Análise de desempenho de vendas em telecomunicações utilizando técnicas de mineração de dados

Nowadays, telecommunications is one of the most dynamic and strategic areas in the world. Organizations are always seeking to find new management practices within an ever increasing competitive environment where resources are getting scarce. In this scenario, data obtained from business and corporate processes have even greater importance, although this data is not yet adequately explored. Knowledge Discovery in Databases (KDD) appears then, as an option to allow the study of complex problems in different areas of management. This work proposes both a systematization of KDD activities using concepts from different methodologies, such as CRISP-DM, SEMMA and FAYYAD approaches and a study concerning the viability of multivariate regression analysis models to explain corporative telecommunications sales using performance indicators. Thus, statistical methods were outlined to analyze the effects of such indicators on the behavior of business productivity. According to business and standard statistical analysis, equations were defined and fit to their respective determination coefficients. Tests of hypotheses were also conducted on parameters with the purpose of validating the regression models. The results show that there is a relationship between these development indicators and the amount of sales

Leprosy control: perspectives & epidemiological and operational aspects

OBJETIVOS: A partir de acervo de 200 textos acadêmicos e de documentos de organismos nacionais e internacionais voltados ao controle da hanseníase publicados no período de 1999 a 2008, procurou-se estudar respectivas possibilidades evolutivas futuras, empregando-se os subsídios do recurso de análise de cenários. MÉTODOS: A reconstrução metodológica adotada foi de natureza qualitativa, fulcrada nas técnicas de revisão bibliográfica e análise de conteúdo. Esta última foi empregada na tipificação documental categorial frequencial contigencial, de acordo com devida fundamentação pertinente. RESULTADOS: Recuperaram-se elementos atuais importantes de natureza epidemiológica e operacional, bem como de respectivas perspectivas. CONCLUSÕES: Projeta-se que a manutenção dos coeficientes de incidência da doença coloca reptos econômicos e sanitários a desafiar desde o modelo neoliberal de organização societária mundial até competências específicas das ações das equipes de saúde em campo.

Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

Modelação e análise da vida útil (metrológica) de medidores tipo indução de energia elétrica ativa

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de um instrumento portátil para detectar falha em rolamento de motor de indução, pela técnica do envelope, usando um DSP de 16 bits e a transformada de Hilbert

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Visão sistêmica do Sítio Arqueológico Piracanjuba: a descoberta de conhecimento em sítios arqueológicos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Conhecimento prévio e aprendizagem significativa de conceitos históricos no ensino médio

Pós-graduação em Educação - FFC

Experimentos de mineração de dados aplicados a sistemas scada de usinas hidrelétricas

O atual modelo do setor elétrico brasileiro permite igualdade de condições a todos os agentes e reduz o papel do Estado no setor. Esse modelo obriga as empresas do setor a melhorarem cada vez mais a qualidade de seu produto e, como requisito para este objetivo, devem fazer uso mais efetivo da enorme quantidade de dados operacionais que são armazenados em bancos de dados, provenientes da operação dos seus sistemas elétricos e que tem nas Usinas Hidrelétricas (UHE) a sua principal fonte de geração de energia. Uma das principais ferramentas para gerenciamento dessas usinas são os sistemas de Supervisão, Controle e Aquisição de Dados (Supervisory Control And Data Acquisition - SCADA). Assim, a imensa quantidade de dados acumulados nos bancos de dados pelos sistemas SCADA, muito provavelmente contendo informações relevantes, deve ser tratada para descobrir relações e padrões e assim ajudar na compreensão de muitos aspectos operacionais importantes e avaliar o desempenho dos sistemas elétricos de potência. O processo de Descoberta de Conhecimento em Banco de Dados (Knowledge Discovery in Database - KDD) é o processo de identificar, em grandes conjuntos de dados, padrões que sejam válidos, novos, úteis e compreensíveis, para melhorar o entendimento de um problema ou um procedimento de tomada de decisão. A Mineração de Dados (ou Data Mining) é o passo dentro do KDD que permite extrair informações úteis em grandes bases de dados. Neste cenário, o presente trabalho se propõe a realizar experimentos de mineração de dados nos dados gerados por sistemas SCADA em UHE, a fim de produzir informações relevantes para auxiliar no planejamento, operação, manutenção e segurança das hidrelétricas e na implantação da cultura da mineração de dados aplicada a estas usinas.

