Browsing by Author "Silva, Fernando"
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- An approach to (virtually) recreate historical findingsPublication . Gonçalves, Alexandrino José Marques; Silva, Fernando; Mendes, António JoséThe use of technologies in the preservation and dissemination of the Humanity historical and cultural heritage has become an increasing reality. However, access to some of these projects, namely those involving the use of Virtual Reality techniques, is often rather restricted and limited due to technical specificities used in its development and/or visualization. Availability to the general public, for instance through the Internet, becomes, then, impracticable. VRML (Virtual Reality Modeling Language) emerged from the desire to project World Wide Web to a new level, the three-dimensional level. However, even though there are not many alternatives, VRML is not used often. In fact, the number of projects available that use this language is lower than expected. Why? Generally the development of realistic VRML environments results in a set of big files that difficult its download. The complex calculations often necessary to display the virtual environment also create difficulties, since they demand too much for low end computers. This paper intends to present some VRML optimization techniques that allow the creation of a very low file size and a realistic historical environment that can be accessed from any current personal computer. As a result, you can make your own historical tour at: the Flavian Forum of Conimbriga: http://www.forumflaviano.web.pt; House of Skeletons (Conimbriga): http://www.casadosesqueletos.web.pt.
- Artificial intelligence applied to the stone manufacturing industry: A systematic literature reviewPublication . Santos Silva, Alexandre; Antunes, Carolina; Miragaia, Rolando; Costa, Rogério Luís C.; Silva, Fernando; Ribeiro, JoséNatural stone has long been used in construction, as its properties provide functional and visual value, and the natural stone market currently holds significant importance in the global economy. It is important to consider integrating new technologies in the production chain to aid the industry in moving forward, increasing profit margins and reducing wasted material. This article reviews recent trends in using Artificial Intelligence and Machine Learning techniques in the industry between 2017 and 2024, following a methodology for Systematic Literature Reviews in computer science. It was found that extensive research has been conducted on the subject of tile classification, with solid solutions proposed, achieving results that can be considered robust enough for industrial application. Other subjects comprise tasks regarding stone cutting and defect detection, as well as variable prediction, and quarry activity monitoring. Some authors propose solutions to integrate new technologies into the complete production chain. While more research needs to be done on specific subjects, this review provides a solid first step to future research.
- Big Data Analytics in IOT: Challenges, Open Research Issues and ToolsPublication . Constante, Fabián; Silva, Fernando; Herrera, Boris; Pereira, AntónioTerabytes of data are generated day-to-day from modern information systems, cloud computing and digital technologies, as the increasing number of Internet connected devices grows. However, the analysis of these massive data requires many efforts at multiple levels for knowledge extraction and decision making. Therefore, Big Data Analytics is a current area of research and development that has become increasingly important. This article investigates cutting-edge research efforts aimed at analyzing Internet of Things (IoT) data. The basic objective of this article is to explore the potential impact of large data challenges, research efforts directed towards the analysis of IoT data and various tools associated with its analysis. As a result, this article suggests the use of platforms to explore big data in numerous stages and better understand the knowledge we can draw from the data, which opens a new horizon for researchers to develop solutions based on open research challenges and topics. © Springer International Publishing AG, part of Springer Nature 2018.
- Characteristics of patients with COPD using mobile apps in daily lifePublication . Araújo Oliveira, Ana Luisa; Flora, Sofia; Santos, Liliana; Morais, Nuno; Ribeiro, Jose; Silva, Fernando; Silva, Candida; Carreira, Bruno; Caceiro, Ruben; Kumar, Dinesh; Marques, Alda; Brooks, Dina; Burtin, Chris; Cruz, Joana
- A Conversational Agent for Promoting Physical Activity Among COPD PatientsPublication . Rodrigues, Ricardo; Caceiro, Ruben; Brites, Marcelo; Flora, Sofia; Cruz, Joana; Silva, Fernando; Ribeiro, JoséChronic Obstructive Pulmonary Disease (COPD) is one of the most prevalent diseases in the world, affecting respiratory performance of many people, limiting the airflow and is not fully reversible. It is a clinical syndrome characterized by chronic respiratory symptoms, structural pulmonary abnormalities or impairment of lung function. In order to help people with this disease, we propose an innovative personalized mHealth coaching platform that will address patient preferences and contextual factors – the OnTRACK platform. This platform is composed of a mobile application for patients, a web platform for healthcare professionals – and a conversational agent (or chatbot), named “Hígia”, which acts as an alternative interface between patients and the platform. This conversational agent includes several of the main functionalities already available in OnTRACK’s smartphone app, complementing and extending it. It allows consulting prescription information in a multitude of ways, getting and setting all personal data, inserting physical activity measurements, and obtaining historical data on physical activity and prescriptions, among others. The evaluation of the conversational agent yielded encouraging results, with users reporting being happier, more motivated, dedicated and confident when interacting with the systems using their voice, while allowing the development team to identify topics for improvement.
