TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

Bid definition method for electricity markets based on an adaptive multiagent system

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

Research on evaluation system of emergency disposal plan for power plant incidents

This paper starts with the analysis of the unusual inherence mechanism, from two aspects: accumulating and human error. We put forward twelve factors affected the decision of the emergency treatment plan in practice and summarized the evaluation index system combining with literature data. Then we screened out eighteen representative indicators by used the FDM expert questionnaire in the first phase. Hereafter, we calculated the weight of evaluation index and sorted them by the FAHP expert questionnaire, and came up with the frame of the evaluation rule by combined with the experience. In the end, the evaluation principles are concluded.

Information and communication technologies in education – a web-based intelligent tutoring system on teaching and learning electrical project

Electrical activity is extremely broad and distinct, requiring by one hand, a deep knowledge on rules, regulations, materials, equipments, technical solutions and technologies and assistance in several areas, as electrical equipment, telecommunications, security and efficiency and rational use of energy, on the other hand, also requires other skills, depending on the specific projects to be implemented, being this knowledge a characteristic that belongs to the professionals with relevant experience, in terms of complexity and specific projects that were made.

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.

Occupational exposure to poultry dust and effects on the respiratory system in workers

Farmers are occupationally exposed to many respiratory hazards at work and display higher rates of asthma and respiratory symptoms than other workers. Dust is one of the components present in poultry production that increases risk of adverse respiratory disease occurrence. Dust originates from poultry residues, molds, and feathers and is biologically active as it contains microorganisms. Exposure to dust is known to produce a variety of clinical responses, including asthma, chronic bronchitis, chronic airways obstructive disease (COPD), allergic alveolitis, and organic dust toxic syndrome (ODTS). A study was developed to determine particle contamination in seven poultry farms and correlate this with prevalence rate of respiratory defects and record by means of a questionnaire the presence of clinical symptoms associated with asthma and other allergy diseases by European Community Respiratory Health Survey. Poultry farm dust contamination was found to contain higher concentrations of particulate matter (PM) PM5 and PM10. Prevalence rate of obstructive pulmonary disorders was higher in individuals with longer exposure regardless of smoking status. In addition, a high prevalence for asthmatic (42.5%) and nasal (51.1%) symptoms was noted in poultry workers. Data thus show that poultry farm workers are more prone to suffer from respiratory ailments and this may be attributed to higher concentrations of PM found in the dust. Intervention programs aimed at reducing exposure to dust will ameliorate occupational working conditions and enhance the health of workers.

The flipped-broadcast learning system, application on Azores

On this work we suggest a teaching solution that can be implemented in Azores, an archipelago of nine islands of Portugal, based in already known system of e-learning, with a twist based on the flipped method. Structured in a cooperative way, the organization of the system allows to isolated groups of people to have access to a certain level of teaching, if they cannot have the possibility to have physical presence in school due to problems emerging from territory discontinuity. Our suggestion can be elaborate in a model that can be adapted to any level of education, and can be adapted also in cases that a cut of budget exists. We suggest the name of fb-learning: Flipped Broadcast Learning.

10 kVp rule – An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Purpose - This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose (E) for pelvis using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Methods and materials - To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60–120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the two alternative forced choice (2AFC) visual grading software. PCXMC software was used to estimate E. Results - A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p > 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. E results show a statistically significant decrease (p = 0.000) on the 75th quartile from 0.37 mSv at 60 kVp to 0.13 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion - Using the 10 kVp rule, no significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant E reduction is observed.

FIA potentiometric system based on periodate polymeric membrane sensors for the assessment of ascorbic acid in commercial drinks

Ascorbic acid is found in many food samples. Its clinical and technological importance demands an easyto- use, rapid, robust and inexpensive method of analysis. For this purpose, this work proposes a new flow procedure based on the oxidation of ascorbic acid by periodate. A new potentiometric periodate sensor was constructed to monitor this reaction. The selective membranes were of PVC with porphyrin-based sensing systems and a lipophilic cation as additive. The sensor displayed a near-Nernstian response for periodate over 1.0x10-2–6.0x10-6 M, with an anionic slope of 73.9 ± 0.9 mV decade-1. It was pH independent in acidic media and presented good selectivity features towards several inorganic anions. The flow set-up operated in double-channel, carrying a 5.0x10-4 M IO- 4 solution and a suitable buffer; these were mixed in a 50-cm reaction coil. The overall flow rate was 7 ml min-1 and the injection volume 70 µl. Under these conditions, a linear behaviour against concentration was observed for 17.7–194.0 µg ml-1, presenting slopes of 0.169 mV (mg/l)-1, a reproducibility of ±1.1 mV (n = 5), and a sampling rate of ~96 samples h-1. The proposed method was applied to the analysis of beverages and pharmaceuticals.

10 kVp rule – An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Background - Pelvis and hip radiography are consistently found to be amongst the highest contributors to the collective effective dose (E) in all ten DOSE DATAMED countries in Europe, representing 2.8 to 9.4% of total collective dose (S) in the TOP 20 exams list. The level of image quality should provide all the diagnostic information in order not to jeopardise the diagnosis, but being able to provide the needed clinical information with the minimum dose. A recent study suggests further research to determine whether the “10 kVp rule” would have value for a range of examinations using Computed Radiography (CR) systems. As a “rule of thumb” increasing the kVp by 10 whilst halving the mAs is suggested to give a similar perceptual image quality when compared to the original exposure factors. Aims - In light of the 10kVp rule, this study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and E for pelvis imaging using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Research questions - Does the 10kVp rule works for the pelvis in relation to image quality in a CR system? Does the image quality differs when the AEC is used instead of manual mode using the 10kVp rule and how this impacts on E?

A distributed system for learning programming on-line

Several Web-based on-line judges or on-line programming trainers have been developed in order to allow students to train their programming skills. However, their pedagogical functionalities in the learning of programming have not been clearly defined. EduJudge is a project which aims to integrate the “UVA On-line Judge”, an existing on-line programming trainer with an important number of problems and users, into an effective educational environment consisting of the e-learning platform Moodle and the competitive learning tool QUESTOURnament. The result is the EduJudge system which allows teachers to apply different pedagogical approaches using a proven e-learning platform, makes problems easy to search through an effective search engine, and provides an automated evaluation of the solutions submitted to these problems. The final objective is to provide new learning strategies to motivate students and present programming as an easy and attractive challenge. EduJudge has been tried and tested in three algorithms and programming courses in three different Engineering degrees. The students’ motivation and satisfaction levels were analysed alongside the effects of the EduJudge system on students’ academic outcomes. Results indicate that both students and teachers found that among other multiple benefits the EduJudge system facilitates the learning process. Furthermore, the experi- ment also showed an improvement in students’ academic outcomes. It must be noted that the students’ level of satisfaction did not depend on their computer skills or their gender.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

Optimizing the renewable generation mix in the Portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.