<p>Demands on the quality and reliability of Volunteered Geographic Information have increased because of its rising popularity. Due to the less controlled data entry, there is a risk that people provide false or inaccurate information to the database. One factor that affects the effect of such updates is the network structure of the database schema, which might reveal the database’s robustness against different kinds of false updates. Therefore, network analyses are needed. The aim is to analyse GIS data models, stored in UML class diagrams, for scale-free and small-world properties. Moreover, a robustness analysis is to be carried out on selected data models in order to find out their error and attack tolerance against, for example, false updates. Three graphs were specified from the UML class diagrams: (1) <em>class graphs</em>: classes as nodes and their interactive relationships as connections; (2) <em>attribute graphs</em>: classes and attributes as nodes, with connections between the classes and their attributes; and (3) <em>schema graphs</em>: attributes as nodes and their interactive relationships inside and outside the tables as links. The analysed class diagrams were stored in XMI, and therefore transformed with XSLT to the Pajek network format. Thereafter, small-world and scale-free analyses as well as a robustness analysis were performed on the graphs. </p><p>The results from the scale-free analyses showed no strict power-laws. Nevertheless, the classes’ relationships and attributes, and the betweenness in the schema graphs were long-tailed distributed. Furthermore, the schema graphs had small-world properties, and the analysed class and schema graphs were robust against errors but fragile against attacks. In a network structure perspective, these results indicate that false updates on random tables of a database should usually do little harm, but falsely updating the most central cells or tables may cause big damage. Consequently, it may be necessary to monitor and constrain sensitive cells and tables in order to protect them from attacks</p>

Background: Biological systems adapt to changing environments by reorganizing their cellula r and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underl ying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic conditiondependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple ob servation s about the changes of metabolic concentrations. The approach was tested with Escherichia colias a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diau xie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical path ways, and (3) ind ependently of the response scale, based on their importance in the reorganization of the cor relation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-ba sed approach does not rely on major changes in concentration to identify metabolites important for st ress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.

Demands on the quality and reliability of Volunteered Geographic Information have increased because of its rising popularity. Due to the less controlled data entry, there is a risk that people provide false or inaccurate information to the database. One factor that affects the effect of such updates is the network structure of the database schema, which might reveal the database’s robustness against different kinds of false updates. Therefore, network analyses are needed. The aim is to analyse GIS data models, stored in UML class diagrams, for scale-free and small-world properties. Moreover, a robustness analysis is to be carried out on selected data models in order to find out their error and attack tolerance against, for example, false updates. Three graphs were specified from the UML class diagrams: (1) class graphs: classes as nodes and their interactive relationships as connections; (2) attribute graphs: classes and attributes as nodes, with connections between the classes and their attributes; and (3) schema graphs: attributes as nodes and their interactive relationships inside and outside the tables as links. The analysed class diagrams were stored in XMI, and therefore transformed with XSLT to the Pajek network format. Thereafter, small-world and scale-free analyses as well as a robustness analysis were performed on the graphs.  The results from the scale-free analyses showed no strict power-laws. Nevertheless, the classes’ relationships and attributes, and the betweenness in the schema graphs were long-tailed distributed. Furthermore, the schema graphs had small-world properties, and the analysed class and schema graphs were robust against errors but fragile against attacks. In a network structure perspective, these results indicate that false updates on random tables of a database should usually do little harm, but falsely updating the most central cells or tables may cause big damage. Consequently, it may be necessary to monitor and constrain sensitive cells and tables in order to protect them from attacks

Population-wide synchronized rhythmic bursts of electrical activity are present in a variety of neural circuits. The proposed general mechanisms for rhythmogenesis are often attributed to intrinsic and synaptic properties. For example, the recurrent excitation through excitatory synaptic connections determines burst initiation, and the slower kinetics of ionic currents or synaptic depression results in burst termination. In such theories, a slow recovery process is essential for the slow dynamics associated with bursting. This thesis presents a new hypothesis that depends on the connectivity pattern among neurons rather than a slow kinetic process to achieve the network-wide bursting. The thesis begins with an introduction of bursts of electrical activity in a purely excitatory neural network and existing theories explaining this phenomenon. It then covers the small-world approach, which is applied to modify the network structure in the simulation, and the Morris-Lecar (ML) neuron model, which is used as the component cells in the network. Simulation results of the dependence of bursting activity on network connectivity, as well as the inherent network properties explaining this dependence are described. This work shows that the network-wide bursting activity emerges in the small-world network regime but not in the regular or random networks, and this small-world bursting primarily results from the uniform random distribution of long-range connections in the network, as well as the unique dynamics in the ML model. Both attributes foster progressive synchronization in firing activity throughout the network during a burst, and this synchronization may terminate a burst in the absence of an obvious slow recovery process. The thesis concludes with possible future work.

