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Publicações

Publicações por Rui Costa Martins

2017

Parallelization Strategies for Spatial Agent-Based Models

Autores
Fachada, N; Lopes, VV; Martins, RC; Rosa, AC;

Publicação
INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING

Abstract
Agent-based modeling (ABM) is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. Large scale emergent behavior in ABMs is population sensitive. As such, the number of agents in a simulation should be able to reflect the reality of the system being modeled, which can be in the order of millions or billions of individuals in certain domains. A natural solution to reach acceptable scalability in commodity multi-core processors consists of decomposing models such that each component can be independently processed by a different thread in a concurrent manner. In this paper we present a multithreaded Java implementation of the PPHPC ABM, with two goals in mind: (1) compare the performance of this implementation with an existing NetLogo implementation; and, (2) study how different parallelization strategies impact simulation performance on a shared memory architecture. Results show that: (1) model parallelization can yield considerable performance gains; (2) distinct parallelization strategies offer specific trade-offs in terms of performance and simulation reproducibility; and, (3) PPHPC is a valid reference model for comparing distinct implementations or parallelization strategies, from both performance and statistical accuracy perspectives.

2016

SimOutUtils – Utilities for Analyzing Time Series Simulation Output

Autores
Fachada, N; Lopes, VV; Martins, RC; Rosa, AC;

Publicação
Journal of Open Research Software

Abstract

2015

Towards a standard model for research in agent-based modeling and simulation

Autores
Fachada, N; Lopes, VV; Martins, RC; Rosa, AC;

Publicação
PeerJ Computer Science

Abstract
Agent-based modeling (ABM) is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. ABMs are very sensitive to implementation details. Thus, it is very easy to inadvertently introduce changes which modify model dynamics. Such problems usually arise due to the lack of transparency in model descriptions, which constrains how models are assessed, implemented and replicated. In this paper, we present PPHPC, a model which aims to serve as a standard in agent based modeling research, namely, but not limited to, conceptual model specification, statistical analysis of simulation output, model comparison and parallelization studies. This paper focuses on the first two aspects (conceptual model specification and statistical analysis of simulation output), also providing a canonical implementation of PPHPC. The paper serves as a complete reference to the presented model, and can be used as a tutorial for simulation practitioners who wish to improve the way they communicate their ABMs.

2013

Port Wine Oxidation Management: A Multiparametric Kinetic Approach

Autores
Martins, RC; Monforte, AR; Silva Ferreira, A;

Publicação
J. Agric. Food Chem. - Journal of Agricultural and Food Chemistry

Abstract

2018

Detection of BCG bacteria using a magnetoresistive biosensor: A step towards a fully electronic platform for tuberculosis point-of-care detection

Autores
Barroso, TG; Martins, RC; Fernandes, E; Cardoso, S; Rivas, J; Freitas, PP;

Publicação
Biosensors and Bioelectronics

Abstract
Tuberculosis is one of the major public health concerns. This highly contagious disease affects more than 10.4 million people, being a leading cause of morbidity by infection. Tuberculosis is diagnosed at the point-of-care by the Ziehl-Neelsen sputum smear microscopy test. Ziehl-Neelsen is laborious, prone to human error and infection risk, with a limit of detection of 104 cells/mL. In resource-poor nations, a more practical test, with lower detection limit, is paramount. This work uses a magnetoresistive biosensor to detect BCG bacteria for tuberculosis diagnosis. Herein we report: i) nanoparticle assembly method and specificity for tuberculosis detection; ii) demonstration of proportionality between BCG cell concentration and magnetoresistive voltage signal; iii) application of multiplicative signal correction for systematic effects removal; iv) investigation of calibration effectiveness using chemometrics methods; and v) comparison with state-of-the-art point-of-care tuberculosis biosensors. Results present a clear correspondence between voltage signal and cell concentration. Multiplicative signal correction removes baseline shifts within and between biochip sensors, allowing accurate and precise voltage signal between different biochips. The corrected signal was used for multivariate regression models, which significantly decreased the calibration standard error from 0.50 to 0.03 log10 (cells/mL). Results show that Ziehl-Neelsen detection limits and below are achievable with the magnetoresistive biochip, when pre-processing and chemometrics are used. © 2017 Elsevier B.V.

2018

Positioning. Navigation and Awareness of the !VAMOS! Underwater Robotic Mining System

Autores
Almeida, J; Martins, A; Almeida, C; Dias, A; Matias, B; Ferreira, A; Jorge, P; Martins, R; Bleier, M; Nuechter, A; Pidgeon, J; Kapusniak, S; Silva, E;

Publicação
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Abstract

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