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Papers by Alcides Esquivel

Research paper thumbnail of Memory in network flows and its effects on community detection, ranking, and spreading

Research paper thumbnail of Técnica de visualización científica para datos escalares discretos

Metodos Numericos Para Calculo Y Diseno En Ingenieria Revista Internacional, 2010

Research paper thumbnail of Utilización de árboles de cubrimiento para interpolar usando funciones de base radial enfocando a la visualización científica de grandes volúmenes de datos

Metodos Numericos Para Calculo Y Diseno En Ingenieria Revista Internacional, 2009

Research paper thumbnail of Robustness of journal rankings by network flows with different amounts of memory

As the number of scientific journals has multiplied, journal rankings have become increasingly im... more As the number of scientific journals has multiplied, journal rankings have become increasingly important for scientific decisions. From submissions and subscriptions to grants and hirings, researchers, policy makers, and funding agencies make important decisions with influence from journal rankings such as the ISI journal impact factor. Typically, the rankings are derived from the citation network between a selection of journals and unavoidably depend on this selection. However, little is known about how robust rankings are to the selection of included journals. Here we compare the robustness of three journal rankings based on network flows induced on citation networks. They model pathways of researchers navigating scholarly literature, stepping between journals and remembering their previous steps to different degree: zero-step memory as impact factor, one-step memory as Eigenfactor, and two-step memory, corresponding to zero-, first-, and second-order Markov models of citation flow between journals. We conclude that higher-order Markov models perform better and are more robust to the selection of journals. Whereas our analysis indicates that higher-order models perform better, the performance gain for the second-order Markov model comes at the cost of requiring more citation data over a longer time period.

Research paper thumbnail of Técnicas de Visualización Científica para el estudio de discontinuidades en los resultados provenientes de la aplicación de Métodos Libres de Malla y Partículas

Research paper thumbnail of El método de los segmentos

Metodos Numericos Para Calculo Y Diseno En Ingenieria Revista Internacional, 2008

Research paper thumbnail of Networks with Memory

Research paper thumbnail of The genetic network of plasmid-mediated antibiotic multiresistance

Research paper thumbnail of A Survey of Routing Attacks and Security Measures in Mobile Ad-Hoc Networks

Corr, May 27, 2011

Mobile ad hoc networks (MANETs) are a set of mobile nodes which are self-configuring and connecte... more Mobile ad hoc networks (MANETs) are a set of mobile nodes which are self-configuring and connected by wireless links automatically as per the defined routing protocol. The absence of a central management agency or a fixed infrastructure is a key feature of MANETs. These nodes communicate with each other by interchange of packets, which for those nodes not in wireless range goes hop by hop. Due to lack of a defined central authority, securitizing the routing process becomes a challenging task thereby leaving MANETs vulnerable to attacks, which results in deterioration in the performance characteristics as well as raises a serious question mark about the reliability of such networks. In this paper we have attempted to present an overview of the routing protocols, the known routing attacks and the proposed countermeasures to these attacks in various works.

Research paper thumbnail of Robustness of journal rankings by network flows with different amounts of memory

Journal of the Association for Information Science and Technology, 2015

Research paper thumbnail of Comparing network covers using mutual information

In network science, researchers often use mutual information to understand the difference between... more In network science, researchers often use mutual information to understand the difference between network partitions produced by community detection methods. Here we extend the use of mutual information to covers, that is, the cases where a node can belong to more than one module. In our proposed solution, the underlying stochastic process used to compare partitions is extended to deal with covers, and the random variables of the new process are simply fed into the usual definition of mutual information. With partitions, our extended process behaves exactly as the conventional approach for partitions, and thus, the mutual information values obtained are the same. We also describe how to perform sampling and do error estimation for our extended process, as both are necessary steps for a practical application of this measure. The stochastic process that we define here is not only applicable to networks, but can also be used to compare more general set-to-set binary relations.

Research paper thumbnail of Compression of flow can reveal overlapping modular organization in networks

Computing Research Repository, 2011

To better understand the overlapping modular organization of large networks with respect to flow,... more To better understand the overlapping modular organization of large networks with respect to flow, here we introduce the map equation for overlapping modules. In this information-theoretic framework, we use the correspondence between compression and regularity detection. The generalized map equation measures how well we can compress a description of flow in the network when we partition it into modules with

Research paper thumbnail of Networks with memory

Research paper thumbnail of Memory in network flows and its effects on spreading dynamics and community detection

Nature Communications, 2014

Research paper thumbnail of Compression of Flow Can Reveal Overlapping-Module Organization in Networks

Research paper thumbnail of Dynamics of interacting information waves in networks

Research paper thumbnail of Nuevos Métodos de interpolación de grandes volúmenes de datos provenientes de la aplicación de los métodos de partículas o puntos (libres de malla) para su visualización científica

