Relevant bibliographies by topics / Complex Networks of treaties

Academic literature on the topic 'Complex Networks of treaties'

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Published: 11 March 2023

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Journal articles on the topic "Complex Networks of treaties"

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Denters, Erik, and Tarcisio Gazzini. "The Role of African Regional Organizations in the Promotion and Protection of Foreign Investment." Journal of World Investment & Trade 18, no. 3 (December 26, 2017): 449–92. http://dx.doi.org/10.1163/22119000-12340048.

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A complex, fragmented and heterogeneous network of domestic and international legal instruments promotes and protects foreign investment in Africa. While bilateral treaties seem to be increasingly unpopular, regionalism is clearly on the rise in the continent. The article examines how regional treaties have contributed to upgrade the current regulation of foreign investment. From this perspective, Africa can be seen as a normative laboratory. Regional treaties, most prominently those concluded within the Economic Community of West African States (ECOWAS) and the Southern African Development Community (SADC), contain several important novelties meant to rebalance the rights and obligations of the various stakeholders as well as to safeguard host State policy space. The content of these treaties has been brought more in line with the evolution of international law, especially with regard to the protection of the environment, social and human rights, transparency, corruption, public scrutiny, economic development, and corporate responsibility.
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Fang, Xinli, Qiang Yang, and Wenjun Yan. "Outer Synchronization between Complex Networks with Nonlinear Time-Delay Characteristics and Time-Varying Topological Structures." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/437673.

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This paper exploits the network outer synchronization problem in a generic context for complex networks with nonlinear time-delay characteristics and nonidentical time-varying topological structures. Based on the classic Lyapunov stability theory, the synchronization criteria and adaptive control strategy are presented, respectively, by adopting an appropriate Lyapunov-Krasovskii energy function and the convergence of the system error can also be well proved. The existing results of network outer synchronization can be obtained by giving certain conditions, for example, treating the coupling matrices as time-invariant, and by applying the suggested generic synchronization criteria and control scheme. The numerical simulation experiments for networks scenarios with dynamic chaotic characteristics and time-varying topologies are carried out and the result verifies the correctness and effectiveness of the proposed control solution.
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Liu, Xiangrong, Zengyan Hong, Juan Liu, Yuan Lin, Alfonso Rodríguez-Patón, Quan Zou, and Xiangxiang Zeng. "Computational methods for identifying the critical nodes in biological networks." Briefings in Bioinformatics 21, no. 2 (February 12, 2019): 486–97. http://dx.doi.org/10.1093/bib/bbz011.

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Abstract A biological network is complex. A group of critical nodes determines the quality and state of such a network. Increasing studies have shown that diseases and biological networks are closely and mutually related and that certain diseases are often caused by errors occurring in certain nodes in biological networks. Thus, studying biological networks and identifying critical nodes can help determine the key targets in treating diseases. The problem is how to find the critical nodes in a network efficiently and with low cost. Existing experimental methods in identifying critical nodes generally require much time, manpower and money. Accordingly, many scientists are attempting to solve this problem by researching efficient and low-cost computing methods. To facilitate calculations, biological networks are often modeled as several common networks. In this review, we classify biological networks according to the network types used by several kinds of common computational methods and introduce the computational methods used by each type of network.
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SMITH, REGINALD D. "THE DYNAMICS OF INTERNET TRAFFIC: SELF-SIMILARITY, SELF-ORGANIZATION, AND COMPLEX PHENOMENA." Advances in Complex Systems 14, no. 06 (December 2011): 905–49. http://dx.doi.org/10.1142/s0219525911003451.

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The Internet is one of the largest and most complex communication and information exchange networks ever created. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, BGP storms, and comparisons of the Internet and biological models will be covered.
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Sacco, Pier Luigi, Alex Arenas, and Manlio De Domenico. "The Resilience of the Multirelational Structure of Geopolitical Treaties is Critically Linked to Past Colonial World Order and Offshore Fiscal Havens." Complexity 2023 (January 7, 2023): 1–9. http://dx.doi.org/10.1155/2023/5280604.

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The governance of the political and economic world order builds on a complex architecture of international treaties at various geographical scales. In a historical phase of high institutional turbulence, assessing the stability of such architecture with respect to the unilateral defection of single countries and the breakdown of single treaties is important. We carry out this analysis on the whole global architecture and find that the countries with the highest disruption potential are mostly medium-small and micro countries. Political stability is highly dependent on many former colonial overseas territories that are today part of the global network of fiscal havens, as well as on emerging economies, mostly from South-East Asia. Economic stability depends on medium-sized European and African countries. Single global treaties have surprisingly less disruptive potential, with the major exception of the WTO. Our results suggest that the potential fragility of the world order seems to be more directly related to global inequality and fiscal injustice than commonly believed and that the legacy of the colonial world order is still strong in the current international relations scenario. In particular, vested interests related to tax avoidance seem to have a structural role in the political architecture of global governance.
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Wiley, David J., Ilona Juan, Hao Le, Xiaodong Cai, Lisa Baumbach, Christine Beattie, and Gennaro D'Urso. "Yeast Augmented Network Analysis (YANA): a new systems approach to identify therapeutic targets for human genetic diseases." F1000Research 3 (June 2, 2014): 121. http://dx.doi.org/10.12688/f1000research.4188.1.

