Traffic information, now available through a number of different sources, is re-shaping the way planners, operators and users think about the transportation network. It provides a powerful tool to mitigate the negative impacts of uncertainty, and an invaluable resource to manage and operate the network in real-time. More information also invites to think about traditional transportation problems from a different perspective, searching for a better utilization of the improved knowledge of the network state. This dissertation is concerned with modeling and evaluating the system-level impacts of providing information to network users, assuming that the data is utilized to guide an Adaptive System-Optimum (ASO) routing behavior. Within this context, it studies the optimal deployment of sensors for the support of ASO strategies, and it introduces a novel SO assignment approach, the Information-Based System Optimum (IBSO) assignment paradigm. The proposed sensor deployment model explicitly captures the impact of sensors' location on the expected cost of ASO assignment strategies. Under such strategies, a-priori routing decisions may be adjusted based on real-time information. The IBSO assignment paradigm leads to optimal flow patterns which take into account the ability of vehicles to collect information as they travel. The approach regards a subset of the system's assets as probes, which may face higher expected costs than regular vehicles in the search for information. The collected data is utilized to adjust routing decisions in real time, improving the expected system performance. The proposed problem captures the system-level impact of adaptive route choices on stochastic networks. The models developed in this work are rigorously formulated, and their properties analyzed to support the generation of specialized solution methodologies based on state-space partitioning and Tabu Search principles. Solution techniques are tested under a variety of scenarios, and implemented to the solution of several case studies. The magnitude and nature of the information impacts observed in this study illustrate problem characteristics with important theoretical, methodological and practical implications. The findings presented in this dissertation allow envisioning a number of practical applications which may promote a more efficient utilization of novel sensing and communication technologies, allowing the full realization of their potential. / text

In the past, most entrepreneurship researches were constructed on static, unilateral, single-level perspectives. They were used to adopt logic positivism as methodology so that it¡¦s hard to see the dynamic process of entrepreneurship. In this paper, I avoid following such paradigm and seek a novel solution in entrepreneurship study. I adopt complexity adaptive system (CAS) as a new theoretical perspective and narrative inquiry as a fresh methodology. In this way, entrepreneurship is viewed as a dynamic process, and all the accounts are arranged in four entrepreneurship stories: ¡§The first step : far from equilibrium¡¨, ¡§Strange attractors : vision and core capability¡¨, ¡§Dawn of the chaos : self-organization¡¨, and ¡§The pattern accompanied innovation: emergence¡¨. Through the lens of CAS, this research expresses that successful entrepreneurship is simply not the result of perfect planning in advance or opportunity identification. In fact, entrepreneurs try to enact self-organizing through interactions with the outsiders and finally generate innovation. Organizations should view chaos as normal condition thus they can keep evolution to survive. With these metaphors, the research attempt to inspire entrepreneurs and make their entrepreneurship come off.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第20507号 / 情博第635号 / 新制||情||110(附属図書館) / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 石田 亨, 教授 矢守 克也, 教授 吉川 正俊 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

Multi-Agent Systems (MASs) and Partial and Ordinary Differential Equations (PDEs and ODEs respectively) have often been employed by researchers to effectively model and simulate Complex Adaptive Systems (CASs). PDEs and ODEs are reduction based approaches which view the system globally and ignore any local interactions and processes. MASs are considered by many to be a better tool to model CASs, but have issues as well. Case in point, there is concern that present day MASs fail to capture the true essence of inter-cellular communication in a CAS. In this work we present a realistic and utilizable communication framework for inter-agent communication for a CAS simulation. We model the dynamic properties of the communication signals and show that our model is a realistic model for inter-cellular communication. We validate our system by modeling and simulating pattern formation in Dictyostelium discoideum, a unicellular organism. / Master of Science