Research paper thumbnail of Memory in network flows and its effects on community detection, ranking, and spreading

Research paper thumbnail of Técnica de visualización científica para datos escalares discretos

Metodos Numericos Para Calculo Y Diseno En Ingenieria Revista Internacional, 2010

Research paper thumbnail of Utilización de árboles de cubrimiento para interpolar usando funciones de base radial enfocando a la visualización científica de grandes volúmenes de datos

Metodos Numericos Para Calculo Y Diseno En Ingenieria Revista Internacional, 2009

Research paper thumbnail of Robustness of journal rankings by network flows with different amounts of memory

As the number of scientific journals has multiplied, journal rankings have become increasingly im... more As the number of scientific journals has multiplied, journal rankings have become increasingly important for scientific decisions. From submissions and subscriptions to grants and hirings, researchers, policy makers, and funding agencies make important decisions with influence from journal rankings such as the ISI journal impact factor. Typically, the rankings are derived from the citation network between a selection of journals and unavoidably depend on this selection. However, little is known about how robust rankings are to the selection of included journals. Here we compare the robustness of three journal rankings based on network flows induced on citation networks. They model pathways of researchers navigating scholarly literature, stepping between journals and remembering their previous steps to different degree: zero-step memory as impact factor, one-step memory as Eigenfactor, and two-step memory, corresponding to zero-, first-, and second-order Markov models of citation flow between journals. We conclude that higher-order Markov models perform better and are more robust to the selection of journals. Whereas our analysis indicates that higher-order models perform better, the performance gain for the second-order Markov model comes at the cost of requiring more citation data over a longer time period.

Research paper thumbnail of Técnicas de Visualización Científica para el estudio de discontinuidades en los resultados provenientes de la aplicación de Métodos Libres de Malla y Partículas

Research paper thumbnail of El método de los segmentos

Metodos Numericos Para Calculo Y Diseno En Ingenieria Revista Internacional, 2008

Research paper thumbnail of Networks with Memory

Research paper thumbnail of The genetic network of plasmid-mediated antibiotic multiresistance

Research paper thumbnail of A Survey of Routing Attacks and Security Measures in Mobile Ad-Hoc Networks

Corr, May 27, 2011

Mobile ad hoc networks (MANETs) are a set of mobile nodes which are self-configuring and connecte... more Mobile ad hoc networks (MANETs) are a set of mobile nodes which are self-configuring and connected by wireless links automatically as per the defined routing protocol. The absence of a central management agency or a fixed infrastructure is a key feature of MANETs. These nodes communicate with each other by interchange of packets, which for those nodes not in wireless range goes hop by hop. Due to lack of a defined central authority, securitizing the routing process becomes a challenging task thereby leaving MANETs vulnerable to attacks, which results in deterioration in the performance characteristics as well as raises a serious question mark about the reliability of such networks. In this paper we have attempted to present an overview of the routing protocols, the known routing attacks and the proposed countermeasures to these attacks in various works.

Research paper thumbnail of Robustness of journal rankings by network flows with different amounts of memory

Journal of the Association for Information Science and Technology, 2015

Research paper thumbnail of Comparing network covers using mutual information

In network science, researchers often use mutual information to understand the difference between... more In network science, researchers often use mutual information to understand the difference between network partitions produced by community detection methods. Here we extend the use of mutual information to covers, that is, the cases where a node can belong to more than one module. In our proposed solution, the underlying stochastic process used to compare partitions is extended to deal with covers, and the random variables of the new process are simply fed into the usual definition of mutual information. With partitions, our extended process behaves exactly as the conventional approach for partitions, and thus, the mutual information values obtained are the same. We also describe how to perform sampling and do error estimation for our extended process, as both are necessary steps for a practical application of this measure. The stochastic process that we define here is not only applicable to networks, but can also be used to compare more general set-to-set binary relations.

Research paper thumbnail of Compression of flow can reveal overlapping modular organization in networks

Computing Research Repository, 2011

To better understand the overlapping modular organization of large networks with respect to flow,... more To better understand the overlapping modular organization of large networks with respect to flow, here we introduce the map equation for overlapping modules. In this information-theoretic framework, we use the correspondence between compression and regularity detection. The generalized map equation measures how well we can compress a description of flow in the network when we partition it into modules with

Research paper thumbnail of Networks with memory

Research paper thumbnail of Memory in network flows and its effects on spreading dynamics and community detection

Nature Communications, 2014

Research paper thumbnail of Compression of Flow Can Reveal Overlapping-Module Organization in Networks

Research paper thumbnail of Dynamics of interacting information waves in networks

Research paper thumbnail of Nuevos Métodos de interpolación de grandes volúmenes de datos provenientes de la aplicación de los métodos de partículas o puntos (libres de malla) para su visualización científica