Diversificação das espécies de Rhinella do grupo crucifer (Anura, Bufonidae) na Mata Atlântica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Uma abordagem usando visualização de software como apoio à refatoração para aspectos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Seeing beyond reading: a survey on visual text analytics

We review recent visualization techniques aimed at supporting tasks that require the analysis of text documents, from approaches targeted at visually summarizing the relevant content of a single document to those aimed at assisting exploratory investigation of whole collections of documents.Techniques are organized considering their target input materialeither single texts or collections of textsand their focus, which may be at displaying content, emphasizing relevant relationships, highlighting the temporal evolution of a document or collection, or helping users to handle results from a query posed to a search engine.We describe the approaches adopted by distinct techniques and briefly review the strategies they employ to obtain meaningful text models, discuss how they extract the information required to produce representative visualizations, the tasks they intend to support and the interaction issues involved, and strengths and limitations. Finally, we show a summary of techniques, highlighting their goals and distinguishing characteristics. We also briefly discuss some open problems and research directions in the fields of visual text mining and text analytics.

Nondetection Index of Anti-Islanding Passive Protection of Synchronous Distributed Generators

Synchronous distributed generators are prone to operate islanded after contingencies, which is usually not allowed due to safety and power-quality issues. Thus, there are several anti-islanding techniques; however, most of them present technical limitations so that they are likely to fail in certain situations. Therefore, it is important to quantify and determine whether the scheme under study is adequate or not. In this context, this paper proposes an index to evaluate the effectiveness of anti-islanding frequency-based relays commonly used to protect synchronous distributed generators. The method is based on the calculation of a numerical index that indicates the time period that the system is unprotected against islanding considering the global period of analysis. Although this index can precisely be calculated based on several electromagnetic transient simulations, a practical method is also proposed to calculate it directly from simple analytical formulas or lookup tables. The results have shown that the proposed approach can assist distribution engineers to assess and set anti-islanding protection schemes.

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

The Dynamics of Passive Torsional Fatigue Test Rigs: Innovative Applications of Universal Joints

The dynamics of a passive back-to-back test rig have been characterised, leading to a multi-coordinate approach for the analysis of arbitrary test configurations. Universal joints have been introduced into a typical pre-loaded back-to-back system in order to produce an oscillating torsional moment in a test specimen. Two different arrangements have been investigated using a frequency-based sub-structuring approach: the receptance method. A numerical model has been developed in accordance with this theory, allowing interconnection of systems with two-coordinates and closed multi-loop schemes. The model calculates the receptance functions and modal and deflected shapes of a general system. Closed form expressions of the following individual elements have been developed: a servomotor, damped continuous shaft and a universal joint. Numerical results for specific cases have been compared with published data in literature and experimental measurements undertaken in the present work. Due to the complexity of the universal joint and its oscillating dynamic effects, a more detailed analysis of this component has been developed. Two models have been presented. The first represents the joint as two inertias connected by a massless cross-piece. The second, derived by the dynamic analysis of a spherical four-link mechanism, considers the contribution of the floating element and its gyroscopic effects. An investigation into non-linear behaviour has led to a time domain model that utilises the Runge-Kutta fourth order method for resolution of the dynamic equations. It has been demonstrated that the torsional receptances of a universal joint, derived using the simple model, result in representation of the joint as an equivalent variable inertia. In order to verify the model, a test rig has been built and experimental validation undertaken. The variable inertia of a universal joint has lead to a novel application of the component as a passive device for the balancing of inertia variations in slider-crank mechanisms.

Model reduction techniques in flexible multibody dynamics with application to engine cranktrain simulation

The development of a multibody model of a motorbike engine cranktrain is presented in this work, with an emphasis on flexible component model reduction. A modelling methodology based upon the adoption of non-ideal joints at interface locations, and the inclusion of component flexibility, is developed: both are necessary tasks if one wants to capture dynamic effects which arise in lightweight, high-speed applications. With regard to the first topic, both a ball bearing model and a journal bearing model are implemented, in order to properly capture the dynamic effects of the main connections in the system: angular contact ball bearings are modelled according to a five-DOF nonlinear scheme in order to grasp the crankshaft main bearings behaviour, while an impedance-based hydrodynamic bearing model is implemented providing an enhanced operation prediction at the conrod big end locations. Concerning the second matter, flexible models of the crankshaft and the connecting rod are produced. The well-established Craig-Bampton reduction technique is adopted as a general framework to obtain reduced model representations which are suitable for the subsequent multibody analyses. A particular component mode selection procedure is implemented, based on the concept of Effective Interface Mass, allowing an assessment of the accuracy of the reduced models prior to the nonlinear simulation phase. In addition, a procedure to alleviate the effects of modal truncation, based on the Modal Truncation Augmentation approach, is developed. In order to assess the performances of the proposed modal reduction schemes, numerical tests are performed onto the crankshaft and the conrod models in both frequency and modal domains. A multibody model of the cranktrain is eventually assembled and simulated using a commercial software. Numerical results are presented, demonstrating the effectiveness of the implemented flexible model reduction techniques. The advantages over the conventional frequency-based truncation approach are discussed.