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About

Luis Paulo Reis is an Associate Professor at the University of Minho in Portugal and Director of LIACC â?? Artificial Intelligence and Computer Science Laboratory where he also coordinates the Human-Machine Intelligent Cooperation Research Group. He is a IEEE Senior Member and vice-president of both the Portuguese Society for Robotics and the Portuguese Association for Artificial Intelligence. During the last 25 years he has lectured courses, at the University, on Artificial Intelligence, Intelligent Robotics, Multi-Agent Systems, Simulation and Modelling, Educational/Serious Games and Computer Programming. He was principal investigator of more than 10 research projects in those areas. He won more than 50 scientific awards including wining more than 15 RoboCup international competitions and best papers at conferences such as ICEIS, Robotica, IEEE ICARSC and ICAART. He supervised 17 PhD and 95 MSc theses to completion. He organized more than 50 scientific events and belonged to the Program Committee of more than 250 scientific events. He is the author of more than 250 publications in international conferences and journals (indexed at SCOPUS or ISI Web of Knowledge).

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Details

Details

Publications

2019

Preface

Authors
Costa, AP; Moreira, A; Reis, LP;

Publication
Advances in Intelligent Systems and Computing

Abstract

2019

An overview of assessing the quality of peer review reports of scientific articles

Authors
Sizo, A; Lino, A; Reis, LP; Rocha, A;

Publication
International Journal of Information Management

Abstract
Assuring the quality control of publications in the scientific literature is one of the main challenges of the peer review process. Consequently, there has been an increasing demand for computing solutions that will help to maintain the quality of this process. Recently, the use of Artificial Intelligence techniques has been highlighted, applied in the detection of plagiarism, bias, among other functions. The assessment of the reviewer's review has also been considered as important in the process, but, little is known about it, for instance, which techniques have been applied in this assessment or which criteria have been assessed. Therefore, this systematic literature review aims to find evidence regarding the computational approaches that have been used to evaluate reviewers' reports. In order to achieve this, five online databases were selected, from which 72 articles were identified that met the inclusion criteria of this review, all of which have been published since 2000. The result returned 10 relevant studies meeting the evaluation requirements of scientific article reviews. The review revealed that mechanisms to rank review reports according to a score, as well as the word analysis, are the most common tools, and that there is no consensus on quality criteria. The systematic literature review has shown that reviewers’ report assessment is a valid tool for maintaining quality throughout the process. However, it still needs to be further developed if it is to be used as a resource which surpass a single conference or journal, making the peer review process more rigorous and less based on random choice. © 2018 Elsevier Ltd

2018

Developments and Advances in Intelligent Systems and Applications

Authors
Rocha, Á; Reis, LP;

Publication
Studies in Computational Intelligence

Abstract

2018

Real-time tool for human gait detection from lower trunk acceleration

Authors
Gonçalves, HR; Moreira, R; Rodrigues, A; Minas, G; Reis, LP; Santos, CP;

Publication
Advances in Intelligent Systems and Computing

Abstract
The continuous monitoring of human gait would allow to more objectively verify the abnormalities that arise from the most common pathologies. Therefore, this manuscript proposes a real-time tool for human gait detection from lower trunk acceleration. The vertical acceleration signal was acquired through an IMU mounted on a waistband, a wearable device. The proposed algorithm was based on a finite state machine (FSM) which includes a set of suitable decision rules and the detection of Heel-Strike (HS), Foot-flat (FF), Toe-off (TO), Mid-Stance (MS) and Heel-strike (HS) events for each leg. Results involved 7 healthy subjects which had to walk 20 m three times with a comfortable speed. The results showed that the proposed algorithm detects in real-time all the mentioned events with a high accuracy and time-effectiveness character. Also, the adaptability of the algorithm has also been verified, being easily adapted to some gait conditions, such as for different speeds and slopes. Further, the developed tool is modular and therefore can easily be integrated in another robotic control system for gait rehabilitation. These findings suggest that the proposed tool is suitable for the real-time gait analysis in real-life activities. © Springer International Publishing AG, part of Springer Nature 2018.

2018

Trends and Advances in Information Systems and Technologies - Volume 1 [WorldCIST'18, Naples, Italy, March 27-29, 2018]

Authors
Rocha, A; Adeli, H; Reis, LP; Costanzo, S;

Publication
WorldCIST (1)

Abstract