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Dive into the research topics where Fernando de Carvalho Gomes is active.

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Featured researches published by Fernando de Carvalho Gomes.


international workshop on discrete algorithms and methods for mobile computing and communications | 2001

Reactive GRASP with path relinking for channel assignment in mobile phone networks

Fernando de Carvalho Gomes; Panos M. Pardalos; Carlos A. S. Oliveira; Mauricio G. C. Resende

The Frequency Assignment Problem (FAP) arises in wireless networks when the number of available frequency channels is smaller than the number of users. FAP is NP-hard and plays an important role in the network planning. Usually, the number of available channels is much smaller than the number of users accessing the wireless network. In this case, the reuse of frequency channels is mandatory. Consequently, this may cause interference. Nowadays, cellular phone operators use various techniques designed to cope with channel shortage and, as a consequence, to avoid interference. For instance, frequency division by time or code, and local frequency clustering models have been used. These techniques are bounded by the number of users, i.e. as the number of users increases, they tend to become obsolete. In this work, we propose to minimize the total interference of the system, using a metaheuristic based on GRASP (Greedy Randomized Adaptive Search Procedure). A reactive heuristic has been used in order to automatically balance GRASP parameters. Furthermore, Path Relinking, which consists of an intensification strategy, has been applied. We report experimental results given by our proposed approach.


Computers & Operations Research | 2008

A parallel multistart algorithm for the closest string problem

Fernando de Carvalho Gomes; Cláudio Nogueira de Meneses; Panos M. Pardalos; Gerardo Valdisio R. Viana

In this paper we describe and implement a parallel algorithm to find approximate solutions for the Closest String Problem (CSP). The CSP, also known as Motif Finding problem, has applications in Coding Theory and Computational Biology. The CSP is NP-hard which motivates us to think about heuristics to solve large instances. Several approximation algorithms have been designed for the CSP, but all of them have a poor performance guarantee. Recently some researchers have shown empirically that integer programming techniques can be successfully used to solve moderate-size instances (10-30 strings each of which is 300-800 characters long) of the CSP. However, real-world instances are larger than those tested. In this paper we show how a simple heuristic can be used to find near-optimal solutions to that problem. We implemented a parallel version of this heuristic and report computational experiments on large-scale instances. These results show the effectiveness of our approach.


WCITD/NF | 2010

Infrastructure and Business Model for Universal Broadband Access in Developing Regions: The Ceara State Digital Belt

Cid F. Gomes; Fernando de Carvalho Gomes; Marcial P. Fernandez

With regard to digital services access, many rural and remote urban area in developing countries are underserved, if served at all. In a monopolized environment, telecommunications are of low quality and costly. Broadband Internet and other digital services are restricted to small percentage of people. In some cases the operator prefers to pay fines instead of providing services to remote areas. In this paper we present an infrastructure together with its business model that is being installed in the Brazilian Ceara state. This infrastructure was entirely constructed by the state government, but the operational costs (OPEX) will be paid by investors willing to share data transportation. Different groups will be chosen among interested investors by public auction, in order to enforce competition. Moreover, a new state company will be created that will offer low cost data transportation services, assuring that high bandwidth will be available to more than 80% of the state population.


processing of the portuguese language | 2018

Analyzing Actions in Play-by-Forum RPG

Artur de Oliveira da Rocha Franco; José Wellington Franco da Silva; Vladia Pinheiro; José Gilvan Rodrigues Maia; Fernando de Carvalho Gomes; Miguel Franklin de Castro

Interactive Storytelling (IS) technologies are enabling richer experiences for electronic games. Current computational IS models are based on investigations about how games are planned by game designers and actually played by the audience. Unfortunately, most research efforts are limited to the structured data for obtaining insights about IS models. This paper presents a study aimed at determining which actions modeled by Role-Playing Games (RPG) are more important for actual gameplay and how these actions are related. For doing so, we first extracted textual data from existing adventures found in a play-by-forum RPG portal. Such gameplay data is written in Portuguese and reflect natural gameplay without observer intervention. Our analyses from a natural language processing perspective provide valuable insights for IS models in reducing the gameplay chasm between electronic and tabletop RPG.


International Workshop on Machine Learning, Optimization and Big Data | 2016

Learning Optimal Decision Lists as a Metaheuristic Search for Diagnosis of Parkinson’s Disease

Fernando de Carvalho Gomes; José Gilvan Rodrigues Maia

Decision Lists are a very general model representation. In learning decision structures from medical datasets one needs a simple understandable model. Such a model should correctly classify unknown cases. One must search for the most general decision structure using the training dataset as input, taking into account both complexity and goodness-of-fit of the underlying model. In this paper, we propose to search the Decision List state space as an optimization problem using a metaheuristic. We implemented the method and carried out experimentation over a well-known Parkinson’s Disease training set. Our results are encouraging when compared to other machine learning references on the same dataset.


Arquivos De Neuro-psiquiatria | 2000

Diagnóstico de tumores do ângulo ponto-cerebelar com o auxílio de técnicas de inteligência artificial

Flávio Leitão; Fernando de Carvalho Gomes; Sebastião Diógenes; Flávio Leitão Filho

We are concerned in this paper with learning classification procedures from known cases. More precisely, we provide a diagnostic model that discriminate between cerebellum-pontine angle (CPA) tumors and otorhinolaryngological (ENT) disorders. Usually, in order to distinguish between CPA tumors and ENT disorders one must perform clinical-neurological examination together with expensive radiological imagery (CT and MRI). The proposed model was obtained through artificial intelligence methods and presented a good accuracy level (88.4%) when tested against new cases, considering only clinical examination without radiological imagery results.Trata-se de estudo multidisciplinar, cujo objetivo e a obtencao de modelo discriminatorio entre diagnostico de tumores do ângulo ponto-cerebelar (APC) e de disturbios otorrinolaringologicos. Presentemente, a realizacao de um acurado exame neurologico e/ou otorrinolaringologico e incapaz de firmar diagnostico de tumor do APC, sem valer-se de exames radiologicos de alto custo (tomografia computadorizada, ressonância magnetica). O modelo proposto foi obtido atraves da utilizacao de tecnicas de inteligencia artificial e apresentou bom nivel de acuracia (88,4%) no teste de novos casos, considerando-se apenas o exame clinico e sem o auxilio de exames radiologicos.


Computers & Operations Research | 2006

Experimental analysis of approximation algorithms for the vertex cover and set covering problems

Fernando de Carvalho Gomes; Cláudio Nogueira de Meneses; Panos M. Pardalos; Gerardo Valdisio R. Viana


Archive | 2002

Models for Parallel and Distributed Computation: Theory, Algorithmic Techniques, and Applications

Ricardo C. Corrêa; Inex Dutra; Mario Fiallos; Fernando de Carvalho Gomes


Archive | 2002

Models for Parallel and Distributed Computation

Ricardo C. Corrêa; Inês de Castro Dutra; Mario Fiallos; Fernando de Carvalho Gomes


Archive | 2000

A Greedy Randomized Approach for Channel Allocation in Mobile Phone Networks

Carlos A. S. Oliveira; Fernando de Carvalho Gomes; Mauricio G. C. Resende

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Ricardo C. Corrêa

Federal University of Ceará

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Flávio Leitão

Federal University of Ceará

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