999 resultados para Sistemas de Comunicação Alternativos e Suplementares
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Os dados de telefonia celular são um instrumento valioso para analisar o comportamento da população urbana, uma vez que informação sobre a mobilidade das pessoas é difícil de obter. Estes podem oferecer estimativas em relação ao deslocamento e à ocupação da população nos espaços públicos, ajudando a elaborar medidas de planejamento urbano mais especificas e eficientes. A fim de examinar a movimentação ao redor da cidade do Rio de Janeiro em dias de grandes eventos, propomos uma metodologia com o objetivo de identificar aspectos desses eventos que permitem conhecer o público e oferecer soluções para os planejadores desenharem estratégias para a organização e segurança desses participantes. Palavras-chaves: mobilidade urbana. dados CDR. eventos públicos. Rio de Janeiro
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Since some years, mobile technologies in healthcare (mHealth) stand for the transformational force to improve health issues in low- and middle-income countries (LMICs). Although several studies have identified the prevailing issue of inconsistent evidence and new evaluation frameworks have been proposed, few have explored the role of entrepreneurship to create disruptive change in a traditionally conservative sector. I argue that improving the effectiveness of mHealth entrepreneurs might increase the adoption of mHealth solutions. Thus, this study aims at proposing a managerial model for the analysis of mHealth solutions from the entrepreneurial perspective in the context of LMICs. I identified the Khoja–Durrani–Scott (KDS) framework as theoretical basis for the managerial model, due to its explicit focus on the context of LMICs. In the subsequent exploratory research I, first, used semi-structured interviews with five specialists in mHealth, local healthcare systems and investment to identify necessary adaptations to the model. The findings of the interviews proposed that especially the economic theme had to be clarified and an additional entrepreneurial theme was necessary. Additionally, an evaluation questionnaire was proposed. In the second phase, I applied the questionnaire to five start-ups, operating in Brazil and Tanzania, and conducted semi-structured interviews with the entrepreneurs to gain practical insights for the theoretical development. Three of five entrepreneurs perceived that the results correlated with the entrepreneurs' expectations of the strengths and weaknesses of the start-ups. Main shortcomings of the model related to the ambiguity of some questions. In addition to the findings for the model, the results of the scores were analyzed. The analysis suggested that across the participating mHealth start-ups the ‘behavioral and socio-technical’ outcomes were the strongest and the ‘policy’ outcomes were the weakest themes. The managerial model integrates several perspectives, structured around the entrepreneur. In order to validate the model, future research may link the development of a start-up with the evolution of the scores in longitudinal case studies or large-scale tests.
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The recent and widespread availability of affordable mobile phone technology in developing countries has paved the way for the development of a number of mobile money and electronic remittance services. One of the most successful of these services is Safaricom’s M-PESA program, launched in the East African nation of Kenya in March 2007. Since then, the program has successfully enrolled over 15.2 million users, transferred more than US$1.4 trillion in electronic funds, and contributed significantly to poverty alleviation and financial inclusion efforts in Kenya. M-Pesa is a mobile phone based money transfer system in Kenya which grew at a blistering pace following its inception in 2007. This case study will analyze the critical factors that make M-PESA such a unique success in Kenya specifically.
