在龐大且開放的分散式計算環境中，傳統的信賴模型由於缺乏完善的信賴程度更新機制，很容易出現節點間推薦優良服務的效能低落、服務熱點產生、甚至是無法有效排擠詐欺服務的問題，因而導致額外成本的付出。本論文利用社會學行動理論與人際環境關係理論，設計的一個新的信賴模型。在此信賴模型中，發展節點間的 「合作」、 「競爭」 以及 「同業公會」 等橫向關係，提升節點間信賴程度的更新效率，進而增進信賴模型的穩定性。我們設計了一個有視覺化介面的分散式計算環境動態模擬器，以測試信賴模型在面對動態環境中無法預期的計算節點 「上線」、 「離線」、 「無預警當機」 甚至 「出現詐欺服務」 時的應變能力。模擬實驗證實，我們的信賴模型在整體服務滿意度、計算成本等指標上，均有較佳的表現。 / In a large open distributed computing environment, due to the lack of a good mechanism for trust update among computing nodes, traditional trust model often encounters problems such as low quality of service recommendation, occurrence of hot spots, and no effective mechanism to exclude deceptive nodes. In this thesis, we use the action theory and inter-person relation theory in social science to design a new trust model with relations between nodes such as cooperation, competition, and guild to improve the efficiency and stability of trust update. We have designed a dynamic simulator with a visual interface for distributed computing to test the abilities of the trust model under scenarios such as bringing nodes on-line, taking nodes off-line, unexpectedly service outage, and occurrence of deceptive nodes. Our experiments revealed that our trust model has superior performance in various indices such as service satisfaction and computational cost.

Este trabalho explora o uso da Análise de Redes Sociais (ARS) como ferramenta de grande valor, aquela que perpassa pelas mais variadas disciplinas, como protagonista do estudo em alguns casos, como coadjuvante em outros. Para a Ciência da Informação, a ARS vem sendo empregada em estudos bibliométricos, procurando responder a questionamentos que intrigam pesquisadores da área ou de outros segmentos do conhecimento. Assim, a ARS ocupa seu espaço como o objeto principal dos estudos, enfatizando-a como ferramenta e, também, pelo seu uso direto em pesquisas nas quais aparece, frequentemente em conjunto com a estatística. Dessa forma, a ARS é empregada, pensando em Ciência da Informação, em ambos os papéis: como protagonista, nas frentes que abordam sua história, seus métodos e suas métricas, e, como coadjuvante, contribuindo na análise de redes de coautoria através de suas métricas de centralidade, mostrando a fluência das informações, determinando a posição de autores com relação à colaboração e seus comportamentos em rede para áreas como a Ciência da Informação, a Educação e a Sociologia. Os gráficos e tabelas foram elaborados com o apoio dos programas Microsoft Excel e, fundamentalmente para as redes de interesse, o programa de uso livre Pajek. Este último, alimentado por programas em VBScript, possibilitou, através de seus recursos de geração de imagens representativas das redes, a confecção dos gráficos e o cálculo dos indicadores para cada uma das três redes. Para a obtenção dos dados de entrada, foram utilizados os mecanismos de busca pela expressão \"Social Networks\" nas bases ASSIA (Sociologia), ERIC (Educação) e LISA (Ciência da Informação) e, com o uso de seus mecanismos internos, a massa foi exportada e empregada como exemplo de bases viabilizando a aplicação e verificação da metodologia proposta nos moldes dos estudos realizados. / This dissertation explores the use of Social Network Analysis (SNA) as a valuable tool, which runs through the most varied disciplines, as a protagonist in same study cases, as an adjunct in other cases. For the Information Science, the SNA has been used in bibliometric studies, trying to answer questions that intrigue researchers in this field or other segments of knowledge. So, the SNA occupies its place as the main object of the studies, emphasizing it as a tool and also for its direct use in researches in which it appears, often in conjunction with the statistics. Thus, the SNA is used, concerning the Information Science, in both roles: as the protagonist, foremost addressing its history, its methods and metrics, and, as an adjunct, contributing for the analysis of networks of co-authorship through its centrality metrics, showing the flow of information, determining the position of the authors, related to their collaboration and their behaviors on the network, for areas of study such as Information Science, Education and Sociology. The graphs and charts were elaborated with the support of Microsoft Excel program and, fundamentally to the networks of interest, the program of free use called Pajek. The latter, powered by VBScript programs, enabled, through its resources of generating representative network images, the elaboration of the graphs and the calculation of the indicators for each one of the three networks. To obtain the input data, search engines were used by the expression \"Social Networks\" in ASSIA (Sociology), ERIC (Education) and LISA (Information Science) bases and, using its internal mechanisms, the mass was exported and used as an example of bases enabling the application and verification of the proposed methodology along the lines of the studies.