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Genetic interaction networks that underlie most human diseases are highly complex and poorly defined. Better-defined networks will allow identification of a greater number of therapeutic targets.Here we introduce our Yeast Augmented Network Analysis (YANA) approach and test it with the X-linked spinal muscular atrophy (SMA) disease gene UBA1. First, we express UBA1 and a mutant variant in fission yeast and use high-throughput methods to identify fission yeast genetic modifiers of UBA1. Second, we analyze available protein-protein interaction network databases in both fission yeast and human to construct UBA1 genetic networks. Third, from these networks we identified potential therapeutic targets for SMA. Finally, we validate one of these targets in a vertebrate (zebrafish) SMA model. This study demonstrates the power of combining synthetic and chemical genetics with a simple model system to identify human disease gene networks that can be exploited for treating human diseases.
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Arel-Bundock, Vincent. "The Unintended Consequences of Bilateralism: Treaty Shopping and International Tax Policy." International Organization 71, no. 2 (2017): 349–71. http://dx.doi.org/10.1017/s0020818317000108.

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AbstractThe international tax system is a complex regime composed of thousands of bilateral tax treaties. These agreements coordinate policies between countries to avoid double taxation and encourage international investment. I argue that by solving this coordination problem on a bilateral basis, states have inadvertently created opportunities for treaty shopping by multinationals. These opportunities, in turn, reduce the potency of fiscal policy, put pressure on governments to change their domestic tax laws, and ultimately constrain state autonomy. This constraint is theoretically distinct from the usual race-to-the-bottom story and it generates different testable implications. I use a motivating case study to show how multinationals leverage the structure of the treaty network to reduce their tax burden. Then, I develop a new measure of treaty-shopping opportunities for firms in 164 countries. Where the proliferation of tax treaties allows multinationals to engage in treaty shopping, states’ fiscal autonomy is limited, and governments tend to maintain lower tax rates.
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Borschberg, Peter. "Luso-Johor-Dutch Relations in the Straits of Malacca and Singapore, c. 1600-1623." Itinerario 28, no. 2 (July 2004): 15–43. http://dx.doi.org/10.1017/s0165115300019471.

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The study of the early European colonial presence in Asia has been stimulated in recent years by a series of excellent works. These have been both of general and specialist nature, written not only by historians, but also by political scientists as well as specialists of international relations. The truly excellent study published in 2002 by Edward Keene, can be taken as a point in case. Central to his revisitation of seventeenth-century treaties of the United Dutch East India Company (VOC) with the Emperor of Kandy, is the notion of divided sovereignty expounded by Hugo Grotius around 1600-1610. It was against the backdrop of such concepts of divided sovereignty that the VOC could ultimately conclude its complex web of treaty relationships that broadly characterise the Dutch colonial empire in the East Indies up the advent of the French Revolution and the Napoleonic Wars. There is some legitimacy in contending that Keene's postulations effectively rework and reinterpret, at the level of international relations, what was once conveniently dubbed the ‘Age of Partnership’, i.e. an age characterised by trade-driven colonial empires that grew upon a complex, sometimes self-contradictory network of treaty relationships as well as formal and informal cooperation garnered from native elites. Admittedly such relations were often but not always based on unequal power and treaty relationships. Despite the uneven playing fields created by many such Euro-Asian treaties, especially those forged in the late sixteenth and early seventeenth centuries, the conclusion of treaties was assumed on the basis of the nominal co-equality of sovereigns and plenipotentiary agents acting on their behalf. European and Asian treaty partners were accepted as contracting equals, and this is particularly stunning given that the feudal world of European power politics at the time was, by comparison, probably more complex and legally structured than Asia. Certainly, the underlying power relations behind these early modern agreements were completely different from those imposed by the mature colonial powers on Asia at the zenith of nineteenth-century imperialism!
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ZHENG DA-FANG, SHEN SHUN-QING, and TAO RUI-BAO. "AN EXTENDED GENERATING FUNCTION TECHNIQUE FOR TREATING RANDOM WALKS ON COMPLEX NETWORKS." Acta Physica Sinica 37, no. 11 (1988): 1823. http://dx.doi.org/10.7498/aps.37.1823.

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Kim, Rakhyun E. "Is Global Governance Fragmented, Polycentric, or Complex? The State of the Art of the Network Approach." International Studies Review 22, no. 4 (September 18, 2019): 903–31. http://dx.doi.org/10.1093/isr/viz052.

