The puzzle known as tangram was the inspiration behind this composition. Just as the seven pieces of the tangram create shapes, seven contrasting musical fragments appear as thematic materials from which to draw sonic imagery. Sapphic Fragments for two sopranos This composition was constructed from “broken” materials - an analogy for Sappho's dismembered poem. These broken materials were arranged in a pointillistic manner. I drew inspiration from M.C. Escher's works to vary thematic fragments of this work. M.O.N.T.A.G.E. for flute, clarinet, violin and cello This work was influenced by the video work, Wantee, by artist, Laure Prouvost. The title, M.O.N.T.A.G.E., is an acrostic, using words that show intimate relations with my composition: Multicolour, Oscillation, Numbers, Television, the Artist, Gleam, Etc. Once Emerged from the Grey of Night for flute, clarinet, horn, violin, viola and cello This sextet consists of numerous fragments with various colours and textures, forming a musical collage. A picture-poem by Paul Klee offered the starting point for this work. Scale-Free Spaces for flute, guitar, viola and cello I drew compositional ideas from the video installation, Irreversible, by artist Norimichi Hirakawa. This quartet was composed of brief fragments of dots, lines and movements. Various fragments were structured in forms of both simplicity and complexity. For the latter, ideas were drawn from the study in randomness, ‘Scale-Free Network’. String Quartet no. 3 This composition consists of four movements. In the first and third movements, the sound of rain drops and images of light through stained glass are explored. The second and fourth movements effect a structural metamorphoses of musical elements. I drew inspiration from Kafka's novella The Metamorphosis. A Thousand Plateaux for orchestra In this orchestral work, a variety of images of both plateaux and movements were invoked. The work was inspired by both the book, A Thousand Plateaux by Gilles Deleuze and Félix Guattari, and the Alhambra palace in Granada, Spain.

Submitted by Anna Patricia Pachas Manrique (annapamanrique@gmail.com) on 2017-02-23T20:20:56Z No. of bitstreams: 1 20_02 (1).pdf: 1460371 bytes, checksum: e98c8f4713680550a770e8efcc7ffa14 (MD5) / Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2017-08-03T17:52:37Z (GMT) No. of bitstreams: 1 20_02 (1).pdf: 1460371 bytes, checksum: e98c8f4713680550a770e8efcc7ffa14 (MD5) / Made available in DSpace on 2017-08-18T14:34:31Z (GMT). No. of bitstreams: 1 20_02 (1).pdf: 1460371 bytes, checksum: e98c8f4713680550a770e8efcc7ffa14 (MD5) Previous issue date: 2016-08-29 / The speed and comprehensiveness global level with the pathogen has spread in recent years has drawn attention to the importance of the contact’s social network structure. In fact, the topology of the networks in which members of society interact has influenced the dynamics of epidemics. Studies have shown that pathogens when disiparem in scale-free networks have different effects when compared broadcast in random networks, such as the classic models. In these there were epidemic threshold, may somehow the health ministry have a control on the dissipation of diseases by applying certain measures such as vaccines. Already in models in which are considered the networks, specifically the free network scale, the threshold disappears. Thus, the epidemic threshold depends on the topology is required to include within this structure models Because of the importance of these networks, random networks and scalefree have been implemented along the epidemics of propagation models to check the epidemic threshold and the characteristic time, noting that the epidemic threshold disappears / A velocidade e a abrangência a nível mundial com que os agentes patogênicos tem se disseminado nos últimos anos tem chamado a atenção para a importância da estrutura da rede social de contato . De fato, a topologia das redes na qual os membros da sociedade interagem têm influenciado na dinâmica das epidemias.Estudos têm demostrado que os agentes patogênicos ao se dissiparem em redes livres de escala tem efeitos diferentes se comparado quando difundidos em redes aleatórias, como nos modelos clássicos. Nestes existiam limiar de epidemia ,podendo de alguma forma as entidades de saúde ter um controle sobre a dissipação das enfermidades , aplicando certas medidas como as vacinas por exemplo. Já nos modelos nos quais são consideradas as redes , especificamente a rede livre de escala,este limiar desaparece. Desta forma, o limiar de epidemia ao depender da topologia se faz necessário incluir esta estrutura dentro dos modelos epidemiológicos. Devido a importância destas redes , redes aleatórias e principalmente redes livres de escala foram implementadas junto a modelos de propagação de epidemias para verificar o limiar de epidemia e o tempo característico , verificando que o limiar de epidemia desaparece.