Within the interdisciplinary field of new materialism Karen Barad’s theory of agential realism deconstructs our current euro-western metaphysical perception of the world and our existence within it, to then re-build an understanding based on relatively new findings within quantum physics. In this thesis I try to recreate Barad’s theory to see what ethical consequences might come from it. Together with practical examples within the discourse of today’s social world and our global connectedness I hope to create a better understanding of the impact of our actions and being on our culture and what we call the natural world. Removing the unique agency given to human culture and language to instead, with the help of post-humanistic ideas, add agency as a universal enactment rather than an attribute, we should start to see ourselves as active and real parts of the world-building that is our home. One main question that I see arise in the end is: what does responsibility entail when we all are one and the same?

It is estimated that about 35-40% of adults in the U.S. suffer from insufficient sleep. Chronic sleep deprivation has become a prevalent phenomenon because of contemporary lifestyle and work-related factors. Sleep deprivation can reduce the capabilities and efficiency of attentional performance by impairing perception, increasing effort to maintain concentration, as well as introducing vision disturbance. Thus, it is important to understand the neural mechanisms behind how chronic sleep deprivation impairs sustained attention. In recent years, more attention has been paid to the study of the integration between anatomically distributed and functionally connected brain regions. Functional connectivity has been widely used to characterize brain functional integration, which measures the statistical dependency between neurophysiological events of the human brain. Further, evidence from recent studies has shown the non-stationary nature of brain functional connectivity, which may reveal more information about the human brain. Thus, the objective of this thesis is to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic functional connectivity. A modified spatial cueing paradigm was used to assess human sustained attention in rested wakefulness and chronic sleep deprivation conditions. Partial least squares approach was applied to distinguish brain functional connectivity for the experimental conditions. With the integration of a sliding-window approach, dynamic patterns of brain functional connectivity were identified in two experimental conditions. The brain was modeled as a series of dynamic functional networks in each experimental condition. Graph theoretic analysis was performed to investigate the dynamic properties of brain functional networks, using network measures of clustering coefficient and characteristics path length. In the chronic sleep deprivation condition, a compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed. Specifically, a highly clustered organization of brain functional networks was illustrated with a large clustering coefficient. This organization suggested that brain utilizes more connections to maintain attention in the chronic sleep deprivation condition. A smaller impact of clustering coefficient variation on characteristics path lengths indicated an ineffective adaptability of brain functional networks in the chronic sleep deprivation condition. In the rested wakefulness condition, brain functional networks showed the small-world topology in general, with the average small-world topology index larger than one. Small-world topology was identified as an optimal network structure with the balance between local information processing and global integration. Given the fluctuating values of the index over time, small-world brain networks were observed in most cases, indicating an effective adaptability of the human brain to maintain the dominance of small-world networks in the rested wakefulness condition. On the contrary, given that the average small-world topology index was smaller than one, brain functional networks generally exhibited random network structure. From the perspective of dynamic functional networks, even though there were few cases showing small-world brain networks, brain functional networks failed to maintain the dominance of small-world topology in the chronic sleep deprivation condition. In conclusion, to the best of our knowledge this thesis was the first to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic brain functional connectivity. A compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed in the chronic sleep deprivation condition. Furthermore, chronic sleep deprivation impaired sustained attention by reducing the effectiveness of brain functional networks' adaptability, resulting in the disrupted dominance of small-world brain networks.