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Abstract International institutions such as treaties and organizations shape, and are shaped by, the large web-like architecture of global governance. Yet we know little about what this architecture looks like, why certain structures are observed, and how they are linked to the functioning of international institutions as well as the overall effectiveness of global governance. Over the past decade, network science has emerged as a promising and indispensable approach to unraveling structural nuances and complexities of the system of international institutions. This article presents a state-of-the-art review of this emerging field of research and seeks to stimulate its further development. In this article, I draw connections between various network analyses of global governance that are found in different bodies of literature. In so doing, I integrate three separate but overlapping strands of work on institutional fragmentation, polycentricity, and complexity and bring much-needed conceptual clarity to the debate. Building on previous studies, I propose a framework for operationalizing fragmentation, polycentricity, and complexity in network terms in order to enable systematic and comparative analysis of global governance systems. This article argues that there is much potential in the network approach and makes a case for advancing the “network science of global governance.”
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Dissertations / Theses on the topic "Complex Networks of treaties"

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Sanatkar, Mohammad Reza. "Epidemics on complex networks." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/14097.

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Master of Science
Department of Electrical and Computer Engineering
Karen Garrett
Bala Natarajan
Caterina Scoglio
In this thesis, we propose a statistical model to predict disease dispersal in dynamic networks. We model the process of disease spreading using discrete time Markov chain. In this case, the vector of probability of infection is the state vector and every element of the state vector is a continuous variable between zero and one. In discrete time Markov chains, state probability vectors in each time step depends on state probability vector in the previous time step and one step transition probability matrix. The transition probability matrix can be time variant or time invariant. If this matrix’s elements are functions of elements of vector state probability in previous step, the corresponding Markov chain is non linear dynamical system. However, if those elements are independent of vector state probability, the corresponding Markov chain is a linear dynamical system. We especially focus on the dispersal of soybean rust. In our problem, we have a network of US counties and we aim at predicting that which counties are more likely to get infected by soybean rust during a year based on observations of soybean rust up to that time as well as corresponding observations to previous years. Other data such as soybean and kudzu densities in each county, daily wind data, and distance between counties helps us to build the model. The rapid growth in the number of Internet users in recent years has led malware generators to exploit this potential to attack computer users around the word. Internet users are frequent targets of malicious software every day. The ability of malware to exploit the infrastructures of networks for propagation determines how detrimental they can be to the network’s security. Malicious software can make large outbreaks if they are able to exploit the structure of the Internet and interactions between users to propagate. Epidemics typically start with some initial infected nodes. Infected nodes can cause their healthy neighbors to become infected with some probability. With time and in some cases with external intervention, infected nodes can be cured and go back to a healthy state. The study of epidemic dispersals on networks aims at explaining how epidemics evolve and spread in networks. One of the most interesting questions regarding an epidemic spread in a network is whether the epidemic dies out or results in a massive outbreak. Epidemic threshold is a parameter that addresses this question by considering both the network topology and epidemic strength.
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Venkatesan, Vaidehi. "Cuisines as Complex Networks." University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321969310.

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Gonçalves, Bruno Miguel Tavares. "Topology of complex networks." Master's thesis, Universidade de Aveiro, 2004. http://hdl.handle.net/10773/16685.

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Mestrado em Física da Matéria Condensada
The study of connectivity correlations between nodes has been somewhat neglected in the study of Complex Networks. We try to correct this by using the correlation function, combined with the concept of shell to calculate the connectivity distribution, P(d)(k) and the average connectivity for the neighbours, of a node as a function of distance d. With these results we create a better idea of how the Internet is organized and structured. We also determine that the time evolution of the Internet is coherent with the results obtained in the literature for the case of accelerated growth by the process of edge copying with a probability p=0.58.
O estudo das correlações de conectividade entre nodos tem sido algo negligenciado no estudo de Redes Complexas. Nós tentamos alterar esta situação usando funções de correlação em conjunto com o concenito de camada para calcular a distribuição de conectividades P(d)(k) e a conectividade média dos vizinhos de um nodo como função da distância d. Com estes resultados criamos uma melhor ideia acerca de como a Internet está organizada e estruturada. Concluimos também que a evolução da Internet é coerente com os resultados obtidos na literatura para o caso de crescimento acelerado devido a um processo de cópia de vértices com probabilidade p=0.58.
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Buzzanca, Marco. "Sociality in Complex Networks." Doctoral thesis, Università di Catania, 2018. http://hdl.handle.net/10761/3766.

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The study of network theory is nothing new, as we may find the first example of a proof of network theory back in the 18th century. However, in recent times, many researchers are using their time to investigate networks, giving new life to an old topic. As we are living in the era of information, networks are everywhere, and their complexity is constantly rising. The field of complex networks attempts to address this complexity with innovative solutions. Complex networks all share a series of common topological features, which revolve around the relationship between nodes, where relationship is intended in the most abstract possible way. Nonetheless, it is important to study these relationships because they can be exploited in several scenarios, like web page searching, recommender systems, e-commerce and so on. This thesis presents studies of sociality in complex networks, ranging from the microscale, which focuses the attention on the point of view of single nodes, to the mesoscale, instead shifts the interest in node groups.
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Marchese, Emiliano. "Optimizing complex networks models." Thesis, IMT Alti Studi Lucca, 2022. http://e-theses.imtlucca.it/356/1/Marchese_phdthesis.pdf.

