In a preprint by J. Wood, V. Lomadze, and E. Rogers, chains and boundary maps were defined for 2-D discrete behavioral systems. The corresponding homology groups were studied and tied to trajectory properties. Indeed, the homology groups encapsulated the concepts of autonomy, controllability, and signal restriction. We shall present an extension of their work to n-D discrete behavioral systems. In particular, we shall streamline the construction of the chain groups, the boundary maps between chains, and the study of the resultant homology groups. While constructing this machinery, we shall point out intrinsic flaws in their approach that make extension of their results less systematic. Finishing remarks shall be made on using the homology groups to determine system properties and potentially classify forms of controllability. / Master of Science

In this study I analyze how 70 academic articles concerning Corporate Social Responsibility (CSR) deals with questions of power. Based on Michel Foucault’s discursive theory and Niklas Luhmann’s systems theory, I present a conceptualization of CSR as a discursive system. I claim that paradoxes of power are central in the development of CSR, and that second order observation is vital for the identification of such paradoxes. My analysis shows that articles published in journals related to management theory are much less aware of problems relating to power, as well as being less critical towards such issues. Nonmanagement- articles are found to identify more paradoxes, but they have lesser impact on the CSR-discourse. Power created by social order as well as power created by system bias, are found to be core issues relating to the division of power between corporations and society at large. Also frequently found to be a concern, is power created by systems of thought, indicating both a critique towards the cultural and normative influence of large corporations, as well as a strong focus on developing knowledge within the CSR-discourse. If CSR is to function as a correction of the development of corporations and society, a critical focus on all aspects of power-creation in the CSR-discourse is an important counterweight to the extensively managerial focus.

No description available.

This qualitative study was designed to explore the transition experiences of youth with learning disabilities (LD) educated in the province of Ontario and their families. The primary purpose of this research was to understand what influences the decisions adolescents who have LD make about post-secondary education and employment goals and paths. The expectations and experiences of youth with LD and their families during the transition process were investigated. Adolescents and their parents were the main informants. Facilitators and barriers to the process in terms of each of the systems described in Bronfenbrenner ecological theory and Turnbull and Turnbull’s family systems theory were also examined. A case study method was used in the design of this research and data were collected following Seidman’s three-interview process. Five families consisting of the youth with LD, at least one parent, and in four cases, a sibling participated in this study. The questions focused on family interactions, roles, and the decision-making process. Data from the 18 participants were coded and arranged according to the research questions which were linked to the central ideas in the theoretical framework. The findings revealed that parents’ expectations influenced the decision-making about post high school goals and paths by the youth and their families. In contrast to previous research, it was found that parents’ expectations were generally high for their children with LD and were shaped by their own post high school experiences. The dynamics of family relationships and roles during transition planning depended on the time of diagnosis of LD (primary grades vs. senior high school), attitudes towards LD by the parents, advocacy by parents, self-advocacy abilities of the youth with LD, and the nature of relations among siblings. Additionally, none of the youth with LD had a formal transition plan and the data showed that teachers could facilitate or hinder the transition process. Also emerging from the data were three types of advocacy that were practised by parents. The study findings add to our knowledge about the transition process and in particular how decisions are made and the factors that influence them. Moreover, this study gives a voice to youth with LD and their families as they described their transition experiences to post-secondary education or employment.

