ISEP - Departamento de Engenharia Informática
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- C Tutor usage in relation to student achievement and progress: A study of introductory programming courses in Portugal and SerbiaPublication . Alves, Luís; Gajić, Dušan; Henriques, Pedro Rangel; Ivančević, Vladimir; Ivković, Vladimir; Lalić, Maksim; Luković, Ivan; Pereira, Maria João Varanda; Popov, Srđan; Tavares, Paula CorreiaPrevious research studies on introductory programming courses in engineering education in Portugal and Serbia have indicated that although high motivation and high expectations seem to be reported by students, many students may fail the course. This prompted a further inquiry into student attitudes, behavior, and achievement, and it also led to the introduction of C Tutor, a widely known program visualization tool, into courses in both countries. As a result, in the present study, self-reported student achievement (grades), self-reported student progress (knowledge improvement and confidence), and self-reported usage and helpfulness of C Tutor were investigated. Anonymous data about students and their experience in the course, which also included the usage of C Tutor, were collected in a survey in Portugal and Serbia. Quantitative methods, including descriptive statistics, clustering, statistical testing of independence, and partial correlation analysis, were applied in analyses of survey data. The distribution of grades differed between the two countries, but overall attitudes were similar. Various uncovered patterns involving student attitudes and usage of C Tutor may serve as a starting point for new research studies.
- Computational Intelligence and Decision Making: Trends and ApplicationsPublication . Madureira, Ana Maria; Reis, Cecília; Marques, ViriatoAdvances in Computational Intelligence and Decision Making: Trends and Applications provides an overview and original analysis of new developments and applications in several areas of Computational Intelligence and Information Systems, in general. Computational Intelligence became the roadmap for engineers to develop and analyze novel techniques to solve problems in basic sciences such as physics, chemistry, biology, engineering, environment and social sciences. The material contained in this book addresses the foundations and applications of Artificial Intelligence and Decision Support Systems, Complex and Biological Inspired Systems, Simulation and Evolution of real and artificial life forms, Intelligent Models and Control Systems, Knowledge and Learning Technologies, Web Semantics and Ontologies, Intelligent Tutoring Systems, Intelligent Power Systems, Self-Organized and Distributed Systems, Intelligent Manufacturing Systems and Affective Computing. The contributions are written by international experts, who provide up-to-date aspects of the topics discussed and present recent, original insights of their own experience in these fields. Its aim is the presentation of state-of-the-art technologies in the field of Computational Intelligence as well as the discussion of new research findings in this field. The book is suitable for scientists, engineers, educators and students, as it addresses a large diversity of subjects presented in a broad band of complexity, ranging from simple natural language, found in some state-of-the-art articles, to some more complex mathematical issues, found in control applications, robotics and power systems, such as fractional calculus, fuzzy systems and rough-sets theory. Data Mining techniques, such as Support-Vector Machines and Neural Networks, are presented in application of the Biomedical and Bioinformatics fields, among others. Briefly, we believe that this book provides a good window on most of the subjects that directly or indirectly make use of Computational Intelligence, also showing the contributions that it is already giving, or can be given in a near future, for solving some of the more pressing problems of today’s world, such as energy and environment, society and economy.
- Conceitos básicos para o desenvolvimento de cursos multimédiaPublication . Vaz de Carvalho, Carlos[Excerto] Este módulo pretende descrever, de forma necessariamente sintética, as etapas associadas à criação de cursos de e-learning multimédia. No final, o leitor deverá compreender os conceitos básicos da concepção e desenvolvimento de cursos multimédia e ajustá-los de acordo com as matérias a ensinar e com o perfil dos formandos (utilizadores). Deverá ainda dominar as principais fases do desenvolvimento de cursos multimédia - análise e especificação, concepção, desenvolvimento e integração, avaliação e manutenção - incluindo a compreensão da importância de cada etapa, as ferramentas a utilizar e as competências necessárias.
- Factors for Measuring Photovoltaic Adoption from the Perspective of OperatorsPublication . Nascimento, Felipe Moraes do; Siluk, Julio Cezar Mairesse; Savian, Fernando de Souza; Garlet, Taís Bisognin; Pinheiro, José Renes; Ramos, CarlosThe diffusion of photovoltaic distributed generation is relevant for addressing the political, economic, and environmental issues in the electricity sector. However, the proliferation of distributed generation brings new administrative and operational challenges for the sustainability of electric power utilities. Electricity distributors operate in economies of scale, and the high photovoltaic penetration means that these companies have economic and financial impacts, in addition to influencing the migration of other consumers. Thus, this paper aims to systematically identify and evaluate critical factors and indicators that may influence electricity distributors in predicting their consumers’ adoption of photovoltaic technology, which were subjected to the analysis of 20 industry experts. Results show that the cost of electricity, generation capacity, and cost of the photovoltaic systems are the most relevant indicators, and it is possible to measure a considerable part of them using the internal data of the electricity distributors. The study contributes to the understanding of the critical factors for the forecast of the adoption of consumers to distributed photovoltaic generation, to assist the distribution network operators in the decision making, and the distribution sustainability. Also, it establishes the theoretical, political, and practical implications for the Brazilian scenario and developing countries.