Made available in DSpace on 2015-03-03T15:15:30Z (GMT). No. of bitstreams: 1 GerdivaneFD_DISSERT.pdf: 2461999 bytes, checksum: afd653d46e87e83d8b0144e8086a3d19 (MD5) Previous issue date: 2014-02-21 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / In this work a study of social networks based on analysis of family names is presented. A basic approach to the mathematical formalism of graphs is developed and then main theoretical models for complex networks are presented aiming to support the analysis of surnames networks models. These, in turn, are worked so as to be drawn leading quantities, such as aggregation coefficient, minimum average path length and connectivity distribution. Based on these quantities, it can be stated that surnames networks are an example of complex network, showing important features such as preferential attachment and small-world character / Neste trabalho ? apresentado um estudo das redes sociais baseado na an?lise dos nomes de fam?lias. Faz-se uma abordagem b?sica do formalismo matem?tico dos grafos e em seguida apresenta-se os principais modelos te?ricos para as Redes Complexas com o objetivo de fundamentar a an?lise das redes dos sobrenomes. Estas, por sua vez, s?o trabalhadas de modo a serem extra?das as principais grandezas, tais como coe ciente de agrega??o, menor caminho m?dio e distribui??o de conectividades. Com base nestas grandezas, pode-se a rmar que as redes de sobrenomes s?o um exemplo de rede complexa, exibindo caracter?sticas importantes como liga??o preferencial e o car?ter de mundo pequeno.

The thesis focusses on central nodes' dynamics in cyberspace, representing its key elements. Such approach derives from the theory of networks developed by Albert-László Barabási and it is conceptualised along with cyberspace in security studies and the role of a state in cyberspace. Main question, which is how to improve cybersecurity strategies, is answered by well-structured package of possible positions of a state towards central nodes. It asses the level of involvement in cyberspace, boundaries of intrusion into central nodes and acceptable tools usable against those which are not directly accessible. Powered by TCPDF (www.tcpdf.org)

Environ 25% de la population mondiale est atteinte de troubles psychiatriques qui sont typiquement associés à des problèmes comportementaux, fonctionnels et/ou cognitifs et dont les corrélats neurophysiologiques sont encore très mal compris. Non seulement ces dysfonctionnements réduisent la qualité de vie des individus touchés, mais ils peuvent aussi devenir un fardeau pour les proches et peser lourd dans l’économie d’une société. Cibler les mécanismes responsables du fonctionnement atypique du cerveau en identifiant des biomarqueurs plus robustes permettrait le développement de traitements plus efficaces. Ainsi, le premier objectif de cette thèse est de contribuer à une meilleure caractérisation des changements dynamiques cérébraux impliqués dans les troubles mentaux, plus précisément dans la schizophrénie et les troubles d’humeur. Pour ce faire, les premiers chapitres de cette thèse présentent, en intégral, deux revues de littératures systématiques que nous avons menées sur les altérations de connectivité cérébrale, au repos, chez les patients schizophrènes, dépressifs et bipolaires. Ces revues révèlent que, malgré des avancées scientifiques considérables dans l’étude de l’altération de la connectivité cérébrale fonctionnelle, la dimension temporelle des mécanismes cérébraux à l’origine de l’atteinte de l’intégration de l’information dans ces maladies, particulièrement de la schizophrénie, est encore mal comprise. Par conséquent, le deuxième objectif de cette thèse est de caractériser les changements cérébraux associés à la schizophrénie dans le domaine temporel. Nous présentons deux études dans lesquelles nous testons l’hypothèse que la « disconnectivité temporelle » serait un biomarqueur important en schizophrénie. Ces études explorent les déficits d’intégration temporelle en schizophrénie, en quantifiant les changements de la dynamique neuronale dite invariante d’échelle à partir des données magnétoencéphalographiques (MEG) enregistrés au repos chez des patients et des sujets contrôles. En particulier, nous utilisons (1) la LRTCs (long-range temporal correlation, ou corrélation temporelle à longue-distance) calculée à partir des oscillations neuronales et (2) des analyses multifractales pour caractériser des modifications de l’activité cérébrale arythmique. Par ailleurs, nous développons des modèles de classification (en apprentissage-machine supervisé) pour mieux cerner les attributs corticaux et sous-corticaux permettant une distinction robuste entre