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Актуальность темы магистерской диссертации заключается в ее тесной связи с глобальной пандемией нового коронавируса, при этом особое внимание уделяется распространению эпидемии и борьбе с ней. Целью исследования является предоставление научной и научно обоснованной поддержки путем разработки моделей и симуляций политики профилактики эпидемий в сообществе. Основная цель диссертационной работы – оценить факторы, влияющие на эффективность стратегий профилактики и контроля, а также раскрыть ключевые факторы и механизмы передачи эпидемии. Посредством симуляционных экспериментов, анализа и сравнения результатов создается исчерпывающая информация, которая поможет лицам, принимающим решения, формулировать и осуществлять более эффективную политику профилактики эпидемий на уровне сообщества. Целью данного исследования является изучение влияния мобильности населения и планировки жилого массива на передачу заболеваний и эффективность стратегий профилактики эпидемий. Предметом исследования является разработка системы моделирования и симуляции политики предотвращения эпидемий на уровне сообщества с использованием модели SIR и сети «малого мира» в жилом сообществе с численностью населения 500 человек. Научная новизна данного исследования заключается в сочетании классической модели SIR с сетевой моделью маленького мира, а также в использовании агентной модели и программного обеспечения NetLogo для моделирования. Этот инновационный подход учитывает взаимодействие и связи между людьми в сообществе, позволяя более точно моделировать распространение болезней и оценивать эффекты различных стратегий профилактики эпидемий. Практическая значимость исследования заключается в обеспечении научной основы и руководства для лиц, принимающих решения. Путем проведения симуляционных экспериментов и анализа результатов исследование оптимизирует разработку и реализацию политики профилактики эпидемий на уровне сообщества, эффективно контролируя распространение заболеваний, защищая здоровье населения и решая проблемы, связанные с инфекционными заболеваниями. / The relevance of the master's thesis topic lies in its close connection to the global novel coronavirus pandemic, specifically focusing on the spread and control of the epidemic. The research aims to provide scientific and evidence-based support by developing community epidemic prevention policy models and simulations. The main goal of the thesis is to evaluate the factors influencing the effectiveness of prevention and control strategies and uncover the key factors and mechanisms of epidemic transmission. Through simulation experiments, analysis, and comparison of results, comprehensive information is generated to assist decision makers in formulating and implementing more effective community epidemic prevention policies. The objective of this study is to examine the influence of population mobility and the layout of a residential community on disease transmission and the effectiveness of epidemic prevention strategies. The subject of research focuses on developing a modeling and simulation framework for community epidemic prevention policies using the SIR model and small-world network in a residential community with a population size of 500 individuals. The scientific novelty of this study lies in the combination of the classic SIR model with the small-world network model, along with the introduction of the agent model and NetLogo software for simulation. This innovative approach considers the interactions and connections between individuals in a community, enabling a more accurate modeling of disease spread and evaluation of the effects of different epidemic prevention policies. The practical significance of the research lies in its provision of scientific basis and guidance to decision makers. By conducting simulation experiments and analyzing the results, the study optimizes the formulation and implementation of community epidemic prevention policies, effectively controlling the spread of diseases, protecting public health, and addressing the challenges posed by infectious diseases.