This qualitative study was designed to explore the transition experiences of youth with learning disabilities (LD) educated in the province of Ontario and their families. The primary purpose of this research was to understand what influences the decisions adolescents who have LD make about post-secondary education and employment goals and paths. The expectations and experiences of youth with LD and their families during the transition process were investigated. Adolescents and their parents were the main informants. Facilitators and barriers to the process in terms of each of the systems described in Bronfenbrenner ecological theory and Turnbull and Turnbull’s family systems theory were also examined. A case study method was used in the design of this research and data were collected following Seidman’s three-interview process. Five families consisting of the youth with LD, at least one parent, and in four cases, a sibling participated in this study. The questions focused on family interactions, roles, and the decision-making process. Data from the 18 participants were coded and arranged according to the research questions which were linked to the central ideas in the theoretical framework. The findings revealed that parents’ expectations influenced the decision-making about post high school goals and paths by the youth and their families. In contrast to previous research, it was found that parents’ expectations were generally high for their children with LD and were shaped by their own post high school experiences. The dynamics of family relationships and roles during transition planning depended on the time of diagnosis of LD (primary grades vs. senior high school), attitudes towards LD by the parents, advocacy by parents, self-advocacy abilities of the youth with LD, and the nature of relations among siblings. Additionally, none of the youth with LD had a formal transition plan and the data showed that teachers could facilitate or hinder the transition process. Also emerging from the data were three types of advocacy that were practised by parents. The study findings add to our knowledge about the transition process and in particular how decisions are made and the factors that influence them. Moreover, this study gives a voice to youth with LD and their families as they described their transition experiences to post-secondary education or employment.

No description available.

No description available.

Background/Aims: Urie Bronfenbrenner's bioecological systems model is well regarded in the field of child development. Although this model is not commonly used by literacy researchers, I argue that Bronfenbrenner's emphasis on the roles of personal characteristics, proximal processes, contextual systems, and historical time has explanatory power in the area of literacy. Methods: I review this body of literature and describe a visual representation that clarifies the relevant aspects of the theory. Results: Adoption of Bronfenbrenner's model increases the likelihood that literacy development will be understood as occurring at the site of transaction between cognitive processes and social practices. Literacy researchers who have applied this theory differ in the degree to which they have attended to Bronfenbrenner's guidance relative to adequate research practice and, as such, findings from this research range from less to more theoretically sound and useful. Conclusion: As contemporary literacy researchers consider employing Bronfenbrenner's theory to frame their work, it is necessary for them to account for all aspects of his rich and complex model.

<p>There exists many applications with so-called costly problems, which means that the objective function you want to maximize or minimize cannot be described using standard functions and expressions. Instead one considers these objective functions as ``black box'' where the parameter values are sent in and a function value is returned. This implies in particular that no derivative information is available.The reason for describing these problems as expensive is that it may take a long time to calculate a single function value. The black box could, for example, solve a large system of differential equations or carrying out a heavy simulation, which can take anywhere from several minutes to several hours!These very special conditions therefore requires customized algorithms. Common optimization algorithms are based on calculating function values every now and then, which usually can be done instantly. But with an expensive problem, it may take several hours to compute a single function value. Our main objective is therefore to create algorithms that exploit all available information to the limit before a new function value is calculated. Or in other words, we want to find the optimal solution using as few function evaluations as possible.A good example of real life applications comes from the automotive industry, where on the development of new engines utilize advanced models that are governed by a dozen key parameters. The goal is to optimize the model by changing the parameters in such a way that the engine becomes as energy efficient as possible, but still meets all sorts of demands on strength and external constraints.</p>

There exists many applications with so-called costly problems, which means that the objective function you want to maximize or minimize cannot be described using standard functions and expressions. Instead one considers these objective functions as ``black box'' where the parameter values are sent in and a function value is returned. This implies in particular that no derivative information is available.The reason for describing these problems as expensive is that it may take a long time to calculate a single function value. The black box could, for example, solve a large system of differential equations or carrying out a heavy simulation, which can take anywhere from several minutes to several hours!These very special conditions therefore requires customized algorithms. Common optimization algorithms are based on calculating function values every now and then, which usually can be done instantly. But with an expensive problem, it may take several hours to compute a single function value. Our main objective is therefore to create algorithms that exploit all available information to the limit before a new function value is calculated. Or in other words, we want to find the optimal solution using as few function evaluations as possible.A good example of real life applications comes from the automotive industry, where on the development of new engines utilize advanced models that are governed by a dozen key parameters. The goal is to optimize the model by changing the parameters in such a way that the engine becomes as energy efficient as possible, but still meets all sorts of demands on strength and external constraints.