abstract: This dissertation studies routing in small-world networks such as grids plus long-range edges and real networks. Kleinberg showed that geography-based greedy routing in a grid-based network takes an expected number of steps polylogarithmic in the network size, thus justifying empirical efficiency observed beginning with Milgram. A counterpart for the grid-based model is provided; it creates all edges deterministically and shows an asymptotically matching upper bound on the route length. The main goal is to improve greedy routing through a decentralized machine learning process. Two considered methods are based on weighted majority and an algorithm of de Farias and Megiddo, both learning from feedback using ensembles of experts. Tests are run on both artificial and real networks, with decentralized spectral graph embedding supplying geometric information for real networks where it is not intrinsically available. An important measure analyzed in this work is overpayment, the difference between the cost of the method and that of the shortest path. Adaptive routing overtakes greedy after about a hundred or fewer searches per node, consistently across different network sizes and types. Learning stabilizes, typically at overpayment of a third to a half of that by greedy. The problem is made more difficult by eliminating the knowledge of neighbors' locations or by introducing uncooperative nodes. Even under these conditions, the learned routes are usually better than the greedy routes. The second part of the dissertation is related to the community structure of unannotated networks. A modularity-based algorithm of Newman is extended to work with overlapping communities (including considerably overlapping communities), where each node locally makes decisions to which potential communities it belongs. To measure quality of a cover of overlapping communities, a notion of a node contribution to modularity is introduced, and subsequently the notion of modularity is extended from partitions to covers. The final part considers a problem of network anonymization, mostly by the means of edge deletion. The point of interest is utility preservation. It is shown that a concentration on the preservation of routing abilities might damage the preservation of community structure, and vice versa. / Dissertation/Thesis / Ph.D. Computer Science 2011

