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.

The purpose of this thesis was to explore how microstate human interactions produce macro level self-organization and emergence in a supply disruption scenario, as well as discover factors and typical human behaviour that bring about disruptions. This study argues that the complex adaptive system’s view of complexity is most suited scholarly foundation for this research enquiry. Drawing on the dissipative structure based explanation of emergence and self-organization in a complex adaptive system, this thesis further argues that an energy gradient between the ongoing and designed system conditions, known as adaptive tension, causes supply chains to self-organize and emerge. This study adopts a critical realist ontology operationalized by a qualitative case research and grounded theory based analysis. The data was collected using repertory grid interviews of 22 supply chain executives from 21 firms. In all 167 cases of supply disruptions were investigated. Findings illustrate that agent behaviours like loss of trust, over ambitious pursuit, use of power and privilege, conspiring against best practices and heedless performance were contributing to disruption. Impacted by these behaviours, supply chains demonstrated impaired disruption management capabilities and increased disruption probability. It was also discovered that some of these system patterns and microstate agent behaviours pushed the supply chains to a zone of emergent complexity where these networks self-organized and emerged into new structures or embraced changes in prevailing processes or goals. A conceptual model was developed to explain the transition from micro agent behaviour to system level self-organization and emergence. The model described alternate pathways of a supply chain under adaptive tension. The research makes three primary research contributions. Firstly, based upon the theoretical model, this research presents a conceptualization of supply chain emergence and self-organization from dissipative structures and adaptive tension based view of complexity. Secondly, it formally introduces and validates the role of behavioural and cognitive element of human actions in a supply chain scenario. Lastly, it affirms the complex adaptive system based conceptualization of supply chain networks. These contributions succeed in providing organizations with an explanation for observed deviations in their operations performance using a behavioural aspect of human agents.

<p>There is a common belief amongst those who are involved in projects that as project complexity increases the difficulty to manage a project increases and thus the probability to succeed in project completion considerably decreases. Perception of complexity in a project usually refers to common criteria from traditional project management thinking such as the scale of the project; cost; duration; and the degree of risk to its owner. However, whether a project is perceived to be complex or not may not be purely a product of the size of the project. It may also be derived from the person’s experience in projects. The aim of this study is to identify attributes of perception of project complexity and observe whether experience is also a determining factor in perceiving a project as complex. The research is based on the assumption that a complex project may exhibit behaviour similar to complex adaptive system. This study proposes a theoretical framework based on projects understood as complex adaptive systems. A project experience matrix is developed which will be useful to help link degree and type of experience to perceptions of project complexity.</p><p>This study employs a comparative study between two cases to explore and compare the perception of complexity in each case. Qualitative and quantitative data were obtained through semi-structured interview and questionnaires, then analysed accordingly. The outcomes of this research attempted to find answers to the following questions: How do project managers and team members perceive a project as complex (project complexity)?” In answering this question we explored how project managers and team members perceived project complexity. The major question above was elaborated by some minor specific questions. These are: Which attributes of complex adaptive systems are attributed by project managers and team members to project complexity? Is project experience a determining factor to the perception of project complexity? Based on our sample we found no significant differences between attributes of complex adaptive systems and perception of project complexity; no significant association between depth and context of experience and perception of project complexity. We also found no significant differences between the Chinese and Indonesian samples.</p>

