Hybrid Maneuver for Gradient Search with Multiple Coordinated AUVs

This work presents a hybrid maneuver for gradient search with multiple AUV's. The mission consists in following a gradient field in order to locate the source of a hydrothermal vent or underwater freshwater source. The formation gradient search exploits the environment structuring by the phenomena to be studied. The ingredients for coordination are the payload data collected by each vehicle and their knowledge of the behaviour of other vehicles and detected formation distortions.

Response Time Analysis for Fixed-Priority Tasks with Multiple Probabilistic Parameters

Demo presented in 12th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015). 8 to 12, Jun, 2015. La Roche-en-Ardenne, Belgium. Extended abstract.

E-assessment in mathematics courses with multiple-choice questions tests

With the implementation of the Bologna Process several challenges have been posed to higher education institution, particularly in Portugal. One of the main implications is related to the change of the paradigm of a teacher centered education, to a paradigm that is student centered. This change implies the change of the way to assess courses in higher education institutions. Continuous and formative assessments emerged as the focus, catalyzed by electronic assessment, or e-assessment. This paper presents a case of the implementation of an e-assessment strategy, implemented in order to allow continuous, formative assessment in numerous mathematics classes using multiple-choice questions tests implement in Moodle open-source learning management system. The implementation can be considered a success.

E-assessment in mathematics courses with multiple-choice questions tests

With the implementation of the Bologna Process several challenges have been posed to higher education institution, particularly in Portugal. One of the main implications is related to the change of the paradigm of a teacher centered education, to a paradigm that is student centered. This change implies the change of the way to assess courses in higher education institutions. Continuous and formative assessments emerged as the focus, catalyzed by electronic assessment, or e-assessment. This paper presents a case of the implementation of an e-assessment strategy, implemented in order to allow continuous, formative assessment in numerous mathematics classes using multiple-choice questions tests implement in Moodle open-source learning management system. The implementation can be considered a success.

Multiple brain abscesses due to Penicillium spp infection

We present a case of central nervous system (CNS) infection by a member of the Penicillium genera in a HIV-negative man in Brazil. The patient was admitted complaining of loss of visual fields and speech disturbances. CT scan revealed multiple brain abscesses. Stereothacic biopsies revealed fungal infection and amphotericin B treatment begun with initial improvement. The patient died few days later as a consequence of massive gastrointestinal bleeding due to ruptured esophageal varices. The necropsy and final microbiologic analyses disclosed infection by Penicillium sp. There are thousands of fungal species of the Penicillium genera. Systemic penicilliosis is caused by the P. marneffei and was formerly a rare disease, but now is one of the most common opportunistic infection of AIDS patients in Southeast Asia. The clinical presentation usually involves the respiratory system and the skin, besides general symptoms like fever and weight loss. Penicillium spp infection caused by species other than P. marneffei normally cause only superficial or allergic disease but rare cases of invasive disease do occur. We report the fourth case of Penicillium spp CNS infection.

Decentralized Target Tracking based on Multi-Robot Cooperative Triangulation

Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

Single operation multiple data - paralelismo de dados ao nível da sub-rotina

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Feature Extraction in Densely Sensed Environments: Extensions to Multiple Broadcast Domains

The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with a low overhead. In this article, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.

Testing Nelder-Mead Based Repulsion Algorithms for Multiple Roots of Nonlinear Systems via a Two-Level Factorial Design of Experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Cutting path as a rural postman problem

The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.

High diagnostic efficiency of IgM-ELISA with the use of multiple antigen peptides (MAP1) from T. gondii ESA (SAG-1, GRA-1 and GRA-7), in acute toxoplasmosis

The main serological marker for the diagnosis of recent toxoplasmosis is the specific IgM antibody, along with IgG antibodies of low avidity. However, in some patients these antibodies may persist long after the acute/recent phase, contributing to misdiagnosis in suspected cases of toxoplasmosis. In the present study, the diagnostic efficiency of ELISA was evaluated, with the use of peptides derived from T. gondii ESA antigens, named SAG-1, GRA-1 and GRA-7. In the assay referred to, we studied each of these peptides individually, as well as in four different combinations, as Multiple Antigen Peptides (MAP), aiming to establish a reliable profile for the acute/recent toxoplasmosis with only one patient serum sample. The diagnostic performance of the assay using MAP1, with the combination of SAG-1, GRA-1 and GRA-7 peptides, demonstrated better discrimination of the acute/recent phase from non acute/recent phase of toxoplasmosis. Our results show that IgM antibodies to MAP1 may be useful as a serological marker, enhancing the diagnostic efficiency of the assay for acute/recent phase of toxoplasmosis.

Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.