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Publications

2019

Learning Preferential Perceptual Exposure for HDR Displays

Authors
Bashford Rogers, T; Melo, M; Marnerides, D; Bessa, M; Debattista, K; Chalmers, A;

Publication
IEEE ACCESS

Abstract
High dynamic range (HDR) displays are capable of displaying a wider dynamic range of values than conventional displays. As HDR content becomes more ubiquitous, the use of these displays is likely to accelerate. As HDR displays can present a wider range of values, traditional strategies for mapping HDR content to low dynamic range (LDR) displays can be replaced with either directly displaying values, or using a simple shift mapping (exposure adjustment). The latter approach is especially important when considering ambient lighting, as content viewed in a dark environment may appear substantially different to a bright one. This paper seeks to identify an exposure value which is suitable for displaying specific HDR content on an HDR display under a range of ambient lighting levels. Based on data captured with human participants, this paper establishes user preferred exposure values for a variety of maximum display brightnesses, content and ambient lighting levels. These are then used to develop two models to predict preferred exposure. The first is based on linear regression using straightforward image statistics which require minimal computation and memory to be computed, making this method suitable to be directly used in display hardware. The second is a model based on convolutional neural networks (CNN) to learn image features which best predict exposure values. The CNN model generates better results than the first model at the cost of memory and computation time.

2019

Real-time provision of multiple electricity market products by an aggregator of prosumers

Authors
Iria, J; Soares, F;

Publication
APPLIED ENERGY

Abstract
The foreseen participation of aggregators of prosumers in the electricity markets will require the development of computational tools to support them in the definition and delivery of market products. This paper proposes a new hierarchical model predictive control (MPC) to support an aggregator in the delivery of multiple market products through the real-time control of heterogeneous flexible resources. The hierarchical MPC covers the participation of an aggregator in both energy and secondary reserve markets. The results show that the aggregator is capable of delivering several combinations of energy and secondary reserve without compromising the comfort and preferences of its clients.

2019

Low Cost Underwater Acoustic Positioning System with a Simplified DoA Algorithm

Authors
Guedes, P; Viana, N; Silva, J; Amaral, G; Ferreira, H; Dias, A; Almeida, JM; Martins, A; Silva, EP;

Publication
OCEANS 2019 MTS/IEEE SEATTLE

Abstract
For the context of a mobile tracking system, an underwater acoustic positioning system was developed, using three hydrophones to compute the direction of an acoustic source relative to an Autonomous Surface Vehicle (ASV). The paper presents an algorithm for the Direction of Arrival (DoA) of an acoustic source, which allows to estimate its position. Preliminary results will be shown in this paper relative to the detection and identification (ID) of the acoustic sources, as well as an analysis of the proposed algorithm. The solution allows the position estimation of an acoustic source, which can be used in tracking solutions. The system can be applied in an ASV or fixed buoys, as long as the baseline's hydrophones are at equal angular distances. The main objective is to track targets with the DoA algorithm as well to estimate their position, improving what was done in [1].

2019

BULLY WHO? THEATRICAL PLAY AND VICARIOUS EXPERIENCES OF DOING AND ACTING WITH EMOTIONS

Authors
Raimundo, J; Cardoso, P; Carvalhais, M; Coelho, A;

Publication
DIGICOM 2019 - 3RD INTERNATIONAL CONFERENCE ON DESIGN AND DIGITAL COMMUNICATION

Abstract
Digital media expanded people's creative horizons by placing knowledge, tools, design procedures and its practices within reach, yet it also called for new literacies. Games can encourage reflection and interaction in alternative ways, and ease learning and the articulation of knowledge between individuals, thus they may be valuable for such requirements. In spite of this, games are still struggling to find their way into classrooms and workplaces as tools for creativity, as educators are not prepared to design them for such purposes, which limits their use in scope and in substance. With this in mind, we developed Bully Who?, an analogue game prototype for players to learn to deal with bullying in a creative way, by acting as a stage for embodying the roles of aggressors and victims, making players aware of their emotions and consequences involved. To check for viability, usability and potential, we resorted to play-testing sessions involving a small sample of twenty-five, socially-diverse individuals. This study helped us draw several conclusions: 1) simulating embodied, dramatized actions increases awareness of one's emotions and helps speculating on the state of others' - something valuable to cultivate emotional intelligence; 2) theatrical gameplay can help establish an attitude favourable for game-based learning; 3) games can act as ground to bridge intergenerational exchange for problem-solving; 4) according to participants the prototype has the potential to be adapted to stimulate creative discussion on similar social concerns.

2019

Técnicas de Aprendizado de Máquina Aplicadas na Previsão de Produtividade de Operadores de Centros de Teleatendimento

Authors
OLIVEIRA, E; Manuel Torres, J; Silva Moreira, R; França Lima, R;

Publication
Anais do 14º Simpósio Brasileiro de Automação Inteligente

Abstract

2019

ALBidS: A Decision Support System for Strategic Bidding in Electricity Markets

Authors
Pinto, T; Vale, ZA;

Publication
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS '19, Montreal, QC, Canada, May 13-17, 2019

Abstract

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