The World Wide Web provides a new communicated environment for learning. In this research, we developed the ¡§online tutoring agents¡¨ to improve students¡¦ learning with the functionality of user profiles¡¦ tracking, recording, analysis and feedback. To solve students¡¦ problems in system adaptability and learning progress control, we provided necessary messages for user and real-time feedback according to their profiles. We have developed a novel learning environment for different students according to their demands. To assist student and teacher for completing their works, our research implemented ¡§online tutoring agents¡¨ in e-learning system. For students, ¡§online tutoring agents¡¨ supports group corporations, learning guideline and learning activities. Our ¡§online tutoring agents¡¨ provided the effective learning environment to save time for students. For teachers, ¡§online tutoring agents¡¨ can assist teacher to control schedule and students¡¦ learning activities as well as term project progress. The ¡§online tutoring agents¡¨ we proposed can provide good and customized environment for both teachers and students.

The constructivist grounded theory, actualizing collaborative learning, conceptualizes how British Columbia primary grade teachers interacted with the professional learning endeavour Changing Results for Young Readers (CR4YR). CR4YR was a British Columbia Ministry of Education initiated and co-facilitated cross-school Network Learning Community that included educators from four levels of the school system. While Network Learning Communities, such as the CR4YR initiative, have been increasingly utilized as professional learning models for educators, a review of the literature indicated that questions remained as to how teachers, who were unaccustomed to collaborative learning endeavour, adapted to environments in which vulnerability was the primary learning tool. This study addressed this knowledge gap. The theory, actualizing collaborative learning, emerged from analysis of data gathered through semi-structured interviews with 22 CR4YR participants in five British Columbia school districts. The interviewees included school district administrators, Reading Advocates, and teachers. The resulting theory specifies that collaborative learning in CR4YR was built upon the interaction of the four sub-processes: establishing trust, identifying with collaborative learning, becoming vulnerable, and mobilizing collaboration to the school. The participants’ utilization of the four sub-processes was impacted by three contextual factors which were skilled leadership, interlinking points of contact, and the extended time period allocated for the CR4YR initiative. The theory extends current conceptualizations of professional learning in network learning communities by identifying the contextual factors and sub-processes that support teachers as they acclimatize to collaborative learning in cross-school environments with representation from multiple levels of the school system. / Graduate / wilmot94@telus.net

Supply chain management (SCM) is the oversight of materials, information, and finances as they move in a process from supplier to manufacturer to wholesaler to retailer to consumer. Supply chain management involves coordinating and integrating these flows both within and among companies as efficiently as possible. The supply chain consists of interconnected components that can be complex and dynamic in nature. Therefore, an interruption in one subnetwork of the system may have an adverse effect on another subnetworks, which will result in a supply chain disruption. Disruptions from an event or series of events can have costly and widespread ramifications. When a disruption occurs, the speed at which the problem is discovered becomes critical. There is an urgent need for efficient monitoring of the supply chain. By examining the vulnerability of the supply chain network, supply chain managers will be able to mitigate risk and develop quick response strategies in order to reduce supply chain disruption. However, modeling these complex supply chain systems is a challenging research task. This research is concerned with developing an extended Bayesian Network approach to analyze supply chain disruptions. The aim is to develop strategies that can reduce the adverse effects of the disruptions and hence improve overall system reliability. The supply chain disruptions is modeled using Bayesian Networks-a method of modeling the cause of current and future events, which has the ability to model the large number of variables in a supply chain and has proven to be a powerful tool under conditions of uncertainty. Two impact factors are defined. These are the Bayesian Impact Factor (BIF) and the Node Failure Impact Factor (NFIF). An industrial example is used to illustrate the application proposed to make the supply chain more reliable.