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Analyzing real-world networks ultimately amounts at com- paring their empirical properties with the outcome of a proper, statistical model. The far most common, and most useful, approach to define benchmarks rests upon the so-called canonical formalism of statistical mechanics which has led to the definition of the broad class of models known as Exponential Random Graphs (ERGs). Generally speaking, employing a model of this family boils down at maximizing a likelihood function that embodies the available information about a certain system, hence constituting the desired benchmark. Although powerful, the aforementioned models cannot be solved analytically, whence the need to rest upon numerical recipes for their optimization. Generally speaking, this is a hard task, since real-world networks can be enormous in size (for example, consisting of billions of nodes and links), hence requiring models with ‘many’ parameters (say, of the same order of magnitude of the number of nodes). This evidence calls for optimization algorithms which are both fast and scalable: the collection of works constituting the present thesis represents an attempt to fill this gap. Chapter 1 provides a quick introduction to the topic. Chapter 2 deals specifically with ERGs: after reviewing the basic concepts constituting the pillars upon which such a framework is based, we will discuss several instances of it and three different numerical techniques for their optimization. Chapter 3, instead, focuses on the detection of mesoscale structures and, in particular, on the formalism based upon surprise: as the latter allows any partition of nodes to be assigned a p-value, detecting a specific, mesoscale structural organization can be understood as the problem of finding the corresponding, most significant partition - i.e. an optimization problem whose score function is, precisely, surprise. Finally, chapter 4 deals with the application of a couple of ERGs and of the surprise-based formalism to cryptocurrencies (specifically, Bitcoin).
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Trusina, Ala. "Complex Networks : Structure, Function , Evolution." Doctoral thesis, Umeå University, Physics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-608.

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A complex system is a system for which the statement "the whole is greater than the sum of its parts" holds. A network can be viewed as a backbone of a complex system. Combining the knowledge about the entities constituting the complex system with the properties of the interaction patterns we can get a better understanding of why the whole is greater than the sum. One of the purposes of network studies, is to relate the particular structural and dynamical properties of the network to the function it is designed to perform. In the present work I am briefly presenting some of the advances that have been achieved in the field of the complex networks together with the contributions which I have been involved in.

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Iyer, Swami. "Evolutionary dynamics on complex networks." Thesis, University of Massachusetts Boston, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3564666.

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Many complex systems such as the Internet can be represented as networks, with vertices denoting the constituent components of the systems and edges denoting the patterns of interactions among the components. In this thesis, we are interested in how the structural properties of a network, such as its average degree, degree distribution, clustering, and homophily affect the processes that take place on it. In the first part of the thesis we focus on evolutionary game theory models for studying the evolution of cooperation in a population of predominantly selfish individuals. In the second part we turn our attention to an evolutionary model of disease dynamics and the impact of vaccination on the spread of infection. Throughout the thesis we use a network as an abstraction for a population, with vertices representing individuals in the population and edges specifying who can interact with whom. We analyze our models for a well-mixed population, i.e., an infinite population with random mixing, and compare the theoretical results with those obtained from computer simulations on model and empirical networks.

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Taylor, Alan J. "Computational tools for complex networks." Thesis, University of Strathclyde, 2009. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=12414.

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Cooper, Kathryn. "Complex Networks : Similarity and Dynamics." Thesis, Imperial College London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516486.