SILVA, Samuel Morais da. Propriedades dinâmicas de redes de Kleinberg. 2015. 71 f. Dissertação (Mestrado em Física) - Programa de Pós-Graduação em Física, Departamento de Física, Centro de Ciências, Universidade Federal do Ceará, Fortaleza, 2015. / Submitted by Edvander Pires (edvanderpires@gmail.com) on 2015-10-28T21:53:53Z No. of bitstreams: 1 2015_dis_smsilva.pdf: 6345616 bytes, checksum: 705401ad498eb92e473d5a63a9e41c49 (MD5) / Approved for entry into archive by Edvander Pires(edvanderpires@gmail.com) on 2015-10-28T21:54:08Z (GMT) No. of bitstreams: 1 2015_dis_smsilva.pdf: 6345616 bytes, checksum: 705401ad498eb92e473d5a63a9e41c49 (MD5) / Made available in DSpace on 2015-10-28T21:54:08Z (GMT). No. of bitstreams: 1 2015_dis_smsilva.pdf: 6345616 bytes, checksum: 705401ad498eb92e473d5a63a9e41c49 (MD5) Previous issue date: 2015 / A great number of systems defined as complex consist of interconnected parts or individual components performing a network or graph. Communication between the parts is essential for their existence so that it is necessary a better understanding of their ability to communicate depending on the amount of information that transits. The dynamics of package transport in these systems and the emergence of congestion are problems of high scientific and economic interest. In this work we investigate the dynamical properties of transport of packages (informations) between sources and previously defined destinations, considering different models of spatially embbeded networks such as lattice and Kleinberg. More precisely, we study a second-order continuous phase transition from a phase of free transport to a congestion phase, when the packages are accumulated in certain regions of the network. By means of a Finite Size Scaling, we describe this phase transition characterizing its critical exponents. For 1D and 2D lattice networks, we observe that the critical parameter $p_c$ scales with exponents approximately $-1$ and $-0.5$ with respect to the system size. In the case of Kleinberg newtorks where shortcuts between two nodes $i$ and $j$ are added to the network according to a probability distibution given by $P(r_ {ij}) sim r_{ij}^{-alpha}$, we show that the best scenario occurs when $alpha = d$, where $d$ is the dimention of the topology structure. In this regime, package traffic were shown to be more resilient to the increase of number of packages in the network. The confirmation of our result is obtained not only from direct measure of order parameter, that is, the ratio between undelivered and generated packets, but is also supported by our analysis of finite size. / Um grande número de sistemas complexos são constituídos de partes ou componentes individuais interligados. A comunicação nestes sistemas é essencial para a sua existência sendo necessário o estudo de sua capacidade de se comunicar dependendo da quantidade de informação que está circulando na rede. A dinâmica do transporte de pacotes de informação em tais sistemas e o surgimento de seu congestionamento são problemas de elevado interesse científico e econômico. Neste trabalho, nós determinamos como os elementos de vários modelos de rede espacialmente embebidos, sendo redes regulares e redes de Kleinberg, alteram suas propriedades dinâmicas de transporte de pacotes tratando-as como redes de comunicação. Mais precisamente, estudamos uma transição de fase contínua de segunda ordem de uma fase de transporte de pacote livre para uma fase de congestão, quando os pacotes são acumulados na rede, e descrevemos esta transição por meio de expoentes críticos. Para as redes regulares em $1D$ e $2D$, vimos que respectivamente, o parâmetro crítico $p_c$ escala com expoentes de aproximadamente $-1$ e $-0.5$ para o tamanho do sistema. Já nas redes de Kleinberg, nós mostramos que o melhor cenário, quando o tráfego de pacotes é mais resiliente para o aumento do número de pacotes, é conseguido quando os atalhos são adicionados à rede entre dois nós, nomeadamente nós $ i $ e $ j $, com probabilidade $P(r_ {ij}) sim r_{ij}^{-alpha}$ quando $alpha = d $, onde $ d $ é a dimensão da estrutura subjacente. Além disso, este resultado é obtido não só a partir da medição direta do parâmetro de ordem, ou seja, a relação entre o número de pacotes não entregues e pacotes gerados, mas também é suportada pela nossa análise de tamanho finito.

Made available in DSpace on 2010-04-20T20:57:00Z (GMT). No. of bitstreams: 3 LuizRogeriodeCamargos2006.pdf.jpg: 10723 bytes, checksum: 516814bd3cbd115cd30ae6b389b2c4a1 (MD5) LuizRogeriodeCamargos2006.pdf.txt: 283928 bytes, checksum: ec5321762f0b1782efdd12edf9bce626 (MD5) LuizRogeriodeCamargos2006.pdf: 1071970 bytes, checksum: 57350165057e9863f9e430e137e29a22 (MD5) Previous issue date: 2006-12-18T00:00:00Z / This thesis is a critical discussion, under the light of expectation formation, of the relation that interposes between economic science as body of knowledge and its agents. First, we examine significant approaches of expectation formation currently used in economic analysis, indicating its insufficiencies. We argue that the incorporation of expectation, in any analytical treatment, must involve, mainly, epistemic basis. Second, under the perspective of the reflexive modernity theory developed by Anthony Giddens, we search to identify plausible basis for a theory of economic expectation. We argue that the process of expectation formation is a social construction derived from the interdependence between experts and laypeople. We call this conclusion by hypothesis of socially constructed expectation (HESC). Third, we propose an analytical framework to incorporate the HESC. Basically, expectation information spreads out through media and by face to face interactions between agents. New information does not necessarily mean expectation update, but it goes to mainly depend on economic knowledge and neighborhood of the agent. For last, an application example: the model-HESC was submitted to three macroeconomic experiments, comparing its results with those gotten by Mankiw and Reis (2002). Although the similarities, there are significant differences. The first conclusion of this thesis is methodological: expectations of the agents in macroeconomic models are not determined from equations of the model. The second is normative: knowledge and neighborhood are able to perpetuate inefficiencies due to errors of expectations. The third concerns with positive economics: the differences between the results gotten in the model of information-rigid of the authors above and those in the model-HESC point with respect to new explanatory possibilities. / Esta tese é uma discussão crítica, sob a ótica da formação de expectativas, da relação que se interpõe entre ciência econômica, como corpo de conhecimento, e seus agentes. Primeiro, examinamos abordagens relevantes sobre expectativas na análise econômica, indicando suas insuficiências. Argumentamos que a incorporação de expectativa, em qualquer tratamento analítico, deve envolver, principalmente, fundamentos epistêmicos. Segundo, sob a perspectiva da teoria de modernidade reflexiva desenvolvida por Anthony Giddens, buscamos identificar bases plausíveis para uma teoria de expectativa econômica. Concluímos que o processo de formação de expectativa é construção social, a partir da interdependência entre expertos e leigos. Denominamos esta conclusão por hipótese de expectativas socialmente construídas (HESC). Terceiro, propusemos um arcabouço analítico para incorporar a HESC. Basicamente, informação de expectativa se difunde através da mídia e do contato face a face entre agentes. Nova informação não resulta necessariamente em revisão de expectativas, o que vai depender, principalmente, de conhecimento econômico e vizinhança do agente. Por último, um exemplo de aplicação: o modelo-HESC foi submetido a três experimentos macroeconômicos, e seus resultados comparados àqueles obtidos por Mankiw e Reis (2002). A primeira conclusão desta tese é metodológica: expectativas dos agentes em modelos macroeconômicos não são determinadas a partir de equações do próprio modelo. A segunda é normativa: conhecimento e vizinhança são capazes de perpetuar ineficiências decorrentes de erros de expectativas. A terceira está relacionado com economia positiva: as diferenças entre os resultados do modelo de informação-rígida obtidos pelos autores acima e aqueles do modelo-HESC apontam para novas possibilidades explanatórias.