The current research used grounded theory methodology (GTM) to construct a conceptualization of personal knowledge within a knowledge management (KM) perspective. The need for the current research was based on the use of just two categories of knowledge, explicit and tacit, within KM literature to explain diverse characteristics of personal knowledge. The construct of tacit knowledge has often been explicated and debated in KM literature. The debate over tacit knowledge arose from the complex epistemological roots of tacit knowing and the construct of tacit knowledge popularized by organizational knowledge creation theory. The ongoing debate over tacit knowledge in KM literature has shed little light on personal knowledge within a KM perspective. The current research set aside the debate over tacit knowledge and pursued the construct of personal knowledge from the perspective of the knower using GTM. Thirty-seven interviews were conducted with fourteen participants. Interviews were audio recorded and coding was accomplished with the qualitative data analysis software MAXQDA. A total of eight categories were identified. These were organized into two groups. The core category being overwhelmed represented the absence of personal knowledge. The categories questioning self, seeking help, and microthinking fit under being overwhelmed. Together these categories were inverse indicators because they all decreased as knowledge acquisition progressed. The core category being confident represented the presence of personal knowledge. The categories remembering, multitasking, and speed fit under being overwhelmed. Together these categories were direct indicators because they all increased as knowledge acquisition progressed. Three significant conclusions were drawn from the current research. These conclusions led to the conceptualization of personal knowledge from a KM perspective. The first significant conclusion was the conceptualization of a process of knowing as Integrated Complexity: From Overwhelmed to Confident (ICOC). The second significant conclusion was personal knowing as first-person epistemology is a universally lived experience that includes commitments to internal and external requirements as well as a bias toward integration. The third significant conclusion was personal knowledge can be viewed as a complex adaptive system. Finally, the current research concluded that personal knowledge within a KM perspective is a complex adaptive system maintained through acts of first-person epistemology.

Emergency response team (ERT) member characteristics that contribute to High Reliability performance during patient care resuscitation events or other Critical Incident Management Situations are poorly understood. Findings from this study describe individual characteristics that experienced interprofessional ERT members perceive as contributing to High Reliability performance within the critical incident management context. This study supports the need for interprofessional research about emergency response teams’ High Reliability in hospital-based settings. ERT High Reliability, or “better than expected” team performance has been linked to overall patient care and safety. The purpose of this study was to identify and describe individual team member characteristics that contribute to High Reliability performance of ERT members and the overall emergency response team in a naturalistic setting during Critical Incident Management Situations. Using a qualitative descriptive design, data collection included participant observations, field notes, and interviews. Narrative data were audio-taped, transcribed and coded using Ethnograph v6©. Data content were analyzed thematically using inductive interpretive methods. Two major domains derived from the data were Self-Regulation and Whole-Team Regulation. The overarching theme, Orchestrating High Reliability at the Edge of Chaos, encompassed characteristics contributing to High Reliability performance of the ERT during Critical Incident Management Situations.

