ESTGV - DEMGI - Artigo em revista científica, indexada ao WoS/Scopus
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- Adaptive and Scalable Database Management with Machine Learning Integration: A PostgreSQL Case StudyPublication . Abbasi, Maryam; Bernardo, Marco V.; Vaz, Paulo; Silva, José; Martins, Pedro; ANTUNES VAZ, PAULO JOAQUIM; Silva, JoséThe increasing complexity of managing modern database systems, particularly in terms of optimizing query performance for large datasets, presents significant challenges that traditional methods often fail to address. This paper proposes a comprehensive framework for integrating advanced machine learning (ML) models within the architecture of a database management system (DBMS), with a specific focus on PostgreSQL. Our approach leverages a combination of supervised and unsupervised learning techniques to predict query execution times, optimize performance, and dynamically manage workloads. Unlike existing solutions that address specific optimization tasks in isolation, our framework provides a unified platform that supports real-time model inference and automatic database configuration adjustments based on workload patterns. A key contribution of our work is the integration of ML capabilities directly into the DBMS engine, enabling seamless interaction between the ML models and the query optimization process. This integration allows for the automatic retraining of models and dynamic workload management, resulting in substantial improvements in both query response times and overall system throughput. Our evaluations using the Transaction Processing Performance Council Decision Support (TPC-DS) benchmark dataset at scale factors of 100 GB, 1 TB, and 10 TB demonstrate a reduction of up to 42% in query execution times and a 74% improvement in throughput compared with traditional approaches. Additionally, we address challenges such as potential conflicts in tuning recommendations and the performance overhead associated with ML integration, providing insights for future research directions. This study is motivated by the need for autonomous tuning mechanisms to manage large-scale, hetero geneous workloads while answering key research questions, such as the following: (1) How can machine learning models be integrated into a DBMS to improve query optimization and workload management? (2) What performance improvements can be achieved through dynamic configuration tuning based on real-time workload patterns? Our results suggest that the proposed framework significantly reduces the need for manual database administration while effectively adapting to evolving workloads, offering a robust solution for modern large-scale data environments.
- An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturingPublication . Babcinschi, Mihail; Freire, Bernardo; Ferreira, Lucía; Señaris, Baltasar; Vidal, Felix; Vaz, Paulo; Neto, PedroIncreasingly, industry is looking to better integrate their industrial processes and related data. Interoperability is key since the organizations need to share data between them, between departments and the different stages of a given technological process. The problem is that many times there are no standard data formats for data exchange between heterogeneous engineering tools. In this paper we present an integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing (MAM). Data such as the MAM robot targets and process parameters are shared and edited along the different sub-stages of the process, from Computer-Aided Design (CAD), to path planning, to multiphysics simulation, to robot simulation and production. The AutomationML neutral data format allows the implementation of optimization loops connecting different sub-stages, for example the multi-physics simulation and the path planning. A practical use case using the Direct Energy Deposition (DED) process is presented and discussed. Results demonstrated the effectiveness of the proposed AutomationML-based solution.