Process variations and circuit aging continue to be main challenges to the power-efficiency of VLSI circuits, as considerable power budget must be allocated at design time to mitigate timing variations. Modern designs incorporate adaptive techniques for variation compensation to reduce the extra power consumption. The efficiency of existing adaptive approaches, however, is often significantly attenuated by the fine-grained nature of variations in nanometer technology such as random dopant fluctuation, litho-variation, and different rates of transistor degradation due to non-uniform activity factors. This dissertation addresses the limitations from existing adaptation techniques, and proposes new adaptive approaches to effectively compensate the fine-grained variations. Adaptive supply voltage (ASV) is one of the effective adaptation approaches for power-performance tuning. ASV has advantages on controlling dynamic and leakage power, while voltage generation and delivery overheads from conventional ASV systems make their application to mitigate fine-grained variations demanding. This dissertation presents a dual-level ASV system which provides ASV at both coarse-grained and fine-grained level, and has limited power routing overhead. Significant power reduction from our dual-ASV system demonstrates its superiority over existing approaches. Another novel technique on supply voltage adaptation for variation resilience in VLSI interconnects is proposed. A programmable boostable repeater design boosts switching speed by raising its internal voltage rail transiently and autonomously, and achieves fine-grained voltage adaptation without stand-alone voltage regulators or additional power grid. Since interconnect is a widely recognized bottleneck to chip performance and tremendous repeaters are employed on chip designs, boostable repeater has plenty of chances to improve system robustness. A low cost scheme for delay variation detection is essential to compose an efficient adaptation system. This dissertation presents an area-efficient built-in delay testing scheme which exploits BIST SCAN architecture and dynamic clock skew control. Using this built-in delay testing scheme, a fine-grained adaptation system composed of the proposed boostable repeater design and adaptive clock skew control is proposed, and demonstrated to mitigate process variation and aging induced timing degradations in a power as well as area efficient manner.

There is a common belief amongst those who are involved in projects that as project complexity increases the difficulty to manage a project increases and thus the probability to succeed in project completion considerably decreases. Perception of complexity in a project usually refers to common criteria from traditional project management thinking such as the scale of the project; cost; duration; and the degree of risk to its owner. However, whether a project is perceived to be complex or not may not be purely a product of the size of the project. It may also be derived from the person’s experience in projects. The aim of this study is to identify attributes of perception of project complexity and observe whether experience is also a determining factor in perceiving a project as complex. The research is based on the assumption that a complex project may exhibit behaviour similar to complex adaptive system. This study proposes a theoretical framework based on projects understood as complex adaptive systems. A project experience matrix is developed which will be useful to help link degree and type of experience to perceptions of project complexity. This study employs a comparative study between two cases to explore and compare the perception of complexity in each case. Qualitative and quantitative data were obtained through semi-structured interview and questionnaires, then analysed accordingly. The outcomes of this research attempted to find answers to the following questions: How do project managers and team members perceive a project as complex (project complexity)?” In answering this question we explored how project managers and team members perceived project complexity. The major question above was elaborated by some minor specific questions. These are: Which attributes of complex adaptive systems are attributed by project managers and team members to project complexity? Is project experience a determining factor to the perception of project complexity? Based on our sample we found no significant differences between attributes of complex adaptive systems and perception of project complexity; no significant association between depth and context of experience and perception of project complexity. We also found no significant differences between the Chinese and Indonesian samples.

Today's embedded distributed real-time systems, are exposed to large variations in resource usage due to complex software applications, sophisticated hardware platforms, and the impact of their run-time environment. As eciency becomes more important, the applications running on these systems are extended with on-line resource managers whose job is to adapt the system in the face of such variations. Distributed systems are often heterogeneous, meaning that the hardware platform consists of computing nodes with dierent performance, operating systems, and scheduling policies, linked through one or more networks using dierent protocols. In this thesis we explore whether resource managers used in such distributed embedded systems are stable, meaning that the system's resource usage is controlled under all possible run-time scenarios. Stability implies a bounded worst-case behavior of the system and can be linked with classic real-time systems' properties such as bounded response times for the software applications. In the case of distributed systems, the stability problem is particularly hard because software applications distributed over the dierent resources generate complex, cyclic dependencies between the resources, that need to be taken into account. In this thesis we develop a detailed mathematical model of an adaptive, distributed real-time system and we derive conditions that, if satised, guarantee its stability.

In search of mutable tectonics is a research investigation linking principles found in natural systems, investigated by various fields in biology, physics, and mathematics, in the creation of a design methodology in Architecture. Specifically the report looks into natural system with packing and stacking strategies like bone formation, foam or soap bubbles, and sphere packing. Rules and physical observations of the natural are carried forward in the development of a topological language, through digital investigations, which define relationships between variations in spatial configurations and structural members. What we hope to achieve here is that by studying natural systems already realized in the natural world a more adaptive system of design between form, structure and space is immediately established; resulting in the discovery of emergent spaces which intrinsically conveys an emergent structural system and vise versa. The outcome is the creation of an adaptive networked process in the design formulation in Architecture.