abstract: This dissertation explores how practices and interactions of actors at different scales structure social networks and lead to the emergence of social complexity in middle range societies. To investigate this process, I apply a complex adaptive systems approach and a methodology that combines network science with analytical tools from economics to the three sub-periods of the Prehistoric Bronze Age (The Philia Phase, PreBA 1 and PreBA 2) on Cyprus, a transformational period marked by social and economic changes evident in the material record. Using proxy data representative of three kinds of social interactions or facets of social complexity, the control of labor, participation in trade networks, and access to resources, at three scales, the community, region and whole island, my analysis demonstrates the variability in and non-linear trajectory for the emergence of social complexity in middle range society. The results of this research indicate that complexity emerges at different scales, and times in different places, and only in some facets of complexity. Cycles of emergence are apparent within the sub-periods of the PreBA, but a linear trajectory of increasing social complexity is not evident through the period. Further, this research challenges the long-held notion that Cyprus' involvement in the international metal trade lead to the emergence of complexity. Instead, I argue based on the results presented here, that the emergence of complexity is heavily influenced by endogenous processes, particularly the social interactions that limited participation in an on-island exchange system that flourished on the island during the Philia Phase, disintegrated along the North Coast during the PreBA 1 and was rebuilt across the island by the end of the period. Thus, the variation seen in the emergence of social complexity on Cyprus during the PreBA occurred as the result of a bottom-up process in which the complex and unequal interactions and relationships between social actors structured and restructured social networks across scales differently over time and space. These results speak more broadly about the variability of middle range societies and the varying conditions under which social complexity can emerge and add to our understanding of this phenomenon. / Dissertation/Thesis / Doctoral Dissertation Anthropology 2017

