Abstract
This work presents a case study of the use of information and communication technologies (ICT) as part of the promotion of cooperative learning supported by computer in exterior lighting design, with solar energy. The influence and importance of ICT in various aspects, among which is the field of education, is already a subject practically defined and accepted. In this context the cooperative learning, including ICT, gives rise to the research area called cooperative learning supported by computer (CSCL). This study indicates the effectiveness of Problem Based Learning (PBL) in educating engineering students to make students more responsible in the contents area as well as in generic competences. By using PBL students get the opportunity to work or simulate real problems, making the learning experience much more meaningful. This method can also be seen as a benefit for Electrical Engineering programme where educators strive for improved teaching and learning.

Abstract
M. T. Valdez, C. F. Agreira, C. M. Ferreira, F. P. Maciel Barbosa. Teaching, Learning and Exploring the Use of Project-Based Learning // Electronics and Electrical Engineering. - Kaunas: Technologija, 2010. - No. 9(105). - P. 117-120. Education in academic institutions of higher education is not an easy task, with engineering students needing to be competent in the contents areas as well as in a generic way. This paper describes the implementation of a strategy of the PBL model applied to design a curriculum unit of Electric Power Systems Project (EPSP) of the Electrical Engineering course. This curriculum unit aims to provide students with knowledge to design, model, analyze, and project interior and exterior lighting systems. The results show that students have really benefited from the experience of actually working as members of a team rather than learning using conventional classes. III. 4, bibl. 23 (in English; abstracts in English and Lithuanian).

Abstract
A better environment can be achieved through the reduced emission of pollutants, the optimization of green energy production and the optimization of maintenance interventions, which is an important contribution in getting equipment functioning as efficiently and effectively as possible and, of no less importance, to minimize the downtime caused by faults. These are the key points presented in this paper, which also emphasizes the very recent contribution of 3D models in aiding fault diagnosis and terology in general. The way to achieve the above-mentioned objectives is through on-condition maintenance in two main fields, wind farms and Diesel engines. In wind farms, maintenance is done through the control of variables, such as vibration signals and the balance of electrical currents. As for Diesel engines, on-condition variables are the emissions of PM10, NO(x), CO, HC and CO(2). However, there are problems in both situations, namely, in the first case, the distance and accessibility of the generators and, in the second case, the problems associated with the fact that the equipment is not static. Another common problem in both situations is the measuring and transmission of the values of the on-condition variables, because, in the case of wind farms, the machine is placed on top of the tower and, in the case of Diesel engines, the vehicles are in operation most of the time and most of the measurements need be made while the vehicles are running. Also, although the two situations seem different, they have many issues in common, such as those above-mentioned, for which we will propose convergent solutions that have an Integrated Modular System for Terology (SMIT - Sistema Modular Integrado de Terologia) as a base platform. In addition, to collect, transmit and manage data, we also propose low-cost hardware devices and open-source software, with time series, Hidden Markov Models and genetic algorithms incorporated into them, to enable the prediction of new maintenance interventions. Another important development that is mentioned, with the objective of achieving a more effective terology system, is the implementation of 3D models to aid fault diagnosis and maintenance interventions in general. All these subjects are treated in this paper in a cohesive and synergistic way in order to achieve more effective terology management with an environmental perspective.

Abstract
The use of open-source software in many institutions and organizations is increasing. However, a balance should be considered between the software cost and the cost of its technical support and reliability. In this article, a maintenance system for wind farms will be presented. It is connected to an information system for maintenance, called SNIFF (Terology Integrated Modular System) as a general base to manage the assets and as a support strategic line to the evolution of this system, which incorporates on-condition maintenance modules, and the support to the research and development done around this theme. The SMIT system is based on a TCP/IP network, using a Linux server running a PostgreSQL database and Apache web server with PHP, and Octave and R software for numerical analysis. Maintenance technicians, chiefs, economic and production management personnel can access SMIT database through SMIT clients for Windows. In addition, this maintenance system for wind systems uses also special low cost hardware for data acquisition on floor level. The hardware uses a distributed TCP/IP network to synchronize SMIT server master clock through Precision Time Protocol. Usually, the manufactures construct, deploy and give the means for the suppliers to perform the wind system's maintenance. This is a very competitive area, where companies tend to hide the development details and implementations. Within this scenario, the development of maintenance management models for multiple wind equipments is important, and will allow countries to be more competitive in a growing market. For on-condition monitoring, the algorithms are based on Support Vector Machines and time series analysis running under Octave and R open-source software's.

Abstract
This study illustrates and discusses an original approach to classify the electricity consumers according to their daily load patterns. This approach exploits the notion of entropy introduced by Renyi for setting up specific clustering procedures. The proposed procedures differ with respect to typical methods adopted for electricity consumer classification, based on the Euclidean distance notion. The algorithms tested include firstly a classical method based on the between-cluster entropy and its slight variation. Then, a novel procedure is presented, based on the calculation of the similarity between centroids, with successive refinement to allow effective identification of the outliers. The outcomes of the classification carried out by using the proposed procedure are compared to the results of other available techniques, using a set of clustering validity indicators for ranking the clustering methods. On the basis of these results, it emerges that the novel procedure exhibits better clustering performance with respect to both the literature approaches and the classical entropy-based method, for different numbers of clusters. The results obtained are of key relevance for assisting the electricity suppliers in identifying a reduced number of load pattern-dependent classes, to be associated with distinct consumer groups for load aggregation or tariff purposes. © 2010 © The Institution of Engineering and Technology.

Abstract
This paper presents a new control chip design, based on Field Programmable Gate Array (FPGA) technology, for multi-motor electric vehicles. The control chip builds around a reusable intellectual property (IP) core, named Propulsion Control System (PCS); which features motor control functions with field orientation methods, and energy loss minimization of induction motors. To reduce the cost, implementation issues related with the limited number of dedicated multipliers were overcome using an efficient computational block, based on resource sharing strategy. Due to the parallel processing offered by FPGAs, the resulting implementation can be effortlessly adapted to different electric vehicles topologies, like single or multi-motor drive. As proof of concept, two prototypes with single and multi-motor configurations were developed with the control chip design implemented in a low cost Xilinx Spartan 3 FPGA. Experimental verification of the energy loss minimization algorithm is provided, showing considerable energy savings (>15%) in low speed conditions and improving the electric vehicle range per charge.