Perceived effectiveness of alternative programming : a case study /

The topic of this research was alternative programming in secondary public education. The purpose of this research was to explore the perceived effectiveness of two public secondary programs that are aJternative to mainstream or "regular" education. Two case study sites were used to research diverse ends of the aJtemative programming continuum. The first case study demonstrated a gifted program and the second demonstrated a behavioral program. Student needs were examined in terms of academic needs, emotional needs, career needs, and social needs. Research conducted in these sites examined how the students, teachers, onsite staff, and program administrators perceived that individual needs were met and unmet in these two programs. The study was qualitative and exploratory, using deductive and inductive research techniques. Similar themes of best practice that were identified in the case study sites aided in the development of a teaching and learning model. Four themes were identified as important within the case study sites. These themes included the commitment and motivation of teachers and the support of administration in the gifted program, and the importance of location and the flow of information and communication in the behavior program. Six themes emerged that were similar across the case study sites. These themes included the individual nature of programming, recognition of student achievement, the alternative program as a place of safety and community, importance of interpersonal capacity, priority of basic needs, and, finally, matching student capacity with program expectations. The model incorporates these themes and is designed as a resource for teachers, program administrators, parents, and policy makers of alternative educational programs.

Simultaneous extraction of order parameters and orientational distribution fuctions from 31[superscript]P NMR spectra of magnetically partially oriented phospholipid bilayers

Order parameter profiles extracted from the NMR spectra of model membranes are a valuable source of information about their structure and molecular motions. To al1alyze powder spectra the de-Pake-ing (numerical deconvolution) ~echnique can be used, but it assumes a random (spherical) dist.ribution of orientations in the sample. Multilamellar vesicles are known to deform and orient in the strong magnetic fields of NMR magnets, producing non-spherical orientation distributions. A recently developed technique for simultaneously extracting the anisotropies of the system as well as the orientation distributions is applied to the analysis of partially magnetically oriented 31p NMR spectra of phospholipids. A mixture of synthetic lipids, POPE and POPG, is analyzed to measure distortion of multilamellar vesicles in a magnetic field. In the analysis three models describing the shape of the distorted vesicles are examined. Ellipsoids of rotation with a semiaxis ratio of about 1.14 are found to provide a good approximation of the shape of the distorted vesicles. This is in reasonable agreement with published experimental work. All three models yield clearly non-spherical orientational distributions, as well as a precise measure of the anisotropy of the chemical shift. Noise in the experimental data prevented the analysis from concluding which of the three models is the best approximation. A discretization scheme for finding stability in the algorithm is outlined

The impact of integrated programming on student attitude and achievement in grade 9 academic mathematics and science

This research studioo the effect of integrated instruction in mathematics and~ science on student achievement in and attitude towards both mathematics and science. A group of grade 9 academic students received instruction in both science and mathematics in an integrated program specifically developed for the purposes of the research. This group was compared to a control group that had received science and mathematics instruction in a traditional, nonintegrated program. The findings showed that in all measures of attitude, there was no significant difference between the students who participated in the integrated science and mathematics program and those who participated in a traditional science and mathematics program. The findings also revealed that integration did improve achievement on some of the measures used. The performance on mathematics open-ended problem-solving tasks improved after participation in the integrated program, suggesting that the integrated students were better able to apply their understanding of mathematics in a real-life context. The performance on the final science exam was also improved for the integrated group. Improvement was not noted on the other measures, which included EQAO scores and laboratory practical tasks. These results raise the issue of the suitability of the instruments used to gauge both achievement and attitude. The accuracy and suitability of traditional measures of achievement are considered. It is argued that they should not necessarily be used as the measure of the value of integrated instruction in a science and mathematics classroom.

When job dissatisfaction leads to customer-oriented citizenship behaviors

This thesis places boundary conditions on the withdrawal model in the frontline setting of service organizations by considering continuance commitment and supervisory support as moderators of the relationship between job dissatisfaction and customer-oriented citizenship behaviors (COCBs). Departing from traditional research in the areas of the service-profit chain and employee withdrawal, the author advances our understanding of conditions that may lead frontline service employees who are dissatisfied to deposit COCBs into the organizational system. Specifically, based on principles derived from social exchange theory, high continuance commitment and high supervisory support are expected to lead to COCBs, because under this condition the benefits of performing such behaviors are increased (i.e., promotion-based, reciprocity-based), while the costs are decreased (i.e., opportunity costs). Utilizing a sample of 127 frontline employees from both the financial services and travel agency industries, the hypothesized relationships are empirically supported using moderated hierarchical regression analysis. To conclude discussion, implications of the results for both academics and p

Predictors of shy children's coping with a social conflict : mediators and moderators

