852 resultados para information networks
Resumo:
The movement of water through the landscape can be investigated at different scales. This study dealt with the interrelation between bedrock lithology and the geometry of the overlying drainage systems. Parameters of fractal analysis, such as fractal dimension and lacunarity, were used to measure and quantify this relationship. The interrelation between bedrock lithology and the geometry of the drainage systems has been widely studied in the last decades. The quantification of this linkage has not yet been clearly established. Several studies have selected river basins or regularly shaped areas as study units, assuming them to be lithologically homogeneous. This study considered irregular distributions of rock types, establishing areas of the soil map (1:25,000) with the same lithologic information as study units. The tectonic stability and the low climatic variability of the study region allowed effective investigation of the lithologic controls on the drainage networks developed on the plutonic rocks, the metamorphic rocks, and the sedimentary materials existing in the study area. To exclude the effect of multiple in- and outflows in the lithologically homogeneous units, we focused this study on the first-order streams of the drainage networks. The geometry of the hydrologic features was quantified through traditional metrics of fluvial geomorphology and scaling parameters of fractal analysis, such as the fractal dimension, the reference density, and the lacunarity. The results demonstrate the scale invariance of both the drainage networks and the set of first-order streams at the study scale and a relationship between scaling in the lithology and the drainage network.
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Of the many state-of-the-art methods for cooperative localization in wireless sensor networks (WSN), only very few adapt well to mobile networks. The main problems of the well-known algorithms, based on nonparametric belief propagation (NBP), are the high communication cost and inefficient sampling techniques. Moreover, they either do not use smoothing or just apply it o ine. Therefore, in this article, we propose more flexible and effcient variants of NBP for cooperative localization in mobile networks. In particular, we provide: i) an optional 1-lag smoothing done almost in real-time, ii) a novel low-cost communication protocol based on package approximation and censoring, iii) higher robustness of the standard mixture importance sampling (MIS) technique, and iv) a higher amount of information in the importance densities by using the population Monte Carlo (PMC) approach, or an auxiliary variable. Through extensive simulations, we confirmed that all the proposed techniques outperform the standard NBP method.
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n this paper we propose the use of Networks of Bio-inspired Processors (NBP) to model some biological phenomena within a computational framework. In particular, we propose the use of an extension of NBP named Network Evolutionary Processors Transducers to simulate chemical transformations of substances. Within a biological process, chemical transformations of substances are basic operations in the change of the state of the cell. Previously, it has been proved that NBP are computationally complete, that is, they are able to solve NP complete problems in linear time, using massively parallel computations. In addition, we propose a multilayer architecture that will allow us to design models of biological processes related to cellular communication as well as their implications in the metabolic pathways. Subsequently, these models can be applied not only to biological-cellular instances but, possibly, also to configure instances of interactive processes in many other fields like population interactions, ecological trophic networks, in dustrial ecosystems, etc.
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We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.
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Seepage flow measurement is an important behavior indicator when providing information about dam performance. The main objective of this study is to analyze seepage by means of an artificial neural network model. The model is trained and validated with data measured at a case study. The dam behavior towards different water level changes is reproduced by the model and a hysteresis phenomenon detected and studied. Artificial neural network models are shown to be a powerful tool for predicting and understanding seepage phenomenon.
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La posibilidad de utilizar sistemas cuánticos para procesar y transmitir información ha impulsado la aparición de tecnologías de información cuántica, p. ej., distribución cuántica de claves. Aunque prometedoras, su uso fuera del laboratorio es actualmente demasiado costoso y complicado. En este trabajo mostramos como utilizarlas en redes ópticas de telecomunicaciones. Al utilizar una infraestructura existente y pervasiva, y compartirla con otras señales, tanto clásicas como cuánticas, el coste se reduce drásticamente y llega a un mayor público. Comenzamos integrando señales cuánticas en los tipos más utilizados de redes ópticas pasivas, por su simplicidad y alcance a usuarios finales. Luego ampliamos este estudio, proponiendo un diseño de red óptica metropolitana basado en la división en longitud de onda para multiplexar y direccionar las señales. Verificamos su funcionamiento con un prototipo. Posteriormente, estudiamos la distribución de pares de fotones entrelazados entre los usuarios de dicha red con el objetivo de abarcar más tecnologías. Para ampliar la capacidad de usuarios, rediseñamos la red troncal, cambiando tanto la topología como la tecnología utilizada en los nodos. El resultado es una red metropolitana cuántica que escala a cualquier cantidad de usuarios, a costa de una mayor complejidad y coste. Finalmente, tratamos el problema de la limitación en distancia. La solución propuesta está basada en codificación de red y permite, mediante el uso de varios caminos y nodos, modular la cantidad de información que tiene cada nodo, y así, la confianza depositada en él. ABSTRACT The potential use of quantum systems to process and transmit information has impulsed the emergence of quantum information technologies such as quantum key distribution. Despite looking promising, their use out of the laboratory is limited since they are a very delicate technology due to the need of working at the single quantum level. In this work we show how to use them in optical telecommunication networks. Using an existing infrastructure and sharing it with other signals, both quantum and conventional, reduces dramatically the cost and allows to reach a large group of users. In this work, we will first integrate quantum signals in the most common passive optical networks, for their simplicity and reach to final users. Then, we extend this study by proposing a quantum metropolitan optical network based on wavelength-division multiplexing and wavelengthaddressing, verifying its operation mode in a testbed. Later, we study the distribution of entangled photon-pairs between the users of the network with the objective of covering as much different technologies as possible. We further explore other network architectures, changing the topology and the technology used at the nodes. The resulting network scales better at the cost of a more complex and expensive infrastructure. Finally, we tackle the distance limitation problem of quantum communications. The solution offered is based on networkcoding and allows, using multiple paths and nodes, to modulate the information leaked to each node, and thus, the degree of trust placed in them.
