Mining social individuals movements and friends based on mobile devices

Trabalho de Projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Sustainable Development Action Plan at ISEP - From Concept to Engineering Practice

Some of the main challenges in Incorporating Sustainable Development practices into Engineering Education reside in establishing the bridge between concept and application. In particular the relation between value creation and the knowledge economy, innovation and entrepreneurship, as the main vehicles to a relevant application of the sustainable development concept, is not yet part of the majority of the engineering curricula in schools. Porto Polytechnical Engineering School (ISEP), a Global Reporting Initiative training partner in Portugal, as just presented its Sustainable Development Action Plan, with the main objective of creating a new kind of engineers, with Sustainable Development at the core of their degrees. The plan has several issues like publish an annual sustainability report, sustainable buildings, minimization of energy consumption and water policy, waste management, sustainable mobility, green procurement, EMAS certification, research and postgraduate activity and promotion of lectures and seminars in Sustainable Development.

The European Project Semester at ISEP: Learning to Learn Engineering

The European Project Semester at ISEP (EPS@ISEP) is a one semester project-based learning programme addressed to engineering students from diverse scientific backgrounds and nationalities. The students, organized in multicultural teams, are challenged to solve real world multidisciplinary problems, accounting for 30 ECTU. The EPS package, although focused on project development (20 ECTU), includes a series of complementary seminars aimed at fostering soft, project-related and engineering transversal skills (10 ECTU). This paper presents the study plan, resources, operation and results of the EPS@ISEP that was created in 2011 to apply the best engineering education practices and promote the internationalization of ISEP. The results show that the EPS@ISEP students acquire during one semester the scientific, technical and soft competences necessary to propose, design and implement a solution for a multidisciplinary problem.

Desenho e implementação de um sistema computacional para apoiar a gestão de projectos utilizando técnicas de data mining

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

Software languages engineering: experimental evaluation

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Assessing Reading Abilities of Mechanical Engineering College Students: A Prospecting Study*

Reading is a basic competence that students have to master to be successful. Despite this fact, recent studies show that there may be a significant decline in the reading abilities of college students, one of the most educated segments of any population. This work is a prospecting study regarding the assessment of reading abilities of college students, namely in the context of Engineering education. Based on an existing screening test for assessing reading difficulties of children and teenagers, this work presents the results obtained by administrating that test to students at a top engineering institution in Portugal. An outcome of this study is the determination of a time range suitable for a massive, time limited, use of the previously mentioned test to assess college students, thus enabling a basic tool that will permit, in future works, to screen reading abilities in wider college populations. This work also shows evidence that ca. 20% of college students present a poor reading performance, revealing a strong need for monitoring college students’ reading abilities along different generations.

Influence of Soil Chemistry and Plant Physiology in the Phytoremediation of Cu, Mn, and Zn

Different anthropogenic sources of metals can result from agricultural, industrial, military, mining and urban activities that contribute to environmental pollution. Plants can be grown for phytoremediation to remove or stabilize contaminants in water and soil. Copper (Cu), manganese (Mn) and zinc (Zn) are trace essential metals for plants, although their role in homeostasis in plants must be strictly regulated to avoid toxicity. In this review, we summarize the processes involved in the bioavailability, uptake, transport and storage of Cu, Mn and Zn in plants. The efficiency of phytoremediation depends on several factors including metal bioavailability and plant uptake, translocation and tolerance mechanisms. Soil parameters, such as clay fraction, organic matter content, oxidation state, pH, redox potential, aeration, and the presence of specific organisms, play fundamental roles in the uptake of trace essential metals. Key processes in the metal homeostasis network in plants have been identified. Membrane transporters involved in the acquisition, transport and storage of trace essential metals are reviewed. Recent advances in understanding the biochemical and molecular mechanisms of Cu, Mn and Zn hyperaccumulation are described. The use of plant-bacteria associations, plant-fungi associations and genetic engineering has opened a new range of opportunities to improve the efficiency of phytoremediation. The main directions for future research are proposed from the investigation of published results.

Simple and stable dynamic traffic engineering for provider scale ethernet

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

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.

Optimização do processo de perfuração em maciços rochosos: consequências técnico-económicas

Este estudo centra-se na temática da perfuração de maciços rochosos. A perfuração, dependendo do seu objectivo, diâmetro e comprimento, tem um vasto leque de aplicações incluindo a perfuração para o desmonte com explosivos e colocação de elementos de contenção. Este estudo esta focado na perfuração, tendo normalmente um papel preponderante no rendimento dos ciclos de trabalho em que esta inserida. O processo de perfuração implica uma estreita interacção das ferramentas de perfuração com maciço rochoso a perfurar, como tal um conhecimento rigoroso dos parâmetros geológicos, geotécnicos, geomecânicos do maciço rochoso e preponderante para auxiliar a gestão, do ponto de vista técnico-económico, da operação de perfuração. Este estudo tem como principal objectivo a optimização técnico-económica desta operação através da introdução de processos baseados nas boas práticas de engenharia na perfuração de maciços rochosos, nomeadamente a definição e introdução do processo de afiação dos bits no ciclo de perfuração. Na caracterização do maciço rochoso, para além da pesquisa e recolha bibliográfica pretende-se recorrer a ensaios ”in situ” e laboratoriais que permitam obter informacao útil para a avaliação da perfurabilidade e abrasividade do maciço rochoso.

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.

A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

Vibration control with shape-memory alloys in civil engineering structures

Dissertação apresentada à Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Doutor em Engenharia Civil

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.