Thesis (Ph.D.), Faculty of Humanities, School of Education, University of the Witwatersrand, 2009 / People who hold doctoral degrees are considered valuable national resources able to produce knowledge to address pressing problems, and important sources of labour for the higher education sector. However, in 2006, only 1100 people graduated with doctoral degrees in South Africa. This limits the potential for research and improvements in higher education. In addition, 618 of those graduates were white, making it difficult to address equity concerns. Within the higher education sector there are debates about how to increase enrolments in doctoral education and the best way to run PhD programmes for effective learning, high quality research results and for efficiency. But there is little South African-based empirical research into what makes people undertake PhDs, how the programmes work and what learning and knowledge result. This study explores how different stakeholders – national and institutional policymakers, academic staff and doctoral people – understand the PhD; how these understandings influence the practice of doctoral education; and how different practices affect the PhD experience and the learning and knowledge produced. The primary research question I address is: “How do existing models and pedagogies of doctoral programmes shape the learning of doctoral people and the outcomes of doctoral programmes in South Africa?” The origins of the Doctor of Philosophy degree are often traced back to the nineteenth century reforms of German universities when the idea emerged that all scholars should be actively involved in research. But this is a simplistic view. By examining the evolution of the PhD in greater depth, it becomes clear that it has undergone continuous change and has always served both the high-minded pursuit of knowledge and the more prosaic pursuit of skills for employment. The literature reflects ongoing tension between the scholarly view of the PhD as knowledge generation by an emerging scholar, and the labour market view of the PhD as developing high-level research skills. In the South African context both of these views can be observed, but I also identified a view of the PhD as ongoing personal development through an engagement with knowledge. The three views of the PhD are underpinned by different discourses which inform the practice of doctoral education. In South Africa, the traditional model of individual supervision dominates, and it varies by discipline, department and supervisor. But patterns of practice can be discerned and I identify four of these and discuss how supervisors construct their individual supervision practice. Doctoral education is also a function of the people who do PhDs. Much of the research undertaken in the overdeveloped world focuses on younger people who are starting out on academic careers. However, in South Africa, many people doing PhDs are older and midway through careers which are often not academic. This leads me to propose a model of intersecting contexts, as an alternative to McAlpine and Norton‟s nested context model of doctoral education, which more accurately reflects the local situation. I discuss the PhD experience and make use of the intersecting contexts model to develop the notion of congruence between the PhD, the contexts and the PhD person with more positive experiences being related to higher degrees of congruence. Finally, I consider how the outcomes of doctoral education, the learning and knowledge which result, relate to the expectations of the different stakeholders. The research took the form of a qualitative study with a multiple case-study design employing theoretical replication. I examined doctoral education in four academic units at three South African universities with the units selected to represent different disciplines. All four units were in previously advantaged universities from the English-speaking tradition and all were successfully producing PhD graduates. These rich pictures of how doctoral education takes place contribute empirical evidence to current debates about the PhD in South Africa. At a conceptual level I identify the competing discourses about what a PhD is. I provide a more nuanced understanding of the practice of doctoral education within the overarching model of individual supervision. The intersecting contexts model provides a way to understand the expectations and circumstances of doctoral people and the notion of congruence illuminates their varied experiences. Finally, the study confirms that the outcomes of doctoral education, in terms of learning and knowledge generated, meet at least some of the expectations of policy-makers, supervisors and people who do PhDs.

Thesis advisor: Patrick J. McQuillan / In the 2007-2008 school year, the author conducted a collaborative case study (Stake, 2000) with the goal of discovering and describing "emergent learning" in three high school classrooms. Emergent learning, defined as the acquisition of new knowledge by an entire group when no individual member of the group possessed it before, is implied by the work of many theorists working on an educational analog of a natural phenomenon called a complex adaptive system. Complex adaptive systems are well networked collectives of agents that are non-linear, bounded and synergistic. The author theorized that classes that maximized the features of complex adaptive systems could produce emergent learning (a form of synergy), and that there was a continuum of this complexity, producing a related continuum of emergence. After observing a co-curricular jazz group, an English class, and a geometry class for most of one academic year, collecting artifacts and interviewing three students and a teacher from each class, the author determined that there was indeed a continuum of complexity. He found that the actively complex nature of the Jazz Rock Ensemble produced an environment where emergence was the norm, with the ensemble producing works of music, new to the world, with each performance. The English section harnessed the chaotic tendencies of students to optimize cognitive dissonance and frequently produce emergent learning, while the mathematics section approached the learning process in a way that was too rigidly linear to allow detectable emergence to occur. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Lynch School of Education. / Discipline: Teacher Education, Special Education, Curriculum and Instruction.

Les circuits modernes sont de plus en plus sensibles aux variations technologiques et environnementales qui n'ont plus seulement un effet global sur les circuits mais aussi un effet local sur ceux-ci.Dans ce contexte, les composants reprogrammables que sont les FPGA représentent un support technologique intéressant. En effet, ces composants permettent d'adapter l'implantation physique du système grâce à une simple reconfiguration du circuit.C'est pourquoi, dans ce manuscrit, nous présentons un flot d'adaptation complet visant à compenser les variations des circuits. Pour cela, une étude de toutes les phases de conception des capteurs numériques est réalisée. Nous proposons ensuite une approche originale et unique de caractérisation basée sur l'analyse électromagnétique. Il est notamment montré que cette approche permet de se défaire des biais de mesure engendrés par les méthodes de mesure directe. L'utilisation conjointe des capteurs et de cette méthode d'analyse permet une caractérisation fine et précise des variations technologiques de n'importe quel type de circuit FPGA.Enfin, la cartographie issue de la phase de caractérisation permet ensuite de calibrer les capteurs pour une utilisation en ligne. Nous utilisons donc ensuite ces capteurs pour le monitoring dynamique d'un système MPSOC. / Modern circuits are more and more sensitive to environmental and technology changes.In this context, reprogrammable components like FPGAs represent an interesting technological support. Indeed, these components can adapt the physical layout of the system through a simple reconfiguration of the circuit.In this manuscript, we present a comprehensive adaptative flow to compensate the variations in circuits.For this, a study of all phases of digital sensor design is realized. We then propose a novel and unique characterization approach based on the electromagnetic analysis. It is particularly shown that this approach allows to get rid of measurement bias caused by direct measurement. The joint use of sensors and the method of analysis allows a detailed and accurate characterization of technological variations of any type of FPGA.Finally, the cartography issued from the characterization phase is then used to calibrate the sensors for online use. Then, we employ these sensors for monitoring the dynamics of a system MPSOC.

