34 documents found, page 1 of 4
A Practical Performance Benchmark of Post-Quantum Cryptography Across Heterogen...
Abbasi, Maryam; Cardoso, Filipe; Vaz, Paulo; Silva, José; Martins, PedroThe emergence of large-scale quantum computing presents an imminent threat to contemporary public-key cryptosystems, with quantum algorithms such as Shor’s algorithm capable of efficiently breaking RSA and elliptic curve cryptography (ECC). This vulnerability has catalyzed accelerated standardization efforts for post-quantum cryptography (PQC) by the U.S. National Institute of Standards and Technology (NIST) an...
Head-to-Head Evaluation of FDM and SLA in Additive Manufacturing: Performance, ...
Abbasi, Maryam; ANTUNES VAZ, PAULO JOAQUIM; Martins, Pedro; Silva, JoséThis paper conducts a comprehensive experimental comparison of two widely used additive manufacturing (AM) processes, Fused Deposition Modeling (FDM) and Stereolithography (SLA), under standardized conditions using the same test geometries and protocols. FDM parts were printed with both Polylactic Acid (PLA) and Acryloni trile Butadiene Styrene (ABS) filaments, while SLA used a general-purpose photopolymer resi...
Performance and Scalability of Data Cleaning and Preprocessing Tools: A Benchma...
Martins, Pedro; Cardoso, Filipe; Vaz, Paulo; Silva, José; Abbasi, MaryamData cleaning remains one of the most time-consuming and critical steps in modern data science, directly influencing the reliability and accuracy of downstream analytics. In this paper, we present a comprehensive evaluation of five widely used data cleaning tools—OpenRefine, Dedupe, Great Expectations, TidyData (PyJanitor), and a baseline Pandas pipeline—applied to large-scale, messy datasets spanning three dom...
Comprehensive Evaluation of Deepfake Detection Models: Accuracy, Generalization...
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 g...
Machine Learning Approaches for Predicting Maize Biomass Yield: Leveraging Feat...
Abbasi, Maryam; Vaz, Paulo; Silva, José; Martins, Pedro; Silva, José; ANTUNES VAZ, PAULO JOAQUIMThe efficient prediction of corn biomass yield is critical for optimizing crop production and addressing global challenges in sustainable agriculture and renewable energy. This study employs advanced machine learning techniques, including Gradient Boosting Machines (GBMs), Random Forests (RFs), Support Vector Machines (SVMs), and Artificial Neural Networks (ANNs), integrated with comprehensive environmental, so...
Real-Time Gesture-Based Hand Landmark Detection for Optimized Mobile Photo Capt...
Marques, Pedro; ANTUNES VAZ, PAULO JOAQUIM; Silva, José; Martins, Pedro; Abbasi, MaryamGesture recognition technology has emerged as a transformative solution for natural and intuitive human–computer interaction (HCI), offering touch-free operation across diverse fields such as healthcare, gaming, and smart home systems. In mobile contexts, where hygiene, convenience, and the ability to operate under resource constraints are critical, hand gesture recognition provides a compelling alternative to ...
Adaptive and Scalable Database Management with Machine Learning Integration: A ...
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 PostgreS...
Data Privacy and Ethical Considerations in Database Management
Pina, Eduardo; Ramos, José; Jorge, Henrique; ANTUNES VAZ, PAULO JOAQUIM; Vaz, Paulo; Silva, José; Wanzeller, Cristina; Abbasi, Maryam; Martins, PedroData 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 individua...
Enhancing Visual Perception in Immersive VR and AR Environments: AI-Driven Colo...
Abbasi, Maryam; Silva, José; Martins, Pedro; ANTUNES VAZ, PAULO JOAQUIM; Silva, JoséThe visual fidelity of virtual reality (VR) and augmented reality (AR) environments is essential for user immersion and comfort. Dynamic lighting often leads to chromatic distortions and reduced clarity, causing discomfort and disrupting user experience. This paper introduces an AI-driven chromatic adjustment system based on a modified U-Net architecture, optimized for real-time applications in VR/AR. This syst...
Comparison of Semi-structured Data on MSSQL and PostgreSQL
Alves, Leandro; Cardoso, Filipe; Oliveira, Pedro; Rocha, Júlio; Wanzeller, Cristina; Martins, Pedro; Abbasi, MaryamThe present study intends to compare the performance of two Data Base Management Systems, specifically Microsoft SQL Server and PostgreSQL, focusing on data insertion, queries execution, and indexation. To simulate how Microsoft SQL Server performs with key-value oriented datasets we use a converted TPC-H lineitem table. The data set is explored in two different ways, firsts using the key-value-like format and ...