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RAMOS, MARLON FERREIRA. "OPINION DYNAMICS IN COMPLEX NETWORKS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26418@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
FUNDAÇÃO DE APOIO À PESQUISA DO ESTADO DO RIO DE JANEIRO
BOLSA NOTA 10
Esta tese aborda diversos problemas que podem ser tratados mediante modelos de dinâmica de opiniões, segundo os quais os indivíduos, conectados de acordo com redes complexas, interagem mediante regras que moldam as preferências e o posicionamento desses indivíduos com relação a uma determinada questão. A metodologia utilizada para investigar os padrões emergentes dessas interações consiste na utilização de diversas técnicas da física estatística. A tese está organizada em torno de quatro problemas distintos, com uma questão particular a ser respondida em cada caso, buscando sempre a validação empírica dos resultados teóricos e computacionais. No primeiro trabalho, é respondida a seguinte questão básica sobre propriedades da rede que podem ter impacto sobre os processos de propagação: quais são os valores típicos das distâncias, coeficiente de aglomeração e outras grandezas estruturais da rede, quando considerado o ensemble de redes aleatórias com uma assortatividade fixa? No segundo trabalho, investigamos os padrões que surgem na avaliação de filmes, considerando como fonte o IMDb (Internet Movie Database). Encontramos que a distribuição de votos apresenta um comportamento livre de escala com um expoente muito próximo de 3/2. Curiosamente, esse padrão é robusto, independente de atributos dos filmes como nota média, idade ou gênero. A análise empírica aponta para um mecanismo de propagação de adoções simples, que gera uma dinâmica de avalanches de campo médio. No terceiro trabalho, abordamos o problema de múltiplas escolhas por meio de um modelo que inclui a possibilidade de indecisão e onde as escolhas dos indivíduos evoluem segundo uma regra de pluralidade. Mostramos que essa dinâmica em redes com a propriedade de mundo pequeno produz diferentes estados estacionários realísticos, que dependem do número de alternativas e da distribuição de graus: consenso, distribuição de adoções larga similar à reais e situações onde a indecisão predomina, quando o número de alternativas é suficientemente grande. Por último, investigamos o surgimento de posições extremas na sociedade, mediante pesquisas em uma ampla gama de questões. O aumento de atitudes extremas tem como precursor uma relação não linear entre a fração de extremistas e a de moderados. Propomos um modelo, com regras de ativação baseadas na teimosia dos indivíduos, que permite interpretar o início da não linearidade em termos de uma transição abrupta do tipo percolação de inicialização onde acontecem cascatas de extremismo. Como conclusão geral, destacamos que esta tese ilustra como os modelos de opinião, aliados às enormes bases de dados, fornecem resultados com poder de interpretação e predição dos padrões empíricos.
This thesis addresses several problems that can be treated through models of opinion dynamics, according to which individuals, connected according to complex networks, interact through rules that shape their preferences and opinions in relation to a particular issue. The methodology used to investigate the patterns that emerge from those interactions relies on the use of various techniques of statistical physics. The thesis is organized around four distinct problems, with a particular question to be answered in each case, always looking for empirical validation of the theoretical and computational results. In the first work, it is answered the following basic question about network properties that can have impact on the spreading processes: what are the typical values of the distances, clustering coefficient and other structural quantities, when considering the ensemble of random networks with fix assortativity? In the second study, we investigated the patterns that emerge in the ratings of films, considering as source IMDb (Internet Movie Database). We found that the distribution of votes has a scale-free behavior with a exponent close to 3/2. Interestingly, this pattern is robust, independently of movie attributes such as average note, age or gender. The empirical analysis points to a simple mechanism of adoption propagation, that generates mean-field avalanches. In the third study, we discuss the problem of multiple choices by means of a model which includes the possibility of indecision and where the choices of individuals evolve according to a plurality rule. We show that this dynamics on top of networks with the small-world property produces different stationary states that depend on the number of alternatives and on the degree distribution: consensus, wide adoption distributions similar to actual ones and situations where indecision prevails when the number of alternatives is large enough. Finally, we investigate the appearance of extreme positions in society, through the polls on a wide variety of questions. The increase of extreme opinions has as precursor a non-linear relationship between the fraction of extremists and that of moderates. We propose a model with activation rules, based on the stubbornness of the individuals, which enables interpreting the beginning of the non-linearity in terms of an abrupt transition of the class of bootstrap percolation, where activation cascades occur. As a general conclusion, we emphasize that this thesis illustrates how opinion models, combined with huge databases, provide results with power of interpretation and prediction of empirical patterns.
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Books on the topic "Complex Networks of treaties"

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da F. Costa, Luciano, Alexandre Evsukoff, Giuseppe Mangioni, and Ronaldo Menezes, eds. Complex Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25501-4.

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Menezes, Ronaldo, Alexandre Evsukoff, and Marta C. González, eds. Complex Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-30287-9.

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Fortunato, Santo, Giuseppe Mangioni, Ronaldo Menezes, and Vincenzo Nicosia, eds. Complex Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01206-8.

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Ben-Naim, Eli, Hans Frauenfelder, and Zoltan Toroczkai, eds. Complex Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/b98716.

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Menezes, Ronaldo. Complex Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Teixeira, Andreia Sofia, Diogo Pacheco, Marcos Oliveira, Hugo Barbosa, Bruno Gonçalves, and Ronaldo Menezes, eds. Complex Networks XII. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81854-8.

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Contucci, Pierluigi, Ronaldo Menezes, Andrea Omicini, and Julia Poncela-Casasnovas, eds. Complex Networks V. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05401-8.

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Cornelius, Sean P., Clara Granell Martorell, Jesús Gómez-Gardeñes, and Bruno Gonçalves, eds. Complex Networks X. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14459-3.

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Ghoshal, Gourab, Julia Poncela-Casasnovas, and Robert Tolksdorf, eds. Complex Networks IV. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36844-8.

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Göknar, İzzet Cem, and Levent Sevgi, eds. Complex Computing-Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-30636-6.

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Book chapters on the topic "Complex Networks of treaties"

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Arora, Sanjeev, Summers Kalishman, Denise Dion, Karla Thornton, Glen Murata, Connie Fassler, Steven M. Jenkusky, et al. "Knowledge Networks for Treating Complex Diseases in Remote, Rural, and Underserved Communities." In Learning Trajectories, Innovation and Identity for Professional Development, 47–70. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1724-4_3.

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Silva, Thiago Christiano, and Liang Zhao. "Complex Networks." In Machine Learning in Complex Networks, 15–70. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-17290-3_2.

