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.

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.

Engineering Temporal and Spatial Aspects in OWL using Patterns

WWW is a huge, open, heterogeneous system, however its contents data is mainly human oriented. The Semantic Web needs to assure that data is readable and “understandable” to intelligent software agents, though the use of explicit and formal semantics. Ontologies constitute a privileged artifact for capturing the semantic of the WWW data. Temporal and spatial dimensions are transversal to the generality of knowledge domains and therefore are fundamental for the reasoning process of software agents. Representing temporal/spatial evolution of concepts and their relations in OWL (W3C standard for ontologies) it is not straightforward. Although proposed several strategies to tackle this problem but there is still no formal and standard approach. This work main goal consists of development of methods/tools to support the engineering of temporal and spatial aspects in intelligent systems through the use of OWL ontologies. An existing method for ontology engineering, Fonte was used as framework for the development of this work. As main contributions of this work Fonte was re-engineered in order to: i) support the spatial dimension; ii) work with OWL Ontologies; iii) and support the application of Ontology Design Patterns. Finally, the capabilities of the proposed approach were demonstrated by engineering time and space in a demo ontology about football.

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.

Classificações geomecânicas mineiras para o dimensionamento de maciços rochosos: o aplicativo MGC-RocDesign|Calc

Este trabalho tem como objetivo destacar a importância da utilização de software de geoengenharia no estudo das classificações de maciços rochosos nas engenharias de minas e geotécnica. Esta investigação pretendeu demonstrar a importância das classificações geomecânicas e índices geológico‐geomecânicos, tais como a Rock Mass Rating (RMR), Rock Tunnelling Quality Index (Q‐system), Surface Rock Classification (SRC), Rock Quality Designation (RQD), Geological Strength Index (GSI) and Hydro‐Potential Value (HP). Para esse efeito foi criada e desenvolvida uma calculadora geomecânica – MGC‐RocDesign|CALC: ‘Mining Geomechanics Classification systems for rock engineering design (version beta)’ – para de certa forma tornar mais simples, rápido e preciso o estudo das classificações geomecânicas sem que seja necessário recorrer manualmente às fastidiosas tabelas das classificações. A MGC‐RocDesign|CALC foi criada e desenvolvida no programa de folha de cálculo Microsoft Excel™ em linguagem Visual Basic for Applications© proporcionando o ambiente de carregamento de dados mais apelativos para o utilizador. Foi ainda integrada neste aplicativo a Calculadora Geotech|CalcTools que resulta da fusão das bases de dados ScanGeoData|BGD e SchmidtData|UCS criadas por Fonseca et al. (2010). Toda a informação foi integrada numa base de dados dinâmica associada a uma plataforma cartográfica em Sistemas de Informação Geográfica. Apresenta‐se como caso de estudo um dos trechos subterrâneos do maciço rochoso da antiga mina de volfrâmio das Aveleiras/Tibães (Mosteiro de Tibães, Braga, NW de Portugal). Além disso, apresenta‐se uma proposta de zonamento geomecânico do maciço rochoso da antiga mina das Aveleiras/Tibães com o objetivo de apoiar o dimensionamento de maciços rochosos. Por fim, apresenta‐se uma reflexão em termos de aplicabilidade, das potencialidades e das limitações da Calculadora Geomecânica MGC‐RocDesign|CALC.

Development of Biomimetic Robots in the EPS Engineering Programme Capstone Project

This paper proposes the development of biologically inspired robots as the capstone project of the European Project Semester (EPS) framework. EPS is a one semester student centred international programme offered by a group of European engineering schools (EPS Providers) as part of their student exchange programme portfolio. EPS is organized around a central module (the EPS project) and a set of complementary supportive modules. Project proposals refer to open multidisciplinary real world problems. Its purpose is to expose students to problems of a greater dimension and complexity than those faced throughout the degree programme as well as to put them in contact with the socalled real world, in opposition to the academic world. Students are organized in teams, grouping individuals from diverse academic backgrounds and nationalities, and each team is fully responsible for conducting its project. EPS provides an integrated framework for undertaking capstone projects, which is focused on multicultural and multidisciplinary teamwork, communication, problem-solving, creativity, leadership, entrepreneurship, ethical reasoning and global contextual analysis. The design and development of biologically inspired robots allows the students to fulfil the previously described requirements and objectives and, as a result, we recommend the adoption of these projects within the EPS project capstone module for the benefit of engineering students.