Les systèmes d’imagerie médicale ultrasonore ont considérablement amélioré le diagnostic clinique par une meilleure qualité des images grâce à des systèmes plus sensibles et des post-traitements. La communauté scientifique de l’imagerie ultrasonore a consenti à un très grand effort de recherche sur les posttraitements et sur le codage de l’excitation sans s’intéresser, outre mesure, aux méthodes de commandeoptimale. Ce travail s’est donc légitimement tourné vers les méthodes optimales basées sur l’utilisationd’une rétroaction de la sortie sur l’entrée. Pour rendre applicable ces méthodes, ce problème complexe decommande optimale a été transformé en un problème d’optimisation paramétrique sous-optimal et plussimple. Nous avons appliqué ce principe au domaine de l’imagerie ultrasonore : l’échographie, l’imagerieharmonique native et l’imagerie harmonique de contraste avec ou sans codage de la commande.La simplicité de l’approche nous a permis, par une modification de la fonction de coût, de l’adapter àl’imagerie harmonique. Cette adaptation montre que la méthode peut être appliquée à l’imagerie ultrasonoreen générale. / Medical ultrasound imaging systems have greatly improved the clinical diagnosis by improvingthe image quality thanks to more sensitive systems and post-processings. The scientific community has madea great effort of research on post-processing and on encoding the excitation. The methods of the optimalcontrol have been neglected. Our work has focused on the optimal methods based on the feedback fromoutput to input. We have transformed the complex problem of optimal control into an easier suboptimalparametric problem. We apply the principle of optimal control to the ultrasound imaging, the ultrasoundharmonic imaging and to the constrast harmonic imaging with or without encoding.The simplicity of the method has allowed us to adapt it to harmonic imaging by a change in the costfunction. This adaptation shows that our method can usually be applied to the ultrasound imaging.

The purpose of this thesis was to explore how microstate human interactions produce macro level self-organization and emergence in a supply disruption scenario, as well as discover factors and typical human behaviour that bring about disruptions. This study argues that the complex adaptive system’s view of complexity is most suited scholarly foundation for this research enquiry. Drawing on the dissipative structure based explanation of emergence and self-organization in a complex adaptive system, this thesis further argues that an energy gradient between the ongoing and designed system conditions, known as adaptive tension, causes supply chains to self-organize and emerge. This study adopts a critical realist ontology operationalized by a qualitative case research and grounded theory based analysis. The data was collected using repertory grid interviews of 22 supply chain executives from 21 firms. In all 167 cases of supply disruptions were investigated. Findings illustrate that agent behaviours like loss of trust, over ambitious pursuit, use of power and privilege, conspiring against best practices and heedless performance were contributing to disruption. Impacted by these behaviours, supply chains demonstrated impaired disruption management capabilities and increased disruption probability. It was also discovered that some of these system patterns and microstate agent behaviours pushed the supply chains to a zone of emergent complexity where these networks self-organized and emerged into new structures or embraced changes in prevailing processes or goals. A conceptual model was developed to explain the transition from micro agent behaviour to system level self-organization and emergence. The model described alternate pathways of a supply chain under adaptive tension. The research makes three primary research contributions. Firstly, based upon the theoretical model, this research presents a conceptualization of supply chain emergence and self-organization from dissipative structures and adaptive tension based view of complexity. Secondly, it formally introduces and validates the role of behavioural and cognitive element of human actions in a supply chain scenario. Lastly, it affirms the complex adaptive system based conceptualization of supply chain networks. These contributions succeed in providing organizations with an explanation for observed deviations in their operations performance using a behavioural aspect of human agents.

The aim of diploma theses is the design of an adaptive robotic workplace. The theoretical part focus on the division of robotic systems and the technical description of individual devices that were used in the implementation of the solution. The practical part contains an analysis of solutions and optimization of the entire production process in terms of minimizing the trajectory, smoothness of movements, time interval, which were analyzed in RoboSim software and in Roboshop software source code was created. Part of the theses is the design for an adaptive production process. The result of the work is an algorithm for controlling robot movements between individual processes. The theses contain a variant solution and possible innovative solutions for possible expansion of the workplace.