Menschliche Systeme werden seit einiger Zeit modelliert und analysiert auf der Basis der Theorie komplexer Netzwerke. Dies erlaubt es quantitativ zu untersuchen, welche strukturellen und zeitlichen Merkmale eines Systems Ausbreitungsprozesse beeinflussen, z.B. von Informationen oder von Infektionskrankheiten. Im ersten Teil der Arbeit wird untersucht, wie eine modular-hierarchische Struktur von statischen Netzwerken eine schnelle Verbreitung von Signalen ermöglicht. Es werden neue Heuristiken entwickelt um die Random-Walk-Observablen “First Passage Time” und “Cover Time” auf lokal geclusterten Netzwerken zu ermitteln. Vergleiche mit der Approximation eines gemittelten Mediums zeigen, dass das Auftreten der beobachteten Minima der Observablen ein reiner Netzwerkeffekt ist. Es wird weiterhin dargelegt, dass nicht alle modular-hierarchischen Netzwerkmodelle dieses Phänomen aufweisen. Im zweiten Teil werden zeitlich veränderliche face-to-face Kontaktnetzwerke auf ihre Anfälligkeit für Infektionskrankheiten untersucht. Mehrere Studien belegen, dass Menschen vornehmlich Zeit in Isolation oder kleinen, stark verbundenen Gruppen verbringen, und dass ihre Kontaktaktivität einem zirkadianen Rhythmus folgt. Inwieweit diese beiden Merkmale die Ausbreitung von Krankheiten beeinflussen, ist noch unklar. Basierend auf einem neuen Modell wird erstmals gezeigt, dass zirkadian variierende Netzwerke Trajektorien folgen in einem Zustandsraum mit einer strukturellen und einer zeitlichen Dimension. Weiterhin wird dargelegt, dass mit zunehmender Annäherung der zeitlichen Dimension von System und Krankheit die systemische Infektionsanfälligkeit sinkt. Dies steht in direktem Widerspruch zu Ergebnissen anderer Studien, die eine zunehmende Anfälligkeit vorhersagen, eine Diskrepanz, die auf die Ungültigkeit einer weit verbreiteten Approximation zurückzuführen ist. Die hier vorgestellten Ergebnisse implizieren, dass auf dem Gebiet die Entwicklung neuer theoretischer Methoden notwendig ist. / Human systems have been modeled and analyzed on the basis of complex networks theory in recent time. This abstraction allows for thorough quantitative analyses to investigate which structural and temporal features of a system influence the evolution of spreading processes, such as the passage of information or of infectious diseases. The first part of this work investigates how the ubiquitous modular hierarchical structure of static real-world networks allows for fast delivery of messages. New heuristics are developed to evaluate random walk mean first passage times and cover times on locally clustered networks. A comparison to average medium approximations shows that the emergence of these minima are pure network phenomena. It is further found that not all modular hierarchical network models provide optimal message delivery structure. In the second part, temporally varying face-to-face contact networks are investigated for their susceptibility to infection. Several studies have shown that people tend to spend time in small, densely-connected groups or in isolation, and that their connection behavior follows a circadian rhythm. To what extent both of these features influence the spread of diseases is as yet unclear. Therefore, a new temporal network model is devised here. Based on this model, circadially varying networks can for the first time be interpreted as following trajectories through a newly defined systemic state space. It is further revealed that in many temporally varying networks the system becomes less susceptible to infection when the time-scale of the disease approaches the time-scale of the network variation. This is in direct conflict with findings of other studies that predict increasing susceptibility of temporal networks, a discrepancy which is attributed to the invalidity of a widely applied approximation. The results presented here imply that new theoretical advances are necessary to study the spread of diseases in temporally varying networks.

