Data analysis applied to the evaluation of a technological nature teaching model as a regional development tool

This paper presents the creation and development of technological schools directly linked to the business community and to higher public education. Establishing themselves as the key interface between the two sectors they make a signigicant contribution by having a greater competitive edge when faced with increasing competition in the tradional markets. The development of new business strategies supported by references of excellence, quality and competitiveness also provides a good link between the estalishment of partnerships aiming at the qualification of education boards at a medium level between the technological school and higher education with a technological foundation. We present a case study as an example depicting the success of Escola Tecnológica de Vale de Cambra.

A Distributed System for the Dissemination of DGPS Data through the Internet

In this paper we describe a low cost distributed system intended to increase the positioning accuracy of outdoor navigation systems based on the Global Positioning System (GPS). Since the accuracy of absolute GPS positioning is insufficient for many outdoor navigation tasks, another GPS based methodology – the Differential GPS (DGPS) – was developed in the nineties. The differential or relative positioning approach is based on the calculation and dissemination of the range errors of the received GPS satellites. GPS/DGPS receivers correlate the broadcasted GPS data with the DGPS corrections, granting users increased accuracy. DGPS data can be disseminated using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to provide mobile platforms within our campus with DGPS data for precise outdoor navigation. To achieve this objective, we designed and implemented a three-tier client/server distributed system that, first, establishes Internet links with remote DGPS sources and, then, performs campus-wide dissemination of the obtained data. The Internet links are established between data servers connected to remote DGPS sources and the client, which is the data input module of the campus-wide DGPS data provider. The campus DGPS data provider allows the establishment of both Intranet and wireless links within the campus. This distributed system is expected to provide adequate support for accurate outdoor navigation tasks.

Implementation of a Campus wide DGPS Data Server

Although the Navigation Satellite Timing and Ranging (NAVSTAR) Global Positioning System (GPS) is, de facto, the standard positioning system used in outdoor navigation, it does not provide, per se, all the features required to perform many outdoor navigational tasks. The accuracy of the GPS measurements is the most critical issue. The quest for higher position readings accuracy led to the development, in the late nineties, of the Differential Global Positioning System (DGPS). The differential GPS method detects the range errors of the GPS satellites received and broadcasts them. The DGPS/GPS receivers correlate the DGPS data with the GPS satellite data they are receiving, granting users increased accuracy. DGPS data is broadcasted using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to have access, within the ISEP campus, to DGPS correction data. To achieve this objective we designed and implemented a distributed system composed of two main modules which are interconnected: a distributed application responsible for the establishment of the data link over the Internet between the remote DGPS stations and the campus, and the campus-wide DGPS data server application. The DGPS data Internet link is provided by a two-tier client/server distributed application where the server-side is connected to the DGPS station and the client-side is located at the campus. The second unit, the campus DGPS data server application, diffuses DGPS data received at the campus via the Intranet and via a wireless data link. The wireless broadcast is intended for DGPS/GPS portable receivers equipped with an air interface and the Intranet link is provided for DGPS/GPS receivers with just a RS232 DGPS data interface. While the DGPS data Internet link servers receive the DGPS data from the DGPS base stations and forward it to the DGPS data Internet link client, the DGPS data Internet link client outputs the received DGPS data to the campus DGPS data server application. The distributed system is expected to provide adequate support for accurate (sub-metric) outdoor campus navigation tasks. This paper describes in detail the overall distributed application.

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

Adherend thickness effect on the tensile fracture toughness of a structural adhesive using an optical data acquisition method

Adhesive bonding is nowadays a serious candidate to replace methods such as fastening or riveting, because of attractive mechanical properties. As a result, adhesives are being increasingly used in industries such as the automotive, aerospace and construction. Thus, it is highly important to predict the strength of bonded joints to assess the feasibility of joining during the fabrication process of components (e.g. due to complex geometries) or for repairing purposes. This work studies the tensile behaviour of adhesive joints between aluminium adherends considering different values of adherend thickness (h) and the double-cantilever beam (DCB) test. The experimental work consists of the definition of the tensile fracture toughness (GIC) for the different joint configurations. A conventional fracture characterization method was used, together with a J-integral approach, that take into account the plasticity effects occurring in the adhesive layer. An optical measurement method is used for the evaluation of crack tip opening and adherends rotation at the crack tip during the test, supported by a Matlab® sub-routine for the automated extraction of these quantities. As output of this work, a comparative evaluation between bonded systems with different values of adherend thickness is carried out and complete fracture data is provided in tension for the subsequent strength prediction of joints with identical conditions.