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Rubido, Nicolás. "Complex Networks." In Energy Transmission and Synchronization in Complex Networks, 13–43. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22216-5_2.

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Burguillo, Juan C. "Complex Networks." In Self-organizing Coalitions for Managing Complexity, 35–56. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69898-4_3.

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Liu, Jing, Hussein A. Abbass, and Kay Chen Tan. "Complex Networks." In Evolutionary Computation and Complex Networks, 23–36. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-60000-0_2.

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Erciyes, K. "Complex Networks." In Texts in Computer Science, 417–42. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73235-0_14.

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Bertin, Eric. "Complex Networks." In Statistical Physics of Complex Systems, 181–206. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79949-6_6.

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Amaral, Ines. "Complex Networks." In Encyclopedia of Big Data, 198–201. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-32010-6_40.

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Amaral, Ines. "Complex Networks." In Encyclopedia of Big Data, 1–3. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-32001-4_40-1.

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Danziger, Michael M., Louis M. Shekhtman, Amir Bashan, Yehiel Berezin, and Shlomo Havlin. "Vulnerability of Interdependent Networks and Networks of Networks." In Understanding Complex Systems, 79–99. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23947-7_5.

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Conference papers on the topic "Complex Networks of treaties"

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Yang, Zhun, Adam Ishay, and Joohyung Lee. "NeurASP: Embracing Neural Networks into Answer Set Programming." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/243.

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We present NeurASP, a simple extension of answer set programs by embracing neural networks. By treating the neural network output as the probability distribution over atomic facts in answer set programs, NeurASP provides a simple and effective way to integrate sub-symbolic and symbolic computation. We demonstrate how NeurASP can make use of a pre-trained neural network in symbolic computation and how it can improve the neural network's perception result by applying symbolic reasoning in answer set programming. Also, NeurASP can make use of ASP rules to train a neural network better so that a neural network not only learns from implicit correlations from the data but also from the explicit complex semantic constraints expressed by the rules.
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Xie, Chunyu, Ce Li, Baochang Zhang, Chen Chen, Jungong Han, and Jianzhuang Liu. "Memory Attention Networks for Skeleton-based Action Recognition." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/227.

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Skeleton-based action recognition task is entangled with complex spatio-temporal variations of skeleton joints, and remains challenging for Recurrent Neural Networks (RNNs). In this work, we propose a temporal-then-spatial recalibration scheme to alleviate such complex variations, resulting in an end-to-end Memory Attention Networks (MANs) which consist of a Temporal Attention Recalibration Module (TARM) and a Spatio-Temporal Convolution Module (STCM). Specifically, the TARM is deployed in a residual learning module that employs a novel attention learning network to recalibrate the temporal attention of frames in a skeleton sequence. The STCM treats the attention calibrated skeleton joint sequences as images and leverages the Convolution Neural Networks (CNNs) to further model the spatial and temporal information of skeleton data. These two modules (TARM and STCM) seamlessly form a single network architecture that can be trained in an end-to-end fashion. MANs significantly boost the performance of skeleton-based action recognition and achieve the best results on four challenging benchmark datasets: NTU RGB+D, HDM05, SYSU-3D and UT-Kinect.
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Hwang, Yunsuk, Jiajing Lin, David Schechter, and Ding Zhu. "Predicting Well Performance in Naturally Fractured Reservoir." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-11604.

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Multiple hydraulic fracture treatments in reservoirs with natural fractures create complex fracture networks. Predicting well performance in such a complex fracture network system is an extreme challenge. The statistical nature of natural fracture networks changes the flow characteristics from that of a single linear fracture. Simply using single linear fracture models for individual fractures, and then summing the flow from each fracture as the total flow rate for the network could introduce significant error. In this paper we present a semi-analytical model by a source method to estimate well performance in a complex fracture network system. The method simulates complex fracture systems in a more reasonable approach. The natural fracture system we used is fractal discrete fracture network model. We then added multiple dominating hydraulic fractures to the natural fracture system. Each of the hydraulic fractures is connected to the horizontal wellbore, and some of the natural fractures are connected to the hydraulic fractures through the network description. Each fracture, natural or hydraulically induced, is treated as a series of slab sources. The analytical solution of superposed slab sources provides the base of the approach, and the overall flow from each fracture and the effect between the fractures are modeled by applying the superposition principle to all of the fractures. The fluid inside the natural fractures flows into the hydraulic fractures, and the fluid of the hydraulic fracture from both the reservoir and the natural fractures flows to the wellbore. This paper also shows that non-Darcy flow effects have an impact on the performance of fractured horizontal wells. In hydraulic fracture calculation, non-Darcy flow can be treated as the reduction of permeability in the fracture to a considerably smaller effective permeability. The reduction is about 2% to 20%, due to non-Darcy flow that can result in a low rate. The semi-analytical solution presented can be used to efficiently calculate the flow rate of multistage-fractured wells. Examples are used to illustrate the application of the model to evaluate well performance in reservoirs that contain complex fracture networks.
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Nita, Andreea, and Laurentiu Rozylowicz. "Dynamics of the international environmental treaties - perspectives for future cooperation." In 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2020. http://dx.doi.org/10.1109/asonam49781.2020.9381333.

