Self-aware and self-expressive camera networks

Smart cameras perform on-board image analysis, adapt their algorithms to changes in their environment, and collaborate with other networked cameras to analyze the dynamic behavior of objects. A proposed computational framework adopts the concepts of self-awareness and self-expression to more efficiently manage the complex tradeoffs among performance, flexibility, resources, and reliability. The Web extra at http://youtu.be/NKe31-OKLz4 is a video demonstrating CamSim, a smart camera simulation tool, enables users to test self-adaptive and self-organizing smart-camera techniques without deploying a smart-camera network.

A self -testing approach for autonomic software

As researchers and practitioners move towards a vision of software systems that configure, optimize, protect, and heal themselves, they must also consider the implications of such self-management activities on software reliability. Autonomic computing (AC) describes a new generation of software systems that are characterized by dynamically adaptive self-management features. During dynamic adaptation, autonomic systems modify their own structure and/or behavior in response to environmental changes. Adaptation can result in new system configurations and capabilities, which need to be validated at runtime to prevent costly system failures. However, although the pioneers of AC recognize that validating autonomic systems is critical to the success of the paradigm, the architectural blueprint for AC does not provide a workflow or supporting design models for runtime testing. ^ This dissertation presents a novel approach for seamlessly integrating runtime testing into autonomic software. The approach introduces an implicit self-test feature into autonomic software by tailoring the existing self-management infrastructure to runtime testing. Autonomic self-testing facilitates activities such as test execution, code coverage analysis, timed test performance, and post-test evaluation. In addition, the approach is supported by automated testing tools, and a detailed design methodology. A case study that incorporates self-testing into three autonomic applications is also presented. The findings of the study reveal that autonomic self-testing provides a flexible approach for building safe, reliable autonomic software, while limiting the development and performance overhead through software reuse. ^

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization

Non-ambient solid-state characterization of crystalline molecular organic semiconductors

The research project is focused on the investigation of the polymorphism of crystalline molecular material for organic semiconductor applications under non-ambient conditions, and the solid-state characterization and crystal structure determination of the different polymorphic forms. In particular, this research project has tackled the investigation and characterization of the polymorphism of perylene diimides (PDIs) derivatives at high temperatures and pressures, in particular N,N’-dialkyl-3,4,9,10-perylendiimide (PDI-Cn, with n = 5, 6, 7, 8). These molecules are characterized by excellent chemical, thermal, and photostability, high electron affinity, strong absorption in the visible region, low LUMO energies, good air stability, and good charge transport properties, which can be tuned via functionalization; these features make them promising n-type organic semiconductor materials for several applications such as OFETs, OPV cells, laser dye, sensors, bioimaging, etc. The thermal characterization of PDI-Cn was carried out by a combination of differential scanning calorimetry, variable temperature X-ray diffraction, hot-stage microscopy, and in the case of PDI-C5 also variable temperature Raman spectroscopy. Whereas crystal structure determination was carried out by both Single Crystal and Powder X-ray diffraction. Moreover, high-pressure polymorphism via pressure-dependent UV-Vis absorption spectroscopy and high-pressure Single Crystal X-ray diffraction was carried out in this project. A data-driven approach based on a combination of self-organizing maps (SOM) and principal component analysis (PCA) is also reported was used to classify different π-stacking arrangements of PDI derivatives into families of similar crystal packing. Besides the main project, in the framework of structure-property analysis under non-ambient conditions, the structural investigation of the water loss in Pt- and Pd- based vapochromic potassium/lithium salts upon temperature, and the investigation of structure-mechanical property relationships in polymorphs of a thienopyrrolyldione endcapped oligothiophene (C4-NT3N) are reported.

Análise do jogo de goalball : modelação e interpretação dos padrões de jogo da Paralimpíada de Pequim 2008

Universidade Estadual de Campinas . Faculdade de Educação Física

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

A mathematical view of biological complexity

This essay is a trial on giving some mathematical ideas about the concept of biological complexity, trying to explore four different attributes considered to be essential to characterize a complex system in a biological context: decomposition, heterogeneous assembly, self-organization, and adequacy. It is a theoretical and speculative approach, opening some possibilities to further numerical and experimental work, illustrated by references to several researches that applied the concepts presented here. (C) 2008 Elsevier B.V. All rights reserved.