les patients et les sujets sains. Vu que ces études se basent sur des données MEG spontanées enregistrées au repos soit avec les yeux ouvert, ou les yeux fermées, nous nous sommes par la suite intéressés à la possibilité de trouver un marqueur qui combinerait ces enregistrements. La troisième étude originale explore donc l’utilité des modulations de l’amplitude spectrale entre yeux ouverts et fermées comme prédicteur de schizophrénie. Les résultats de ces études démontrent des changements cérébraux importants chez les patients schizophrènes au niveau de la dynamique d’invariance d’échelle. Elles suggèrent une dégradation du traitement temporel de l’information chez les patients, qui pourrait être liée à leurs symptômes cognitifs et comportementaux. L’approche multimodale de cette thèse, combinant la magétoencéphalographie, analyses non-linéaires et apprentissage machine, permet de mieux caractériser l’organisation spatio-temporelle du signal cérébrale au repos chez les patients atteints de schizophrénie et chez des individus sains. Les résultats fournissent de nouvelles preuves supportant l’hypothèse d’une « disconnectivité temporelle » en schizophrénie, et étendent les recherches antérieures, en explorant la contribution des structures cérébrales profondes et en employant des mesures non-linéaires avancées encore sous-exploitées dans ce domaine. L’ensemble des résultats de cette thèse apporte une contribution significative à la quête de nouveaux biomarqueurs de la schizophrénie et démontre l’importance d’élucider les altérations des propriétés temporelles de l’activité cérébrales intrinsèque en psychiatrie. Les études présentées offrent également un cadre méthodologique pouvant être étendu à d’autres psychopathologie, telles que la dépression. / Psychiatric disorders affect nearly a quarter of the world’s population. These typically bring about debilitating behavioural, functional and/or cognitive problems, for which the underlying neural mechanisms are poorly understood. These symptoms can significantly reduce the quality of life of affected individuals, impact those close to them, and bring on an economic burden on society. Hence, targeting the baseline neurophysiology associated with psychopathologies, by identifying more robust biomarkers, would improve the development of effective treatments. The first goal of this thesis is thus to contribute to a better characterization of neural dynamic alterations in mental health illnesses, specifically in schizophrenia and mood disorders. Accordingly, the first chapter of this thesis presents two systematic literature reviews, which investigate the resting-state changes in brain connectivity in schizophrenia, depression and bipolar disorder patients. Great strides have been made in neuroimaging research in identifying alterations in functional connectivity. However, these two reviews reveal a gap in the knowledge about the temporal basis of the neural mechanisms involved in the disruption of information integration in these pathologies, particularly in schizophrenia. Therefore, the second goal of this thesis is to characterize the baseline temporal neural alterations of schizophrenia. We present two studies for which we hypothesize that the resting temporal dysconnectivity could serve as a key biomarker in schizophrenia. These studies explore temporal integration deficits in schizophrenia by quantifying neural alterations of scale-free dynamics using resting-state magnetoencephalography (MEG) data. Specifically, we use (1) long-range temporal correlation (LRTC) analysis on oscillatory activity and (2) multifractal analysis on arrhythmic brain activity. In addition, we develop classification models (based on supervised machine-learning) to detect the cortical and sub-cortical features that allow for a robust division of patients and healthy controls. Given that these studies are based on MEG spontaneous brain activity, recorded at rest with either eyes-open or eyes-closed, we then explored the possibility of finding a distinctive feature that would combine both types of resting-state recordings. Thus, the third study investigates whether alterations in spectral amplitude between eyes-open and eyes-closed conditions can be used as a possible marker for schizophrenia. Overall, the three studies show changes in the scale-free dynamics of schizophrenia patients at rest that suggest a deterioration of the temporal processing of information in patients, which might relate to their cognitive and behavioural symptoms. The multimodal approach of this thesis, combining MEG, non-linear analyses and machine-learning, improves the characterization of the resting spatiotemporal neural organization of schizophrenia patients and healthy controls. Our findings provide new evidence for the temporal dysconnectivity hypothesis in schizophrenia. The results extend on previous studies by characterizing scale-free properties of deep brain structures and applying advanced non-linear metrics that are underused in the field of psychiatry. The results of this thesis contribute significantly to the identification of novel biomarkers in schizophrenia and show the importance of clarifying the temporal properties of altered intrinsic neural dynamics. Moreover, the presented studies offer a methodological framework that can be extended to other psychopathologies, such as depression.