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Cai, Derun, Moxian Song, Chenxi Sun, Baofeng Zhang, Shenda Hong, and Hongyan Li. "Hypergraph Structure Learning for Hypergraph Neural Networks." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/267.

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Hypergraphs are natural and expressive modeling tools to encode high-order relationships among entities. Several variations of Hypergraph Neural Networks (HGNNs) are proposed to learn the node representations and complex relationships in the hypergraphs. Most current approaches assume that the input hypergraph structure accurately depicts the relations in the hypergraphs. However, the input hypergraph structure inevitably contains noise, task-irrelevant information, or false-negative connections. Treating the input hypergraph structure as ground-truth information unavoidably leads to sub-optimal performance. In this paper, we propose a Hypergraph Structure Learning (HSL) framework, which optimizes the hypergraph structure and the HGNNs simultaneously in an end-to-end way. HSL learns an informative and concise hypergraph structure that is optimized for downstream tasks. To efficiently learn the hypergraph structure, HSL adopts a two-stage sampling process: hyperedge sampling for pruning redundant hyperedges and incident node sampling for pruning irrelevant incident nodes and discovering potential implicit connections. The consistency between the optimized structure and the original structure is maintained by the intra-hyperedge contrastive learning module. The sampling processes are jointly optimized with HGNNs towards the objective of the downstream tasks. Experiments conducted on 7 datasets show shat HSL outperforms the state-of-the-art baselines while adaptively sparsifying hypergraph structures.
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Ma, Yuan-sheng, Xu Liu, Pei-fu Gu, Hai-feng Li, and Jing-fa Tang. "Evaluation of Chracteristic of Optical Thin Film By Neural Network System." In Optical Interference Coatings. Washington, D.C.: Optica Publishing Group, 1995. http://dx.doi.org/10.1364/oic.1995.mb13.

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Controlling and mastering the optical constant of thin film is a key factor concern for the optical coating. Each optical constant must be controlled very well to make the films meet requires desired. At present, there are many methods to characterize the optical constants of the films, for example: the envelop method, ellipsometry measurement, waveguide prism methode etc.[1]. All of them use numerical inversion technique to obtain the optical constants from the physical parameters measured. These methods are very well for treating their problems, but they have their main shortages of indefinite and very complex. We propose now an artifical neural network (ANN) model to simulate the relationship between the spectral character and optical constant of the thin films. ANN is a simplified mathematical model of biological network, it is extremely strong in dealing fuzzy and indefinite problem, and is widely used for the signal process and recgonization. Neural networks have the ability to learn directly from example data rather than following programmed rules based on a knowledge base, and can treat the problem extremely fast and tolerate data containg experimental error[2].
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McClure, Mark W., Mohsen Babazadeh, Sogo Shiozawa, and Jian Huang. "Fully Coupled Hydromechanical Simulation of Hydraulic Fracturing in Three-Dimensional Discrete Fracture Networks." In SPE Hydraulic Fracturing Technology Conference. SPE, 2015. http://dx.doi.org/10.2118/spe-173354-ms.

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Abstract We developed a hydraulic fracturing simulator that implicitly couples fluid flow with the stresses induced by fracture deformation in large, complex, three-dimensional discrete fracture networks. The simulator can describe propagation of hydraulic fractures and opening and shear stimulation of natural fractures. Fracture elements can open or slide, depending on their stress state, fluid pressure, and mechanical properties. Fracture sliding occurs in the direction of maximum resolved shear stress. Nonlinear empirical relations are used to relate normal stress, fracture opening, and fracture sliding to fracture aperture and transmissivity. Fluid leakoff is treated with a semianalytical one-dimensional leakoff model that accounts for changing pressure in the fracture over time. Fracture propagation is treated with linear elastic fracture mechanics. Non-Darcy pressure drop in the fractures due to high flow rate is simulated using Forchheimer's equation. A crossing criterion is implemented that predicts whether propagating hydraulic fractures will cross natural fractures or terminate against them, depending on orientation and stress anisotropy. Height containment of propagating hydraulic fractures between bedding layers can be modeled with a vertically heterogeneous stress field or by explicitly imposing hydraulic fracture height containment as a model assumption. The code is efficient enough to perform field-scale simulations of hydraulic fracturing with a discrete fracture network containing thousands of fractures, using only a single compute node. Limitations of the model are that all fractures must be vertical, the mechanical calculations assume a linearly elastic and homogeneous medium, proppant transport is not included, and the locations of potentially forming hydraulic fractures must be specified in advance. Simulations were performed of a single propagating hydraulic fracture with and without leakoff to validate the code against classical analytical solutions. Field-scale simulations were performed of hydraulic fracturing in a densely naturally fractured formation. The simulations demonstrate how interaction with natural fractures in the formation can help explain the high net pressures, relatively short fracture lengths, and broad regions of microseismicity that are often observed in the field during stimulation in low permeability formations, and which are not predicted by classical hydraulic fracturing models. Depending on input parameters, our simulations predicted a variety of stimulation behaviors, from long hydraulic fractures with minimal leakoff into surrounding fractures to broad regions of dense fracturing with a branching network of many natural and newly formed fractures.
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Schulz, Alexander, Fabian Hinder, and Barbara Hammer. "DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/319.

