Julio César Santos dos Anjos

A Extensão Universitária como Vetor de Desenvolvimento Regional e Inovação Educacional: o caso do Campus Jardins de Anita da UFC em Itapajé

Israel Eduardo de Barros Filho, Julio César Santos dos Anjos

Professores pouco qualificados, com baixa valorização, pais que participam pouco da educação dos filhos e falta de estrutura básica para aulas são problemas comuns no cenário educacional do país. Aliado ao baixo desempenho brasileiro em rankings e avaliações internacionais, com índices que …

Reconhecimento de Padrões: Uma Comparação Entre Máquinas de Vetores de Suporte e Máquinas de Vetores de Relevância

Jônatas Fernandes, Leandro Adegas, Giovanna Dias, Julio César Santos dos Anjos

Este trabalho trata da comparação entre os classificadores máquinas de vetores de suporte (support vector machines, SVM) e máquinas de vetores de relevância (relevance vector machines, RVM). Dois conjuntos de dados gerados a partir da biblioteca numpy, um definido previamente e outro …

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Multi-agent systems modeling of command and control systems: a metrics-driven approach to simulator evaluation and co-simulation

Leonardo Filipe Batista Silva de Carvalho, Vitor Simon de Souza, Alisson Nunes Bonatto, T. Perez et autres

This paper explores the use of Multi-Agent Systems (MAS) to model networked Command and Control (C2) systems to support the development of C2 military applications. The study focused on the modeling of systems capable of simulating and evaluating important characteristics of networked …

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EnBaSe: Enhancing Image Classification in IoT Scenarios through Entropy-Based Selection of Non-IID Data

Ernesto G. Valente Neto, Solon A. Peixoto, Julio César Santos dos Anjos

This study presents an analysis of the scalability and dispersion of results in Federated Learning (FL) using two algorithms: EnBaSe, based on entropy, and Random, a random selection approach. The Random algorithm ensures that each member of the population has an equal …

Adding Data Quality to Federated Learning Performance Improvement

Ernesto G. Valente Neto, Solon A. Peixoto, Valderi Reis Quietinho Leithardt, Juan F. De Paz et autres

Massive data generation from Internet of Things (IoT) devices increases the demand for efficient data analysis to extract meaningful insights. Federated Learning (FL) allows IoT devices to collaborate in AI training models while preserving data privacy. However, selecting high-quality data for training …

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A Platform for Early Class Dropout Prediction of University Students

Guilherme Antonio Borges, Julio César Santos dos Anjos, André Rodrigues, Fernando Boavida et autres

Higher education faces significant challenges, with student dropout rates remaining a critical issue. While much research has focused on course-level dropout, less attention has been given to the early identification of at-risk students within individual courses. In this context, this study reviews …

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Security Authentication on the Edge: A Step Further to Defense in Depth for Internet of Battle Things

Márcio Antônio Lawisch, Julio César Santos dos Anjos, Edison Pignaton de Freitas

Currently, the demand for the security of network assets in companies grows dramatically because of several factors, including the growth of the attack surface combined with the variety of connection standards and correlated to the emerging Internet of Things (IoT) related devices …

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Micro-Chain: A Cluster Architecture for Managing NDN Microservices

Otávio Augusto Rocha da Cruz, Antonio Silva, Paulo Mendes, Denis Lima do Rosário et autres

Network Functions Virtualization (NFV) and Information-Centric Networking (ICN) are promising networking paradigms for the future of the Internet. Concurrently, microservice architecture offers an attractive alternative to monolithic architecture for software development. This work addresses a scenario composed of these concepts, where an …

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Federated Learning for Sleep Detection Problems

Guilherme Antonio Borges, Julio César Santos dos Anjos, Jorge Sá Silva

Human-in-the-loop cyber-physical Systems use data from various sources to provide valuable assistance to users, but privacy concerns arise when sensitive information is shared. Federated Learning is a promising solution that enables the processing of user data without sharing sensitive information. While this …

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Data quantitative and qualitative study in Brazilian Open Data Portals

Shirlei L. O. Do Carmo, Cláudio F. R. Geyer, Julio César Santos dos Anjos

Open data is a concept attributed to sharing data with anyone, and in addition to being accessed, this data can be manipulated and redistributed. The optimized and interchangeable use of open data can lead to so-called open innovation, which can be understood …

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Hardware-Independent Embedded Firmware Architecture Framework

Mauricio D. O. Farina, Daniel Henrique Pohren, Alexandre dos Santos Roque, Antonio Silva et autres

Unlike other forms of development, the way firmware development is designed is somewhat outdated. It is not unusual to come across whole systems implemented in a cross-dependent monolithic way. In addition, the software of many implementations is hardware-dependent. Hence, significant hardware changes …

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Micro-Chain: Towards the use of NDN microservices

Otávio Augusto Rocha da Cruz, Carlos Eduardo Pereira, Edison Pignaton de Freitas, Paulo Mendes et autres

Network Functions Virtualization (NFVs) and Information-Centric Networking (ICN) are promising networking paradigms for the future of the Internet. In addition, microservice architecture offers an attractive alternative to monolithic architecture for developing applications. Employing ICN NFVs implemented as microservices enables the use of …

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