A Bayesian network approach to self-organization and learning is introduced for use with intelligent agents. Bayesian networks, with the help of influence diagrams, are employed to create a decision-theoretic intelligent agent. Influence diagrams combine both Bayesian networks and utility theory. In this research, an intelligent agent is modeled by its belief, preference, and capabilities attributes. Each agent is assumed to have its own belief about its environment. The belief aspect of the intelligent agent is accomplished by a Bayesian network. The goal of an intelligent agent is said to be the preference of the agent and is represented with a utility function in the decision theoretic intelligent agent. Capabilities are represented with a set of possible actions of the decision-theoretic intelligent agent. Influence diagrams have utility nodes and decision nodes to handle the preference and capabilities of the decision-theoretic intelligent agent, respectively. Learning is accomplished by Bayesian networks in the decision-theoretic intelligent agent. Bayesian network learning methods are discussed intensively in this paper. Because intelligent agents will explore and learn the environment, the learning algorithm should be implemented online. None of the existent Bayesian network learning algorithms has online learning. Thus, an online Bayesian network learning method is proposed to allow the intelligent agent learn during its exploration. Self-organization of the intelligent agents is accomplished because each agent models other agents by observing their behavior. Agents have belief, not only about environment, but also about other agents. Therefore, an agent takes its decisions according to the model of the environment and the model of the other agents. Even though each agent acts independently, they take the other agents behaviors into account to make a decision. This permits the agents to organize themselves for a common task. To test the proposed intelligent agent's learning and self-organizing abilities, Windows application software is written to simulate multi-agent systems. The software, IntelliAgent, lets the user design decision-theoretic intelligent agents both manually and automatically. The software can also be used for knowledge discovery by employing Bayesian network learning a database. Additionally, we have explored a well-known herding problem to obtain sound results for our intelligent agent design. In the problem, a dog tries to herd a sheep to a certain location, i.e. a pen. The sheep tries to avoid the dog by retreating from the dog. The herding problem is simulated using the IntelliAgent software. Simulations provided good results in terms of the dog's learning ability and its ability to organize its actions according to the sheep's (other agent) behavior. In summary, a decision-theoretic approach is applied to the self-organization and learning problems in intelligent agents. Software was written to simulate the learning and self-organization abilities of the proposed agent design. A user manual for the software and the simulation results are presented. This research is supported by the Office of Naval Research with the grant number N00014-98-1-0779. Their financial support is greatly appreciated. / Ph. D.

This thesis examines the collaborative development of corporate responsibility (CR) standards from the perspective of organisational learning theory. The author proposes that standards development projects can be understood as Network Learning episodes where learning is reflected in changes in structures, interpretations and practices accompanied by learning processes. Network Learning alone is seen as insufficient to reflect the diverse contributions and outcomes in the special case of CR standards. Concepts from multi-stakeholder learning like the role of dissensus in learning and the empowerment of weaker stakeholders are therefore used to create a synthesis of the two theories in a single conceptual framework. This framework is then tested against a pilot case and three case studies of corporate social responsibility (CSR) standards including the development of the new ISO international standard on social responsibility (SR). The data validates and extended this framework to yield a Multi-Stakeholder Network Learning theory capable of describing the how participants and non-participant stakeholders learn in this context. New concepts are generated from the data, like dislocated learning, which demonstrate how participants in the process and those they represent can experience quite different learning outcomes. Stakeholders whose learning is aligned with the learning of their participant representatives truly have a stake in these influential standards. However, where representatives fail to learn from those represented, the latter's stake is diminished. By shedding light on the mechanisms of effective collaborative learning this work contributes to learning theory, the practice of standardization and the normative stakeholder empowerment agenda.

This thesis examines the collaborative development of corporate responsibility (CR) standards from the perspective of organisational learning theory. The author proposes that standards development projects can be understood as Network Learning episodes where learning is reflected in changes in structures, interpretations and practices accompanied by learning processes. Network Learning alone is seen as insufficient to reflect the diverse contributions and outcomes in the special case of CR standards. Concepts from multi-stakeholder learning like the role of dissensus in learning and the empowerment of weaker stakeholders are therefore used to create a synthesis of the two theories in a single conceptual framework. This framework is then tested against a pilot case and three case studies of corporate social responsibility (CSR) standards including the development of the new ISO international standard on social responsibility (SR). The data validates and extended this framework to yield a Multi-Stakeholder Network Learning theory capable of describing the how participants and non-participant stakeholders learn in this context. New concepts are generated from the data, like dislocated learning, which demonstrate how participants in the process and those they represent can experience quite different learning outcomes. Stakeholders whose learning is aligned with the learning of their participant representatives truly have a stake in these influential standards. However, where representatives fail to learn from those represented, the latter¿s stake is diminished. By shedding light on the mechanisms of effective collaborative learning this work contributes to learning theory, the practice of standardization and the normative stakeholder empowerment agenda. / British Standards Institution

