Diego Pinheiro

Network analysis of cultural funding in Brazil: uncovering regional differences and signatures

Diogo Pacheco, Gustavo Moraes, Diego Pinheiro, Josemar Faustino et autres

Abstract This study investigates how cultural funding patterns reflect regional inequalities through network analysis techniques. Public funding of cultural projects should preserve diversity but can intensify socioeconomic inequalities; hence, countries can benefit from macro analyses of funding data. We present a network-based …

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The Brazilian Rouanet Law - sponsorship transactions from 2010 to 2014

Diogo Pacheco, Josemar Faustino, Diego Pinheiro, Marcos Oliveira et autres

This dataset contains structured information on cultural projects funded under Brazil’s National Program for Cultural Support (Programa Nacional de Apoio à Cultura, commonly known as Lei Rouanet). The data were originally obtained from publicly available government sources under Brazil’s Information Access Law …

gb, br, nl (code pays fourni par la source)

The Brazilian Rouanet Law - sponsorship transactions from 2010 to 2014

Diogo Pacheco, Josemar Faustino, Diego Pinheiro, Marcos Oliveira et autres

This dataset contains structured information on cultural projects funded under Brazil’s National Program for Cultural Support (Programa Nacional de Apoio à Cultura, commonly known as Lei Rouanet). The data were originally obtained from publicly available government sources under Brazil’s Information Access Law …

gb, br, nl (code pays fourni par la source)

Larger cities, more commuters, more crime? The role of inter-city commuting in the scaling of urban crime

Simon Puttock, Umberto Barros, Diego Pinheiro, Marcos Oliveira

Abstract Cities attract a daily influx of non-resident commuters, reflecting their roles within wider urban networks—not as isolated places. However, it remains unclear how this interconnectivity shapes the way crime scales with population, given that larger cities tend to receive more commuters …

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Hybrid Routing and Spectrum Allocation in Elastic Optical Networks by Machine Learning and Topological Metrics

Renan V. B. Carvalho, Diego Pinheiro, Henrique A. Dinarte, Raul C. Almeida et autres

To meet the increasing demands for data, elastic optical networks (EONs) require highly efficient resource management. While classical Routing and Spectrum Assignment (RSA) algorithms establish a path and allocate spectrum, advanced versions such as Routing, Modulation-format-selection, and Spectrum Assignment (RMSA) also optimize …

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A Methodology to Comprehend the Features Importance in Hybrid RSA Using ML

Renan V. B. Carvalho, Diego Pinheiro, Henrique A. Dinarte, Raul C. Almeida et autres

The hybrid routing and spectrum assignment (HRSA) algorithm for the RSA problem in elastic optical networks (EONs) outperforms the classical RSA algorithms. However, the decision-making process remains largely unexplained. Here, we propose a methodology to study how topological features steer HRSA's adaptive …

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Towards screening of children students with autism spectrum disorder based on executive functions with serious game and machine learning approaches

Sara Raquel Araujo Leal, Franciely Alves de Souza, Lucas Candeia Teixeira, Diego Pinheiro et autres

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Prediction of Gold Standard Gait Data from Inertial Data: A Machine Learning Approach

William da Rosa Fröhlich, Diego Pinheiro, Sandro José Rigo, Rafael Reimann Baptista et autres

Biomechanics laboratories typically use kinematic cameras and force platforms as the gold standard for gait assessment. However, these systems are expensive and have limited availability. Wearable devices, equipped with sensors—primarily inertial sensors—can capture movement data, enabling the inference of human gait behavior. …

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Larger cities, more commuters, more crime? The role of inter-city commuting in the scaling of urban crime

Simon Puttock, Umberto Barros, Diego Pinheiro, Marcos Oliveira

Cities attract a daily influx of non-resident commuters, reflecting their roles within wider urban networks -- not as isolated places. However, it remains unclear how this interconnectivity shapes the way crime scales with population, given that larger cities tend to receive more …

A Unified Framework for Replicability of Anomaly Detection in Multiple Time Series: Enhancing GANF and RanSynCoders Pipelines with MFCC Feature Extraction for Acoustic Data

Cristofer Silva, Matheus Coelho, Umberto Barros, Andrea Maria N C Ribeiro et autres

Anomaly detection, a ubiquitous pattern recognition methodology for identifying atypical data, has been applied across a myriad of domains. In the industry, it has been used to identify malfunctions in industrial machinery in advance and suggest predictive maintenance based on multiple time …

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Towards the Identification of Money Laundering in Bank Transactions using Recurrent Neural Networks

Edvaldo Veiga, Andrea Maria N C Ribeiro, Rodrigo de Paula Monteiro, Marcos Oliveira et autres

Money laundering has a significant impact on both society and the economy, costing up to 2 trillion dollars of the global gross domestic product. Detecting money laundering involves analyzing banking data to identify its occurrence and its typologies, such as the typology …

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Exploring the Impact of Topological Features on Ordering Routing and Spectrum Assignment in Elastic Optical Networks

Renan V. B. Carvalho, Diego Pinheiro, Henrique A. Dinarte, Raul C. Almeida et autres

We explore the influence of topological features on a hybrid routing and spectrum assignment (HRSA) algorithm in elastic optical networks that prioritizes either routing or spectrum assignment for network source-destination node pairs. We use logistic regression to extract information about how the …

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