arXiv subjects

Daniel O. Cajueiro

Publications and source records attributed to Daniel O. Cajueiro.

14 recordsLinked to original sources

arXiv2023

A comprehensive review of automatic text summarization techniques: method, data, evaluation and coding

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 "backward citations" (papers that are cited by the set of papers we knew beforehand) and the "forward citations" (newer papers that cite the set of papers we knew beforehand). In order to organize the different methods, we present the diverse approaches to ATS guided by the mechanisms they use to generate a summary. Besides presenting the methods, we also present an extensive review of the datasets available for summarization tasks and the methods used to evaluate the quality of the summaries. Finally, we present an empirical exploration of these methods using the CNN Corpus dataset that provides golden summaries for extractive and abstractive methods.

cs.CL↗

arXiv2023

Questions of science: chatting with ChatGPT about complex systems

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 reflect common opinions, ideas, and language patterns found in the community. Our exploration covers both teaching and learning, and research topics. We recognize the value of ChatGPT as a source for the community's ideas.

physics.soc-ph↗

arXiv2022

Impact of memory and bias in kinetic exchange opinion models on random networks

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, since past interactions can affect future ones. We have also considered the impact of a parameter $p$ that regulates how often an agent changes its interaction to match its opinion, thus introducing bias in the interactions. For high values of $p$ an agent is more likely to start having a negative interaction with an agent of opposing opinion and a positive interaction with an agent of the same opinion. The model is defined on the top of random networks with mean connectivity $\langle k \rangle$. We analyze the impact of both $p$ and $\langle k \rangle$ on the emergence of ordered and disordered states in the population. Our results suggest a rich phenomenology regarding critical phenomena, with the presence of metastable states and a non-monotonic behavior of the order parameter. We show that the fraction of neutral agents in the disordered state decreases as the bias $p$ increases.

physics.soc-ph↗

arXiv2021

What is the potential for a second peak in the evolution of SARS-CoV-2 in emerging and developing economies? Insights from a SIRASD model considering the informal economy

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 socioeconomic attributes that are observed in emerging and developing countries. Considering epidemiological parameters estimated from data of the propagation of SARS-CoV-2 in Brazil -- where there is a significant stake of the population making their living in the informal economy and thus prone to not follow self-isolation -- we assert that if the confinement measures are lifted too soon, namely as much as one week of consecutive declining numbers of new cases, it is very likely the appearance of a second peak. Our approach should be valid for any country where the number of people involved in the informal economy is a large proportion of the total labor force. In summary, our results point out the crucial relevance of target policies for supporting people in the informal economy to properly comply with preventive measures during the pandemic.

q-bio.PE↗

arXiv2020

Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil

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 new territory, sub-notification of the real numbers of infected people and the timely introduction of social distancing policies to flatten the spread of the disease. We use two variations of the SIR model and we include a parameter that comprises the effects of social distancing measures. Short and long term forecasts show that the social distancing policy imposed by the government is able to flatten the pattern of infection of the COVID-19. However, our results also show that if this policy does not last enough time, it is only able to shift the peak of infection into the future keeping the value of the peak in almost the same value. Furthermore, our long term simulations forecast the optimal date to end the policy. Finally, we show that the proportion of asymptomatic individuals affects the amplitude of the peak of symptomatic infected, suggesting that it is important to test the population.

q-bio.PE↗

arXiv2017

Pendular behavior of public transport networks

In this paper, we propose a methodology that bears close resemblance to the Fourier analysis of the first harmonic to study networks subjected to pendular behavior. In this context, pendular behavior is characterized by the phenomenon of people's dislocation from their homes to work in the morning and people's dislocation in the opposite direction in the afternoon. Pendular behavior is a relevant phenomenon that takes place in public transport networks because it may reduce the overall efficiency of the system as a result of the asymmetric utilization of the system in different directions. We apply this methodology to the bus transport system of Brasilia, which is a city that has commercial and residential activities in distinct boroughs. We show that this methodology can be used to characterize the pendular behavior of this system, identifying the most critical nodes and times of the day when this system is in more severe demanded.

physics.soc-ph↗

arXiv2013

A dynamical programming approach for controlling the directed abelian Dhar-Ramaswamy model

A dynamical programming approach is used to deal with the problem of controlling the directed abelian Dhar-Ramaswamy model on two-dimensional square lattice. Two strategies are considered to obtain explicit results to this task. First, the optimal solution of the problem is characterized by the solution of the Bellman equation obtained by numerical algorithms. Second, the solution is used as a benchmark to value how far from the optimum other heuristics that can be applied to larger systems are. This approach is the first attempt on the direction of schemes for controlling self-organized criticality that are based on optimization principles that consider explicitly a tradeoff between the size of the avalanches and the cost of intervention.

