Escola Superior de Tecnologia e Gestão
Permanent URI for this community
Browse
Browsing Escola Superior de Tecnologia e Gestão by Sustainable Development Goals (SDG) "04:Educação de Qualidade"
Now showing 1 - 10 of 27
Results Per Page
Sort Options
- 5th Symposium of Applied Science for Young Researchers: ProceedingsPublication . Fernandes, Florbela P.; Torres, Helena; Pinto, Pedro; Malta, SilvestreThis document presents the proceedings of the 5th Symposium of Applied Science for Young Researchers – SASYR 2025. This scientific event welcomed scientific works on the topics covered by the following four research centers: – CeDRI (from IPB, Instituto Politécnico de Bragança) – 2Ai (from IPCA, Instituto Politécnico do Cávado e do Ave) – GECAD (from IPP, Instituto Politécnico do Porto) – ADiT-lab (from IPVC, Instituto Politécnico de Viana do Castelo) The primary objective of SASYR 2025 is to create a welcoming and relaxed environment for young researchers to present their work, discuss recent findings, and explore new ideas. In this way, this event offers an opportunity for the CeDRI, 2Ai, GECAD, and ADiT-lab research communities to leverage synergies and promote collaborations, thereby enhancing the quality of their research. The SASYR 2025 took place at Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal, on 2 July 2025.
- A prototype to enhance academic attendance using BLE beaconsPublication . Simas, Sily; Oliveira, Pedro Filipe; Matos, PauloThis project addresses the prototyping and application of an attendance control solution in an academic context, using Beacons. The introduction highlights the importance of effectively managing student attendance to ensure active participation in educational activities and provide insights into student engagement. BLE Beacons technology is compared to other RF signaling technologies, highlighting its advantages in terms of range, power consumption, cost, frequency, and data rate. BLE Beacon is chosen as the preferred technology due to its combination of adequate range, low power consumption, affordable cost, compatibility, security, and flexibility. The results section presents Estimote Beacons as devices used, highlighting their advanced features and techniques used, such as proximity and triangulation, to determine student presence. A visual summary of the project is presented in a flowchart that illustrates the operating processes of each stage. This solution promises to significantly improve the efficiency, safety, and quality of the academic environment, while simplifying the attendance recording process and providing valuable insights into student behavior.
- Automated preprocessing of olive leaf images for cultivar classification using YOLO11Publication . Mendes, João; Lima, José; Rodrigues, Nuno; Pereira, Ana I.Olive cultivation is a pillar of Mediterranean agriculture, deeply rooted in both tradition and economic importance. This paper presents a novel two-phase methodology for the automated preprocessing of olive leaf images to facilitate accurate cultivar classification. Leveraging the state-of-the-art YOLO11 framework, two models (YOLO11n and YOLO11s) were employed for detection and segmentation tasks. A comprehensive dataset, combining in-situ captured images with publicly available data, was meticulously annotated using both manual and semi-automatic processes. The detection model identifies individual olive leaves, while the segmentation model isolates the leaves by replacing the background with a uniform white, thereby simulating laboratory conditions. Experimental results demonstrate that YOLO11n outperforms YOLO11s in terms of mean Average Precision and F1-score, confirming the feasibility of deploying the system on mobile devices for real-time, in-field classification.
- Categorizing Students of the MathE Platform: A Fuzzy Clustering PerspectivePublication . Leite, Gabriel A.; Azevedo, Beatriz Flamia; Pacheco, Maria F.; Fernandes, Florbela P.; Pereira, Ana I.Active learning and technology integration offer enhanced student engagement and adaptive learning, accommodating diverse preferences. This work uses fuzzy clustering method to analyze the data of students who answer questions on the MathE platform. To do this, the Fuzzy c-means algorithm was used, which allows flexibility and adaptability in the clustering partitioning, especially in situations where data elements may exhibit overlapping characteristics or belong to multiple categories. Thereby, two datasets are considered: the first is composed of 121 students who answered questions from the Vector Space subtopic, and the second dataset comprises the answers of 297 students who answered to any topic or subtopic of the platform. The results show that the fuzzy clustering method is appropriate for analyzing the student’s data since most students are highly associated with more than one cluster. Besides, the findings can support the formulation of intervention strategies to improve the student’s academic achievement.
- Comparing RL policies for robotic pusherPublication . Bonjour, Pedro; Lopes, Rui PedroReinforcement learning (RL) has been consolidated as a promising approach to optimizing robotic tasks, allowing the improvement of performance and energy efficiency. This study investigates the effectiveness of five RL algorithms in the Pusher environment. Advantage Actor-Critic (A2C), Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), Soft Actor-Critic (SAC) and Twin Delayed Deep Deterministic Policy Gradient (TD3). We evaluated training time, computational efficiency, and reward values to identify the most balanced solution between accuracy and energy consumption. The results indicate that the PPO offers the best compromise between performance and efficiency, with reduced training time and stability in learning. SAC achieves the best rewards but requires more training time, while A2C faces difficulties in continuous spaces. DDPG and TD3, despite t he good results, have high computational consumption, which limits their viability for real-time industrial applications. These findings highlight the importance of considering energy efficiency when choosing RL algorithms for robotic applications. As a future direction, we propose the implementation of these algorithms in a real-world environment, as well as the exploration of hybrid approaches that combine different strategies to improve accuracy and minimize energy consumption.