- Motivation and physical activity in COPD: An exploratory studyPublication . Pimenta, Sara; Flora, Sofia; Silva, Cândida G.; Oliveira, Ana; Morais, Nuno; Ribeiro, José; Silva, Fernando; Caceiro, Rúben; Carreira, Bruno P.; Januário, Filipa; Andrade, Lília; Rodrigues, Fátima; Brooks, Dina; Burtin, Chris; Marques, Alda; Cruz, JoanaA key factor for the adoption of an active lifestyle is self-determined motivation; however, it is often overlooked in COPD. Understanding the motives underlying patients’ decision to be (or not) physically active will provide insight into future interventions. This study assessed the motives for patients with COPD to engage in physical activity (PA) and their association with PA behaviour. A cross-sectional study was conducted in stable patients with COPD. Motivation was assessed with the Exercise Motivation Inventory-2 (EMI-2; score 0[Not at all true for me]–5[Very true for me]; 5 dimensions) and PA with accelerometry [ActiGraph-GT3X+, 7 days; moderate to vigorous PA (MVPA), steps/day]. Spearman’s correlations (ρ) were used to assess their relationship. 60 participants were enrolled (67.2±7.7 years; 76.7% men; FEV1 49.5±19.7pp). Patients’ motives to be physically active were mostly Health, Fitness and Psychological. Correlations with PA were weak and non-significant (p>0.05) (Table 1). Patients with COPD value Health, Fitness and Psychological motives to be physically active, although these are not related to their PA behaviour. Findings highlight the complex nature of PA and the need to further explore factors influencing PA and motivation in this population.
- Optimizing Multiple Sequence Alignment by Improving Mutation Operators of a Genetic AlgorithmPublication . Silva, Fernando José Mateus da; Pérez, Juan Manuel Sánchez; Pulido, Juan Antonio Gómez; Rodríguez, Miguel A. Vega; Silva, Fernando;Searching for the best possible alignment for a set of sequences is not an easy task, mainly because of the size and complexity of the search space involved. Genetic algorithms are predisposed for optimizing general combinatorial problems in large and complex search spaces. We have designed a Genetic Algorithm for this purpose, AlineaGA, which introduced new mutation operators with local search optimization. Now we present the contribution that these new operators bring to this field, comparing them with similar versions present in the literature that do not use local search mechanisms. For this purpose, we have tested different configurations of mutation operators in eight BAliBASE alignments, taking conclusions regarding population evolution and quality of the final results. We conclude that the new operators represent an improvement in this area, and that their combined use with mutation operators that do not use optimization strategies, can help the algorithm to reach quality solutions.
- Perfil de atividade física de pessoas com Doença Pulmonar Obstrutiva Crónica (DPOC) em PortugalPublication . Raposo, João; Pimenta, Sara; Alves-Guerreiro, José; Flora, Sofia; Caceiro, Rúben; Morais, Nuno; Oliveira, Ana; Silva, Cândida G.; Ribeiro, José; Silva, Fernando; Januário, Filipa; Carreira, Bruno P.; Rodrigues, Fátima; Marques, Alda; Cruz, JoanaIntrodução e objetivos: A participação em atividade física (AF) regular está associada a um menor risco de mortalidade e melhor qualidade de vida relacionada com a saúde. Apesar de se saber que as pessoas com Doença Pulmonar Obstrutiva Crónica (DPOC) apresentam níveis baixos de AF quando comparadas com indivíduos saudáveis da mesma idade e sexo, desconhece-se ainda a caracterização diária dos níveis de AF destas pessoas em Portugal. Este estudo teve como objetivos caracterizar o perfil de AF de pessoas com DPOC portuguesas e explorar a sua relação com características clínicas. Material e Métodos: Foi realizado um estudo observacional transversal em pessoas com DPOC clinicamente estáveis, nas regiões Centro e Lisboa e Vale do Tejo. Foram recolhidos dados sociodemográficos, antropométricos, função pulmonar [Volume Expiratório Forçado no 1º segundo (FEV1)], sintomas e exacerbações (GOLD ABCD), dispneia (modified Medical Research Council), tolerância ao exercício (teste de marcha dos 6-min) e estado de saúde (COPD Assessment Test). A AF foi avaliada através de acelerometria (ActiGraph GT3X+) durante 7 dias e consistiu em: tempo despendido em AF Moderada a Vigorosa (AFMV) e em AF Total (min/dia), e número de passos/dia. Realizou-se estatística descritiva e correlações de Spearman (ρ) entre as variáveis de AF e as medidas clínicas. Resultados: Os participantes (n=102, 82 do sexo masculino, FEV1=48±19%previsto) apresentaram uma mediana [Q1–Q3] de 20 [9–41] min/dia em AFMV, 144 [100–208] min em AF Total e realizaram 4438 [2821–6944] passos/dia. Apenas 24% dos participantes atingiram ≥7000 passos/dia e 41% os ≥30 min/dia de AFMV recomendados na literatura. O tempo despendido em AFMV e o n.º de passos/dia apresentaram correlações moderadas com a dispneia (ρ=-0.401 e ρ=0.537, respetivamente; p<0.001) e com a tolerância ao exercício (ρ=0.560 e ρ=0.525, respetivamente; p<0.001). O tempo em AFMV apresentou ainda correlação com os graus ABCD (ρ=-0.430, p<0.001). Conclusões: A maioria das pessoas com DPOC é fisicamente inativa. Os sintomas, exacerbações e tolerância ao esforço estão associados à AF nesta população e devem ser considerados em intervenções de promoção de AF.