Reliable and Fast Hand-Offs in Low-Power Wireless Networks

Hand-off (or hand-over), the process where mobile nodes select the best access point available to transfer data, has been well studied in wireless networks. The performance of a hand-off process depends on the specific characteristics of the wireless links. In the case of low-power wireless networks, hand-off decisions must be carefully taken by considering the unique properties of inexpensive low-power radios. This paper addresses the design, implementation and evaluation of smart-HOP, a hand-off mechanism tailored for low-power wireless networks. This work has three main contributions. First, it formulates the hard hand-off process for low-power networks (such as typical wireless sensor networks - WSNs) with a probabilistic model, to investigate the impact of the most relevant channel parameters through an analytical approach. Second, it confirms the probabilistic model through simulation and further elaborates on the impact of several hand-off parameters. Third, it fine-tunes the most relevant hand-off parameters via an extended set of experiments, in a realistic experimental scenario. The evaluation shows that smart-HOP performs well in the transitional region while achieving more than 98 percent relative delivery ratio and hand-off delays in the order of a few tens of a milliseconds.

Sustainability Evaluation of Biodiesel Produced from Microalgae Chlamydomonas sp Grown in Brewery Wastewater

This study performs a sustainability evaluation of biodiesel from microalga Chlamydomonas sp. grown in 20 % (v/v) of brewery’s wastewater, blended with pentose sugars (xylose, arabinose or ribose resulting from the hydrolysis of brewer’s spent grains (BSG). The life cycle steps considered for the study are: microalgae cultivation, biomass processing and lipids extraction at the brewery site, and its conversion to biodiesel at a dedicated external biofuel’s plant. Three sustainability indicators (LCEE, FER and GW) were considered and calculated using experimental data. Literature data was used, whenever necessary, to complement life cycle data, thus allowing a more accurate sustainability evaluation. A comparative analysis of the biodiesel life cycle steps was also conducted, with the main goal of identifying which steps need to be improved. Results show that biomass processing, especially cell harvesting, microalgae cultivation, and lipids extraction are the main process bottlenecks. It is also analysed the influence on the microalgae biodiesel sustainability of adding each pentose sugar to the cultivation media, concluding that it strongly influences the biomass and lipid productivity. In particular, the addition of xylose is preferable in terms of lipid productivity, but from a sustainability point of view, ribose is the best, though the difference from xylose is not significant. Nevertheless, culture without pentose addition presents the best sustainability results.

Analysis of the Respiratory Dynamics During Normal Breathing by Means of Pseudophase Plots and Pressure–Volume Loops

This paper reports on the analysis of tidal breathing patterns measured during noninvasive forced oscillation lung function tests in six individual groups. The three adult groups were healthy, with prediagnosed chronic obstructive pulmonary disease, and with prediagnosed kyphoscoliosis, respectively. The three children groups were healthy, with prediagnosed asthma, and with prediagnosed cystic fibrosis, respectively. The analysis is applied to the pressure-volume curves and the pseudophase-plane loop by means of the box-counting method, which gives a measure of the area within each loop. The objective was to verify if there exists a link between the area of the loops, power-law patterns, and alterations in the respiratory structure with disease. We obtained statistically significant variations between the data sets corresponding to the six groups of patients, showing also the existence of power-law patterns. Our findings support the idea that the respiratory system changes with disease in terms of airway geometry and tissue parameters, leading, in turn, to variations in the fractal dimension of the respiratory tree and its dynamics.

