Modelagem de churn a partir de registros de solicitações de reparo de clientes

O objetivo deste trabalho é criar um modelo que permita predizer quais clientes possuem tendência a abandonar a empresa (churn) através da base de dados de solicitações de reparo dos clientes de banda larga. Este tema ganha importância à medida que a concorrência neste mercado se acirra e novas tecnologias para acesso à banda larga são disponibilizadas aos clientes. Para este estudo foram utilizadas as bases de dados de solicitações de reparo e de solicitações de desligamento do serviço. O primeiro modelo criado utilizou as variáveis tempo até o reparo e a quantidade de solicitações de reparo. Na busca por um modelo com maior nível de acerto, foi criado um segundo modelo no qual se consideraram as variáveis motivo da reclamação e causa do defeito. O resultados do estudo indicam que as variáveis tempo até o reparo e quantidade de solicitações de reparo influenciam na taxa de solicitações de desligamento, assim como alguns motivos de solicitação de reparo e causa de defeito são mais relevantes para a decisão de desligamento. No entanto, o nível de acerto dos modelos criados é baixo. Portanto, a utilização destes modelos para identificação e abordagem de clientes propensos a solicitar desligamento implica em ajustes no nível de certeza do modelo e consequente redução na quantidade de clientes a serem abordados.

Adaptação organizacional: um caso na área de transportes

A teoria geral dos sistemas, aplicada às organizações, ao enfatizar a importância do ambiente e ao fornecer um arcabouço metodológico simples, facilitou o desenvolvimento das referidas pesquisas e teorias. O presente trabalho analisa o problema de adaptação do setor de transportes no Brasil á partir especialmente da segunda metade da década de 70 e da adaptação organizacional da área de transportes de uma empresa de energia elétrica.

Características jurídicas do mercado brasileiro de audiovisual: a construção da Lei 12.485 de 2011 e seus desdobramentos

A Lei 12.485 de 2011 surgiu com a finalidade de reformar o aparato regulatório nacional sobre o mercado de televisão por assinatura. Dentre as justificativas oficiais para sua criação são elencadas como as mais importantes a ampliação da concorrência no setor, a necessidade de promover a diversidade das fontes de informação, o combate à formação de concentrações econômicas no setor e a promoção do desenvolvimento econômico e social do país. Com vistas a atingir tais objetivos, a Lei cria uma série de provisões destinadas a estabelecer mecanismos coordenação da atuação dos agentes, de controle da estrutura e da imposição de obrigações relacionadas à veiculação de conteúdos nacionais independentes. Por outro lado, somente estas justificativas não são suficientes para que se possa compreender quais são as principais alterações trazidas pela nova legislação e o que representam para o mercado. Isso porque as discussões sobre a introdução desta reforma no mercado tiveram como pano de fundo uma disputa intensa entre grupos que na maioria das vezes tinham interesses conflitantes e estavam inseridos em um cenário econômico e político bastante particular. Dessa forma, a análise da reforma da regulação sobre a comunicação audiovisual deve ultrapassar a mera comparação entre a redação de diferentes textos legais e investigar de modo aprofundado uma série de elementos que influenciaram a construção do novo aparato regulatório do setor, assim como os reais motivos para que se empreendesse essa reformulação das regras jurídicas. Com isso em vista, o presente trabalho se propõe a reconstruir este processo, analisando o histórico da regulação, de que maneira o mercado nacional se consolidou, quais seus principais agentes, o contexto econômico posto à época das reformas, de que maneira transcorreu o processo legislativo até a aprovação do texto final, para, somente então, apontar quais as principais características da nova legislação e em que influencia o setor. Ao final, também busca identificar quais são os eventuais problemas e desafios que podem surgir desse processo, tanto para o desenvolvimento do mercado quanto para o funcionamento da regulação, sopesando os riscos inerentes à adoção de diferentes estratégias regulatórias tomando como base os diversos aspectos apresentados.

The eager fight for supremacy in the online service industry: a comparative study of M&A activities: case studies of Apple, Google and Microsoft

A indústria de serviços online é caracterizada por um volume alto de Fusões e Aquisições no período de 2005 a 2015. As líderes de mercado, Apple, Google e Microsoft, incorporaram essa forma de crescimento inorgânico em suas estratégias corporativas. Essa tese examina as atividades de Fusões e Aquisições dessas três empresas. Consequentemente, ela tem foco em dois aspectos principais. Primeiro, existe o objetivo de saciar uma escassez na literatura acadêmica, no que se diz respeito ao estabelecimento de uma conexão entre a estratégia corporativa dessas empresas e as decisões tomadas de Fusões e Aquisições. Segundo, há também o objetivo de estimar possíveis futuros desenvolvimentos no setor. Através de uma análise de conteúdo qualitativa das publicações das empresas, relatórios de análise de mercado, e outros conteúdos de terceiros, estudos de caso foram desenvolvidos. Os resultados mostram o processo de posicionamento estratégico por parte da Apple, Google e Microsoft, dentro do mercado de serviços online, entre os anos de 2005 e 2015. As recorrentes fusões e aquisições são analisadas, no que se diz respeito as estratégias corporativas dessas empresas e a responsividade perante as atividades de seus competidores. Os resultados evidenciam atividades agressivas de Fusões e Aquisições em grupos estratégicos em comum entre as três empresas, especialmente no mercado de aparelhos de comunicação móvel e serviços de comunicação.

Análise e síntese de antenas e superfícies seletivas de frequência utilizando computação evolucionária e inteligência de enxames

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

Aplicações de Dispositivos de Microondas utilizando Substrato EBG/PBG para Comunicações Móveis

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.

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

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

Classificação Automática de Modulação Digital com uso de Correntropia para Ambientes de Rádio Cognitivo

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)

Obtenção dos parâmetros-x de estruturas planares

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

Avaliação de desempenho da codificação wavelet em canais seletivos em frequência

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

Arquiteturas eficientes para sensoriamento espectral e classificação automática de modulações usando características cicloestacionárias

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

Rastreabilidade de camarão amazônico proveniente de cultivo e ambiente natural utilizando a técnica de isótopos estáveis

Pós-graduação em Aquicultura - FCAV

Instalação de uma rede mesh metropolitana utilizando o padrão IEEE 802.11a e implementação do serviço Voip (Wman-Voip)

Pós-graduação em Engenharia Elétrica - FEIS

Construção de Códigos Espaço-temporais de Treliça via Partição de Reticulados

Pós-graduação em Engenharia Elétrica - FEIS

Monitoramento de dados via internet baseado em telefonia celular

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)