The thesis is focused on central nodes' dynamics in cyberspace, representing its key elements. This approach is derived from the theory of networks developed by Albert-László Barabási and applied on different aspects of cyberspace, which brings different views at known events and issues and discovers relationship between central and common nodes. Cyberspace is perceived in its broadest shape as a fluid result of social constructivism influenced by behaviour of its users. Final outcomes are summarised to recommendations for a new approach to a cybersecurity strategy. Powered by TCPDF (www.tcpdf.org)

The focus of this thesis is resource management in large-scale systems. Our primary concerns are energy management and practical principles for self-organization and self-management. The main contributions of our work are: 1. Models. We proposed several models for different aspects of resource management, e.g., energy-aware load balancing and application scaling for the cloud ecosystem, hierarchical architecture model for self-organizing and self-manageable systems and a new cloud delivery model based on auction-driven self-organization approach. 2. Algorithms. We also proposed several different algorithms for the models described above. Algorithms such as coalition formation, combinatorial auctions and clustering algorithm for scale-free organizations of scale-free networks. 3. Evaluation. Eventually we conducted different evaluations for the proposed models and algorithms in order to verify them. All the simulations reported in this thesis had been carried out on different instances and services of Amazon Web Services (AWS). All of these modules will be discussed in detail in the following chapters respectively.

Neste trabalho, foram utilizadas técnicas e conceitos tipicamente encontrados em estudos de Redes Complexas, uma sub-área da Física Estatística, para caracterizar a Internet e sua evolução em uma década, de 1998 a 2007. Foi considerada como unidade básica de análise, a estrutura Sistema Autônomo. Nesta caracterização, foram utilizadas várias ferramentas computacionais desenvolvidas em linguagem C/C++, que permitiram classificar, simular e modelar propriedades dinâmicas. Dentre estas propriedades podemos destacar o coeficiente de conectividade, fundamental para os estudos topológicos, e o parâmetro menor caminho médio, ambos baseados nas propriedades da matriz adjacência. Os dados experimentais foram inicialmente obtidos nos roteadores de borda da RedeRio de Computadores - FAPERJ e posteriormente, os dados relativos ao intervalo de estudo, foram retirados da base de dados disponibilizada pela Universidade de Oregon. Foi proposto um modelo de crescimento de uma rede complexa baseado nas premissas de crescimento contínuo e conexão preferencial não linear com suporte aos mecanismos de rearranjo e novas conexões entre nós já existentes. Este modelo se mostrou bastante adequado no estudo das propriedades consideradas. Foi desenvolvido um método para cálculo do menor caminho médio que apresentou performance superior àqueles normalmente utilizados pela comunidade acadêmica. O comportamento da topologia sob o ponto de vista da distribuição de probabilidades de conexão e do ranque de conectividade, apresentaram comportamento linear constante no período estudado com coeficientes médios iguais a -2,0 e -0,93, respectivamente. O parâmetro menor caminho médio global da Internet permaneceu praticamente inalterado e igual a 4, 2 ao longo da década estudada. / Connection networks are observed in many areas of human knowledge. The characterization and topological studies of these networks may be performed through distribution of connectivity degrees, rank properties, shortest path length between nodes, adjacency matrix etc, typical concepts from Complex networks, a filed of study of Statistical Physics domain. In this thesis we characterize the Internet connections evolution from 1998 to 2007. The Internet may be seen under several levels of reach and complexity considering different