- Herb-Drug Interactions: A Holistic Decision Support System in HealthcarePublication . Martins, Andreia; Maia, Eva; Praça, IsabelComplementary and alternative medicine are commonly used concomitantly with conventional medications leading to adverse drug reactions and even fatality in some cases. Furthermore, the vast possibility of herb-drug interactions prevents health professionals from remembering or manually searching them in a database. Decision support systems are a powerful tool that can be used to assist clinicians in making diagnostic and therapeutic decisions in patient care. Therefore, an original and hybrid decision support system was designed to identify herb-drug interactions, applying artificial intelligence techniques to identify new possible interactions. Different machine learning models will be used to strengthen the typical rules engine used in these cases. Thus, using the proposed system, the pharmacy community, people's first line of contact within the Healthcare System, will be able to make better and more accurate therapeutic decisions and mitigate possible adverse events.
- MigraR: An open-source, R-based application for analysis and quantification of cell migration parametersPublication . Shaji, Nirbhaya; Nunes, Florbela; Rocha, M Ines; Gomes, Elsa Ferreira; Castro, HelenaCell migration is essential for many biological phenomena with direct impact on human health and disease. One conventional approach to study cell migration involves the quantitative analysis of individual cell trajectories recorded by time-lapse video microscopy. Dedicated software tools exist to assist the automated or semi-automated tracking of cells and translate these into coordinate positions along time. However, cell biologists usually bump into the difficulty of plotting and computing these data sets into biologically meaningful figures and metrics. Methods: This report describes MigraR, an intuitive graphical user interface executed from the RStudioTM (via the R package Shiny), which greatly simplifies the task of translating coordinate positions of moving cells into measurable parameters of cell migration (velocity, straightness, and direction of movement), as well as of plotting cell trajectories and migration metrics. One innovative function of this interface is that it allows users to refine their data sets by setting limits based on time, velocity and straightness. Results: MigraR was tested on different data to assess its applicability. Intended users of MigraR are cell biologists with no prior knowledge of data analysis, seeking to accelerate the quantification and visualization of cell migration data sets delivered in the format of Excel files by available cell-tracking software. Conclusions: Through the graphics it provides, MigraR is an useful tool for the analysis of migration parameters and cellular trajectories. Since its source code is open, it can be subject of refinement by expert users to best suit the needs of other researchers. It is available at GitHub and can be easily reproduced.
- Plano de ação para a sustentabilidade do ISEPPublication . Cardoso, Marilio; Castanheira, Luís; Meira Castro, Ana C.; Caetano, Nídia Sá; Silva, AntónioO Instituto Superior de Engenharia do Porto (ISEP) apresentou, no passado mês de Janeiro, o seu Plano de Acção para a Sustentabilidade (PASUS). Este documento resultou do trabalho de uma comissão de cinco docentes, nomeada para o efeito pela presidência do ISEP, os quais apresentam formações de base diferenciadas e actuam em áreas distintas, potenciando uma visão heterogénea mas, também por isso, global e integradora das diversas questões relacionadas com a sustentabilidade.
- Prediction of football match results with Machine LearningPublication . Rodrigues, Fátima; Pinto, ÂngeloFootball is one of the most popular sports in the world, so the perception of the game and the prediction of results is of general interest to fans, coaches, media and gamblers. Although predicting football results is a very complex task, the football betting business has grown over time. The unpredictability of football results and the growing betting business justify the development of prediction models to support gamblers. In this article, we develop machine learning methods that take multiple statistics of previous matches and attributes of players from both teams as inputs to predict the outcome of football matches. Several prediction models were tested, with the experimental results showing encouraging performance in terms of the profit margin of football bets.
- Proceedings of the 7th European Conference on Games-Based LearningPublication . European Conference on Games-Based Learning; Escudeiro, Paula; Carvalho, Carlos Vaz de[Excerpt from the Preface] These proceedings represent the work of researchers participating in the 7th European Conference on Games-Based Learning, wich is being organised and hosted this year by the Instituto Superior de Engenharia do Porto (ISEP), Porto, Portugal. The Conference Chair is Dr. Carlos Vaz de Carvalho and the Programme Chair is Dr. Paula Escudeiro, both from the Instituto Superior de Engenharia do Porto, Porto, Portugal. The conference will be opened with a keynote from Dr. Baltasar Fernández-Manjón, from Complutense University of Madrid, Spain, on the topic of Learning Analytics Applied to Serious Games. The opening keynote address on the second day is by Paulo Gomes, Game Director and Producer at BIGMOON STUDIOS. The Conference is a valuable platform for individuals to present their research findings, display their work in progress and discuss conceptual advances in a many different areas and specialties within Games-Based Learning. It also offers the opportunity for like minded individuals to meet, discuss and share knowledge.
- The Usage of Data Augmentation Strategies on the Detection of Murmur Waves in a Pcg SignalPublication . Torres, J.; Oliveira, J.; Gomes, Elsa FerreiraCardiac auscultation is a key screening tool used for cardiovascular evaluation. When used properly, it speeds up treatment and thus improving the patient’s life quality. However, the analysis and interpretation of the heart sound signals is subjective and dependent of the physician’s experience and domain knowledge. A computer assistant decision (CAD) system that automatically analyse heart sound signals, can not only support physicians in their clinical decisions but also release human resources to other tasks. In this paper, and to the best of our knowledge, for the first time a SMOTE strategy is used to boost a Convolutional Neural Network performance on the detection of murmur waves. Using the SMOTE strategy, a CNN achieved an overall of 88.43%.