and were required to push and release a slide along a confined pathway using their non-dominant hand to a target distance. The retention data revealed that as a function of age, a self-controlled KR schedule facilitated superior retention performance and performance estimations in younger adults compared to their yoked counterparts.

The effects of a general excercise program on task self-efficacy and social physique anxiety in older adults

Older adults represent the most sedentary segment of the adult population, and thus it is critical to investigate factors that influence exercise behaviour for this age group. The purpose of this study was to examine the influence of a general exercise program, incorporating cardiovascular, strength, flexibility, and balance components, on task selfefficacy and SPA in older adult men and women. Participants (n=114, Mage = 67 years) were recruited from the Niagara region and randomly assigned to a 12-week supervised exercise program or a wait-list control. Task self-efficacy and SPA measures were taken at baseline and program end. The present study found that task self-efficacy was a significant predictor of leisure time physical activity for older adults. In addition, change in task self-efficacy was a significant predictor of change in SPA. The findings of this study suggest that sources of task self-efficacy should be considered for exercise interventions targeting older adults.

Genetic programming for the RoboCup Rescue Simulation System

The Robocup Rescue Simulation System (RCRSS) is a dynamic system of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. This thesis provides the first known attempt of applying Genetic Programming (GP) to the development of behaviours necessary to perform well in the RCRSS. Specifically, this thesis studies the suitability of GP to evolve the operational behaviours required of each type of rescue agent in the RCRSS. The system developed is evaluated in terms of the consistency with which expected solutions are the target of convergence as well as by comparison to previous competition results. The results indicate that GP is capable of converging to some forms of expected behaviour, but that additional evolution in strategizing behaviours must be performed in order to become competitive. An enhancement to the standard GP algorithm is proposed which is shown to simplify the initial search space allowing evolution to occur much quicker. In addition, two forms of population are employed and compared in terms of their apparent effects on the evolution of control structures for intelligent rescue agents. The first is a single population in which each individual is comprised of three distinct trees for the respective control of three types of agents, the second is a set of three co-evolving subpopulations one for each type of agent. Multiple populations of cooperating individuals appear to achieve higher proficiencies in training, but testing on unseen instances raises the issue of overfitting.

Nietzsche's children : a physiological analysis of the scholar's task

Throughout Nietzsche's writings we find discussions of the proper relationship of the scholar/scientist to the philosopher, wi th the scholar of ten being presented in a derogatory light. In this thesis, I examine Nietzsche's por t rai t of the scholar through the lens of his physiological or clinical perspective as articulated by Dr. Daniel R. Ahern in his monograph entitled Nietzsche as Cultural Physician. My aim in doing so is to grasp the affirmative, creative aspect of this seemingly destructive polemic against scholars. I begin wi th a detailed discussion of Nietzsche's por t rai t of the scholar in Beyond Good and Evil. This includes an explication of Ahern's position, followed by an application of the diagnostic perspective to Nietzsche's discussion of the objective type, the skeptic, and the critic. I then look at how the characteristics of all three types are present in the Nietzschean 'free spirit.' I also discuss the physiological basis of esotericism in Nietzsche's work, as well as Nietzsche's revaluation of the scholarly vi r tue known as Red/ichkeit (or 'honesty'). I conclude wi th comments on the free spirit's relationship to the future.

Automatic Structure Generation using Genetic Programming and Fractal Geometry

Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented, with a focus on both performance and visual results. Although subjective, these results o er insight into future applications and study in the fi eld of computational aesthetics and automated structure design.

A stochastic dynamic programming approach for pricing options on stock-index futures

The aim of this thesis is to price options on equity index futures with an application to standard options on S&P 500 futures traded on the Chicago Mercantile Exchange. Our methodology is based on stochastic dynamic programming, which can accommodate European as well as American options. The model accommodates dividends from the underlying asset. It also captures the optimal exercise strategy and the fair value of the option. This approach is an alternative to available numerical pricing methods such as binomial trees, finite differences, and ad-hoc numerical approximation techniques. Our numerical and empirical investigations demonstrate convergence, robustness, and efficiency. We use this methodology to value exchange-listed options. The European option premiums thus obtained are compared to Black's closed-form formula. They are accurate to four digits. The American option premiums also have a similar level of accuracy compared to premiums obtained using finite differences and binomial trees with a large number of time steps. The proposed model accounts for deterministic, seasonally varying dividend yield. In pricing futures options, we discover that what matters is the sum of the dividend yields over the life of the futures contract and not their distribution.

The effects of estimating good vs. poor knowledge of results during acquisition of a spatial motor task

Recent studies have shown that providing learners Knowledge of Results (KR) after “good trials” rather than “poor trials” is superior for learning. The present study examined whether requiring participants to estimate their three best or three worst trials in a series of six trial blocks before receiving KR would prove superior to learning compared to not estimating their performance. Participants were required to push and release a slide along a confined pathway using their non-dominant hand to a target distance (133cm). The retention and transfer data suggest those participants who received KR after good trials demonstrated superior learning and performance estimations compared to those receiving KR after poor trials. The results of the present experiment offer an important theoretical extension in our understanding of the role of KR content and performance estimation on motor skill learning.

