Marcos OliveiraUniversity of Exeter | UoE · Department of Computer Science
Marcos Oliveira
Doctor of Philosophy
About
56
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399
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Introduction
Additional affiliations
May 2020 - present
January 2018 - July 2021
July 2017 - December 2017
Education
August 2013 - December 2017
June 2011 - May 2013
July 2006 - June 2011
Publications
Publications (56)
Crime is a major threat to society’s well-being but lacks a statistical characterization that could lead to uncovering some of its underlying mechanisms. Evidence of nonlinear scaling of urban indicators in cities, such as wages and serious crime, has motivated the understanding of cities as complex systems—a perspective that offers insights into r...
Abstract In the last decades, the notion that cities are in a state of equilibrium with a centralised organisation has given place to the viewpoint of cities in disequilibrium and organised from bottom to up. In this perspective, cities are evolving systems that exhibit emergent phenomena built from local decisions. While urban evolution promotes t...
Swarm intelligence is the collective behavior emerging in systems with locally interacting components. Because of their self-organization capabilities, swarm-based systems show essential properties for handling real-world problems, such as robustness, scalability, and flexibility. Yet, we fail to understand why swarm-based algorithms work well, and...
Crime rates per capita are used virtually everywhere to rank and compare cities. However, their usage relies on a strong linear assumption that crime increases at the same pace as the number of people in a region. In this paper, we demonstrate that using per capita rates to rank cities can produce substantially different rankings from rankings adju...
Uncovering how inequality emerges from human interaction is imperative for just societies. Here we show that the way social groups interact in face-to-face situations can enable the emergence of disparities in the visibility of social groups. These disparities translate into members of specific social groups having fewer social ties than the averag...
Human travelling behaviours are markedly regular, to a large extent predictable, and mostly driven by biological necessities and social constructs. Not surprisingly, such predictability is influenced by an array of factors ranging in scale from individual preferences and choices, through social groups and households, all the way to the global scale...
How easy is it to uniquely identify a person based on their web browsing behavior? Here we show that when people navigate the Web, their online traces produce fingerprints that identify them. By merely knowing their most visited web domains, four data points are enough to identify 95% of the individuals. These digital fingerprints are stable and re...
Nominal assortativity (or discrete assortativity) is widely used to characterize group mixing patterns and homophily in networks, enabling researchers to analyze how groups interact with one another. Here we demonstrate that the measure presents severe shortcomings when applied to networks with unequal group sizes and asymmetric mixing. We characte...
Human travelling behaviours are markedly regular, to a large extent, predictable, and mostly driven by biological necessities (e.g. sleeping, eating) and social constructs (e.g. school schedules, synchronisation of labour). Not surprisingly, such predictability is influenced by an array of factors ranging in scale from individual (e.g. preference,...
We present a unique collection of four data sets to study social behaviour, collected during international scientific conferences. Interactions between participants were tracked using the SocioPatterns platform, which allows collecting face-to-face physical proximity events every 20 seconds. Through accompanying surveys, we gathered extensive infor...
Football club managers have a challenging and remarkably volatile job—the practice of sacking and replacing managers is widespread in the modern game. However, it is still unclear what exactly motivates managerial dismissal in clubs. More than ever, high-quality statistics are available to clubs, suggesting that dismissal decisions tend to be well...
Nominal assortativity (or discrete assortativity) is widely used to characterize group mixing patterns in networks, enabling researchers to analyze how groups interact with one another. Here we demonstrate that the measure presents severe shortcomings when applied to networks with unequal group sizes and asymmetric mixing. We characterize these sho...
In this chapter, we provide an overview of recent advances in data-driven and theory-informed complex models of social networks and their potential in understanding societal inequalities and marginalization. We focus on inequalities arising from networks and network-based algorithms and how they affect minorities. In particular, we examine how homo...
In this paper, we present a unique collection of four data sets to study social behaviour. The data were collected at four international scientific conferences, during which we measured face-to-face contacts along with additional information about individuals. Building on innovative methods developed in the last decade to study human social behavio...
Memetic algorithms are known for their enhanced solution refinement capabilities. These capabilities are a result of incorporating local-search methods into population-based metaheuristics such as swarm and evolutionary algorithms. However, designing a memetic algorithm is not a trivial task. The inclusion of local-search procedures must consider t...
