Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex Systems-of-Systems, which form the subject matter of the research presented here, may be considered to be systems that are constituted of several components, each of which could themself be regarded as being a complete system in its own right. These component systems are typically largely managed independently of one another. They each have their own intrinsic goals which they are capable of fulfilling autonomously. These goals are additional to any to which they might contribute as part of the overall System-of-Systems that is being investigated. Systems-of-Systems are epitomised by features such as the prevalence of complex webs of mutual interdependency amongst their component systems, the involvement of a broad diversity of stakeholders and the participation of a number of independent decision-makers, each of whom competes with the others for strictly limited resources. Furthermore, the components of Systems-of-Systems may often be found to be widely scattered across an extensive geographical region. Sometimes such systems may even span global distances. Complex Systems-of-Systems of such a nature would appear to be becoming ever more prevalent in the increasingly interconnected and ever shrinking world which is engendered, in particular, by the proliferation of modern information and communication technology. Systems-of-Systems may arise in both commercial and public sector contexts, hence commercial organisations and governments, alike, confront the daunting challenge of planning, establishing and maintaining novel systems of this type. However, it is to be anticipated that significant difficulties might be encountered in applying existing systems engineering methods, which were designed for dealing with far more monolithic types of system, to the treatment of Systems-of- Systems. Instead, the successful achievement of acceptable resolutions to the various Systems-of-Systems issues and conundrums with which the responsible planners can be expected to be confronted would appear to demand the application of sophisticated distributed decision aids, in order to alleviate the the intolerable burden which the decision-makers would otherwise be forced to endure. Such aids need to be able to take a genuinely fair and unbiased account of the interests of a multitude of stakeholders. At the same time, they must be able to satisfactorily accommodate the enforcement of a range of highly involved and intricate constraints upon the various alternative interventions which might potentially be contemplated. In order to underpin the development of decision aids of the kind demanded, it has been sought to establish some basic theoretical foundations for Systems-of-Systems. This body of theory has then been applied to the identification of the methods which might be most suitable for the treatment of Systems-of-Systems questions. Finally, some decision-support tools which are intended to facilitate the implementation of the methods that have been recommended have been described. Any attempt to dictate a single â??bestâ?? intervention to the decision-makers would generally be totally unacceptable. As a result, the objective which has been pursued has been to seek to filter out and identify a relatively sparing number of what would appear to be the most reasonable alternatives from some much more profuse range of possibilities. These may then be afforded more intensive scrutiny by the pertinent decision-makers.

Partant des composés ATiO3 (A=Ba, Pb, Sr) bien connus pour leurs propriétés de type ferroélectriques, il est possible de concevoir des super-réseaux de basse dimensionnalité (multi-couches, phases de type ,…) où ces propriétés peuvent être modulées en fonction de la composition, de l'épaisseur des couches mises en jeu, des contraintes aux interfaces. Nous proposons ici d'étudier par calculs de premiers principes les instabilités structurales et la dynamique de réseau pour des systèmes simples dans cette famille. En définissant clairement les zones interfaciales et de cœur des couches, et en étudiant la convergence de leurs propriétés en fonction de l'épaisseur, ce travail vise à établir des potentiels interatomiques modèles, analytiques et transférables, pour la prédiction des propriétés dynamiques et des instabilités structurales de super-réseaux étendus et/ou complexes. / The aim of the present thesis is to investigate, from first-principles, the ferroelectricproperties and related phase transition behaviors in perovskite type compounds. Wewill not focus only on the bulk perovskite systems, but also on related layered superlatticeswhere the interface may play an important role and induce new phenomena.

Made available in DSpace on 2015-03-26T13:33:39Z (GMT). No. of bitstreams: 1 texto completo.pdf: 3071922 bytes, checksum: 48d46b8aebf39c5cd1a3b7b837b070fa (MD5) Previous issue date: 2009-07-31 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / The research objective was to develop a resource management proposal based on wood fuel usage. Relied on the classic resource management science and its principles, presuppositions and hypothesis from biological science, the research aimed to overcome theoretical vulnerabilities from developed frameworks of this science resulted of lack of prediction and explanation of empirical problems. It also aimed to introduce elements from the social science which could explain better the wood fuel usage dynamics. The analysis started with the evaluation of concepts and their relationships in the classic resource management science. After the identification of some vulnerability in the classic model, the research exposes a way that could overcome some of these by the usage of systems basic thinking and the New Institutional Economics approach. These theories showed how difficult is to comprehend collective human behavior and this evidence directed the research to new concepts and proposals which helped the process of understanding collective human behavior with wood fuel use. The application of the framework was based in Lavras Novas, district belonged to Ouro Preto city, MG, which has a complex dynamic of wood fuel usage. This application allowed a comparison of the framework with the usage pattern in the locality which allowed the analysis of the theoretical and empirical viability of the framework and made possible the suggestion of utilities of the framework to future researchers in resource management area. / O presente trabalho objetivou desenvolver uma proposta de manejo de recursos tendo como referência empírica o uso da madeira energética. Sendo orientado pela ciência clássica do manejo de recursos apoiada pelos princípios, pressupostos e hipóteses das ciências biológicas, a proposta da pesquisa consistiu em superar as vulnerabilidades teóricas dos modelos desenvolvidos por essa ciência, resultantes de anomalias empíricas não previstas e não explicadas, e introduzir elementos explicativos aos modelos por meio da identificação de alternativas teóricas nas ciências sociais. Desta maneira, a análise inicial recaiu sobre conceitos e relações entre esses conceitos, conforme apresentados pela proposição clássica de manejo de recursos. A partir dessa apresentação e da identificação das suas vulnerabilidades, houve a exposição de como a abordagem sistêmica e a teoria da nova economia institucional podem suprir, pelos conceitos, pressupostos e relações entre os conceitos, algumas daquelas vulnerabilidades. Não obstante, a partir dessas teorias, identificou-se, ainda, a complexidade da compreensão do comportamento grupal entre seres humanos, o que direcionou a investigação teórica para conceitos e proposições que permitiram apreender o comportamento coletivo em um ambiente estruturado pelo uso energético da madeira para diversos fins. A delimitação do ambiente, representado pelo distrito de Lavras Novas por apresentar uma complexa dinâmica de uso socioeconômico do recurso, permitiu a comparação do sistema teórico desenvolvido com o padrão de utilização do recurso na localidade. Isso permitiu analisar a viabilidade teórica e prática do sistema desenvolvido em relação ao padrão de utilização encontrado empiricamente e sugerir possíveis aplicabilidades do modelo para a pesquisa em manejo de recursos.

