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Publicações

2018

A comparison of hierarchical multi-output recognition approaches for anuran classification

Autores
Colonna, JG; Gama, J; Nakamura, EF;

Publicação
MACHINE LEARNING

Abstract
In bioacoustic recognition approaches, a flat classifier is usually trained to recognize several species of anurans, where the number of classes is equal to the number of species. Consequently, the complexity of the classification function increases proportionally with the number of species. To avoid this issue, we propose a hierarchical approach that decomposes the problem into three taxonomic levels: the family, the genus, and the species. To accomplish this, we transform the original single-labelled problem into a multi-output problem (multi-label and multi-class) considering the biological taxonomy of the species. We then develop a top-down method using a set of classifiers organized as a hierarchical tree. We test and compare two hierarchical methods, using (1) one classifier per parent node and (2) one classifier per level, against a flat approach. Thus, we conclude that it is possible to predict the same set of species as a flat classifier, and additionally obtain new information about the samples and their taxonomic relationship. This helps us to better understand the problem and achieve additional conclusions by the inspection of the confusion matrices at the three classification levels. In addition, we propose a soft decision rule based on the joint probabilities of hierarchy pathways. With this we are able to identify and reject confusing cases. We carry out our experiments using cross-validation performed by individuals. This form of CV avoids mixing syllables that belong to the same specimens in the testing and training sets, preventing an overestimate of the accuracy and generalizing the predictive capabilities of the system. We tested our methods in a dataset with sixty individual frogs, from ten different species, eight genera, and four families, achieving a final Macro-Fscore of 80 and 70% with and without applying the rejection rule, respectively.

2018

Educational Data Mining: A Literature Review

Autores
Martins, MPG; Migueis, VL; Fonseca, DSB;

Publicação
2018 13TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)

Abstract
With the aim of disseminating the potential and the capacity of Educational Data Mining (EDM) as an instrument of investigation and analysis in the support to the management of Higher Education Institutions, this paper presents a brief description of some of the most relevant studies in the area. The analysis carried out allows to highlight the innovations that EDM has been promoting, as well as current and future research trends.

2018

Deep Homography Based Localization on Videos of Endoscopic Capsules

Autores
Pinheiro, G; Coelho, P; Salgado, M; Oliveira, HP; Cunha, A;

Publicação
PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM)

Abstract
Endoscopic capsules are vitamin-sized devices that create 8 to 10 hour videos of the digestive tract. They are the leading diagnosing method for the small bowel, a region not easily accessible with traditional endoscopy techniques. However, these capsules do not provide localization information, even though it is crucial for the diagnosis, follow-ups and surgical interventions. Currently, the capsule localization is either estimated based on scarce gastrointestinal tract landmarks or given by additional hardware that causes discomfort to the patient and represents a cost increase. Current software methods show great potential, but still need to improve in order to overcome their limitations. In this work, a visual odometry method for capsule localization inside the small bowel is proposed.

2018

Off-axis point spread function characterization in laser guide star adaptive optics systems

Autores
Beltramo Martin, O; Correia, CM; Mieda, E; Neichel, B; Fusco, T; Witzel, G; Lu, JR; Véran, JP;

Publicação
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Abstract
Adaptive optics (AO) restore the angular resolution of ground-based telescopes, but at the cost of delivering a time- and space-varying point spread function (PSF) with a complex shape. PSF knowledge is crucial for breaking existing limits on the measured accuracy of photometry and astrometry in science observations. In this paper, we concentrate our analyses of the anisoplanatism signature only on to the PSF. For large-field observations (20 arcmin) with single-conjugated AO, PSFs are strongly elongated due to anisoplanatism that manifests itself as three different terms for laser guide star (LGS) systems: angular, focal and tilt anisoplanatism. First, we propose a generalized model that relies on a point-wise decomposition of the phase and encompasses the non-stationarity of LGS systems. We demonstrate that it is more accurate and less computationally demanding than existing models: it agrees with end-to-end physical-optics simulations to within 0.1 per cent of PSF measurables, such as the Strehl ratio, FWHM and the fraction of variance unexplained (FVU). Secondly, we study off-axis PSF modelling with respect to the Cn2(h) profile (heights and fractional weights). For 10-mclass telescopes, PSF morphology is estimated at the 1 per cent level as long as we model the atmosphere with at least seven layers, whose heights and weights are known with precisions of 200 m and 10 per cent, respectively. As a verification test, we used the Canada's National Research Council - Herzberg NFIRAOS Optical Simulator (HeNOS) testbed data, featuring four lasers. We highlight the capability of retrieving off-axis PSF characteristics within 10 per cent of the FVU, which complies with the expected range from the sensitivity analysis. Our new off-axis PSF modelling method lays the groundwork for testing on-sky in the near future.

2018

Novel probabilistic optimization model for lead-acid and vanadium redox flow batteries under real-time pricing programs

Autores
Lujano Rojas, JM; Zubi, G; Dufo Lopez, R; Bernal Agustin, JL; Catalao, JPS;

Publicação
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Abstract
The integration of storage systems into smart grids is being widely analysed in order to increase the flexibility of the power system and its ability to accommodate a higher share of wind and solar power. The success of this process requires a comprehensive techno-economic study of the storage technology in contrast with electricity market behaviour. The focus of this work is on lead-acid and vanadium redox flow batteries. This paper presents a novel probabilistic optimization model for managing energy storage systems. The model is able to incorporate the forecasting error of electricity prices, offering with this a near-optimal control option. Using real data from the Spanish electricity market from the year 2016, the probability distribution of forecasting error is determined. The model determines electricity price uncertainty by means of Monte Carlo Simulation and includes it in the energy arbitrage problem, which is eventually solved by using an integer-coded genetic algorithm. In this way, the probability distribution of the revenue is determined with consideration of the complex behaviours of lead acid and vanadium redox flow batteries as well as their associated operating devices such as power converters.

2018

An Information System to Remotely Monitor Oncological Palliative Care Patients

Autores
Reis, A; da Guia, EB; Sousa, A; Silva, A; Rocha, T; Barroso, J;

Publicação
Trends and Advances in Information Systems and Technologies - Volume 2 [WorldCIST'18, Naples, Italy, March 27-29, 2018]

Abstract
For oncological patients, the introduction of palliative care in the early stages of the disease’s progression can have great benefits. The Portuguese government recently introduced a program to provide home palliative care support by creating specialized mobile teams, able to track, visit and address the patients’ problems. These teams must be available for the patient, when necessary and if necessary. The teams must also have updated knowledge about the daily evolution of the patients’ health. The Douro Sul Healthcare Centers, together with the University of Trás-os-Montes e Alto Douro, developed and implemented an ICT system to track the status of each and every one of the patients. The system has several components, including: a mobile app for the patients or their caregivers to report daily how the patient’s symptoms have evolved over the last 24 h; a web app for the teams to browser their patients’ status. © Springer International Publishing AG, part of Springer Nature 2018.

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