Electronic commerce is in a state of growth and the number of firms engaging in electronic commerce has increased rapidly during the late 1990s. As a result, electronic commerce has become an essential part of commercial life. As firms have struggled to implement electronic commerce there have been successes and failures. Hence there is a need to improve our understanding of how electronic commerce can and should be deployed.  In this thesis electronic commerce is explored and discussed in terms of what firms need to know and how they can acquire that knowledge in order to engage in electronic commerce to remain or become competitive. The focus is on the process of acquiring new capabilities for electronic commerce. Capabilities are regarded as high-performance routines that can reside within and between organisations and confer a firm with a temporary competitive advantage. These capabilities can be acquired by utilisation of four categories of means: in-house innovation, cloning, collaboration and firm purchasing.  Four hypothesises for understanding and explaining capability acquisition are formulated with regard to how the means can be used. By surveying the literature, drawing on numerous research traditions in an eclectic manner, it is posited that the supply of capabilities, the current capability portfolio, the nature and maturity of the firm trajectory, and the performance of the firm influence the capability acquisition process.  The cases of Compaq and Dell in Sweden are employed to investigate the issue of capability acquisition. Compaq has utilised an indirect approach working through intermediaries, while Dell has utilised a direct approach working directly with customers. The cases are analysed with the four hypothesises. Five capabilities are identified as critical for electronic commerce: addressability, interactivity, customisation, personalisation and postponement. It is shown that these capabilities are acquired in a process following a trajectory. This process involves suppliers, partners, customers and competitors. It is shown that firms working indirectly acquire capabilities mainly from competitors. In contrast, firms working directly acquire capabilities mainly from customers. Furthermore, working directly with customers – as opposed to working indirectly – is found to be a good vehicle for acquiring electronic commerce capability. / Diss. Stockholm : Handelshögsk., 2002

The Bayesian network (BN) formalism is a powerful representation for encoding domains characterised by uncertainty. However, before it can be used it must first be constructed, which is a major challenge for any real-life problem. There are two broad approaches, namely the hand-crafted approach, which relies on a human expert, and the data-driven approach, which relies on data. The former approach is useful, however issues such as human bias can introduce errors into the model. We have conducted a literature review of the expert-driven approach, and we have cherry-picked a number of common methods, and engineered a framework to assist non-BN experts with expert-driven construction of BNs. The latter construction approach uses algorithms to construct the model from a data set. However, construction from data is provably NP-hard. To solve this problem, approximate, heuristic algorithms have been proposed; in particular, algorithms that assume an order between the nodes, therefore reducing the search space. However, traditionally, this approach relies on an expert providing the order among the variables --- an expert may not always be available, or may be unable to provide the order. Nevertheless, if a good order is available, these order-based algorithms have demonstrated good performance. More recent approaches attempt to ''learn'' a good order then use the order-based algorithm to discover the structure. To eliminate the need for order information during construction, we propose a search in the entire space of Bayesian network structures --- we present a novel approach for carrying out this task, and we demonstrate its performance against existing algorithms that search in the entire space and the space of orders. Finally, we employ the hand-crafting framework to construct models for the task of diagnosis in a ''real-life'' medical domain, dementia diagnosis. We collect real dementia data from clinical practice, and we apply the data-driven algorithms developed to assess the concordance between the reference models developed by hand and the models derived from real clinical data.