Spatio-temporal constraints coupled with social constructs have the potential to create fluid predictability to human mobility patterns. Accordingly, predictability in human mobility is non-monotonic and varies according to this spatio-socio-temporal context. Here, we propose that the predictability in human mobility is a {\em state} and not a stat...
Uncovering how inequality emerges from human interaction is imperative for just societies. Here we show that the way social groups interact in face-to-face situations can enable the emergence of degree inequality. We present a mechanism that integrates group mixing dynamics with individual preferences, which reproduces group degree inequality found...
Understanding human activities and movements on the Web is not only important for computational social scientists but can also offer valuable guidance for the design of online systems for recommendations, caching, advertising, and personalization. In this work, we demonstrate that people tend to follow routines on the Web, and these repetitive patt...
This book contains contributions presented at the 12th International Conference on Complex Networks (CompleNet), 24-26 May 2021. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better...
Understanding human activities and movements on the Web is not only important for computational social scientists but can also offer valuable guidance for the design of online systems for recommendations, caching, advertising, and personalization. In this work, we demonstrate that people tend to follow routines on the Web, and these repetitive patt...
Crime rates per capita are used virtually everywhere to rank and compare cities. However, they rely on a strong linear assumption that crime increases at the same pace as the number of people in a region. Here we show that using per capita rates to rank cities can produce substantially different rankings from rankings adjusted for population size....
This book aims to bring together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems. This volume contains contributions presented at the 11th International Conference on Complex Networks (CompleNet) in...
Ant Colony Optimization (ACO) is a swarm-based algorithm inspired by the foraging behavior of ants. Despite its success, the efficiency of ACO has depended on the appropriate choice of parameters, requiring deep knowledge of the algorithm. A true understanding of ACO is linked to the (social) interactions between the agents given that it is through...
Computational swarm intelligence consists of multiple artificial simple agents exchanging information while exploring a search space. Despite a rich literature in the field, with works improving old approaches and proposing new ones, the mechanism by which complex behavior emerges in these systems is still not well understood. This literature gap h...
Though crime is linked to different socio-economic factors, it exhibits remarkable regularities regardless of cities' particularities. In this chapter, we consider two fundamental regularities in crime regarding two essential aspects of criminal activity: time and space. For more than one century, we know that (1) crime occurs unevenly within a cit...
Self-organization is a natural phenomenon that emerges in systems with a large number of interacting components. Self-organized systems show robustness, scalability, and flexibility, which are essential properties when handling real-world problems. Swarm intelligence seeks to design nature-inspired algorithms with a high degree of self-organization...
In the last decades, the notion that cities are in a state of equilibrium with a centralised organisation has given place to the viewpoint of cities in disequilibrium and organised from bottom to up. In this perspective, cities are evolving systems that exhibit emergent phenomena built from local decisions. While urban evolution promotes the emerge...
Modularity plays an important role in brain networks' architecture and influences its dynamics and the ability to integrate and segregate different modules of cerebral regions. Alterations in community structure are associated with several clinical disorders, specially schizophrenia, although its time evolution is not clear yet. In the present work...
Swarm-based models have successfully solved real-world problems in the past two decades and yet they continue to exhibit a major shortcoming of premature convergence. Previous research suggests that an appropriate exploitation-exploration balance can prevent premature convergence and different approaches have been proposed to control this balance....
Tipping is a social norm in many countries and widely recognized as an anomalous behavior, in that a tip is common enough to have become expected when dealing with tipped industries (e.g., restaurants, bars, taxi trips), while at the same time defying rational-agent assumptions of economics. Such intriguing consumer behavior has led to its wide stu...
Urban communities can benefit from behavior regulation of their members in the interest of collective values. The absence of such control is related to the concept of social dis-organization and is hypothesized to be associated with crime and antisocial behavior in neighborhoods. Social disorganization is, however, hard to quantify due to the lack...
This is the code for: Oliveira, Marcos, Carmelo JA Bastos-Filho, and Ronaldo Menezes. ”Towards a network-based approach to analyze particle swarm optimizers.” Swarm Intelligence (SIS), 2014 IEEE Symposium on. IEEE, 2014.
