A web-based intelligent tutoring system on teaching and learning electrical project

The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.

Learning objects recommendation in an adaptive educational hypermedia system

The aim of this paper is presenting the modules of the Adaptive Educational Hypermedia System PCMAT, responsible for the recommendation of learning objects. PCMAT is an online collaborative learning platform with a constructivist approach, which assesses the user’s knowledge and presents contents and activities adapted to the characteristics and learning style of students of mathematics in basic schools. The recommendation module and search and retrieval module choose the most adequate learning object, based on the user's characteristics and performance, and in this way contribute to the system’s adaptability.

Multi-apprentice learning for meta-heuristics parameter tuning in a multi agent scheduling system

The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance.

Self-optimizing through CBR learning

In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

PCMAT, an adaptive learning platform

This paper is about PCMAT, an adaptive learning platform for Mathematics in Basic Education schools. Based on a constructivist approach, PCMAT aims at verifying how techniques from adaptive hypermedia systems can improve e-learning based systems. To achieve this goal, PCMAT includes a Pedagogical Model that contains a set of adaptation rules that influence the student-platform interaction. PCMAT was subject to a preliminary testing with students aged between 12 and 14 years old on the subject of direct proportionality. The results from this preliminary test are quite promising as they seem to demonstrate the validity of our proposal.

Adaptation model for PCMAT – Mathematics collaborative learning platform

The aim of this paper is to present an adaptation model for an Adaptive Educational Hypermedia System, PCMAT. The adaptation of the application is based on progressive self-assessment (exercises, tasks, and so on) and applies the constructivist learning theory and the learning styles theory. Our objective is the creation of a better, more adequate adaptation model that takes into account the complexities of different users.

Word learning and text organisation: an intervention case

In the present study we focus on the interaction between the acquisition of new words and text organisation. In the acquisition of new words we emphasise the acquisition of paradigmatic relations such as hyponymy, meronymy and semantic sets. We work with a group of girls attending a private school for adolescents in serious difficulties. The subjects are from disadvantaged families. Their writing skills were very poor. When asked to describe a garden, they write a short text of a single paragraph, the lexical items were generic, there were no adjectives, and all of them use mainly existential verbs. The intervention plan assumed that subjects must to be exposed to new words, working out its meaning. In presence of referents subjects were taught new words making explicit the intended relation of the new term to a term already known. In the classroom subjects were asked to write all the words they knew drawing the relationships among them. They talk about the words specifying the relation making explicit pragmatic directions like is a kind of, is a part of or are all x. After that subjects were exposed to the task of choosing perspective. The work presented in this paper accounts for significant differences in the text of the subjects before and after the intervention. While working new words subjects were organising their lexicon and learning to present a whole entity in perspective.

New syntheses of potential biologically active xanthones and benzoxanthones

10º Encontro Nacional de Química Orgânica e 1º Simpósio Luso-Brasileiro de Química Orgânica, Lisboa, 4-6 Setembro de 2013.

Pratiques d’enseignement en lecture-écriture et apprentissages des élèves au début du primaire

Esta investigação pretende contribuir para o desenvolvimento da investigação interessada nas questões relativas ao ensino/ aprendizagem do modo escrito nos primeiros anos do primeiro ciclo do ensino básico, particularmente tendo em conta as práticas mais propensas a apoiar a aprendizagem bem-sucedida da leitura e de escrita. Especificamente, esta investigação tem como objetivo descrever as práticas de ensino observadas nas áreas da leitura e da escrita com 22 professores, mas também para relacionar essas práticas observadas com o desempenho em leitura e escrita dos seus alunos do primeiro e do segundo ano. Globalmente, os resultados indicam que as práticas observadas, tanto do ponto de vista dos Dispositivos mobilizados como do conteúdo ensinado, são variadas e contribuem para uma visão complexa da entrada na escrita. As análises de correlação sugerem que determinadas práticas, que geralmente procuram a participação activa das crianças e as interações com os outros, estão relacionados com o progresso dos alunos durante o ano letivo.

SiC Multilayer Structures as Light Controlled Photonic Active Filters

Tunable wavelength division multiplexing converters based on amorphous SiC multilayer photonic active filters are analyzed. The configuration includes two stacked p-i-n structures (p(a-SiC:H)-i'(a-SiC:H)-n(a-SiC:H)-p(a-SiC:H)-i(a-Si:H)-n(a-Si:H)) sandwiched between two transparent contacts. The manipulation of the magnitude is achieved through appropriated front and back backgrounds. Transfer function characteristics are studied both theoretically and experimentally. An algorithm to decode the multiplex signal is established. An optoelectronic model supports the optoelectronic logic architecture. Results show that the light-activated device combines the demultiplexing operation with the simultaneous photodetection and self-amplification of an optical signal. The output waveform presents a nonlinear amplitude-dependent response to the wavelengths of the input channels. Depending on the wavelength of the external background and irradiation side, it acts either as a short- or a long-pass band filter or as a band-stop filter. A two-stage active circuit is presented and gives insight into the physics of the device.

Optimal design for active damping in sandwich structures using the Direct MultiSearch method

This paper addresses the problem of optimal positioning of surface bonded piezoelectric patches in sandwich plates with viscoelastic core and laminated face layers. The objective is to maximize a set of modal loss factors for a given frequency range using multiobjective topology optimization. Active damping is introduced through co-located negative velocity feedback control. The multiobjective topology optimization problem is solved using the Direct MultiSearch Method. An application to a simply supported sandwich plate is presented with results for the maximization of the first six modal loss factors. The influence of the finite element mesh is analyzed and the results are, to some extent, compared with those obtained using alternative single objective optimization. (C) 2013 Elsevier Ltd. All rights reserved.

A 5GHz/1.8V CMOS Active Balun Integrated with LNA

The development of high performance monolithic RF front-ends requires innovative RF circuit design to make the best of a good technology. A fully differential approach is usually preferred, due to its well-known properties. Although the differential approach must be preserved inside the chip, there are cases where the input signal is single-ended such as RF image filters and IF filters in a RF receiver. In these situations, a stage able to convert single-ended into differential signals (balun) is needed. The most cited topology, which is capable of providing high gain, consists on a differential stage with one of the two inputs grounded. Unfortunately, this solution has some drawbacks when implemented monolithically. This work presents the design and simulated results of an innovative high-performance monolithic single to differential converter, which overcomes the limitations of the circuits.The integration of the monolithic active balun circuit with an LNA on a 0.18μm CMOS process is also reported. The circuits presented here are aimed at 802.11a. Section 2 describes the balun circuit and section 3 presents its performance when it is connected to a conventional single-ended LNA. Section 4 shows the simulated performance results focused at phase/amplitude balance and noise figure. Finally, the last section draws conclusions and future work.

A educação Pré-Escolar e o 1.º ciclo do Ensino Básico: dinâmicas de cidadania em contextos de práticas curriculares e didáticas

Mestrado (PES II), Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico, 1 de Julho de 2014, Universidade dos Açores.

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.