46 resultados para Open network
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Informática e de Computadores
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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística, na especialização de Teatro na Educação
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With the increasing complexity of current networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbour Cell List (NCL) for Long Term Evolution (LTE) evolved NodeBs (eNBs). An algorithm composed by three decisions were were developed: distance-based, Radio Frequency (RF) measurement-based and Handover (HO) stats-based. The distance-based decision, proposes a new NCL taking account the eNB location and interference tiers, based in the quadrants method. The last two algorithms consider signal strength measurements and HO statistics, respectively; they also define a ranking to each eNB and neighbour relation addition/removal based on user defined constraints. The algorithms were developed and implemented over an already existent radio network optimization professional tool. Several case studies were produced using real data from a Portuguese LTE mobile operator. © 2014 IEEE.
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The long term evolution (LTE) is one of the latest standards in the mobile communications market. To achieve its performance, LTE networks use several techniques, such as multi-carrier technique, multiple-input-multiple-output and cooperative communications. Inside cooperative communications, this paper focuses on the fixed relaying technique, presenting a way for determining the best position to deploy the relay station (RS), from a set of empirical good solutions, and also to quantify the associated performance gain using different cluster size configurations. The best RS position was obtained through realistic simulations, which set it as the middle of the cell's circumference arc. Additionally, it also confirmed that network's performance is improved when the number of RSs is increased. It was possible to conclude that, for each deployed RS, the percentage of area served by an RS increases about 10 %. Furthermore, the mean data rate in the cell has been increased by approximately 60 % through the use of RSs. Finally, a given scenario with a larger number of RSs, can experience the same performance as an equivalent scenario without RSs, but with higher reuse distance. This conduces to a compromise solution between RS installation and cluster size, in order to maximize capacity, as well as performance.
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The emergence of smartphones with Wireless LAN (WiFi) network interfaces brought new challenges to application developers. The expected increase of users connectivity will impact their expectations for example on the performance of background applications. Unfortunately, the number and breadth of the studies on the new patterns of user mobility and connectivity that result from the emergence of smartphones is still insufficient to support this claim. This paper contributes with preliminary results on a large scale study of the usage pattern of about 49000 devices and 31000 users who accessed at least one access point of the eduroam WiFi network on the campuses of the Lisbon Polytechnic Institute. Results confirm that the increasing number of smartphones resulted in significant changes to the pattern of use, with impact on the amount of traffic and users connection time.
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It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.
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Two new tetranuclear complexes [Cu-4(mu-O)(L-1)-Cl-4] and [Cu-4(mu(4)-O)(L-2)(2)Cl-4] (2), where H2L1 is a macrocyclic ligand resulting from [2+2] condensation of 2,6-diformy1-4-methylphanol (DFF) and 1,3-bis(aminopropy1)tetramethyldisiloxane, and HL2 is a 1:2 condensation product: of DFF with trimethylsilyl p-aminobenzoate, have been prepared. The structures of the products were established by Xray diffraction. The complexes have been characterised by FTIR, UV/Vis spectroscopy, ES1 mass-spectrometry and magnetic susceptibility measurements. The latter revealed that the letrftriuclear complexes can be descr bed as two ferromagnetically coupled dinuclear units, in which the two copper(II) ions interact antiferromacinetically. The ccimpi.iunds act as homogeneous catalyst precursors for a number of single-pot reactions, including (I) hydrocarbaxylation, with CO, H2O and K2S2O8, of a variety of linear and cyclic (n = 5-8) alkanes into the corresponding Cn+1 carboxylic acids, (ii) peroxidative oxidation of cyclohexane, and (iii) solvent-free microwave-assisted oxidation of 1-phenyletha.nol.
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We present an analysis and characterization of the regional seismicity recorded by a temporary broadband seismic network deployed in the Cape Verde archipelago between November 2007 and September 2008. The detection of earthquakes was based on spectrograms, allowing the discrimination from low-frequency volcanic signals, resulting in 358 events of which 265 were located, the magnitudes usually being smaller than 3. For the location, a new 1-D P-velocity model was derived for the region showing a crust consistent with an oceanic crustal structure. The seismicity is located mostly offshore the westernmost and geologically youngest areas of the archipelago, near the islands of Santo Antao and Sao Vicente in the NW and Brava and Fogo in the SW. The SW cluster has a lower occurrence rate and corresponds to seismicity concentrated mainly along an alignment between Brava and the Cadamosto seamount presenting normal faulting mechanisms. The existence of the NW cluster, located offshore SW of Santo Antao, was so far unknown and concentrates around a recently recognized submarine cone field; this cluster presents focal depths extending from the crust to the upper mantle and suggests volcanic unrest No evident temporal behaviour could be perceived, although the events tend to occur in bursts of activity lasting a few days. In this recording period, no significant activity was detected at Fogo volcano, the most active volcanic edifice in Cape Verde. The seismicity characteristics point mainly to a volcanic origin. The correlation of the recorded seismicity with active volcanic structures agrees with the tendency for a westward migration of volcanic activity in the archipelago as indicated by the geologic record. (C) 2014 Elsevier B.V. All rights reserved.