Development of Biomimetic Robots in the EPS Engineering Programme Capstone Project

This paper presents the development of a fish-like robot called Bro-Fish. Bro-Fish aims to be an educational toy dedicated to teaching mechanics, programming and the physics of floating objects to youngsters. The underlying intention is to awaken the interest of children for technology, especially biomimetic (biologically inspired) approaches, in order to promote sustainability and raise the level of ecological awareness. The main focus of this project was to create a robot with carangiform locomotion and controllable swimming, providing the opportunity to customize parts and experiment with the physics of floating objects. Therefore, the locomotion principles of fishes and mechanisms developed in related projects were analysed. Inspired by this background knowledge, a prototype was designed and implemented. The main achievement is the new tail mechanism that propels the robot. The tail resembles the undulation motion of fish bodies and is actuated in an innovative way, triggered by an elegant movement of a rotating helicoidal. First experimental tests revealed the potential of the proposed methodology to effectively generate forward propulsion.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

Introducing numerical analysis tools in engineering: a Scilab user case in electronics course

Software tools in education became popular since the widespread of personal computers. Engineering courses lead the way in this development and these tools became almost a standard. Engineering graduates are familiar with numerical analysis tools but also with simulators (e.g. electronic circuits), computer assisted design tools and others, depending on the degree. One of the main problems with these tools is when and how to start use them so that they can be beneficial to students and not mere substitutes for potentially difficult calculations or design. In this paper a software tool to be used by first year students in electronics/electricity courses is presented. The growing acknowledgement and acceptance of open source software lead to the choice of an open source software tool – Scilab, which is a numerical analysis tool – to develop a toolbox. The toolbox was developed to be used as standalone or integrated in an e-learning platform. The e-learning platform used was Moodle. The first approach was to assess the mathematical skills necessary to solve all the problems related to electronics and electricity courses. Analysing the existing circuit simulators software tools, it is clear that even though they are very helpful by showing the end result they are not so effective in the process of the students studying and self learning since they show results but not intermediate steps which are crucial in problems that involve derivatives or integrals. Also, they are not very effective in obtaining graphical results that could be used to elaborate reports and for an overall better comprehension of the results. The developed tool was based on the numerical analysis software Scilab and is a toolbox that gives their users the opportunity to obtain the end results of a circuit analysis but also the expressions obtained when derivative and integrals calculations, plot signals, obtain vector diagrams, etc. The toolbox runs entirely in the Moodle web platform and provides the same results as the standalone application. The students can use the toolbox through the web platform (in computers where they don't have installation privileges) or in their personal computers by installing both the Scilab software and the toolbox. This approach was designed for first year students from all engineering degrees that have electronics/electricity courses in their curricula.

Autonomous guided vehicles applied to industrial engineering and management studies

This article presents a framework to an Industrial Engineering and Management Science course from School of Management and Industrial Studies using Autonomous Ground Vehicles (AGV) to supply materials to a production line as an experimental setup for the students to acquire knowledge in the production robotics area. The students must be capable to understand and put into good use several concepts that will be of utmost importance in their professional life such as critical decisions regarding the study, development and implementation of a production line. The main focus is a production line using AGVs, where the students are required to address several topics such as: sensors actuators, controllers and an high level management and optimization software. The presented framework brings to the robotics teaching community methodologies that allow students from different backgrounds, that normally don’t experiment with the robotics concepts in practice due to the big gap between theory and practice, to go straight to ”making” robotics. Our aim was to suppress the minimum start point level thus allowing any student to fully experience robotics with little background knowledge.

Sustainability Improvement of a composite materials’ industry through recycling and re-engineering process approaches

Recent Advances in Mechanics and Materials in Design

Estudo da antiga mina de volfrâmio das Aveleiras (Mire de Tibães): cartografia geotécnica e avaliação geomecânica

Este trabalho tem como objetivo sublinhar a importância de um estudo geológico‐geotécnico para apoiar a cartografia geotécnica do maciço rochoso subterrâneo da antiga mina de volfrâmio das Aveleiras (Mosteiro de Tibães, Braga). Foi realizado um trabalho de campo sistemático, ao longo de uma rede de galerias subterrâneas com uma extensão aproximada de 155 m. Estas galerias são constituídas, principalmente, por rochas metassedimentares, embora aflorem rochas graníticas num pequeno trecho de uma das galerias. A técnica de amostragem linear de descontinuidades aplicada ao grau de compartimentação do maciço rochoso esteve na base de todos os dados geológicos, geotécnicos e geomecânicos. Além disso, foram coligidos e integrados os dados de campanhas de campo anteriores, realizadas entre 2006 e 2011. Foram igualmente descritos os métodos de avaliação dos dados de campo, bem como a análise estatística dos parâmetros geológico‐geotécnicos. O zonamento geotécnico do maciço rochoso das Aveleiras foi desenvolvido tendo em conta o comportamento do maciço rochoso in situ, e foi apoiado por ensaios laboratoriais de resistência do material‐rocha através do Ensaio de Carga Pontual. Apresenta‐se uma proposta preliminar de zonamento geomecânico com o objectivo de apoiar o projeto de engenharia de maciços rochosos.

Massive Open Online Course management: learning science and engineering through peer-reviewed projects

Massive Open Online Courses (MOOC) are gaining prominence in transversal teaching-learning strategies. However, there are many issues still debated, namely assessment, recognized largely as a cornerstone in Education. The large number of students involved requires a redefinition of strategies that often use approaches based on tasks or challenging projects. In these conditions and due to this approach, assessment is made through peer-reviewed assignments and quizzes online. The peer-reviewed assignments are often based upon sample answers or topics, which guide the student in the task of evaluating peers. This chapter analyzes the grading and evaluation in MOOCs, especially in science and engineering courses, within the context of education and grading methodologies and discusses possible perspectives to pursue grading quality in massive e-learning courses.