128 documents found, page 1 of 13
Adversarial Robustness and Feature Impact Analysis for Driver Drowsiness Detection
Vitorino, João; Rodrigues, Lourenço; Maia, Eva; Praça, Isabel; Lourenço, AndréDrowsy driving is a major cause of road accidents, but drivers are dismissive of the impact that fatigue can have on their reaction times. To detect drowsiness before any impairment occurs, a promising strategy is using Machine Learning (ML) to monitor Heart Rate Variability (HRV) signals. This work presents multiple experiments with different HRV time windows and ML models, a feature impact analysis using Shap...
From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities
Dias, Tiago; Fonseca, Tiago; Vitorino, João; Martins, Andreia; Malpique, Sofia; Praça, IsabelThe emergence of smart cities demands harnessing advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) and promises to unlock cities' potential to become more sustainable, efficient, and ultimately livable for their inhabitants. This work introduces an intelligent city management system that provides a data-driven approach to three use cases: (i) analyze traffic information to...
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusi...
Vitorino, João; Praça, Isabel; Maia, EvaMachine Learning (ML) can be incredibly valuable to automate anomaly detection and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is performed. However, despite the benefits of ML models, they are highly susceptible to adversarial cyber-attack examples specifically crafted to exploit them. A wide range of adversarial attacks have been created and researchers have worked on...
Herb-Drug Interactions: A Holistic Decision Support System in Healthcare
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 diag...
Consumo de fármacos, suplementos e fitoterápicos, e risco de interações: revisã...
Dores, Artemisa Rocha; Peixoto, Miguel; Castro, Maria; Sã, Catarina; Martins, Andreia; Maia, Eva; Praça, Isabel; ForPharmacy team; Marques, AntónioO aumento do consumo de diversos produtos naturais e em particular de suplementos para fins diversos, como melhoria do desempenho físico e/ou intelectual, tem aumentando nos últimos anos, com consequências negativas para a saúde, algumas fatais. A falta de conhecimento sobre estes produtos, crenças erradas, a aquisição sem aconselhamento e em locais pouco seguros parecem contribuir para esta realidade que preci...
Constrained Adversarial Learning and its applicability to Automated Software Te...
Vitorino, João; Dias, Tiago; Fonseca, Tiago; Maia, Eva; Praça, IsabelEvery novel technology adds hidden vulnerabilities ready to be exploited by a growing number of cyber-attacks. Automated software testing can be a promising solution to quickly analyze thousands of lines of code by generating and slightly modifying function-specific testing data to encounter a multitude of vulnerabilities and attack vectors. This process draws similarities to the constrained adversarial example...
Knowledge and beliefs about herb/supplement consumption and herb/supplement–dru...
Dores, Artemisa R.; Peixoto, Miguel; Castro, Maria; Sá, Catarina; Carvalho, Irene P.; Martins, Andreia; Maia, Eva; Praça, Isabel; Marques, AntónioThe increased consumption of a variety of herbs/supplements has been raising serious health concerns. Owing to an inadequate understanding of herb/supplement–drug interactions, the simultaneous consumption of these products may result in deleterious effects and, in extreme cases, even fatal outcomes. This systematic review is aimed at understanding the knowledge and beliefs about the consumption of herbs/supple...
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and...
Vitorino, João; Praça, Isabel; Maia, EvaThe internet of things (IoT) faces tremendous security challenges. Machine learning models can be used to tackle the growing number of cyber-attack variations targeting IoT systems, but the increasing threat posed by adversarial attacks restates the need for reliable defense strategies. This work describes the types of constraints required for a realistic adversarial cyber-attack example and proposes a methodol...
Consumo de fármacos, suplementos e fitoterápicos, e risco de interações: revisã...
R Dores, Artemisa; Peixoto, Miguel; Castro, Maria; Sã, Catarina; Martins, Andreia; Maia, Eva; Praça, Isabel; ForPharmacy team; Marques, AntónioIntrodução: O aumento do consumo de diversos produtos naturais e em particular de suplementos para fins diversos, como melhoria do desempenho físico e/ou intelectual, tem aumentando nos últimos anos, com consequências negativas para a saúde, algumas fatais. A falta de conhecimento sobre estes produtos, crenças erradas, a aquisição sem aconselhamento e em locais pouco seguros parecem contribuir para esta realida...
GECA: um chatbot inteligente para cuidados preventivos
Maia, Eva; Vieira, Pedro; Praça, IsabelIntrodução: Os chatbots são sistemas de processamento de linguagem natural que atuam como um agente de conversação, imitando as interações humanas. Recentemente, o interesse pelos chatbots aumentou e eles foram usados em vários sectores. A saúde não foi exceção, dado o crescente interesse por este tipo de tecnologia aliado à necessidade de apoiar os doentes em casa (Adamopoulou et al., 2020). Usando métodos bas...