basic units. A wide vision is to consider the Internet basic element as an Autonomous System - AS, which is defined as a cluster of LANs or routers submitted to the same policy of usage, connectivity and technically administrated by the same network management group. The complex network considered in this work is composed by Autonomous Systems (vertices) and the established tra connection (edges) between them obtained from the BGP routing table. Many interesting property of this networks is analyzed, e.g. degree distribution (the rank and outdegree exponents) from 1998 to 2007 and the shortest path length (L), obtained by a proposed computational method (Friburgo algorithm) among each pair of ASs represented in the adjacency matrix. Finally, we present the behavior of the power law function and the shortest path length of the Internet for each year. Simulations of the connections network were carried out by a proposed model developed from continuous growth premises, possibilities of new and rearranging connections. This model was based on the concept of potential preferable connection showing a stable exponential factor that reproduces the true shortest path parameter over the decade.

Neste trabalho, foram utilizadas técnicas e conceitos tipicamente encontrados em estudos de Redes Complexas, uma sub-área da Física Estatística, para caracterizar a Internet e sua evolução em uma década, de 1998 a 2007. Foi considerada como unidade básica de análise, a estrutura Sistema Autônomo. Nesta caracterização, foram utilizadas várias ferramentas computacionais desenvolvidas em linguagem C/C++, que permitiram classificar, simular e modelar propriedades dinâmicas. Dentre estas propriedades podemos destacar o coeficiente de conectividade, fundamental para os estudos topológicos, e o parâmetro menor caminho médio, ambos baseados nas propriedades da matriz adjacência. Os dados experimentais foram inicialmente obtidos nos roteadores de borda da RedeRio de Computadores - FAPERJ e posteriormente, os dados relativos ao intervalo de estudo, foram retirados da base de dados disponibilizada pela Universidade de Oregon. Foi proposto um modelo de crescimento de uma rede complexa baseado nas premissas de crescimento contínuo e conexão preferencial não linear com suporte aos mecanismos de rearranjo e novas conexões entre nós já existentes. Este modelo se mostrou bastante adequado no estudo das propriedades consideradas. Foi desenvolvido um método para cálculo do menor caminho médio que apresentou performance superior àqueles normalmente utilizados pela comunidade acadêmica. O comportamento da topologia sob o ponto de vista da distribuição de probabilidades de conexão e do ranque de conectividade, apresentaram comportamento linear constante no período estudado com coeficientes médios iguais a -2,0 e -0,93, respectivamente. O parâmetro menor caminho médio global da Internet permaneceu praticamente inalterado e igual a 4, 2 ao longo da década estudada. / Connection networks are observed in many areas of human knowledge. The characterization and topological studies of these networks may be performed through distribution of connectivity degrees, rank properties, shortest path length between nodes, adjacency matrix etc, typical concepts from Complex networks, a filed of study of Statistical Physics domain. In this thesis we characterize the Internet connections evolution from 1998 to 2007. The Internet may be seen under several levels of reach and complexity considering different basic units. A wide vision is to consider the Internet basic element as an Autonomous System - AS, which is defined as a cluster of LANs or routers submitted to the same policy of usage, connectivity and technically administrated by the same network management group. The complex network considered in this work is composed by Autonomous Systems (vertices) and the established tra connection (edges) between them obtained from the BGP routing table. Many interesting property of this networks is analyzed, e.g. degree distribution (the rank and outdegree exponents) from 1998 to 2007 and the shortest path length (L), obtained by a proposed computational method (Friburgo algorithm) among each pair of ASs represented in the adjacency matrix. Finally, we present the behavior of the power law function and the shortest path length of the Internet for each year. Simulations of the connections network were carried out by a proposed model developed from continuous growth premises, possibilities of new and rearranging connections. This model was based on the concept of potential preferable connection showing a stable exponential factor that reproduces the true shortest path parameter over the decade.