Planeamento e optimização em redes celulares móveis auto-geridas assentes em LTE

O objectivo deste trabalho consiste em avaliar os benefícios das Self Organizing Networks (SON), no que concerne ao planeamento e optimização de redes Long Term Evolution (LTE), não só através do seu estudo, como também através do desenvolvimento e teste de algoritmos, que permitem avaliar o funcionamento de algumas das suas principais funções. O estudo efectuado sobre as SON permitiu identificar um conjunto de funções, tais como a atribuição automática de Physical Cell Id (PCI), o Automatic Neighbour Relation (ANR) e a optimização automática de parâmetros de handover, que permitem facilitar ou mesmo substituir algumas das tarefas mais comuns em planeamento e optimização de redes móveis celulares, em particular, redes LTE. Recorrendo a um simulador LTE destinado à investigação académica, em código aberto e desenvolvido em Matlab®, foi desenvolvido um conjunto de algoritmos que permitiram a implementação das funções em questão. Para além das funções implementadas, foram também introduzidas alterações que conferem a este simulador a capacidade de representar e simular redes reais, permitindo uma análise mais coerente dos algoritmos desenvolvidos. Os resultados obtidos, para além de evidenciarem claramente o benefício dos algoritmos desenvolvidos, foram ainda comparados com os obtidos pela ferramenta profissional de planeamento e optimização Atoll®, tendo-se verificado a franca proximidade de desempenho em algumas das funções. Finalmente, foi desenvolvida uma interface gráfica que permite o desenho, configuração e simulação de cenários, bem como a análise de resultados.

Planeamento e otimização de femto-células em ambiente empresarial

O objetivo deste trabalho consiste em avaliar as capacidades das femto-células, no âmbito do planeamento e otimização de redes Universal Mobile Telecommunication System (UMTS) instaladas no interior de edifícios num ambiente empresarial. A avaliação será feita através do estudo da tecnologia das femto-células, e do planeamento efetuado num cenário real onde, através do desenvolvimento e teste de um conjunto parametrizações, será avaliado o funcionamento das femto-células assim como forma de otimizar o seu desempenho. O estudo realizado permitiu identificar um conjunto de características que as femto-células partilham com as Self-Organizing Networks (SON), como a auto-configuração, auto-otimização de parâmetros rádio, ajuste dinâmico da área de cobertura, atribuição automática de Scrambling Codes (SC) e da frequência da portadora, criação automática de relações de vizinhança, entre outras, que permitem facilitar o processo de planeamento e otimização de redes móveis UMTS. Recorrendo a um cenário empresarial real, foi efetuado um planeamento celular indoor de raiz, através do qual foi possível testar o funcionamento da algumas das principais funções das femto-células, nomeadamente a capacidade de ajuste dinâmico da área de cobertura. Foi também avaliado o funcionamento de um grupo co-localizado de femto-células, onde foi possível testar parametrizações com o objetivo de melhorar o processo de handover entre as femto-células do grupo, e entre estas e a rede macro Global System for Mobile Communications (GSM). A avaliação de cada um de cada uma das parametrizações testada, é efetuada a partir das medidas recolhidas no terreno, recorrendo à ferramenta TEMS® Investigation, assim como aos Key Performance Indicators (KPIs) que as femto-células disponibilizam. Os resultados obtidos mostram o benefício da utilização das femto-células num ambiente empresarial real, assim como os eventuais problemas e desafios que podem surguir do planeamento celular indoor recorrendo à tecnologia das femto-células, sendo apresentada a parametrização que permite obter o melhor desempenho da rede instalada.

Detecção de sectores cruzados e optimização de cobertura em redes LTE

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Optimização da lista de células vizinhas em redes LTE

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Improving accuracy for OTD based 3G geolocation in real urban/suburban environments

This paper presents the recent research results about the development of a Observed Time Difference (OTD) based geolocation algorithm based on network trace data, for a real Universal Mobile Telecommunication System (UMTS) Network. The initial results have been published in [1], the current paper focus on increasing the sample convergence rate, and introducing a new filtering approach based on a moving average spatial filter, to increase accuracy. Field tests have been carried out for two radio environments (urban and suburban) in the Lisbon area, Portugal. The new enhancements produced a geopositioning success rate of 47% and 31%, and a median accuracy of 151 m and 337 m, for the urban and suburban environments, respectively. The implemented filter produced a 16% and 20% increase on accuracy, when compared with the geopositioned raw data. The obtained results are rather promising in accuracy and geolocation success rate. OTD positioning smoothed by moving average spatial filtering reveals a strong approach for positioning trace extracted events, vital for boosting Self-Organizing Networks (SON) over a 3G network.

Neighbour list optimization for real LTE radio network

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.

Caracterização das NUTS da Europa de acordo com a dinâmica de ocupações/uso do solo entre 1990 e 2000

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

A aplicação de redes neuronais na deteção da influência do High Frequency Trading na negociação de ações (caso português)

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão da Informação