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Machine learning algorithms using deep architectures have been able to implement increasingly powerful and successful models. However, they also become increasingly more complex, more difficult to comprehend and easier to fool. So far, most methods in the literature investigate the decision of the model for a single given input datum. In this paper, we propose to visualize a part of the decision function of a deep neural network together with a part of the data set in two dimensions with discriminative dimensionality reduction. This enables us to inspect how different properties of the data are treated by the model, such as outliers, adversaries or poisoned data. Further, the presented approach is complementary to the mentioned interpretation methods from the literature and hence might be even more useful in combination with those. Code is available at https://github.com/LucaHermes/DeepView
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Ribeiro, Lionel H., Huina Li, and Jason E. Bryant. "Use of a CO2-Hybrid Fracturing Design to Enhance Production from Unpropped Fracture Networks." In SPE Hydraulic Fracturing Technology Conference. SPE, 2015. http://dx.doi.org/10.2118/spe-173380-ms.

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Abstract This paper introduces a new CO2-hybrid fracturing fluid design that intends to improve production from ultra-tight reservoirs and reduces freshwater usage. The design consists of: (1) injecting pure CO2 as the pad fluid to generate a complex fracture network, and (2) injecting a gelled slurry (water- or foamed-based) to generate near-wellbore conductivity. The motivation behind this design is that while current aqueous fluids provide sufficient primary hydraulic fracture conductivity back to the wellbore, they under-stimulate the reservoir and leave behind damaged stimulated regions deeper in the fracture network. Much of that (unpropped) stimulated area is ineffective for production due to interfacial tension effects, fines generation, and/or polymer damage. We present simulation work that demonstrates how CO2, with its low viscosity, can extend the bottom-hole treating pressure deeper in the reservoir and generate a larger producible surface area. We also present experimental evidence that CO2 leaves behind higher unpropped fracture conductivities than slick water. This paper does not address the many operational and logistical challenges of using CO2 as a fracturing fluid. Rather, it intends to demonstrate the production uplift potential of the proposed design, which seems particularly attractive in reservoirs capable of sustaining production from unpropped fractures (e.g., reservoirs with low stress anisotropy, high Young's modulus, and a pervasive set of natural fractures).
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Trajkovic, Ljiljana. "Complex Networks." In 2020 IEEE 19th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2020. http://dx.doi.org/10.1109/iccicc50026.2020.9450254.

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Reports on the topic "Complex Networks of treaties"

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Kleinberg, Robert D. Kleinberg Complex Networks. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada612226.

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Lai, Ying-Cheng. Security of Complex Networks. Fort Belvoir, VA: Defense Technical Information Center, February 2010. http://dx.doi.org/10.21236/ada567229.

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Lai, Ying C. Predicting and Controlling Complex Networks. Fort Belvoir, VA: Defense Technical Information Center, June 2015. http://dx.doi.org/10.21236/ada619238.

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Albert-Laszlo Barabasi. The Organization of Complex Metabolic Networks. Office of Scientific and Technical Information (OSTI), May 2006. http://dx.doi.org/10.2172/881797.

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E, Weinan, Jian Liu, Eric Vanden-Eijnden, A. Nadar, Tiejun Li, Hao Shen, D. Crommelin, and Jianfeng Lu. Structure and Dynamics of Complex Networks. Fort Belvoir, VA: Defense Technical Information Center, June 2012. http://dx.doi.org/10.21236/ada574664.

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Colbaugh, Richard, Kristin Glass, and Gerald Willard. Analysis of complex networks using aggressive abstraction. Office of Scientific and Technical Information (OSTI), October 2008. http://dx.doi.org/10.2172/1145172.

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Milenkovic, Olgica, and Angelia Nedich. Compressive Sensing and Coding for Complex Networks. Fort Belvoir, VA: Defense Technical Information Center, March 2013. http://dx.doi.org/10.21236/ada582392.

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Knio, Omar M. Analysis and Reduction of Complex Networks Under Uncertainty. Office of Scientific and Technical Information (OSTI), April 2014. http://dx.doi.org/10.2172/1129444.

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Ghanem, Roger G. Analysis and Reduction of Complex Networks Under Uncertainty. Office of Scientific and Technical Information (OSTI), July 2014. http://dx.doi.org/10.2172/1148680.

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Dorfler, Florian, Michael Chertkov, and Francesco Bullo. Synchronization in Complex Oscillator Networks and Smart Grids. Office of Scientific and Technical Information (OSTI), July 2012. http://dx.doi.org/10.2172/1047105.

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