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Sobre
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Sobre

Professor Associado com Agregação da UTAD e Investigador Sénior do INESC TEC.

Doutorou-se, na UTAD, em 2002, em Engenharia Eletrotécnica e realizou, em 2007, as provas Públicas de Agregação em Informática/Acessibilidade. Passou a Professor Associado da UTAD em dezembro de 2012.

Foi Pró-reitor para a Inovação e Gestão da Informação da UTAD, de 23 Julho de 2010 a 29 Julho de 2013.

Produziu mais de 150 trabalhos académicos, entre capítulos de livros, artigos em revistas e artigos em atas de eventos ciêntificos. Orientou 40 trabalhos de pós-graduação (mestrados e doutoramentos).

Participou em 35 projetos de investigação e desenvolvimento (foi investigador principal em 15 destes projetos).

Participou na organização de vários encontros científicos de natureza internacional, em 2006 coordenou a equipa que criou a conferência “Software Development for Enhancing Accessibility and Fighting Info-exclusion (www.dsai.ws/2016) e em 2016 a conferência Technology and Innovation is Sports, Health and Wellbeing (www.tishw.ws/2016).

As áreas principais de investigação são: Processamento Digital de Imagem, Acessibilidade e Interação pessoa Computador.

Google Scholar: http://scholar.google.com/citations?user=HBVvNYQAAAAJ&hl=en

SCOPUS: http://www.scopus.com/authid/detail.url?authorId=20435746800

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    João Barroso
  • Cluster

    Informática
  • Cargo

    Investigador Coordenador
  • Desde

    01 outubro 2012
011
Publicações

2022

Reliability Analysis Based Improved Directional Simulation Using Harris Hawks Optimization Algorithm for Engineering Systems

Autores
Jafari Asl, J; Ben Seghier, MEA; Ohadi, S; Correia, J; Barroso, J;

Publicação
Engineering Failure Analysis

Abstract

2022

My Buddy: A 3D Game for Children Based on Voice Commands

Autores
Carvalho, D; Rocha, T; Barroso, J;

Publicação
INNOVATIONS IN BIO-INSPIRED COMPUTING AND APPLICATIONS, IBICA 2021

Abstract

2022

Automated Evaluation Tools for Web and Mobile Accessibility: A Systematic Literature Review

Autores
Dias, J; Carvalho, D; Paredes, H; Martins, P; Rocha, T; Barroso, J;

Publicação
INNOVATIONS IN BIO-INSPIRED COMPUTING AND APPLICATIONS, IBICA 2021

Abstract
This research aims at investigating which web accessibility and usability tools, with the focus on the ones that warrant automation, are available to assess the quality of interfaces for people with disabilities and/or special needs, enabling them to navigate and interact with web and mobile apps. Our search strategy identified 72 scientific articles of the most rated conferences and scientific journals, from which 16 were considered for the systematic literature review (SLR). We found that, despite the existence of various tools either for web or mobile apps, they are not completely effective, covering less than 40% of all the problems encountered. Also, no tool was found capable of adapting the application interfaces according to the type of disabilities that users may present. Therefore, a new tool could be a welcome advancement to provide full accessible and usable experiences.

2022

Forecasting Student s Dropout: A UTAD University Study

Autores
Da Silva, DEM; Pires, EJS; Reis, A; Oliveira, PBD; Barroso, J;

Publicação
FUTURE INTERNET

Abstract
In Portugal, the dropout rate of university courses is around 29%. Understanding the reasons behind such a high desertion rate can drastically improve the success of students and universities. This work applies existing data mining techniques to predict the academic dropout mainly using the academic grades. Four different machine learning techniques are presented and analyzed. The dataset consists of 331 students who were previously enrolled in the Computer Engineering degree at the Universidade de Tras-os-Montes e Alto Douro (UTAD). The study aims to detect students who may prematurely drop out using existing methods. The most relevant data features were identified using the Permutation Feature Importance technique. In the second phase, several methods to predict the dropouts were applied. Then, each machine learning technique's results were displayed and compared to select the best approach to predict academic dropout. The methods used achieved good results, reaching an Fl-Score of 81% in the final test set, concluding that students' marks somehow incorporate their living conditions.

2021

Web AR Solution for UAV Pilot Training and Usability Testing

Autores
Ribeiro, R; Ramos, J; Safadinho, D; Reis, A; Rabadao, C; Barroso, J; Pereira, A;

Publicação
SENSORS

Abstract
Data and services are available anywhere at any time thanks to the Internet and mobile devices. Nowadays, there are new ways of representing data through trendy technologies such as augmented reality (AR), which extends our perception of reality through the addition of a virtual layer on top of real-time images. The great potential of unmanned aerial vehicles (UAVs) for carrying out routine and professional tasks has encouraged their use in the creation of several services, such as package delivery or industrial maintenance. Unfortunately, drone piloting is difficult to learn and requires specific training. Since regular training is performed with virtual simulations, we decided to propose a multiplatform cloud-hosted solution based in Web AR for drone training and usability testing. This solution defines a configurable trajectory through virtual elements represented over barcode markers placed on a real environment. The main goal is to provide an inclusive and accessible training solution which could be used by anyone who wants to learn how to pilot or test research related to UAV control. For this paper, we reviewed drones, AR, and human–drone interaction (HDI) to propose an architecture and implement a prototype, which was built using a Raspberry Pi 3, a camera, and barcode markers. The validation was conducted using several test scenarios. The results show that a real-time AR experience for drone pilot training and usability testing is achievable through web technologies. Some of the advantages of this approach, compared to traditional methods, are its high availability by using the web and other ubiquitous devices; the minimization of technophobia related to crashes; and the development of cost-effective alternatives to train pilots and make the testing phase easier for drone researchers and developers through trendy technologies.

Teses
supervisionadas

2021

PDapp - A mobile solution for continuous follow-up of Parkinson’s disease patients

Autor
Nuno Duarte Ribeiro da Silva Fonseca Oliveira

Instituição
UP-FEUP

2020

IncWeb - Framework for a more accessible, usable and inclusive Web

Autor
João Carlos Tomé Dias

Instituição
UTAD

2020

Acessibilidade das plataformas de e-learning na perspectiva da experiência do aluno cego

Autor
Isolda Veronese Moniz Vianna Lisboa

Instituição
UTAD

2020

Um modelo para capacitação individual através da personalização intrínseca de tarefas de crowdsourcing

Autor
Dennis Lourenço Paulino

Instituição
UTAD

2019

Sistema de processamento e visualização de dados de atletas

Autor
Nuno Miguel Ferreira Cerdeira Lopes

Instituição
UTAD