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Um grande nÃmero de sistemas complexos sÃo constituÃdos de partes ou componentes individuais interligados. A comunicaÃÃo nestes sistemas à essencial para a sua existÃncia sendo necessÃrio o estudo de sua capacidade de se comunicar dependendo da quantidade de informaÃÃo que està circulando na rede. A dinÃmica do transporte de pacotes de informaÃÃo em tais sistemas e o surgimento de seu congestionamento sÃo problemas de elevado interesse cientÃfico e econÃmico. Neste trabalho, nÃs determinamos como os elementos de vÃrios modelos de rede espacialmente embebidos, sendo redes regulares e redes de Kleinberg, alteram suas propriedades dinÃmicas de transporte de pacotes tratando-as como redes de comunicaÃÃo. Mais precisamente, estudamos uma transiÃÃo de fase contÃnua de segunda ordem de uma fase de transporte de pacote livre para uma fase de congestÃo, quando os pacotes sÃo acumulados na rede, e descrevemos esta transiÃÃo por meio de expoentes crÃticos. Para as redes regulares em $1D$ e $2D$, vimos que respectivamente, o parÃmetro crÃtico $p_c$ escala com expoentes de aproximadamente $-1$ e $-0.5$ para o tamanho do sistema. Jà nas redes de Kleinberg, nÃs mostramos que o melhor cenÃrio, quando o trÃfego de pacotes à mais resiliente para o aumento do nÃmero de pacotes, à conseguido quando os atalhos sÃo adicionados à rede entre dois nÃs, nomeadamente nÃs $ i $ e $ j $, com probabilidade $P(r_ {ij}) sim r_{ij}^{-alpha}$ quando $alpha = d $, onde $ d $ à a dimensÃo da estrutura subjacente. AlÃm disso, este resultado à obtido nÃo sà a partir da mediÃÃo direta do parÃmetro de ordem, ou seja, a relaÃÃo entre o nÃmero de pacotes nÃo entregues e pacotes gerados, mas tambÃm à suportada pela nossa anÃlise de tamanho finito. / A great number of systems defined as complex consist of interconnected parts or individual components performing a network or graph. Communication between the parts is essential for their existence so that it is necessary a better understanding of their ability to communicate depending on the amount of information that transits. The dynamics of package transport in these systems and the emergence of congestion are problems of high scientific and economic interest. In this work we investigate the dynamical properties of transport of packages (informations) between sources and previously defined destinations, considering different models of spatially embbeded networks such as lattice and Kleinberg. More precisely, we study a second-order continuous phase transition from a phase of free transport to a congestion phase, when the packages are accumulated in certain regions of the network. By means of a Finite Size Scaling, we describe this phase transition characterizing its critical exponents. For 1D and 2D lattice networks, we observe that the critical parameter $p_c$ scales with exponents approximately $-1$ and $-0.5$ with respect to the system size. In the case of Kleinberg newtorks where shortcuts between two nodes $i$ and $j$ are added to the network according to a probability distibution given by $P(r_ {ij}) sim r_{ij}^{-alpha}$, we show that the best scenario occurs when $alpha = d$, where $d$ is the dimention of the topology structure. In this regime, package traffic were shown to be more resilient to the increase of number of packages in the network. The confirmation of our result is obtained not only from direct measure of order parameter, that is, the ratio between undelivered and generated packets, but is also supported by our analysis of finite size.

O presente trabalho propõe-se a oferecer respostas à questão de como a informação é preservada num sistema, focalizando-se na distinção entre os papéis desempenhados pelos constituintes elementares e pelos estruturais na preservação da memória desse sistema. Os sistema simulados circunscreveram-se a malhas, com diferentes graus de regularidade, compostas pelo acoplamento de osciladores não-lineares que apresentam comportamento coerente no estado de equilíbrio. Malhas de Sincronismo de Fase, também conhecidas por PLLs (Phase Locked Loops), foram adotadas como elementos constituintes básicos dos sistemas analisados. Para tanto, utilizou-se a plataforma de cálculo MATLAB-SIMULINK, acompanhando-se as evoluções dos diversos sistemas e de seus parâmetros dinâmicos associados, possibilitando o estabelecimento da correspondência entre os valores dos referidos parâmetros dinâmicos com parâmetros gráficos \"sensíveis\" à estrutura das malhas. Os resultados obtidos indicam a coexistência/cooperação das componentes estrutural e elementar na determinação dos valores dos parâmetros dinâmicos no estado de equilíbrio do sistema. No entanto, evidencia-se que tais componentes apresentam importâncias distintas na determinação dos diferentes parâmetros dinâmicos. / This work was conceived aiming to present some answers to how the information is preserved in a system. The focus was laid on the distinction between the tasks played by the elementary components and the structure of the system. The simulated systems were composed by coupled oscillators, more precisely by PLLs (Phase Locked Loops), arranged in networks of different regularities. Simulations were performed using Matlab-Simulink software to build a correlation between the final state dynamical parameters of the system and its degree of regularity. Results show the influence of both elementary and structural components on the system attained state. However the responses of characteristics parameters of the system to changes in the regularity of the structured network may greatly differ from one parameter to another. This behavior may suggest different strategies to preserve information of the system according to the information to be kept.