- Data Engineering Roadmap for Implementing Business Intelligence in Higher EducationPublication . Sequeira, Romeu; Reis, Arsénio; Branco, Frederico; Alves, PauloThis article addresses the implementation of Business Intelligence (BI) systems in Higher Education Institutions (HEIs), focusing on developing an appropriate data architecture that meets the specificities and requirements of this sector. With the rapid advance of information technologies, HEIs face the growing challenge of managing a considerable volume of data, making it essential to implement BI systems that support informed and efficient decision-making. Using the Design Science Research methodology, this study proposes a BI architecture model that aligns technologies with HEIs' academic and administrative needs and facilitates their integration and ongoing maintenance. The model is designed to be flexible and scalable, allowing adaptations as institutional needs evolve. The article describes the architecture development process, from initial planning to implementation, and discusses how this framework can significantly improve data management and the quality of decision-making processes in educational institutions. The research offers practical and theoretical insights for academics and managers seeking to optimize the use of BI in educational contexts.
- A deep learning approach for average height estimation in oak colony using rgb imagesPublication . Britto, Raphael Duarte; Mendes, João; Grilo, Vinicius; Castro, João Paulo; Santos, Murillo Ferreira dos; Castro, Marina; Pereira, Ana I.; Lima, JoséMany strategies have been developed to monitor the volume of volume of Above Ground Biomass (AGB) in forest areas as a fundamental step for managing carbon concentration. This study explores the use of use of Light Detection and Ranging (LiDAR) data obtained through Unmanned Aerial Vehicles (UAVs) to estimate height values in a vegetation colony composed of oaks (Quercus pyrenaica Willd.) in northern Portugal. The extraction of pertinent information from LiDAR data was facilitated by using the LAStools extension within the Quantum Geographic Information System (QGIS) software framework. The generated raster and image information were used to calculate the height values of the vegetation. Following this extraction, the information was meticulously organized into datasets, which were then employed in Deep Learning (DL) algorithms. The VGG16 model was selected as the underlying framework for the present study. Height predictions were made using dimensions of 16× 16, 32× 32, and 64 × 64 pixels for the Red, Green and Blue (RGB) images. The data was estimated and compared using both the standard format of the VGG16 model and a superficially adapted version of its convolution layers. The algorithm’s efficacy was validated by comparing the forecast results with the data obtained from QGIS, which revealed minimal discrepancies. It was observed that using 64× 64 pixel scale images yielded enhanced accuracy, resulting in reduced values for the Mean Absolute Error (MAE). The study demonstrates the viability of applying DL techniques to accurately capture information about a forest area using RGB images.
- Design and development of a differential drive platform for dragster competitionPublication . Grilo, Vinicius; Ferreira, Edilson; Barbosa, Ana; Chellal, Arezki Abderrahim; José L. LimaRobotics competitions have been increasing in the last years since they bring several impacts on students education, such as technical skill development, teamwork, resilience and decision making withing the STEM skills. The article highlights the significance of robotics competitions as platforms for fostering innovation and driving advancements in the field of robotics. This article primarily focuses on the development of a robot in the Dragster category for the 2023 Portuguese Robotics Open. It outlines the strategies devised to tackle the competition’s challenges and discusses the obstacles encountered along with the corresponding solutions employed. The article delves into the specific details of the challenges faced and the iterative processes undertaken to enhance the robot’s performance and functionalities. By sharing the insights gained from the project, future proposals for iterations of the robot will be presented, aiming to further augment its features and overall performance while sharing knowledge with other teams and community.
- Digital transformation and the new combinations in tourism: a systematic literature reviewPublication . Gutierriz, Ives; Ferreira, João J.; Fernandes, Paula OdeteThis study aims to analyse the research involving the evolution and development of digital transformation and the new combinations in tourism development. To this end, a systematic literature review was conducted in the Scopus and Web of Science databases, which gathered 167 studies published between 1997 and 2023, representing the final sample analysed in this review. The results allow the identification of three main findings: i) there are four thematic groups - Digital Marketing, Digital Economy, Education and Hospitality and Free Digital; ii) there is a growing interest in the research of this topic and the use of available technologies for the development of tourism companies and their businesses and the respective wider economy; and, iii) digital transformation tends to be a positive factor when applied to the tourism sector. This research further proposes a framework that provides a detailed description of these studies with key issues and contributions from the available literature.
- Domínio espaço nos manuais portugueses de físico-química do 7º ano: uma perspetiva de géneroPublication . Fernandes, Ana Maia; Soares, Sandra; Cardim, Sofia; Editora, Atena, AtenaA questão da sub-representação feminina nas áreas STEM tem sido amplamente analisada a nível global, devido à desigualdade de acesso das mulheres a algumas dessas áreas, como a Física. Nesse contexto, a escola desempenha um papel fundamental na democratização do conhecimento e na promoção da igualdade de oportunidades. O viés de género presente nos manuais escolares pode influenciar significativamente as perceções sobre quem possui competência em determinadas áreas do saber, uma vez que essas representações frequentemente perpetuam estereótipos ligados a papéis sociais específicos. O estudo analisou representações de género em imagens do domínio Espaço em manuais portugueses de Físico-Química do 7.º ano. Utilizando um design de investigação mista, identificaram-se desproporções significativas de género e padrões que perpetuam estereótipos masculinos, em linha com a literatura. Os resultados indicaram que, em todas as categorias avaliadas, o número de figuras masculinas foi superior, com a razão entre figuras masculinas e femininas variando de 1,8 a 9,0. No que diz respeito às figuras históricas, foram encontradas apenas duas referências femininas. Nas categorias “pessoas associadas à atividade científica” e “pessoas a realizar atividades relacionadas com os conteúdos do manual”, a desproporção entre homens e mulheres também foi evidente. Nesta última categoria, as atividades desempenhadas pelas figuras femininas, também em alinhamento com a literatura, continuam a reforçar estereótipos de género, destacando papéis maternais ou atividades de lazer.
- «
- 1 (current)
- 2
- 3
- »