Ces dix dernières années, l'étude des réseaux petits-mondes a montré une grande stabilité de certaines métriques issues de la théorie des graphes formels. Elle porte sur l'analyse de réseaux traduisant des activités de l'homme : réseaux d'échanges téléphoniques, de connexions aériennes, de navigation sur le Web, de structure des lexiques linguistiques, mais également de réseaux de diffusion des épidémies ou de réseaux de relations sociales. En revanche, peu d'études ont porté sur l'analyse de la dynamique de ces graphes et leur évolution au cours du temps. C'est cette approche que nous développons dans ce document. Nous nous intéressons ici à des graphes obtenus à partir de comptes rendus professionnels de travailleurs sociaux. Ces graphes modélisent les cooccurrences des mots au sein des phrases. Notre analyse porte sur un lexique professionnel et sur l'évolution de son usage sur une période de près de 40 ans. Après avoir constitué notre matériel à partir des textes écrits (environ 1500 pages dactylographiées), ce corpus d'étude a été quantifié, vérifié, homogénéisé et traité orthographiquement sur un mode semi-automatique. Puis ce corpus normalisé a donné lieu à la constitution d'un graphe global pour la période complète, et d'une quarantaine de graphes pour chacune des sous-périodes étudiées. C'est sur ceux-ci que porte l'analyse de la dynamique d'évolution de graphe issu d'un lexique professionnel. Au final, notre travail permet de pointer le paradoxe existant, entre d'une part la contrainte d'écriture liée à un objet qui ne change que très peu dans la nature de sa mission (le travail d'un éducateur de rue) et d'autre part la permissivité du langage oral qui ne cesse d'évoluer (le langage professionnel). Par ailleurs notre approche propose une certaine automatisation pour dégager l'essentiel d'un "dire professionnel" dans un corpus de comptes rendus. / These last ten years, the study of small-world networks indicated a great stability of certain metrics from the theory of informal graphs. It is about the analysis of networks illustrating man's activities : networks of phone conversations, air connections, web browsing, linguistic vocabularies structure, but also epidemics' spreading or social relations networks. However, few studies focused on the analysis of these graphs' dynamics and their evolution over time. It is this approach that we develop in this document. We will take an interest in graphs obtained from professional reports of social workers. These graphs model the cooccurrences of words within sentences. Our analysis focuses on a professional vocabulary and on the evolution of its use in a period of time of almost 40 years. After our material was produced out of written texts (around 1500 typewritten pages), this corpus of studies has been quantified, checked, homogenized and orthographically dealt with on a semi-automatic mode. Then, this normalized corpus led to the formation of a global graph for the entire period, and of around forty graphs for each of the subperiod under study. Thus the analysis of graphs dynamics changes focuses on a professional vocabulary. Finally, our work enables us to highlight the existing paradox, on one hand, between the writing obligation linked to an object which only changes a tiny bit in the nature of its mission (the work of a street educator), and on the other hand, the permissiveness of oral language that keeps evolving/changing (the professional language). Besides, our approach suggests a certain automation to release the crux of a “ professional saying” in a report's corpus.

Modelos e teorias científicas surgem da necessidade do homem entender melhor o funcionamento do mundo em que vive. Constantemente, novos modelos e técnicas são criados com esse objetivo. Uma dessas teorias recentemente desenvolvida é a da Criticalidade Auto-Organizada. No Capítulo 2 desta tese, apresentamos uma breve introdução a Criticalidade Auto-Organizada. Tendo a criticalidade auto-organizada como pano de fundo, no Capítulo 3, estudamos a dinâmica Bak-Sneppen (e diversas variantes) e a comparamos com alguns algoritmos de otimização. Apresentamos no Capítulo 4, uma revisão histórica e conceitual das redes complexas. Revisamos alguns importantes modelos tais como: Erdös-Rényi, Watts-Strogatz, de configuração e Barabási-Albert. No Capítulo 5, estudamos o modelo Barabási-Albert não-linear. Para este modelo, obtivemos uma expressão analítica para a distribuição de conectividades P(k), válida para amplo espectro do espaço de parâmetros. Propusemos também uma forma analítica para o coeficiente de agrupamento, que foi corroborada por nossas simulações numéricas. Verificamos que a rede Barabási-Albert não-linear pode ser assortativa ou desassortativa e que, somente no caso da rede Barabási-Albert linear, ela é não assortativa. No Capítulo 6, utilizando dados coletados do CD-ROM da revista Placar, construímos uma rede bastante peculiar -- a rede do futebol brasileiro. Primeiramente analisamos a rede bipartida formada por jogadores e clubes. Verificamos que a probabilidade de que um jogador tenha participado de M partidas decai exponencialmente com M, ao passo que a probabilidade de que um jogador tenha marcado G gols segue uma lei de potência. A partir da rede