Cette thèse développe une nouvelle approche pour la conception d'un reservoir computer, l'un des défis de la science et de la technologie modernes. La thèse se compose de deux parties, toutes deux s'appuyant sur l'analogie entre les systèmes optoelectroniques à retard et les dynamiques spatio-temporelles non linéaires. Dans la première partie (Chapitres 1 et 2) cette analogie est utilisée dans une perspective fondamentale afin d'étudier les formes auto-organisées connues sous le nom d'états Chimère, mis en évidence une première fois comme une conséquence de ces travaux. Dans la deuxième partie (Chapitres 3 et 4) la même analogie est exploitée dans une perspective appliquée afin de concevoir et mettre en oeuvre un concept de traitement de l'information inspiré par le cerveau: un réservoir computer fonctionnant en temps réel est construit dans une puce FPGA, grâce à la mise en oeuvre d'une dynamique à retard et de ses couches d'entrée et de sortie, pour obtenir un système traitement d'information autonome intelligent. / The thesis develops a novel approach to design of a reservoir computer, one of the challenges of modern Science and Technology. It consists of two parts, both connected by the correspondence between optoelectronic delayed-feedback systems and spatio-temporal nonlinear dynamics. In the first part (Chapters 1 and 2), this correspondence is used in a fundamental perspective, studying self-organized patterns known as chimera states, discovered for the first time in purely temporal systems. Study of chimera states may shed light on mechanisms occurring in many structurally similar high-dimensional systems such as neural systems or power grids. In the second part (Chapters 3 and 4), the same spatio-temporal analogy is exploited from an applied perspective, designing and implementing a brain-inspired information processing device: a real-time digital reservoir computer is constructed in FPGA hardware. The implementation utilizes delay dynamics and realizes input as well as output layers for an autonomous cognitive computing system.

Cette thèse s'inscrit dans le cadre de systèmes complexes appliqués aux systèmes économiques. Dans cette thèse, un modèle multi-agent a été proposé, qui modélise le cycle de production. Il est consitué d'entreprises, ouvirers/foyers, et une banque, et repecte la conservation de la monnaie. Son hypothèse centrale est que les entreprises se basent sur une marge espérée pour déterminer leur production. Un scénario simple de ce modèle, ou les marges espérées sont homogènes, a été analysé dans le cadre de models de croissance stochastique. Les résultats sont la distribution de tailles d'entreprises rassemblant des lois de puissance, et leur distribution du taux de croissance de forme 'tente', ainsi qu'une dépendence de taille de la variance de la croissance. Ces résultats sont proches aux faits stylisés issus d'études empiriques. Dans un scénario plus complet, le modèle contient des caractéristiques supplémentaires: des marges espérées hétérogèges, ainsi que des paiements d'intérêts, la possibilité de faire faillite. Cela ramène le modèle aux modèles macro-économiques multi-agents. Les extensions sont décrites de façon théorique par des équations de replicateur. Les résultats nouveaux sont la distribution d'age d'entreprises actives, la distribution de leur taux de profit, la distribution de dette, des statistiques sur les faillites, et des cycles de vie caractéristiques. Tout ces résultats sont qualitativement en accord avec des résultats d'études empiriques de plusieurs pays.Le modèle proposé génère des résultats prometteurs, en respectant le principe que des résultats qui apparaissent simultanément peuvent soit etre générés par un même processus, soit par plusieurs aui qui sont compatibles. / The thesis is in the field of complex systems, applied to an economic system. In this thesis, an agent-based model has been proposed to model the production cycle. It comprises firms, workers, and a bank, and respects stock-flow consistency. Its central assumption is that firms plan their production based on an expected profit margin. A simple scenario of the model, where the expected profit margin is the same for all firms, has been analyzed in the context of simple stochastic growth models. Results are a firms' size distribution close to a power law, and tent-shaped growth rate distribution, and a growth rate variance scaling with firm size. These results are close to empirically found stylized facts. In a more comprehensive version, the model contains additional features: heterogeneous profits margins, as well as interest payments and the possibility of bankruptcy. This relates the model to agent-based macroeconomic models. The extensions are described theoretically theoretically with replicator dynamics. New results are the age distribution of active firms, their profit rate distribution, debt distribution, bankruptcy statistics, as well as typical life cycles of firms, which are all qualitatively in agreement with studies of firms databases of various countries.The proposed model yields promising results by respecting the principle that jointly found results may be generated by the same process, or by several ones which are compatible.