De nombreux systèmes complexes provenant de phénomènes naturels ou de la société humaine peuvent être décrits comme des réseaux complexes. Dans cette thèse, sur la base de la théorie des réseaux complexes, nous allons nous pencher sur la structure topologique de ces réseaux complexes et leurs dynamiques. Nous avons créé des modèles pour étudier les influences de la structure sur la dynamique des réseaux et mis en évidence quelques propriétés particulières des systèmes complexes. Cette thèse comporte quatre parties. Dans la première partie, les propriétés empiriques (degré de distribution, coefficient d’agrégation, diamètre, longueur caractéristique de parcours) des réseaux de routes urbaines de la ville du Mans en France sont étudiées. Dans la seconde partie, nous proposons deux modèles pour étudier le mécanisme éventuel conduisant à s’écarter de la loi de puissance simple. Dans le premier modèle, la probabilité d’addition de noeuds et de liens, la création de liens est étudiée ; dans le second modèle, seule la croissance aléatoire et préférentielle de liens est ajoutée. Les résultats de la simulation de ce modèle sont comparés aux données réelles. Dans la troisième partie, les propriétés probabilistes incertaines de la loi de distribution en double puissance sont étudiées. L’optimisation du réseau et l’étude optimale du réseau sans échelle vers l’échec aléatoire sont étudiées en se servant du principe de maximisation de l’entropie. Nous avons défini l’ensemble du réseau à l’équilibre comme des ensembles stationnaires de graphes en utilisant des notions thermodynamiques telle que ”énergie”, ”température”, ” énergie libre” pour les réseaux. Dans la quatrième partie, un modèle d’union-division est mis au point pour étudier l’évolution temporelle de certains réseaux culturels ou économiques. Dans ce modèle, les noeuds représentent les cultures. Plusieurs grandeurs telles que la richesse, l’âge, identité, contenu etc. sont utilisées pour paramétrer l’évolution probable du réseau. Le modèle offre une vision à long terme sur une dynamique apparemment périodique d’ensemble de grandeurs culturelles ou économiques en interaction. / Many complex systems arising from nature and human society can be described as complex networks. In this dissertation, on the basis of complex network theory, we pay attention to the topological structure of complex network and the dynamics on it. We established models to investigate the influences of the structure on the dynamics of networks and to shed light on some peculiar properties of complex systems. This dissertation includes four parts. In the first part, the empirical properties (degree distribution, clustering coefficient, diameter, and characteristic path length) of urban road network of Le Mans city in France are studied. The degree distribution shows a double power-law which we studied in detail. In the second part, we propose two models to investigate the possible mechanisms leading to the deviation from simple power law. In the first model, probabilistic addition of nodes and links, and rewiring of links are considered; in the second one, only random and preferential link growth is included. The simulation results of the modelling are compared with the real data. In the third part,the probabilistic uncertainty behavior of double power law distribution is investigated. The network optimization and optimal design of scale free network to random failures are discussed from the viewpoint of entropy maximization. We defined equilibrium network ensemble as stationary ensembles of graphs by using some thermodynamics like notions such as ”energy”, ”temperature”, ”free energy” for network. In the forth part, an union-division model is established to investigate the time evolution of certain networks like cultural or economical networks. In this model, the nodes represent, for example, the cultures. Several quantities such as richness, age, identity, ingredient etc. are used to parameterize the probabilistic evolution of the network. The model offers a long term view on the apparently periodic dynamics of an ensemble of cultural or economic entities in interaction.