- Aplicação da metodologia DMAIC em uma empresa produtora de componentes de borrachaPublication . Almeida, Ricardo; ANTUNES VAZ, PAULO JOAQUIM; Gomes da Silva, Rosa Maria; AlmeidaIntrodução: Nas últimas décadas, foram feitos grandes desenvolvimentos na indústria. As empresas aprimoraram-se para fazer o produto final com mais qualidade e com grande redução de custos. As metodologias Lean foram implementadas em todos os tipos de indústrias e negócios, rompendo com o tipo de produção que se praticava na época, que se baseava em grandes volumes e pouco flexíveis. As metodologias Lean começaram quando os funcionários e engenheiros da Toyota começaram a desenvolver procedimentos e ferramentas para permitir a produção lean, com desperdício zero e sistemas de produção altamente flexíveis. Objetivo:A reorganização do layout do departamento de manutenção, assim como, a melhoria do processo de gestão das spare partse a criação de fluxos para a reparação de equipamentos e ferramentas. Métodos: A ferramenta utilizada foi o DMAIC, esta subdivide o processo de resolução de problemas em cinco etapas, tais como: Definir, Medir, Analisar, Melhorar, Controlar. Resultados: Com a aplicação desta ferramenta foi possível uma redução do número de deslocações e da distância percorrida, (que por sua vez, permitiu também a diminuição do tempo necessário para a sua realização) deste modo o tempo necessário para a sua realização também diminuiu. As spare parts estão mais organizadas, cada bancada de trabalho possui as peças de substituição de maior consumo. A pontuação obtida nas auditorias 5’S também apresentaram um aumento face aos resultados obtidos antes da intervenção. Conclusão: Conclui-se que a causa raiz e as soluções definidas impactaram positivamente a eliminação da causa e problema iniciais.
- Bibliometric Analysis of Studies on Industry 4.0 Maturity Assessment in SMEsPublication . Guimarães, André; Reis, Pedro; Antonio J. Marques Cardoso; Autor correspondente: Guimarães, A..Introdução: Esta pesquisa pretende contribuir para a organização e análise da literatura científica relacionada com a Avaliação do Nível de Maturidade Digital da Indústria 4.0 (I4.0) em pequenas e médias empresas (PMEs). Destaca-se a relevância contínua da transformação digital, impactando as PMEs e oferecendo oportunidades de integração na economia global. Objetivo: O objetivo principal é utilizar técnicas bibliométricas para analisar e organizar a literatura científica disponível na avaliação do Nível de Maturidade Digital da I4.0 em PMEs. Pretende-se contribuir para compreender as tendências de pesquisa, identificar lacunas de conhecimento e fornecer orientações para futuras investigações. Métodos: Realização de uma revisão abrangente da literatura, abrangendo artigos publicados entre 2011 e 2023 nas plataformas Web of Science (WoS) e SciVerse Scopus (Scopus), pela forte reputação, extenso conteúdo e citações globais. Utilização de técnicas bibliométricas facilitadas pelo VOSviewer e pelo software R-studio´s Bibliometrix R para processamento e análise de dados. Resultados: A análise da literatura revelou insights significativos, incluindo a escassez de pesquisas recentes sobre a avaliação do nível de maturidade digital de PMEs no contexto da I4.0. Identificação de tendências de pesquisa, artigos notáveis com base em citações e publicações, bem como reconhecimento de autores frequentemente citados. Conclusão: A importância do estudo reside na análise minuciosa da literatura existente, na avaliação de tendências de pesquisa chave e na identificação de lacunas, fornecendo insights valiosos. As direções propostas e as prioridades para futuras pesquisas destacam a necessidade de investigações adicionais sobre o nível de maturidade digital das PMEs no contexto da I4.0 e áreas como avaliação de desempenho e competências de gestão.
- Bibliometric Analysis of Studies on Lean Maturity Assessment in SMEsPublication . Guimarães, André; Reis, Pedro; Antonio J. Marques Cardoso; Autor correspondente: Guimarães, A..Introdução: Os princípios Lean têm contribuído significativamente para a eficiência e competitividade das pequenas e médias empresas (PMEs). Contudo, persistem lacunas na literatura científica, particularmente na avaliação da implementação do Lean, nos seus impactos no desempenho e na análise das competências de gestão e conhecimento relacionados. Objetivo: Identificar e analisar as tendências de investigação sobre os princípios Lean e a maturidade Lean em PMEs, avaliando as principais contribuições científicas, os artigos mais citados, os autores mais influentes e as lacunas de investigação que possam orientar trabalhos futuros. Métodos: Foi realizada uma análise bibliométrica de artigos publicados entre 2010 e 2024, disponíveis nas bases Web of Science e Scopus. A análise foi suportada pelos softwares Bibliometrix, em R Studio, e VOSviewer, permitindo a visualização de redes de citações, coautorias e palavras-chave. Resultados: São evidenciadas tendências emergentes e lacunas significativas na investigação sobre maturidade Lean em PMEs. Foram identificados artigos, autores e tópicos de maior destaque, bem como a necessidade de mais estudos sobre a avaliação da maturidade Lean e os seus impactos nas práticas organizacionais e no desempenho das PMEs. Conclusão: Este estudo fornece uma visão abrangente do estado da arte sobre os princípios Lean e a maturidade Lean em PMEs. Ao identificar lacunas e propor direções futuras de investigação, contribui para o avanço das práticas Lean, promovendo uma gestão mais eficiente e competitiva.
