Análise da acuidade visual no implante de LIO fáquica em miopias elevadas

Introdução – Na correção de miopias elevadas, a cirurgia por implante de lente intraocular fáquica tem tido progressivamente uma maior adesão em relação à cirurgia por laser. Compara-se a acuidade visual (AV) antes e após a cirurgia implanto-refrativa, verificando-se a efetividade deste método no incremento da visão em miopias elevadas. Metodologia – Foram analisados, retrospetivamente, 70 olhos de 41 pacientes, com miopia elevada, entre os 20 e 50 anos, submetidos a cirurgia implanto-refrativa entre 2009 e 2012. Resultados – Um dia após cirurgia, 42,86% da amostra melhorou a AV, 34,29% manteve e 22,85% diminuiu. Após 30 dias observou-se um aumento generalizado da quantidade de visão, sendo que: 64,29% atingiu os 10/10 de AV, 24,29% alcançou entre 9/10-7/10 e 11,42% entre 6/10-4/10. Conclusão – Comprovou-se a efetividade desta técnica cirúrgica, verificando-se o aumento da AV em 52,86% da amostra.

Miocene sediments from Foz da Fonte and Penedo sections (Lower Tagus basin): clay minerals and isotopic data

Eight depositional sequences (DS) delimited by regional disconformities had been recognized in the Miocene of Lisbon and Setúbal Peninsula areas. In the case of the western coast of the Setúbal Peninsula, outcrops consisting of Lower Burdigalian to Lower Tortonian sediments were studied. The stratigraphic zonography and the environmental considerations are mainly supported on data concerning to foraminifera, ostracoda, vertebrates and palynomorphs. The first mineralogical and geochemical data determined for Foz da Fonte, Penedo Sul and Penedo Norte sedimentary sequences are presented. These analytical data mainly correspond to the sediments' fine fractions. Mineralogical data are based on X-ray diffraction (XRD), carried out on both the less than 38 nm and 2 nm fractions. Qualitative and semi-quantitative determinations of clay and non-clay minerals were obtained for both fractions. The clay minerals assemblages complete the lithostratigraphic and paleoenvironmental data obtained by stratigraphic and palaeontological studies. Some palaeomagnetic and isotopic data are discussed and correlated with the mineralogical data. Multivariate data analysis (Principal Components Analysis) of the mineralogical data was carried out using both R-mode and Q-mode factor analysis.

An Approach To Publish a Data Warehouse Content as Linked Data

Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Exploring distributed computing tools through data mining tasks

Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collaborative are mainly fixated on for all major grid computing research projects. Most of the university computers labs are occupied with the high puissant desktop PC nowadays. It is plausible to notice that most of the time machines are lying idle or wasting their computing power without utilizing in felicitous ways. However, for intricate quandaries and for analyzing astronomically immense amounts of data, sizably voluminous computational resources are required. For such quandaries, one may run the analysis algorithms in very puissant and expensive computers, which reduces the number of users that can afford such data analysis tasks. Instead of utilizing single expensive machines, distributed computing systems, offers the possibility of utilizing a set of much less expensive machines to do the same task. BOINC and Condor projects have been prosperously utilized for solving authentic scientific research works around the world at a low cost. In this work the main goal is to explore both distributed computing to implement, Condor and BOINC, and utilize their potency to harness the ideal PCs resources for the academic researchers to utilize in their research work. In this thesis, Data mining tasks have been performed in implementation of several machine learning algorithms on the distributed computing environment.

Planning, operations and data handling of planetary science missions

Dissertação para obtenção do Grau de Mestre em Engenharia Física

Stratigraphic interpretation of Well-Log data of the Athabasca Oil Sands of Alberta Canada through Pattern recognition and Artificial Intelligence

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Sensor Data Visualization in Virtual Globe

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

IPTV data reduction strategy to measure real users’ behaviours

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Territorial Strategic Planning as a support instrument for Regional and Local Development: a comparative analysis between Lisbon and Barcelona Metropolitan Areas

MARQUES, B.P. (2011) "Territorial Strategic Planning as a support instrument for Regional and Local Development: a comparative analysis between Lisbon and Barcelona Metropolitan Areas", in Atas do 17.º Congresso da APDR, do 5.º Congresso de Gestão e Conservação da Natureza e do Congresso Internacional da APDR/AECR, Bragança e Zamora, pp. 1265-1272, ISBN 978-989-96353-2-6.

RingDings market analysis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Spatial analysis of crime evolution in Portugal between 1995 and 2013

The main objective of this survey was to perform descriptive analysis of crime evolution in Portugal between 1995 and 2013. The main focus of this survey was to analyse spatial crime evolution patterns in Portuguese NUTS III regions. Most important crime types have been included into analysis. The main idea was to uncover relation between local patterns and global crime evolution; to define regions which have contributed to global crime evolution of some specific crime types and to define how they have contributed. There were many statistical reports and scientific papers which have analysed some particular crime types, but one global spatial-temporal analysis has not been found. Principal Component Analysis and multidimensional descriptive data analysis technique STATIS have been the base of the analysis. The results of this survey has shown that strong spatial and temporal crime patterns exist. It was possible to describe global crime evolution patterns and to define crime evolution patterns in NUTS III regions. It was possible to define three to four groups of crimes where each group shows similar spatial crime dynamics.

SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

A data-driven analytics approach in the study of pneumonia’s fatalities

As huge amounts of data become available in organizations and society, specific data analytics skills and techniques are needed to explore this data and extract from it useful patterns, tendencies, models or other useful knowledge, which could be used to support the decision-making process, to define new strategies or to understand what is happening in a specific field. Only with a deep understanding of a phenomenon it is possible to fight it. In this paper, a data-driven analytics approach is used for the analysis of the increasing incidence of fatalities by pneumonia in the Portuguese population, characterizing the disease and its incidence in terms of fatalities, knowledge that can be used to define appropriate strategies that can aim to reduce this phenomenon, which has increased more than 65% in a decade.