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- An Empirical Comparison of Portuguese and Multilingual BERT Models for Auto-Classification of NCM Codes in International TradePublication . Lima, Ligia; Fernandes, Anita; James Roberto Bombasar; Da Silva, Bruno Alves; Crocker, Paul; LEITHARDT, VALDERI
- PADRES: Tool for PrivAcy, Data REgulation and SecurityPublication . Pereira, Fábio; Crocker, Paul; LEITHARDT, VALDERI
- Nero: A Deterministic Leaderless Consensus Algorithm for DAG-Based CryptocurrenciesPublication . Morais, Rui; Crocker, Paul; LEITHARDT, VALDERIThis paper presents the research undertaken with the goal of designing a consensus algorithm for cryptocurrencies with less latency than the current state-of-the-art while maintaining a level of throughput and scalability sufficient for real-world payments. The result is Nero, a new deterministic leaderless byzantine consensus algorithm in the partially synchronous model that is especially suited for Directed Acyclic Graph (DAG)-based cryptocurrencies. In fact, Nero has a communication complexity of O(n3) and terminates in two message delays in the good case (when there is synchrony). The algorithm is shown to be correct, and we also show that it can provide eventual order. Finally, some performance results are given based on a proof of concept implementation in the Rust language.
- ID-Care: a Model for Sharing Wide Healthcare DataPublication . Humberto Jorge De Moura Costa; Cristiano Andre Da Costa; Antunes, Rodolfo S.; Righi, Rodrigo; Crocker, Paul; LEITHARDT, VALDERIAll over the world, there is a lot of patient health data in different locations such as hospitals, clinics, insurance companies, and other organizations. In this sense, global identification of the patient has emerged as an everyday healthcare challenge. Governments and institutions have to prioritize satisfactory, quick, and integrated decision-making in a wide, dispersed, and global environment because of unexpected challenges like pandemics or threats. In the current scientific literature, some of the existing challenges include support for a standard global unique identification that considers privacy issues, the combination of multiple technological biometry implementations, and personal documents. Thus, we propose a decentralized software model based on blockchain and smart contracts that includes privacy, global unique person identification supporting multiple combinations of documents, and biometric data using the Global Standards 1 - GS1 healthcare industry standard. Furthermore, we defined a methodology to evaluate a hypothetical use case of this model where an integrated and standard global health data sharing personal identification is crucial. For this, we implemented the proposed model in a global-wide continent location through cloud machines, fog computing, and blockchain considering the unique patient data identification and evaluate a use case scenario based on the top 5 most globally visited tourist destinations (France, Spain, the United States of America, China, and Italy), with an approach based on this model. The results show that using a model for a global id for healthcare can help reduce costs, time, and efforts, especially in the context of health threats, where agility and financial support must be prioritized.