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Esta dissertação tem como principal objectivo, propor um sistema de comunicações para as Ilhas Desertas que vise atender às necessidades expostas pelo PNM - Parque Natural da Madeira. Localizadas a 22 milhas marítimas do Funchal, as ilhas Desertas não dispõem de cobertura da rede móvel GSM - Global Standard for Mobile, nem de qualquer outra infra-estrutura de comunicações que permita a comunicação entre os vigilantes e a estação de serviço - doca. Esta falta de comunicação torna-se mais problemática aquando da realização de acções de fiscalização e vigilância, já que em caso de acidente não será possível pedir auxílio. Dada esta realidade propomos a criação de uma rede de rádio móvel terrestre para as Ilhas Desertas, com a instalação de vários repetidores UHF no topo das ilhas. O projecto desta rede será fundamentado com a realização de um estudo de cobertura para as três ilhas que incluirá a avaliação e análise de vários modelos de propagação. Esta análise é realizada com recurso a duas ferramentas de software, Radio-Mobile e DifractionLoss, tendo este último sido desenvolvido no âmbito desta dissertação. De forma a melhorar a cobertura da rede GSM na estação de serviço do PNM na Deserta Grande, sugerem-se duas soluções: a primeira consiste na instalação de um repetidor GSM de frequência deslocada e a segunda na instalação de uma NanoBTS. Além da falta de comunicação na área das ilhas Desertas, a falta de comunicação com a ilha da Madeira é também uma realidade. Perante esta situação sugere-se a criação de uma ligação por feixes hertzianos de alta frequência entre a estação de serviço do PNM na Deserta Grande e a sede do PNM, localizada na zona do Jardim Botânico na Ilha da Madeira. O projecto desta ligação apresenta um planeamento e dimensionamento de acordo com as necessidades apresentadas pelo PNM, assim como um estudo de propagação baseado num procedimento teórico e em simulações de software. É também proposto um sistema de videovigilância controlado remotamente com o objectivo de permitir a monitorização remota dos lobos-marinhos.
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The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm
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The development of wireless telecommunication in the last years has been great. It has been taking academics to conceive new ideas and techniques. Their aims are to increase the capacity and the quality of the system s services. Cells that are smaller every time, frequencies that are every time higher and environments that get more and more complex, all those facts deserve more accurate models the propagation prediction techniques are inserted in this context and results with a merger of error that is compatible with the next generations of communication systems. The objective of this Work is to present results of a propagation measurement campaign, aiming at pointing the characteristics of the mobile systems covering in the city of Natal (state of Rio Grande do Norte, Brazil). A mobile laboratory was set up, using the infra-structure available and frequently used by ANATEL. The measures were taken in three different areas: one characterized by high buildings, high relief, presence of trees and towers of different highs. These areas covered the city s central zone, a suburban / rural zone and a section of coast surrounded by sand dunes. It is important to highlight that the analysis was made taking into consideration the actual reality of cellular systems with covering ranges by reduced cells, with the intent of causing greater re-use of frequencies and greater capacity of telephone traffic. The predominance of telephone traffic by cell in the city of Natal occurs within a range inferior to 3 (three) km from the Radio-Base Station. The frequency band used was 800 MHz, corresponding to the control channels of the respective sites, which adopt the FSK modulation technique. This Dissertation starts by presenting a general vision of the models used for predicting propagation. Then, there is a description of the methodology used in the measuring, which were done using the same channels of control of the cellular system. The results obtained were compared with many existing prediction models, and some adaptations were developed by using regression techniques trying to obtain the most optimized solutions. Furthermore, according to regulations from the old Brazilian Holding Telebrás, a minimum covering of 90% of a determined previously area, in 90% of the time, must be obeyed when implanting cellular systems. For such value to be reached, considerations and studies involving the specific environment that is being covered are important. The objective of this work is contribute to this aspect
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The modern society depends on an efficient communications system able to of transmitting and receiving information with a higher speed and reliability every time. The need for ever more efficient devices raises optimization techniques of microstrip devices, such as techniques to increase bandwidth: thicker substrates and substrate structures with EBG (Electromagnetic Band Gap) and PBG (Photonic Band Gap). This work has how aims the study of the application of PBG materials on substrates of planar structures in microstrip, more precisely in directional quadrature couplers and in rat-race and impedance of transformers. A study of the planar structures in microstrip and substrates EBG is presented. The PBG substrates can be used to optimize the radiation through the air, thus reducing the occurrence of surface waves and the resulting diffraction edge responsible for degradation of radiation pattern. Through specific programs in FORTRAN Power Station obtained the frequencies and couplings for each structure. Are used the program PACMO - Computer Aided Design in Microwave. Results are obtained of the frequency and coupling devices, ranging the frequency band used (cellular communication and Wimax systems) and the permittivity of the substrate, comparing the results of conventional material and PBG materials in the s and p polarizations.