This paper discusses the need to be teaching practice linked to the universe of Digital Technologies of Information and Communication, based on the social networking use of perspective in education and expanding the times and formal learning settings, It is understood social networks as favorable spaces the sharing of information and knowledge and therefore profitable to develop pedagogical practices that need to be disseminated in order to encourage greater use in the school environment. The research aims to analyze the use of social networking as an enriching learning environment of the classroom teaching practice, from an experience developed by the researcher in the optional Portuguese Instrumental discipline, offered by the Department of Arts of the Federal University of Sergipe, which we used the Facebook social networking platform for this purpose. To achieve this goal, established themselves as specific research objectives: discuss the relationship between the use of Digital Technologies of Information and Communication on the relationship between school, work and society in the twenty-first century; present the theoretical basis for the networked learning and communication; present the possibilities of using existing resources on Facebook as a learning environment and evaluate the proposed use of Facebook in support of teaching practice under the student perspective. The subjects are the seventeen students of the discipline, from different areas of graduation, because discipline is optional character for most courses. The research, qualitative approach was performed using the method of the Research Training, using as research tools participant observation in the classroom and in the group created for the discipline on Facebook, a questionnaire with open and closed questions, applied to the end the course and in order to evaluate the proposal from the perspective of future teachers, there was a semi-structured interview only intended for undergraduates students in the class. The collected data were analyzed in the light of the categories set, the results showed the importance of associating platforms and social software to teaching proposals to enhance communication, interaction and participation among students, expanding the times and spaces of learning. However, the biggest search attribute is related to the experience nurtured in the initial training of future teachers, linking theory and practice in the process, promoting new perspectives on the use of Digital Technologies of Information and Communication in education and encouraging future practices in the teaching profession the results will be better perceived in the school ground, in promoting a more connected education with society and with today´s work environment. / Esta dissertação discute a necessidade da prática de ensino estar atrelada ao universo das Tecnologias Digitais de Informação e Comunicação, partindo da perspectiva de uso de redes sociais na educação e expandindo os tempos e espaços formais de aprendizagem, Compreende-se as redes sociais como espaços favoráveis ao compartilhamento de informação e conhecimento e, portanto, profícuas ao desenvolvimento de práticas pedagógicas que precisam ser disseminadas, a fim de fomentar uma maior utilização no ambiente escolar. A pesquisa tem por objetivo analisar a utilização da rede social como ambiente de aprendizagem enriquecedor da prática de ensino presencial, a partir de uma experiência desenvolvida pela pesquisadora na disciplina optativa Português Instrumental, ofertada pelo Departamento de Letras da Universidade Federal de Sergipe, onde se utilizou da plataforma de rede social Facebook para este fim. Para alcançar tal objetivo, estabeleceram-se como objetivos específicos da pesquisa: discutir as relações entre o uso das Tecnologias Digitais de Informação e Comunicação na relação entre escola, trabalho e sociedade no século XXI; apresentar as bases teóricas para a aprendizagem e comunicação em rede; apresentar as possibilidades de uso dos recursos existentes no Facebook como ambiente de aprendizagem e avaliar a proposta de utilização do Facebook como suporte da prática docente, sob a perspectiva discente. Os sujeitos da pesquisa são os dezessete estudantes da disciplina, oriundos de áreas diversas da graduação, pois a disciplina é de caráter optativo para a maioria dos cursos. A pesquisa, de abordagem qualitativa, foi realizada através do método da Pesquisa-formação, utilizando como instrumentos de pesquisa a observação participante em sala de aula e no grupo criado para a disciplina no Facebook, um questionário com perguntas abertas e fechadas, aplicados ao final do curso e, a fim de avaliar a proposta sob o olhar dos futuros docentes, realizou-se uma entrevista semi-estruturada direcionada apenas aos alunos licenciandos da turma. Os dados coletados foram analisados à luz das categorias estabelecidas, cujos resultados evidenciaram a relevância de se associarem plataformas e softwares sociais às propostas de ensino para potencializar a comunicação, a interação e a participação entre os estudantes, ampliando os tempos e espaços de aprendizagem. Porém, o maior atributo da pesquisa relaciona-se à experiência oportunizada na formação inicial dos futuros docentes, articulando teoria e prática no processo, promovendo novos olhares acerca do uso das Tecnologias Digitais de Informação e Comunicação na educação e incentivando futuras práticas no exercício da docência, cujos resultados serão melhor percebidos no chão da escola, na promoção de uma educação mais conectada com a sociedade e com o ambiente de trabalho da atualidade.

In this thesis the major objective is the implementation of the inverse neural network concept in the design of printed lens (transmitarray) antenna. As it is computationally extensive to perform full-wave simulations for entire transmitarray structure and thereafter perform optimization, the idea is to generate a design database assuming that a unit cell of the transmitarray is situated inside a 2D infinite periodic structure. This way we generate a design database of transmission coefficient by varying the unit cell parameters. Since, for the actual design, we need dimensions for each cell on the transmitarray aperture and to do this we need to invert the design database. The major contribution of this thesis is the proposal and the implementation of database inversion methodology namely inverse neural network modelling. We provide the algorithms for carrying out the inversion process as well as provide check results to demonstrate the reliability of the proposed methodology. Finally, we apply this approach to design a transmitarray antenna, and measure its performance.