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Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.
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Co-deposition of nickel and cobalt was carried out on austenitic stainless steel (AISI 304) substrates by imposing a square waveform current in the cathodic region. The innovative procedure applied in this work allows creating a stable, fully developed, and open porous three-dimensional (3D) dendritic structure, which can be used as electrode for redox supercapacitors. This study investigates in detail the influence of the applied current density on the morphology, mass, and chemical composition of the deposited Ni-Co films and the resulting 3D porous network dendritic structure. The morphology and the physicochemical composition were studied by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction (W). The electrochemical behavior of the materials was evaluated by cyclic voltammetry (CV). The results highlight the mechanism involved in the coelectrodeposition process and how the lower limit current density tailors the film composition and morphology, as well as its electrochemical activity.
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In this article, physical layer awareness in access, core, and metro networks is addressed, and a Physical Layer Aware Network Architecture Framework for the Future Internet is presented and discussed, as proposed within the framework of the European ICT Project 4WARD. Current limitations and shortcomings of the Internet architecture are driving research trends at a global scale toward a novel, secure, and flexible architecture. This Future Internet architecture must allow for the co-existence and cooperation of multiple networks on common platforms, through the virtualization of network resources. Possible solutions embrace a full range of technologies, from fiber backbones to wireless access networks. The virtualization of physical networking resources will enhance the possibility of handling different profiles, while providing the impression of mutual isolation. This abstraction strategy implies the use of well elaborated mechanisms in order to deal with channel impairments and requirements, in both wireless (access) and optical (core) environments.
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This paper develops an energy management system with integration of smart meters for electricity consumers in a smart grid context. The integration of two types of smart meters (SM) are developed: (i) consumer owned SM and (ii) distributor owned SM. The consumer owned SM runs over a wireless platform - ZigBee protocol and the distributor owned SM uses the wired environment - ModBus protocol. The SM are connected to a SCADA system (Supervisory Control And Data Acquisition) that supervises a network of Programmable Logic Controllers (PLC). The SCADA system/PLC network integrates different types of information coming from several technologies present in modern buildings. The developed control strategy implements a hierarchical cascade controller where inner loops are performed by local PLCs, and the outer loop is managed by a centralized SCADA system, which interacts with the entire local PLC network. In order to implement advanced controllers, a communication channel was developed to allow the communication between the SCADA system and the MATLAB software. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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We model the cytoskeleton as a fractal network by identifying each segment with a simple Kelvin-Voigt element with a well defined equilibrium length. The final structure retains the elastic characteristics of a solid or a gel, which may support stress, without relaxing. By considering a very simple regular self-similar structure of segments in series and in parallel, in one, two, or three dimensions, we are able to express the viscoelasticity of the network as an effective generalized Kelvin-Voigt model with a power law spectrum of retardation times L similar to tau(alpha). We relate the parameter alpha with the fractal dimension of the gel. In some regimes ( 0 < alpha < 1), we recover the weak power law behaviors of the elastic and viscous moduli with the angular frequencies G' similar to G" similar to w(alpha) that occur in a variety of soft materials, including living cells. In other regimes, we find different power laws for G' and G".
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Innovation is considered crucial for enterprises survival and current economic environment demands the best ways of achieving it. However, the development of complex products and services require the utilization of diverse know-how and technology, which enterprises may not hold. An effective strategy for achieving them is to rely in open innovation. Still, open innovation projects may fail for many causes, e.g. due to the dynamics of collaboration between partners. To effectively benefit from open innovation, it is recommended the utilization of adequate risk models. For achieving such models, a preliminary conceptualization of open innovation and risk is necessary, which includes modeling experiments with existing risk models, such as the FMEA.
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During last decades there has been a trend to build collaboration platforms as enablers for groups of enterprises to jointly provide integrated services and products. As a result, the notion of business ecosystem is getting wider acceptance. However, a critical issue that is still open, despite some efforts in this area, is the identification of adequate performance indicators to measure and motivate sustainable collaboration. This work-in-progress addresses this concern, briefly presenting the state of the art of relevant contributing areas such as, collaborative networks, business ecosystems, enterprise performance indicators, social networks analysis, and supply chains. Complementarily, through an assessment of current gaps, the research challenges are identified and an approach for further development is proposed.