physics.comp-ph↗

arXiv2013

Controlling self-organized criticality in sandpile models

We introduce an external control to reduce the size of avalanches in some sandpile models exhibiting self organized criticality. This rather intuitive approach seems to be missing in the vast literature on such systems. The control action, which amounts to triggering avalanches in sites that are near to be come critical, reduces the probability of very large events, so that energy dissipation occurs most locally. The control is applied to a directed Abelian sandpile model driven by both uncorrelated and correlated deposition. The latter is essential to design an efficient and simple control heuristic, but has only small influence in the uncontrolled avalanche probability distribution. The proposed control seeks a tradeoff between control cost and large event risk. Preliminary results hint that the proposed control works also for an undirected sandpile model.

physics.comp-ph↗

arXiv2013

Controlling self-organized criticality in complex networks

A control scheme to reduce the size of avalanches of the Bak-Tang-Wiesenfeld model on complex networks is proposed. Three network types are considered: those proposed by Erdős-Renyi, Goh-Kahng-Kim, and a real network representing the main connections of the electrical power grid of the western United States. The control scheme is based on the idea of triggering avalanches in the highest degree nodes that are near to become critical. We show that this strategy works in the sense that the dissipation of mass occurs most locally avoiding larger avalanches. We also compare this strategy with a random strategy where the nodes are chosen randomly. Although the random control has some ability to reduce the probability of large avalanches, its performance is much worse than the one based on the choice of the highest degree nodes. Finally, we argue that the ability of the proposed control scheme is related to its ability to reduce the concentration of mass on the network.

physics.soc-ph↗

arXiv2008

The role of optimization in the human dynamics of tasks execution

In order to explain the empirical evidence that the dynamics of human activity may not be well modeled by Poisson processes, a model based on queuing processes were built in the literature \cite{bar05}. The main assumption behind that model is that people execute their tasks based on a protocol that execute firstly the high priority item. In this context, the purpose of this letter is to analyze the validity of that hypothesis assuming that people are rational agents that make their decisions in order minimize the cost of keeping non-executed tasks on the list. Therefore, we build and solve analytically a dynamic programming model with two priority types of tasks and show that the validity of this hypothesis depends strongly on the structure of the instantaneous costs that a person has to face if a given task is kept on the list for more than one step. Moreover, one interesting finding is that in one of the situations the protocol used to execute the tasks generates complex one dimensional dynamics.

physics.soc-ph↗

arXiv2007

Mapping dynamical systems onto complex networks

A procedure to characterize chaotic dynamical systems with concepts of complex networks is pursued, in which a dynamical system is mapped onto a network. The nodes represent the regions of space visited by the system, while edges represent the transitions between these regions. Parameters used to quantify the properties of complex networks, including those related to higher order neighborhoods, are used in the analysis. The methodology is tested for the logistic map, focusing the onset of chaos and chaotic regimes. It is found that the corresponding networks show distinct features, which are associated to the particular type of dynamics that have generated them.

cond-mat.stat-mech↗

arXiv2006

Long-range dependence in Interest Rates and Monetary Policy

This paper studies the dynamics of Brazilian interest rates for short-term maturities. The paper employs developed techniques in the econophysics literature and tests for long-range dependence in the term structure of these interest rates for the last decade. Empirical results suggest that the degree of long-range dependence has changed over time due to changes in monetary policy, specially in the short-end of the term structure of interest rates. Therefore, we show that it is possible to identify monetary arrangements using these techniques from econophysics.

physics.data-an↗

arXiv2006

Econophysics of interest rates and the role of monetary policy

This paper presents empirical evidence using recently developed techniques in econophysics suggesting that the degree of long-range dependence in interest rates depends on the conduct of monetary policy. We study the term structure of interest rates for the US and find evidence that global Hurst exponents change dramatically according to Chairman Tenure in the Federal Reserve Board and also with changes in the conduct of monetary policy. In the period from 1960's until the monetarist experiment in the beginning of the 1980's interest rates had a significant long-range dependence behavior. However, in the recent period, in the second part of the Volcker tenure and in the Greenspan tenure, interest rates do not present long-range dependence behavior. These empirical findings cast some light on the origins of long-range dependence behavior in financial assets.

physics.data-an↗

arXiv2005

The agents' preferences and the topology of networks

In this paper, a new framework to study weighed networks is introduced. The idea behind this methodology is to consider that each node of the network is an agent that desires to satisfy his/her preferences in an economic sense. Moreover, the formation of a link between two agents depends on the benefits and costs associated to this link. Therefore, an edge between two given nodes will only arise if the tradeoff between satisfaction and cost for building it is jointly positive. Using a computational framework, I intend to show that depending on the agents combination of benefits and costs, some very well known networks can naturally arise.

physics.soc-ph↗