- A Case Study of a Solar Oven’s Efficiency: An Experimental ApproachPublication . Silva, José; Serrano, Luís; Martins, Pedro; Ferreira, Hugo; ANTUNES VAZ, PAULO JOAQUIM; Guerra, EmanuelThis research presents the design, construction, and experimental evaluation of a novel box-type solar oven optimized for enhanced thermal efficiency and heat retention, developed to address the challenges of sustainable cooking in temperate climates. The solar oven, measuring 120 cm × 60 cm × 45 cm, incorporates strategically designed rock wool insulation and 5 kg of steel plates as thermal mass, along with a double-glazed glass cover tilted at an experimentally optimized angle of 15° relative to the horizontal plane. Extensive experimental testing was conducted in Viseu, Portugal (40° N latitude) under varying meteorological conditions, including solar irradiance levels ranging from 400 to 900 W/m2 and wind speeds of up to 3 m/s. The results demonstrated that the oven consistently achieved internal temperatures exceeding 160 °C, with a peak temperature of 180 °C, maintaining cooking capability even during periods of intermittent cloud cover. Quantitative analysis showed that the thermal efficiency of the oven reached a peak of 38%, representing a 25–30% improvement over conventional designs. The incorporation of thermal mass reduced temperature fluctuations by up to 40%, and the enhanced insulation reduced conductive heat loss by approximately 30%. Cooking tests validated the oven’s practical effectiveness, with the successful preparation of various foods including rice (90 min), cake (120 min), vegetables (60 min), and bread (110 min). This study provides comprehensive performance data under different meteorological conditions, including detailed temperature profiles, heating rates, and thermal efficiency measurements. By addressing key limitations of prior models, particularly the challenge of temperature stability during variable solar conditions, the proposed solar oven offers a cost-effective, efficient solution that can be adapted for use in diverse climates and regions, with particular relevance to areas seeking sustainable alternatives to traditional cooking methods.
- Comparative analysis of welding processes using different thermoplasticsPublication . Trindade, Adelino; Guimarães, AndréThis study examined and contrasted three widely utilized welding techniques for modern thermoplastics: hot gas welding, laser beam welding, and friction stir welding. These techniques were employed to join various thermoplastic materials, particularly focusing on polypropylene, polyethylene, and polyvinyl chloride. The weld quality was evaluated using visual inspections and tensile strength tests. Additionally, Vickers hardness tests were performed on the welded joints to detect microstructural alterations. The research aimed to deepen the understanding of the mechanisms behind these welding processes and assess the welded joints' strength.
