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Publications

2016

Spontaneous Fluctuations in Sensory Processing Predict Within-Subject Reaction Time Variability

Authors
Ribeiro, MJ; Paiva, JS; Castelo Branco, M;

Publication
FRONTIERS IN HUMAN NEUROSCIENCE

Abstract
When engaged in a repetitive task our performance fluctuates from trial-to trial. In particular, inter-trial reaction time variability has been the subject of considerable research. It has been claimed to be a strong biomarker of attention deficits, increases with frontal dysfunction, and predicts age-related cognitive decline. Thus, rather than being just a consequence of noise in the system, it appears to be under the control of a mechanism that breaks down under certain pathological conditions. Although the underlying mechanism is still an open question, consensual hypotheses are emerging regarding the neural correlates of reaction time inter-trial intra-individual variability. Sensory processing, in particular, has been shown to covary with reaction time, yet the spatio-temporal profile of the moment-to-moment variability in sensory processing is still poorly characterized. The goal of this study was to characterize the intra-individual variability in the time course of single-trial visual evoked potentials and its relationship with inter trial reaction time variability. For this, we chose to take advantage of the high temporal resolution of the electroencephalogram (EEG) acquired while participants were engaged in a 2-choice reaction time task. We studied the link between single trial event-related potentials (ERPs) and reaction time using two different analyses: (1) time point by time point correlation analyses thereby identifying time windows of interest; and (2) correlation analyses between single trial measures of peak latency and amplitude and reaction time. To improve extraction of single trial [RP measures related with activation of the visual cortex, we used an independent component analysis (ICA) procedure. Our FRP analysis revealed a relationship between the N1 visual evoked potential and reaction time. The earliest time point presenting a significant correlation of its respective amplitude with reaction time occurred 175 ms after stimulus onset, just after the onset of the N1 peak. Interestingly, single trial N1 latency correlated significantly with reaction time, while N1 amplitude did not. In conclusion, our findings suggest that inter-trial variability in the timing of extrastriate visual processing contributes to reaction time variability.

2016

Performing universal tasks using a mini iPad: usability assessment per people with intellectual disabilities

Authors
Rocha, Tania; Bessa, Maximino; Cabral, Luciana;

Publication
Proceedings of the XVII International Conference on Human Computer Interaction, Interacción 2016, Salamanca, Spain, September 13 - 16, 2016

Abstract
With this study we aim at assessing if a mini iPad device is a usable option for digital interaction to perform selection, manipulation, and insertion tasks by people with intellectual disabilities. This study builds on previous studies where usability was evaluated for universal tasks using the keyboard and a mouse input device [1]. This allowed us to assess the usability of a small mini iPad and compare it with other two input devices, namely keyboards and the mouse. For usability assessment we registered the following variables: successful conclusion of activities, type of difficulties found, errors and satisfaction indicators. The results showed that this group was much motivated to learn how to handle with the iPad, several asked to repeat the task and no one quit any task requested. Despite the number of errors as registered in their interaction, they always knew how to overcome the error and never showed frustration or demotivation. Furthermore, they had a good performance (relation between variables: time to conclude the task, number of errors and difficulties felt) with the mini iPad device, however when compared with the keyboard and mouse, their performance increased. © 2016 ACM.

2016

Optimization of electricity markets participation with QPSO

Authors
Faia, R; Pinto, T; Vale, Z;

Publication
International Conference on the European Energy Market, EEM

Abstract
All around the world, the electric sector has suffered significant changes. With these alterations, electrical systems have become international, with several countries connected by a system where the management is done in common grounds. With the incorporation of large scale distributed generation, competitiveness in electrical markets has increased as small generators unite in order to be able to compete with large producers. In this game where the main objective is to win, and the premium is money it is necessary to be keen to be able to sell the available electricity at the best possible prices. With the objective of supporting players' decisions, decision support tools play a crucial role. These tools enable market players with suggestions of actions to increase their advantage from market participation. This paper presents a Quantum-based Particle Swarm Optimization (QPSO) methodology to solve the problem of optimal participation in multiple electricity markets. © 2016 IEEE.

2016

Active Management of Electric Vehicles Acting as Distributed Storage

Authors
Soares, FJ; Almeida, PMR; Galus, M; Barbeiro, PNP; Peças Lopes, J;

Publication
Smart Grid Handbook

Abstract

2016

Preface

Authors
Bertogna, M; Pinho, LM; Quiñones, E;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract

2016

The Extraction from News Stories a Causal Topic Centred Bayesian Graph for Sugarcane

Authors
Drury, B; Rocha, C; Moura, MF; Lopes, AdA;

Publication
Proceedings of the 20th International Database Engineering & Applications Symposium, IDEAS 2016, Montreal, QC, Canada, July 11-13, 2016

Abstract
Sugarcane is an important product to the Brazilian economy because it is the primary ingredient of ethanol which is used as a gasoline substitute. Sugarcane is aflected by many factors which can be modelled in a Bayesian Graph. This paper describes a technique to build a Causal Bayesian Network from information in news stories. The technique: extracts causal relations from news stories, converts them into an event graph, removes irrelevant information, solves structure problems, and clusters the event graph by topic distribution. Finally, the paper describes a method for generating inferences from the graph based upon evidence in agricultural news stories. The graph is evaluated through a manual inspection and with a comparison with the EMBRAPA sugarcane taxonomy. © ACM 2016.

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