A Home at School: Building Stronger Indigenous People through Cultural Resurgence in an Urban Ontario Public School Context.

In this thesis, I work through the educational narratives of young Aboriginal women and men as I explore the relationship between cultural programming and student engagement. My analysis is structured through a collaborative Indigenous research project. My overarching task is to explore how a cultural support program, the Native Youth Advancement with Education Hamilton (NYA WEH) Program, offered at Sir John A. Macdonald Secondary School, located in Hamilton, Ontario, Canada, attempts to re-imagine Aboriginal education in ways that directly challenge the residential school legacy. In particular, I work to illuminate how particular forms of Aboriginal education are connected to the graduation rates of Aboriginal youth. I argue that the ways in which the NYA WEH Program navigates Native Studies curriculum, relationships, and notions of culture and tradition are significant to the engagement of Aboriginal youth. This research develops theoretical connections between the contemporary experience of Aboriginal social inequality and educational initiatives which attempt to reverse that legacy. By placing the NYA WEH Program narratives side-by-side with literature supporting Aboriginal education for Self-determination, I work to learn how to best support and encourage Aboriginal student engagement in secondary schools across Ontario.

Equational Reasoning about Object-Oriented Programs

Formal verification of software can be an enormous task. This fact brought some software engineers to claim that formal verification is not feasible in practice. One possible method of supporting the verification process is a programming language that provides powerful abstraction mechanisms combined with intensive reuse of code. In this thesis we present a strongly typed functional object-oriented programming language. This language features type operators of arbitrary kind corresponding to so-called type protocols. Sub classing and inheritance is based on higher-order matching, i.e., utilizes type protocols as basic tool for reuse of code. We define the operational and axiomatic semantics of this language formally. The latter is the basis of the interactive proof assistant VOOP (Verified Object-Oriented Programs) that allows the user to prove equational properties of programs interactively.

Genetic Programming for Non-Photorealistic Rendering

This thesis focuses on developing an evolutionary art system using genetic programming. The main goal is to produce new forms of evolutionary art that filter existing images into new non-photorealistic (NPR) styles, by obtaining images that look like traditional media such as watercolor or pencil, as well as brand new effects. The approach permits GP to generate creative forms of NPR results. The GP language is extended with different techniques and methods inspired from NPR research such as colour mixing expressions, image processing filters and painting algorithm. Colour mixing is a major new contribution, as it enables many familiar and innovative NPR effects to arise. Another major innovation is that many GP functions process the canvas (rendered image), while is dynamically changing. Automatic fitness scoring uses aesthetic evaluation models and statistical analysis, and multi-objective fitness evaluation is used. Results showed a variety of NPR effects, as well as new, creative possibilities.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

The effect of perturbation warning on attention switching abilities during dual-task performance in young and older adults

This study examined whether providing an auditory warning would facilitate attention switching abilities in older adults during dual-tasking. Fifteen young and 16 older adults performed a tracking task while recovering their balance from a support surface translation. For half of the trials, an auditory warning was presented to inform participants of the upcoming translation. Performance was quantified through electromyographic (EMG) recordings of the lower limb muscles, while the ability to switch attention between tasks was determined by tracking task error. Providing warning of an upcoming loss of balance resulted in both young and older adults increasing their leg EMG activity by 10-165% (p<0.05) in preparation for the upcoming translation. However, no differences in the timing of attention switching were observed with or without the warning (p=0.424). Together, these findings suggest that providing a perturbation warning has minimal benefits in improving attention switching abilities for balance recovery in healthy older adults.

The effects of consistency and inconsistency between attentional focus and task objective in learning a golf putting task

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.

Passive Solar Building Design Using Genetic Programming

Passive solar building design is the process of designing a building while considering sunlight exposure for receiving heat in winter and rejecting heat in summer. The main goal of a passive solar building design is to remove or reduce the need of mechanical and electrical systems for cooling and heating, and therefore saving energy costs and reducing environmental impact. This research will use evolutionary computation to design passive solar buildings. Evolutionary design is used in many research projects to build 3D models for structures automatically. In this research, we use a mixture of split grammar and string-rewriting for generating new 3D structures. To evaluate energy costs, the EnergyPlus system is used. This is a comprehensive building energy simulation system, which will be used alongside the genetic programming system. In addition, genetic programming will also consider other design and geometry characteristics of the building as search objectives, for example, window placement, building shape, size, and complexity. In passive solar designs, reducing energy that is needed for cooling and heating are two objectives of interest. Experiments show that smaller buildings with no windows and skylights are the most energy efficient models. Window heat gain is another objective used to encourage models to have windows. In addition, window and volume based objectives are tried. To examine the impact of environment on designs, experiments are run on five different geographic locations. Also, both single floor models and multi-floor models are examined in this research. According to the experiments, solutions from the experiments were consistent with respect to materials, sizes, and appearance, and satisfied problem constraints in all instances.