Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

A rule-based grapheme-to-phone converter for TTS systems in european portuguese

In this paper, a linguistically rule-based grapheme-to-phone (G2P) transcription algorithm is described for European Portuguese. A complete set of phonological and phonetic transcription rules regarding the European Portuguese standard variety is presented. This algorithm was implemented and tested by using online newspaper articles. The obtained experimental results gave rise to 98.80% of accuracy rate. Future developments in order to increase this value are foreseen. Our purpose with this work is to develop a module/ tool that can improve synthetic speech naturalness in European Portuguese. Other applications of this system can be expected like language teaching/learning. These results, together with our perspectives of future improvements, have proved the dramatic importance of linguistic knowledge on the development of Text-to-Speech systems (TTS).

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.

A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.

O b-Learning num contexto de aprendizagem ao longo da vida

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão de Sistemas de e-Learning,

O desenvolvimento curricular no b-learning

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão de Sistemas de e-Learning

Interface Humana Músculo-Facial

Esta dissertação tem como principal objetivo a criação de uma interface humana, baseada na eletromiografia dos músculos orbicular do olho e frontalis. O algoritmo de programação do microcontrolador ATmega2560 deteta o piscar de olhos voluntário, conta o número de vezes que este acontece e verifica se preenche os requisitos necessários à execução de um comando. Para este efeito foram utilizados elétrodos para a captação do sinal eletromiográfico. O sinal analógico é condicionado pela Shield ECG/EMG da Olimex sendo enviado para o arduíno ATmega2560. Este microcontrolador administra todos os atuadores, dos quais o mais importante é um painel de comandos (quatro comandos diferentes), no qual existe um ponteiro motorizado que indica qual a ação a realizar. O código de execução é extremamente simples:  se o utilizador piscar os olhos três vezes, o ponteiro movimenta-se para a secção do painel imediatamente à direita; e  se o utilizador piscar os olhos quatro vezes, o ponteiro movimenta-se para a secção do painel imediatamente à esquerda. Os testes realizados com este dispositivo indicam que os utilizadores demoram menos de 10 minutos a aprender a utilizar e executar todos os comandos do painel. Apenas num dos testes realizados o dispositivo não funcionou. Dos utilizadores que realizaram o teste:  vários usam óculos;  um idoso com graves problemas auditivos, cegueira parcial e dificuldades locomotoras;  nenhum foi incapaz de piscar, pelo menos, um dos olhos voluntariamente; e  a maioria referiu que, com alguma concentração e principalmente se ouvirem o bip sonoro, a aprendizagem de utilização torna-se muito fácil. Apesar dos limites impostos à concretização de um projeto deste tipo (dos quais se evidenciam as dificuldades em conseguir voluntários com paralisia medular, bem como os limites orçamentais), pode-se afirmar que este dispositivo é eficaz e seria uma mais valia quando implementado num cenário de paralisia medular (total ou parcial). A melhoria de qualidade de vida de um utilizador com estes problemas físicos, ou outros que lhe comprometam a locomoção é garantida. O cenário em que vivem é tremendamente limitado sendo urgente criar soluções para tornar estas vidas mais cómodas. Com os devidos aplicativos, o utilizador poderia abrir portas ou janelas, acender ou apagar luzes, pedir ajuda, ajustar a posição da cama, controlar cadeiras de rodas, entre outros. É neste sentido que surge a minha motivação de criar algo que ajude estas pessoas.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

A learning approach to swarm-based path detection and tracking

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Learning networks and moodle use in online courses: a social network analysis study

Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

Proposta e avaliação de modelo de formação em e-learning para profissionais de saúde

Trabalho de projecto de Mestrado em Gestão de Sistemas de E-Learning

An approach to teach Calculus/Mathematical Analysis (for engineering students) using computers and active learning – its conception, development of materials and evaluation

Dissertação para obtenção do Grau de Doutor em Ciências da Educação

Adapter module for self-learning production systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e Computadores

The national physics and chemistry exams and the learning of sciences

Dissertação apresentada para obtenção do Grau de Doutor em Ciências da Educação, pela Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa