Abstract

Abstract
Breakthroughs in sequencing technologies led to an exponential growth of genomic data, providing novel biological insights and therapeutic applications. However, analyzing large amounts of sensitive data raises key data privacy concerns, specifically when the information is outsourced to untrusted third-party infrastructures for data storage and processing (e.g., cloud computing). We introduce Gyosa, a secure and privacy-preserving distributed genomic analysis solution. By leveraging trusted execution environments (TEEs), Gyosa allows users to confidentially delegate their GWAS analysis to untrusted infrastructures. Gyosa implements a computation partitioning scheme that reduces the computation done inside the TEEs while safeguarding the users' genomic data privacy. By integrating this security scheme in Glow, Gyosa provides a secure and distributed environment that facilitates diverse GWAS studies. The experimental evaluation validates the applicability and scalability of Gyosa, reinforcing its ability to provide enhanced security guarantees.

Abstract

Abstract

Abstract
In the context of mobile robotics education, realistic and accessible datasets are fundamental for supporting the development and testing of algorithms. However, collecting real-world data is a limited and challenging task because it is time-consuming and error-prone. Therefore, this paper presents the generation of a synthetic dataset through realistic simulation using the SimTwo environment-a physics-based simulator, and modeling techniques of sensors and actuators. The physical and simulated mobile robot was developed to perform tasks such as following a line, following a wall, and avoiding obstacles. The proposed approach facilitates the creation of customized datasets for training and evaluation algorithms while supporting remote and inclusive learning. Results show that a simulated dataset can effectively replicate real-world behaviors, making them a valuable resource for educational contexts, research, and development. Some emergent machine learning algorithms can be applied to this dataset, being this approach increasingly used to enhance robot localization, by leveraging ML, robots can improve the accuracy, robustness, and adaptability of their localization systems, especially in complex and dynamic environments.

Abstract
Regulations of next-generation networks (NGNs) have played a central role in the transition from copper networks to broadband networks in Fiber to The Home (FTTH), also allowing for a reduction in asymmetries between incumbent operators and their competitors. Despite common European Union directives, telecom infrastructure development varies across countries due to differences in regulation, investment models, legacy networks, operators' behavior, and public policies. This study analyzes the evolution of Very High-Capacity Networks (VHCNs), focusing on the implementation of FTTH in four European countries (Portugal, Spain, France, and Germany), and in South Korea. The latter was included as a benchmark in government-driven broadband development. The analysis considers key factors influencing FTTH development, including infrastructure regulation, fiber investment incentives, incumbent strategies, infrastructure sharing and co-investment, rural coverage plans, and demographic differences of each country. The results show that regulatory measures directly influence the pace of FTTH installation; but its effectiveness also depends on investment incentives, market competition, and demand factors. Portugal, Spain, and France have high FTTH coverage despite different regulatory and investment models. In contrast, Germany relied on xDSL over copper networks for a long time, causing significant delays, with an FTTH coverage rate of 42.5% and a penetration rate of only 12.3%, putting the European Union's 2030 goal of universal 1 Gbps coverage at risk. South Korea shows that long-term public policies, demand-side incentives, and high digital adoption accelerate mass FTTH adoption and turn telecommunications infrastructure into a key driver of economic and technological development.