Quality of Life Predictors and Normative Data

This study identifies predictors and normative data for quality of life (QOL) in a sample of Portuguese adults from general population. A cross-sectional correlational study was undertaken with two hundred and fifty-five (N = 255) individuals from Portuguese general population (mean age 43 years, range 25–84 years; 148 females, 107 males). Participants completed the European Portuguese version of the World Health Organization Quality of Life short-form instrument and the European Portuguese version of the Center for Epidemiologic Studies Depression Scale. Demographic information was also collected. Portuguese adults reported their QOL as good. The physical, psychological and environmental domains predicted 44 % of the variance of QOL. The strongest predictor was the physical domain and the weakest was social relationships. Age, educational level, socioeconomic status and emotional status were significantly correlated with QOL and explained 25 % of the variance of QOL. The strongest predictor of QOL was emotional status followed by education and age. QOL was significantly different according to: marital status; living place (mainland or islands); type of cohabitants; occupation; health. The sample of adults from general Portuguese population reported high levels of QOL. The life domain that better explained QOL was the physical domain. Among other variables, emotional status best predicted QOL. Further variables influenced overall QOL. These findings inform our understanding on adults from Portuguese general population QOL and can be helpful for researchers and practitioners using this assessment tool to compare their results with normative data

An Approach To Publish a Data Warehouse Content as Linked Data

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

O tratamento contabilístico do goodwill nas empresas do PSI- 20

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação de Drª Mónica D’Orey

Transporte marítimo de curta distância na União Europeia e em Portugal

O transporte marítimo sempre assumiu uma importância primordial no transporte, quer de pessoas como de mercadorias. O uso das vias marítimas para o transporte de mercadorias é uma prática utilizada desde os tempos antigos. O transporte marítimo na Europa sempre foi uma forma eficaz e de baixo custo de transportar passageiros e mercadorias de um local para outro. Atualmente, todos os modos de transporte necessitam de melhorar a sua eficiência e reduzir o montante de poluentes que libertam para o meio-ambiente. O transporte marítimo de curta distância (TMCD) é parte essencial no sistema de transporte multimodal Europeu representando cerca de 37% das transações intracomunitárias (tkm). Os resultados alcançados advêm desde que, em 2001, a European Shortsea Network (ESN) em parceria com os Shortsea Promotion Centres (SPC) de cada Estado-Membro da União Europeia (EU) conseguiram efetuar progressos significativos na promoção e desenvolvimento do transporte por esta via. Esta tese de mestrado pretende caraterizar o TMCD na EU e em Portugal e a sua articulação com os outros meios de transporte de mercadorias. Será também analisada a situação Portuguesa ao nível do transporte marítimo de mercadorias fazendo especial relevância à mercadoria contentorizada, às infraestruturas atualmente existentes em Portugal assim como às perspetivas futuras para o setor. A metodologia utilizada inclui a revisão de literatura da investigação efetuada sobre o setor, a recolha de informação primária através do instrumento inquérito e a recolha de informação estatística a partir de fontes secundárias, permitindo a caraterização do setor. O inquérito foi desenvolvido e partilhado com mais de um milhar de empresas a operar em Portugal, nas que se incluem as empresas transportadoras, operadores logísticos, agentes de navegação e as principais empresas exportadoras/importadoras a operar em Portugal, tendo-se obtido 106 respostas válidas. A nível nacional, o inquérito realizado permitiu confirmar que os principais portos logísticos para a movimentação internacional de mercadorias são os portos de Leixões, Lisboa, Sines e Setúbal, estando a maioria das empresas inquiridas localizadas no hinterland destes portos. O inquérito permitiu também concluir que o facto de o transporte rodoviário ser um meio de transporte rápido, de baixo custo para curtas e médias distâncias, de elevada frequência de transporte, de oferecer elevada capacidade e diversos tipos de carga transportada, de oferecer serviços Porta-a-Porta, da elevada flexibilidade e mobilidade oferecida, assim como a rapidez das operações de carga e descarga continuam a contribuir para a elevada competitividade deste modo de transporte de mercadorias, sendo as razões pelo qual este modo é escolhido, pese embora, ser o modo mais poluente por tonelada transportada. Os modos de transporte TMCD e ferroviário apenas são alvo de escolha, como modo de transporte de mercadorias, por parte das empresas mais responsáveis socialmente e ambiental. O inquérito permitiu ainda concluir que, para haver uma melhor articulação entre o TMCD com outros meios de transporte, é necessário que sejam disponibilizados novos serviços, portos e terminais logísticos com serviços privatizados, assim como a redução das tarifas aplicáveis TMCD.

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

A Data Mining Framework for Electric Load Profiling

This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.