Since they were introduced, Particle Swarm Optimizers have suffered from early stagnation due to premature convergence. Assessing swarm spatial diversity might help to mitigate early stagnation but swarm spatial diversity itself emerges from the main property that essentially drives swarm optimizers towards convergence and distinctively distinguish...
Particle swarm optimizers (PSO) have been extensively used in optimization problems, but the scientific community still lacks proper mechanisms to analyze the swarm behavior during the optimization (execution) process. In this paper, we propose to assess the swarm information flow based on particle interactions. We introduce the concept of the swar...
We have never lived in a safer world. After peaking around 1985, both violent crime (homicide, robbery, assaut and rape) and property crimes (burglary, larceny and vehicle theft) are on a downward trend; from 1993 and 2012 crime activity has dropped by more than 40% (total number of crimes). Despite the good news, crime is still prevalent in most l...
In Particle Swarm Optimizers (PSO), the way particles communicate plays an important role on their search behavior influencing the trade-off between exploration and exploitation. The interactions boundaries defined by the swarm topology is an example of this influence. For instance, a swarm with the ring topology tends to explore the environment mo...
It is undoubtedly cliché to say that we are in the Age of Big Data Analytics or Data Science; every computing and IT publication you find talks about Big Data and companies no longer are interested in software engineers and analysts but instead they are looking for Data Scientists! In spite of the excessive use of the term, the truth of the matter...
Politics fascinate people---we all live in places with political structures governing many aspects of our daily lives. In several countries, people identify themselves not only with their country, but they tend to demonstrate some ``regionalism'' in their attitude. We have seen examples of regionalism in different parts of the world (e.g. Kurdistan...
Inteligência Computacional é um termo utilizado para representar um conjunto de técnicas inspiradas na natureza que apresentam habilidade de aprender e/ou lidar com novas situações.
Otimização por Enxame de Partículas (PSO) é uma técnica de otimização baseada em Inteligência de Enxames inspirada no comportamento social de bandos de pássaros na bus...
Particle Swarm Optimizers (PSOs) have been widely used for optimiza- tion problems, but the scientific community still does not have sophisticated mech- anisms to analyze the behavior of the swarm during the optimization process. We propose in this paper to use some metrics described in network sciences, specifi- cally the R-value, the number of ze...
Although some interesting routing algorithms based on HNN were already proposed, they are slower when compared to other routing algorithms. Since HNN are inherently parallel, they are suitable for parallel implementations on parallel platforms, such as Field Programmable Gate Arrays (FPGA) and Graphic Processing Units (GPU). In this chapter, the au...
We propose here to use network sciences, specifically an approach based on the Barabási-Albert model, to define a dynamic communication topology for Particle Swarm Optimizers. We compared our proposal to previous approaches, including a simpler Barabási-Albert-based approach and other most used approaches, and we obtained better results in average...
As Redes Neurais de Hopfield (HNN) são sistemas recorrentes que podem ser utilizados para resolver o problema de roteamento em redes de comunicação. Apesar de sua eficácia e capacidade de adaptação, as HNNs têm tempo de resposta mais alto quando comparadas aos algoritmos tradicionais, considerando que ambos são executados em plataformas sequênciais...
Although some interesting routing algorithms based on HNN were already proposed, they are slower when compared to other routing algorithms. Since HNN are inherently parallel, they are suitable for parallel implementations, such as Graphic Processing Units (GPU). In this paper we propose a fast routing algorithm based on Hopfield Neural Networks (HN...
The routing algorithms influence drastically on the computer networks perfomance.
Therefore, good routing algorithm must be created in order to optimize their resources
and thus fit to the network needs.
Computational Intelligence is a set of techniques with an ability to learn and to deal
with new situations. Among these techniques, Neural Network...
In this paper, we applied to use two multi-objective swarm optimization algorithms, called MOPSO-CDR and MOABC, to tackle the car setup optimization problem. We aim to find the best set of parameters for the car in order to improve its performance during the races. We used The Open Racing Car Simulator (TORCS) in our simulations and we compared our...
Particle swarm optimization (PSO) is a bioinspired technique widely used to solve real optimization problems. In the recent years, the use of Graphics Processing Units (GPU) has been proposed for some general purpose computing applications. Some PSO implementations on GPU were already proposed. The major benefit to implement the PSO for GPU is the...