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In this article, a novel approach to deal with the design of in-building wireless networks deployments is proposed. This approach known as MOQZEA (Multiobjective Quality Zone Based Evolutionary Algorithm) is a hybr id evolutionary algorithm adapted to use a novel fitness function, based on the definition of quality zones for the different objective functions considered. This approach is conceived to solve wireless network design problems without previous information of the required number of transmitters, considering simultaneously a high number of objective functions and optimizing multiple configuration parameters of the transmitters.
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Within the technological framework of Information and Communication Technologies (ICT), consumers are currently requesting multimedia services with simplicity of use, reliability, security and service availability through mobile and fixed access. Network operators are proposing the Next Generation Networks (NGN) to address the challenges of providing both services and network convergence. Apart from these considerations, there is a need to provide social and healthcare assistance services in order to support the progressive aging in the elderly population. In order to achieve this objective, the Ambient Assisted Living (AAL) initiative proposes ICT systems and services to promote autonomy and an independent life among the elderly. This paper describes the design and implementation of a group of services, called “service enablers”, which helps AAL applications to be supported in NGN. The presented enablers are identified to support the teleconsulting applications requirements in an NGN environment, involving the implementation of a virtual waiting room, a virtual whiteboard, a multimedia multiconference and a vital-signs monitoring presence status. A use case is defined and implemented to evaluate the developed enablers' performance.
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In this paper new results on personalized PageRank are shown. We consider directed graphs that may contain dangling nodes. The main result presented gives an analytical characterization of all the possible values of the personalized PageRank for any node.We use this result to give a theoretical justification of a recent model that uses the personalized PageRank to classify users of Social Networks Sites. We introduce new concepts concerning competitivity and leadership in complex networks. We also present some theoretical techniques to locate leaders and competitors which are valid for any personalization vector and by using only information related to the adjacency matrix of the graph and the distribution of its dangling nodes.
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In this work we study Twitter data to understand influence dynamics in social networks. We define user efficiency on Twitter, as the ratio between the emergent spreading process and the activity employed by the user. We characterize this property by means of a quantitative analysis of the structural and dynamical patterns emergent from human interactions, and show it to be universal across several Twitter conversations.
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The ability to generate entangled photon-pairs over a broad wavelength range opens the door to the simultaneous distribution of entanglement to multiple users of a network using a single source and wavelength-division multiplexing technologies. Here we show the design of a metropolitan optical network made of tree-type access networks where entangled photon-pairs are distributed to any pair of users, independently of their location. The resulting network improves the reach, number of users and capabilities of existing proposals. Moreover, it is made up of typical commercial components and uses the existing infrastructure, which allows for moderate deployment costs. Finally, we develop a channel plan and a network design that allow direct optical communications, quantum and classical, between any pair of users. Therefore, multiple quantum information technologies can make use of this network.
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The ability to generate entangled photon pairs over a broad wavelength range opens the door to the simultaneous distribution of entanglement to multiple users in a network by using centralized sources and flexible wavelength-division multiplexing schemes. Here, we show the design of a metropolitan optical network consisting of tree-type access networks, whereby entangled photon pairs are distributed to any pair of users, independent of their location. The network is constructed employing commercial off-the-shelf components and uses the existing infrastructure, which allows for moderate deployment costs. We further develop a channel plan and a network-architecture design to provide a direct optical path between any pair of users; thus, allowing classical and one-way quantum communication, as well as entanglement distribution. This allows the simultaneous operation of multiple quantum information technologies. Finally, we present a more flexible backbone architecture that pushes away the load limitations of the original network design by extending its reach, number of users and capabilities.
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Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model.
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Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.
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Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical con- nections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 dif- ferent brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very- large-scale integration circuits analyses, shows that func- tional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrange- ments for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal?ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organi- zations that can only be identified when the physical locations of the nodes are included in the analysis.