Shy children are at risk for later maladjustment due to ineffective coping with social conflicts through reliance on avoidance, rather than approach-focused, coping. The purpose of the present study was to explore whether the relation between shyness and children's coping was mediated by attributions and moderated by personality selftheories and gender. Participants included a classroom-based sample of 175 children (93 boys), aged 9-13 years (M = 10.11 years, SD = 0.92). Children completed self-report measures assessing shyness, attributions, personality self-theories and coping strategies. Results showed that negative attribution biases partially mediated the negative relations between shyness and social support seeking, as well as problem-solving, and the positive association between shyness and externalizing. Moreover, self-theories moderated the relation between shyness and internalizing coping at the trend level, such that the positive relation was exacerbated among entity-oriented children to a greater degree than incrementally-oriented children. In terms of gender differences, shyness was related to lower use of social support and problem-solving among incrementally-oriented boys and entity-oriented girls. Thus, shy children's perceptions of social conflicts as the outcome of an enduring trait (e.g., social incompetence) may partially explain why they do not act assertively and aggress as a means of social coping. Furthermore, entity-oriented beliefs may exacerbate shy children's reliance on internalizing actions, such as crying. Although an incrementally-oriented stance may enhance shy girls' reliance on approach strategies, it does not appear to serve the same protective role for shy boys. Therefore, copingoriented interventions may need to focus on restructuring shy children's social cognitions and implementing gender-specific programming for their personality biases.

Notice of Change in Reparation Agent- Quebec 1 May 1822

A notice of change in reparation agent between Robert Morrogh and Thomas Douglas from Quebec to Daniel Shannon in Niagara.

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.

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.

Sullivan Agent Confesses, [1948]

The National Seaman’s Association was a labour recruiter hiding behind a union-like name. It was run by H.N. McMaster who collected fees from companies and dues from workers. With McMaster in charge, shipping interests could claim that their seamen had a union, but ship-owners were free to push their vessels and their workers to the breaking point. In 1935, the members on the Great Lakes decided to strike. One year later, they created their own union and amalgamated with a Montreal-based independent body to create the Canadian Seamen’s Union headed by a ship’s cook who became a union leader, John Allan Patrick “Pat” Sullivan. By the late 1940s, almost all sailors on Canadian ships were CSU members. Right from its inception in 1936, Communists were prominent among the leaders of the union. Sullivan had been recruited to the Communist party that year and the union had a close rapport with the party. On June 8, 1940, Pat Sullivan was arrested because of his affiliation with the Communist party. He was incarcerated until March 20, 1942. No charges were laid, no bail was set and there was no trial. After his release, Sullivan was elected second vice-president of the Trades and Labour Congress of Canada. In 1943, Percy Bengough was elected as president and Sullivan was elected as secretary treasurer of the TLC while maintaining his role as president of the CSU. On March 14, 1947 Sullivan made a shocking announcement that he was resigning from the CSU and the Labor-Progressive Party. He claimed that the CSU was under the full control of the Communists. Within a month of this announcement, he emerged as the president of the Canadian Lake Seamen’s Union. Ship-owners never really reconciled themselves to having their industry unionized, and in 1946 there was a seamen’s strike in which the union won the eight-hour day. In 1949, the shipping companies had a plan to get rid of the union and were negotiating behind their back with the Seafarers International Union (SIU). In a brutal confrontation, led by Hal Banks, an American ex-convict, the SIU was able to roust the CSU and take over the bargaining rights of Canadian seamen. On July 15, 1948, Robert Lindsay, who was Sullivan’s Welland business agent said that to the best of his knowledge, Sullivan’s outfit, the CLSU, was under the control of some of the Steamship Companies. Lindsay had heard that there was a movement to get rid of Bengough of the Trades and Labour Congress as well as elements of the CSU. He also had heard that the CLSU wanted to affiliate with the American Federation of Labor. Lindsay’s allegations raised the questions: Were the ship-owners powerful enough to oust Percy Bengough because he supported the seamen? Could the CLSU get an affiliation with the American Federation of Labor? and Would the American Federation of Labor actually affiliate with a union that was siding with employers against a locked-out union?

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.

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.

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM

Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages for object classification is presented. Two main GP approaches for visual pattern classification, namely the block-classifiers and the pixel-classifiers, were studied. Results showed that the pixel-classifiers generally performed better. Using these results, a suitable language was selected for the real-time implementation. Synthetic video data was used in the experiments. The goal of the experiments was to evolve a unique classifier for each texture pattern that existed in the video. The experiments revealed that the system was capable of correctly tracking the textures in the video. The performance of the system was on-par with real-time requirements.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Inverse Illumination Design with Genetic Programming

Interior illumination is a complex problem involving numerous interacting factors. This research applies genetic programming towards problems in illumination design. The Radiance system is used for performing accurate illumination simulations. Radiance accounts for a number of important environmental factors, which we exploit during fitness evaluation. Illumination requirements include local illumination intensity from natural and artificial sources, colour, and uniformity. Evolved solutions incorporate design elements such as artificial lights, room materials, windows, and glass properties. A number of case studies are examined, including many-objective problems involving up to 7 illumination requirements, the design of a decorative wall of lights, and the creation of a stained-glass window for a large public space. Our results show the technical and creative possibilities of applying genetic programming to illumination design.