- Comprehensive Evaluation of Deepfake Detection Models: Accuracy, Generalization, and Resilience to Adversarial AttacksPublication . Abbasi, Maryam; ANTUNES VAZ, PAULO JOAQUIM; Silva, José; Martins, PedroThe rise of deepfakes—synthetic media generated using artificial intelli gence—threatens digital content authenticity, facilitating misinformation and manipu lation. However, deepfakes can also depict real or entirely fictitious individuals, leveraging state-of-the-art techniques such as generative adversarial networks (GANs) and emerging diffusion-based models. Existing detection methods face challenges with generalization across datasets and vulnerability to adversarial attacks. This study focuses on subsets of frames extracted from the DeepFake Detection Challenge (DFDC) and FaceForensics++ videos to evaluate three convolutional neural network architectures—XCeption, ResNet, and VGG16—for deepfake detection. Performance metrics include accuracy, precision, F1-score, AUC-ROC, and Matthews Correlation Coefficient (MCC), combined with an assessment of resilience to adversarial perturbations via the Fast Gradient Sign Method (FGSM). Among the tested models, XCeption achieves the highest accuracy (89.2% on DFDC), strong generalization, and real-time suitability, while VGG16 excels in precision and ResNet provides faster inference. However, all models exhibit reduced performance under adversarial conditions, underscoring the need for enhanced resilience. These find ings indicate that robust detection systems must consider advanced generative approaches, adversarial defenses, and cross-dataset adaptation to effectively counter evolving deep fake threats
- Data Privacy and Ethical Considerations in Database ManagementPublication . Pina, Eduardo; Ramos, José; Jorge, Henrique; ANTUNES VAZ, PAULO JOAQUIM; Vaz, Paulo; Silva, José; Wanzeller, Cristina; Abbasi, Maryam; Martins, Pedro; Silva, José; Wanzeller Guedes de Lacerda, Ana CristinaData privacy and ethical considerations ensure the security of databases by respecting individual rights while upholding ethical considerations when collecting, managing, and using information. Nowadays, despite having regulations that help to protect citizens and organizations, we have been presented with thousands of instances of data breaches, unauthorized access, and misuse of data related to such individuals and organizations. In this paper, we propose ethical considerations and best practices associated with critical data and the role of the database administrator who helps protect data. First, we suggest best practices for database administrators regarding data minimization, anonymization, pseudonymization and encryption, access controls, data retention guidelines, and stakeholder communication. Then, we present a case study that illustrates the application of these ethical implementations and best practices in a real-world scenario, showing the approach in action and the benefits of privacy. Finally, the study highlights the importance of a comprehensive approach to deal with data protection challenges and provides valuable insights for future research and developments in this field
- Digital maturity and business performance in industry 4.0: evidence from industrial firms in Portugal's Dão Lafões regionPublication . Guimarães, André; Reis, Pedro; Antonio J. Marques CardosoPurpose – Digital maturity in the context of Industry 4.0 has become a key driverfor enhancing industrialization and overall business performance in the manufacturing sector. However, limited understanding remains regarding how the different pillars of digital maturity affect organizational and financial outcomes. This study investigates the influence of these pillars on key business performance indicators. Design/methodology/approach – A conceptual framework was developed to support the primary research hypotheses. A survey was conducted with 140 manufacturing companies in the D~ao Laf~oes region (Portugal), assessing subdimensions of digital maturity. Business performance data (ROA, debt, interest rate, productivity and Internationalization) were retrieved from the Iberian Balance Sheet Analysis System. Responses were collected through face-to-face interviews with managers, ensuring high-quality and context-rich data. Multiple linear regression models and robust statistical tests ensured the reliability of the results. Findings – Digital maturity has significant but heterogeneous effects on performance. Strategy and data analytics negatively affect ROA and productivity, while existing competencies positively influence internationalization. Strategy is also associated with higher debt. Other subdimensions show marginal effects on internationalization, debt, and interest rate. Practical implications – This study advances both the Industry 4.0 and performance management literature by demonstrating how distinct digital maturity pillars exert heterogeneous effects on operational and financial indicators. The findings refine existing maturity frameworks by showing that early-stage I4.0 adoption may generate negative short-termimpacts, underscoring the need for phased, capability-driven digital transformation strategies in SME-dominated regions. Originality/value – This study contributes to the literature on Industry 4.0 by providing empirical evidence on the differentiated effects of digital maturity subdimensions on business performance. It offers practical insights for policymakers and businessleadersseeking to optimize digital transformation strategies, particularly in SMEdominated industrial regions