Zobrazeno 1 - 10
of 348
pro vyhledávání: '"Cajueiro, Daniel"'
Even though practitioners often estimate Pareto exponents running OLS rank-size regressions, the usual recommendation is to use the Hill MLE with a small-sample correction instead, due to its unbiasedness and efficiency. In this paper, we advocate th
Externí odkaz:
http://arxiv.org/abs/2409.10448
Zipf's law states that the probability of a variable being larger than $s$ is roughly inversely proportional to $s$. In this paper, we evaluate Zipf's law for the distribution of firm size by the number of employees in Brazil. We use publicly availab
Externí odkaz:
http://arxiv.org/abs/2409.09470
In this study, we delve into the dynamic landscape of machine learning research evolution. Initially, through the utilization of Latent Dirichlet Allocation, we discern pivotal themes and fundamental concepts that have emerged within the realm of mac
Externí odkaz:
http://arxiv.org/abs/2311.03633
Publikováno v:
Chaos, Solitons & Fractals Volume 176, November 2023, 114125
In this work, we study an epidemic model with vaccination coupled with opinion dynamics in a dynamic network. The network structure evolves as agents with differing opinions disconnect from one another and connect with agents that share similar opini
Externí odkaz:
http://arxiv.org/abs/2305.02488
We present an overview of the complex systems field using ChatGPT as a representation of the community's understanding. ChatGPT has learned language patterns and styles from a large dataset of internet texts, allowing it to provide answers that refle
Externí odkaz:
http://arxiv.org/abs/2303.16870
Autor:
Cajueiro, Daniel O., Nery, Arthur G., Tavares, Igor, De Melo, Maísa K., Reis, Silvia A. dos, Weigang, Li, Celestino, Victor R. R.
We provide a literature review about Automatic Text Summarization (ATS) systems. We consider a citation-based approach. We start with some popular and well-known papers that we have in hand about each topic we want to cover and we have tracked the "b
Externí odkaz:
http://arxiv.org/abs/2301.03403
Publikováno v:
Phys. A Stat. Mech. Its Appl. 2022, 607, 128199
In this work we consider the effects of memory and bias in kinetic exchange opinion models. We propose a model in which agents remember the sign of their last interaction with each one of their pairs. This introduces memory effects in the model, sinc
Externí odkaz:
http://arxiv.org/abs/2204.04295
Autor:
Morato, Marcelo Menezes, Bastos, Saulo Benchimol, Cajueiro, Daniel Oliveira, Normey-Rico, Julio Elias
The global COVID-19 pandemic (SARS-CoV-2 virus) is the defining health crisis of our century. Due to the absence of vaccines and drugs that can help to fight it, the world solution to control the spread has been to consider public social distance mea
Externí odkaz:
http://arxiv.org/abs/2005.10797
Autor:
Pires, Marcelo A., Crokidakis, Nuno, Cajueiro, Daniel O., de Menezes, Marcio Argollo, Queirós, Silvio M. Duarte
Publikováno v:
Int. J. Mod. Phys C 32, 2150107 (2021)
We study the potential scenarios from a Susceptible-Infected-Recovered-Asymptomatic-Symptomatic-Dead (SIRASD) model. As a novelty, we consider populations that differ in their degree of compliance with social distancing policies following socioeconom
Externí odkaz:
http://arxiv.org/abs/2005.09019
Autor:
Bastos, Saulo B., Cajueiro, Daniel O.
We model and forecast the early evolution of the COVID-19 pandemic in Brazil using Brazilian recent data from February 25, 2020 to March 30, 2020. This early period accounts for unawareness of the epidemiological characteristics of the disease in a n
Externí odkaz:
http://arxiv.org/abs/2003.14288