bipartida, construímos a rede unipartida de jogadores, que batizamos de rede de jogadores do futebol brasileiro. Nessa rede, determinamos várias grandezas: o comprimento médio do menor caminho e os coeficientes de agrupamento e de assortatividade. A rede de jogadores de futebol brasileiro nos permitiu analisar a evolução temporal dessas grandezas, uma oportunidade rara em se tratando de redes reais. / Models and scientific theories arise from the necessity of the human being to better understand how the world works. Driven by this purpose new models and techniques have been created. For instance, one of these theories recently developed is the Self-Organized Criticality, which is shortly introduced in the Chapter 2 of this thesis. In the framework of the Self-Organized Criticality theory, we investigate the standard Bak-Sneppen dynamics as well some variants of it and compare them with optimization algorithms (Chapter 3). We present a historical and conceptual review of complex networks in the Chapter 4. Some important models like: Erdös-Rényi, Watts-Strogatz, configuration model and Barabási-Albert are revised. In the Chapter 5, we analyze the nonlinear Barabási-Albert model. For this model, we got an analytical expression for the connectivity distribution P(k), which is valid for a wide range of the space parameters. We also proposed an exact analytical expression for the clustering coefficient which corroborates very well with our numerical simulations. The nonlinear Barabási-Albert network can be assortative or disassortative and only in the particular case of the linear Barabási-Albert model, the network is no assortative. In the Chapter 6, we used collected data from a CD-ROM released by the magazine Placar and constructed a very peculiar network -- the Brazilian soccer network. First, we analyzed the bipartite network formed by players and clubs. We find out that the probability of a footballer has played M matches decays exponentially with M, whereas the probability of a footballer to score G gols follows a power-law. From the bipartite network, we built the unipartite Brazilian soccer players network. For this network, we determined several important quantities: the average shortest path length, the clustering coefficient and the assortative coefficient. We were also able to analise the time evolution of these quantities -- which represents a very rare opportunity in the study of real networks.

Real-world large-scale complex networks such as the Internet, social networks and biological networks have increasingly attracted the interest of researchers from many areas. Accurate modelling of the statistical regularities of these large-scale networks is critical to understand their global evolving structures and local dynamical patterns. Traditionally, the Erdos and Renyi random graph model has helped the investigation of various homogeneous networks. During the past decade, a special computational methodology has emerged to study complex networks, the outcome of which is identified by two models: the Watts and Strogatz small-world model and the Barabasi-Albert scale-free model. At the core of the complex network modelling process is the extraction of characteristics of real-world networks. I have developed computer simulation algorithms for study of the properties of current theoretical models as well as for the measurement of two real-world complex networks, which lead to the isolation of three complex network modelling essentials. The main contribution of the thesis is the introduction and study of a new General Two-Stage growth model (GTS Model), which aims to describe and analyze many common-featured real-world complex networks. The tools we use to create the model and later perform many measurements on it consist of computer simulations, numerical analysis and mathematical derivations. In particular, two major cases of this GTS model have been studied. One is named the U-P model, which employs a new functional form of the network growth rule: a linear combination of preferential attachment and uniform attachment. The degree distribution of the model is first studied by computer simulation, while the exact solution is also obtained analytically. Two other important properties of complex networks: the characteristic path length and the clustering coefficient are also extensively investigated, obtaining either analytically derived solutions or numerical results by computer simulations. Furthermore, I demonstrate that the hub-hub interaction behaves in effect as the link between a network's topology and resilience property. The other is called the Hybrid model, which incorporates two stages of growth and studies the transition behaviour between the Erdos and Renyi random graph model and the Barabasi-Albert scale-free model. The Hybrid model is measured by extensive numerical simulations focusing on its degree distribution, characteristic path length and clustering coefficient. Although either of the two cases serves as a new approach to modelling real-world large-scale complex networks, perhaps more importantly, the general two-stage model provides a new theoretical framework for complex network modelling, which can be extended in many ways besides the two studied in this thesis.