- Phenotyping Adopters of Mobile Applications Among Patients With COPD: A Cross-Sectional StudyPublication . Flora, Sofia; Hipólito, Nádia; Brooks, Dina; Marques, Alda; Morais, Nuno; Silva, Cândida; Silva, Fernando; Ribeiro, José; Caceiro, Rúben; Carreira, Bruno; Burtin, Chris; Pimenta, Sara; Cruz, Joana; Oliveira, AnaEffectiveness of technology-based interventions to improve physical activity (PA) in people with COPD is controversial. Mixed results may be due to participants' characteristics influencing their use of and engagement with mobile health apps. This study compared demographic, clinical, physical and PA characteristics of patients with COPD using and not using mobile apps in daily life. Patients with COPD who used smartphones were asked about their sociodemographic and clinic characteristics, PA habits and use of mobile apps (general and PA-related). Participants performed a six-minute walk test (6MWT), gait speed test and wore an accelerometer for 7 days. Data were compared between participants using (App Users) and not using (Non-App Users) mobile apps. A sub-analysis was conducted comparing characteristics of PA–App Users and Non-Users. 59 participants were enrolled (73% Male; 66.3 ± 8.3 yrs; FEV1 48.7 ± 18.4% predicted): 59% were App Users and 25% were PA-App Users. Significant differences between App Users and Non-App Users were found for age (64.2 ± 8.9 vs. 69.2 ± 6.3yrs), 6MWT (462.9 ± 91.7 vs. 414.9 ± 82.3 m), Gait Speed (Median 1.5 [Q1–Q3: 1.4–1.8] vs. 2.0 [1.0–1.5]m/s), Time in Vigorous PA (0.6 [0.2–2.8] vs. 0.14 [0.1–0.7]min) and Self-Reported PA (4.0 [1.0–4.0] vs. 1.0 [0.0–4.0] Points). Differences between PA–App Users and Non-Users were found in time in sedentary behavior (764.1 [641.8–819.8] vs. 672.2 [581.2–749.4] min) and self-reported PA (4.0 [2.0–6.0] vs. 2.0 [0.0–4.0] points). People with COPD using mobile apps were younger and had higher physical capacity than their peers not using mobile apps. PA-App Users spent more time in sedentary behaviors than Non-Users although self-reporting more time in PA.
- Real-Time Low-Cost Active and Assisted Living for the ElderlyPublication . Almeida, António Henrique; Santos, Ivo; Rodrigues, Joel; Frazão, Luis; Ribeiro, José; Silva, Fernando; Pereira, AntónioThe aging of population in recent years and the increase in life expectancy is raising challenges for finding new ways to guarantee healthy and controlled activities for the elderly. Most of them prefer living in their houses than in a community center, even if they live alone or isolated from their family; at home, their normal routine activities and comfort makes them feel well. In this paper, an Active and Assisted Living (AAL) solution to detect irregular situations in everyday life of the elderly living alone is presented. By using low-cost sensors in an Internet of Things (IoT) architecture we aim to gather data in specific areas of an elderly’s house in order to give the system enough input to detect abnormal behavior. These sensors are non-intrusive to the elderly, do not disturb them, and do not force them to wear a device at all times. These sensors can also send information to edge computing devices that analyze the data in real time using machine learning algorithms and alert family or caretakers when an unusual situation arises. The proposed solution provides a system that monitors the main activities performed by the elderly and creates patterns based on that activity to achieve its results and is scalable in terms of sensors and data input.