Esta Tese estuda a implementação de um novo mecanismo de análise e atuação em Redes de Sensores Sem Fio (RSSF) com múltiplos saltos baseado em características de cognição aplicadas aos nós que compõem a rede. Para tanto, é proposto um algoritmo de detecção de variabilidade dos nós sensores, envolvendo movimentação do nó, alcance do sinal da antena do sensor, quantidade de nós que fazem parte da rede e o número de conexões possíveis com nós vizinhos. Além do algoritmo de detecção de variabilidade, propõe-se um sistema multilayer denominado Adaptive Cognitive System (ACS) com base na arquitetura de Cognitive Networks (CN), que abrange: coleta, tratamento e tomada de decisão. O tratamento se refere à parte cognitiva do sistema, contemplando a criação do Cognitive Processor Module (CPMod), que por sua vez, abrange a semântica da rede, aplicação de Lógica Fuzzy e interação com um simulador de Wireless Sensor Networks (WSN) e a tomada de decisão é realizada pelo CPMod com base no resultado de análises executadas em rounds e histórico da rede com o uso de funções de pertinência de fuzzificação e defuzzificação, regras Fuzzy e inferência sobre informações coletadas da rede. Observou-se com os testes realizados na rede, utilizando-se o algoritmo de detecção, que a variabilidade dos nós sensores afeta diretamente o desempenho da rede, devido à necessidade de reestabelecimento de links e rotas entre os nós. Através de testes realizados via software na WSN, identificou-se que com o uso do ACS houve melhora significativa no desempenho em relação ao atraso fim-a-fim, latência, quantidade de pacotes descartados e de energia consumida pelos nós na rede. O ACS demonstrou potencial para a solução de problemas relacionados com as métricas destacadas, realizando ajustes em múltiplas camadas de rede do padrão IEEE 802.15.4 para até 200 nós na rede. / This Dissertation examines the implementation of a mechanism to analyze and act on multi-hop Wireless Sensor Networks (WSN) with the use of cognitive features applied to the network nodes. For this purpose, a variation detection algorithm was proposed for monitoring sensor nodes, involving the node\'s mobility features, signal range of the sensor antenna, the number of nodes in the network and the number of possible connections to neighboring nodes. In addition to the detection algorithm, a multi-layer system is proposed, named Adaptive Cognitive System (ACS). It is based on Cognitive Networks (CN) architecture, including data gathering, information treatment and decision making. The main part of the system is the Cognitive Processor Module (CPMod), which extracts the information about the WSN. In turn the Fuzzy Logic block works in tandem with the semantic engine to feed the codes to CPMod in the decision making process. The codes are the result of analysis performed on rounds using fuzzification and defuzzification membership functions, fuzzy rules and inference over information collected from the network. It was observed in tests performed in the WSN, using the detection algorithm, that the variability in sensor nodes directly affects the network performance due to the effort spent in rerounting links and paths. Through WSN testing performed via software, it was found that using the ACS implies in significant improvement in performance over the end-to-end delay, network latency, dropped packets and amount of energy consumed by nodes on the network. The ACS potential is proven for solving problems related to the previously mentioned metrics, performing adjustments on multiple network layers standardized by IEEE 802.15.4 up to 200 nodes in the network.