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This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables
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Modern wireless systems employ adaptive techniques to provide high throughput while observing desired coverage, Quality of Service (QoS) and capacity. An alternative to further enhance data rate is to apply cognitive radio concepts, where a system is able to exploit unused spectrum on existing licensed bands by sensing the spectrum and opportunistically access unused portions. Techniques like Automatic Modulation Classification (AMC) could help or be vital for such scenarios. Usually, AMC implementations rely on some form of signal pre-processing, which may introduce a high computational cost or make assumptions about the received signal which may not hold (e.g. Gaussianity of noise). This work proposes a new method to perform AMC which uses a similarity measure from the Information Theoretic Learning (ITL) framework, known as correntropy coefficient. It is capable of extracting similarity measurements over a pair of random processes using higher order statistics, yielding in better similarity estimations than by using e.g. correlation coefficient. Experiments carried out by means of computer simulation show that the technique proposed in this paper presents a high rate success in classification of digital modulation, even in the presence of additive white gaussian noise (AWGN)
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Due to major progress of communication system in the last decades, need for more precise characterization of used components. The S-parameters modeling has been used to characterization, simulation and test of communication system. However, limitation of S-parameters to model nonlinear system has created new modeling systems that include the nonlinear characteristics. The polyharmonic distortion modeling is a characterizationg technique for nonlinear systems that has been growing up due to praticity and similarity with S-parameters. This work presents analysis the polyharmonic distortion modeling, the test bench development for simulation of planar structure and planar structure characterization with X-parameters
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Wavelet coding has emerged as an alternative coding technique to minimize the fading effects of wireless channels. This work evaluates the performance of wavelet coding, in terms of bit error probability, over time-varying, frequency-selective multipath Rayleigh fading channels. The adopted propagation model follows the COST207 norm, main international standards reference for GSM, UMTS, and EDGE applications. The results show the wavelet coding s efficiency against the inter symbolic interference which characterizes these communication scenarios. This robustness of the presented technique enables its usage in different environments, bringing it one step closer to be applied in practical wireless communication systems
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The increasing demand for high performance wireless communication systems has shown the inefficiency of the current model of fixed allocation of the radio spectrum. In this context, cognitive radio appears as a more efficient alternative, by providing opportunistic spectrum access, with the maximum bandwidth possible. To ensure these requirements, it is necessary that the transmitter identify opportunities for transmission and the receiver recognizes the parameters defined for the communication signal. The techniques that use cyclostationary analysis can be applied to problems in either spectrum sensing and modulation classification, even in low signal-to-noise ratio (SNR) environments. However, despite the robustness, one of the main disadvantages of cyclostationarity is the high computational cost for calculating its functions. This work proposes efficient architectures for obtaining cyclostationary features to be employed in either spectrum sensing and automatic modulation classification (AMC). In the context of spectrum sensing, a parallelized algorithm for extracting cyclostationary features of communication signals is presented. The performance of this features extractor parallelization is evaluated by speedup and parallel eficiency metrics. The architecture for spectrum sensing is analyzed for several configuration of false alarm probability, SNR levels and observation time for BPSK and QPSK modulations. In the context of AMC, the reduced alpha-profile is proposed as as a cyclostationary signature calculated for a reduced cyclic frequencies set. This signature is validated by a modulation classification architecture based on pattern matching. The architecture for AMC is investigated for correct classification rates of AM, BPSK, QPSK, MSK and FSK modulations, considering several scenarios of observation length and SNR levels. The numerical results of performance obtained in this work show the eficiency of the proposed architectures
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Incluye Bibliografía
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Pós-graduação em Engenharia Elétrica - FEIS
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Pós-graduação em Engenharia Elétrica - FEIS