Artificial Intelligence and Computer Science Laboratory LIACC

United States

Artificial Intelligence and Computer Science Laboratory LIACC

United States

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Vrba P.,Czech Technical University | Marik V.,Czech Technical University | Siano P.,University of Salerno | Leitao P.,Polytechnic Institute of Bragança | And 5 more authors.
IEEE Transactions on Industrial Informatics | Year: 2014

The intention of this paper is to provide an overview of using agent and service-oriented technologies in intelligent energy systems. It focuses mainly on ongoing research and development activities related to smart grids. Key challenges as a result of the massive deployment of distributed energy resources are discussed, such as aggregation, supply-demand balancing, electricity markets, as well as fault handling and diagnostics. Concepts and technologies like multiagent systems or service-oriented architectures are able to deal with future requirements supporting a flexible, intelligent, and active power grid management. This work monitors major achievements in the field and provides a brief overview of large-scale smart grid projects using agent and service-oriented principles. In addition, future trends in the digitalization of power grids are discussed covering the deployment of resource constrained devices and appropriate communication protocols. The employment of ontologies ensuring semantic interoperability as well as the improvement of security issues related to smart grids is also discussed. © 2005-2012 IEEE.

Strasser T.,AIT Austrian Institute of Technology | Andren F.,AIT Austrian Institute of Technology | Kathan J.,AIT Austrian Institute of Technology | Cecati C.,University of L'Aquila | And 12 more authors.
IEEE Transactions on Industrial Electronics | Year: 2015

Renewable energy sources are one key enabler to decrease greenhouse gas emissions and to cope with the anthropogenic climate change. Their intermittent behavior and limited storage capabilities present a new challenge to power system operators to maintain power quality and reliability. Additional technical complexity arises from the large number of small distributed generation units and their allocation within the power system. Market liberalization and changing regulatory framework lead to additional organizational complexity. As a result, the design and operation of the future electric energy system have to be redefined. Sophisticated information and communication architectures, automation concepts, and control approaches are necessary in order to manage the higher complexity of so-called smart grids. This paper provides an overview of the state of the art and recent developments enabling higher intelligence in future smart grids. The integration of renewable sources and storage systems into the power grids is analyzed. Energy management and demand response methods and important automation paradigms and domain standards are also reviewed. © 1982-2012 IEEE.

Oliveira J.L.,Artificial Intelligence and Computer Science Laboratory LIACC | Oliveira J.L.,INESC Porto | Oliveira J.L.,Kyoto University | Ince G.,Honda Corporation | And 6 more authors.
IEEE International Conference on Intelligent Robots and Systems | Year: 2012

In this paper we propose the integration of an online audio beat tracking system into the general framework of robot audition, to enable its application in musically-interactive robotic scenarios. To this purpose, we introduced a staterecovery mechanism into our beat tracking algorithm, for handling continuous musical stimuli, and applied different multi-channel preprocessing algorithms (e.g., beamforming, ego noise suppression) to enhance noisy auditory signals lively captured in a real environment. We assessed and compared the robustness of our audio beat tracker through a set of experimental setups, under different live acoustic conditions of incremental complexity. These included the presence of continuous musical stimuli, built of a set of concatenated musical pieces; the presence of noises of different natures (e.g., robot motion, speech); and the simultaneous processing of different audio sources on-the-fly, for music and speech. We successfully tackled all these challenging acoustic conditions and improved the beat tracking accuracy and reaction time to music transitions while simultaneously achieving robust automatic speech recognition. © 2012 IEEE.

Oliveira J.L.,Artificial Intelligence and Computer Science Laboratory LIACC | Nakamura K.,Honda Corporation | Langlois T.,University of Lisbon | Gouyon F.,INESC Porto | And 5 more authors.
IEEE International Conference on Intelligent Robots and Systems | Year: 2014

In this paper we address the problem of musical genre recognition for a dancing robot with embedded microphones capable of distinguishing the genre of a musical piece while moving in a real-world scenario. For this purpose, we assess and compare two state-of-the-art musical genre recognition systems, based on Support Vector Machines and Markov Models, in the context of different real-world acoustic environments. In addition, we compare different preprocessing robot audition variants (single channel and separated signal from multiple channels) and test different acoustic models, learned a priori, to tackle multiple noise conditions of increasing complexity in the presence of noises of different natures (e.g., robot motion, speech). The results with six different musical genres suggest improved results, in the order of 43.6pp for the most complex conditions, when recurring to Sound Source Separation and acoustic models trained in similar conditions to the testing scenarios. A robot dance demonstration session confirms the applicability of the proposed integration for genre-adaptive dancing robots in real-world noisy environments. © 2014 IEEE.

Oliveira J.L.,University of Porto | Oliveira J.L.,Artificial Intelligence and Computer Science Laboratory LIACC | Oliveira J.L.,INESC Porto | Naveda L.,Ghent University | And 6 more authors.
Eurasip Journal on Audio, Speech, and Music Processing | Year: 2012

Dance movements are a complex class of human behavior which convey forms of non-verbal and subjective communication that are performed as cultural vocabularies in all human cultures. The singularity of dance forms imposes fascinating challenges to computer animation and robotics, which in turn presents outstanding opportunities to deepen our understanding about the phenomenon of dance by means of developing models, analyses and syntheses of motion patterns. In this article, we formalize a model for the analysis and representation of popular dance styles of repetitive gestures by specifying the parameters and validation procedures necessary to describe the spatiotemporal elements of the dance movement in relation to its music temporal structure (musical meter). Our representation model is able to precisely describe the structure of dance gestures according to the structure of musical meter, at different temporal resolutions, and is flexible enough to convey the variability of the spatiotemporal relation between music structure and movement in space. It results in a compact and discrete mid-level representation of the dance that can be further applied to algorithms for the generation of movements in different humanoid dancing characters. The validation of our representation model relies upon two hypotheses: (i) the impact of metric resolution and (ii) the impact of variability towards fully and naturally representing a particular dance style of repetitive gestures. We numerically and subjectively assess these hypotheses by analyzing solo dance sequences of Afro-Brazilian samba and American Charleston, captured with a MoCap (Motion Capture) system. From these analyses, we build a set of dance representations modeled with different parameters, and re-synthesize motion sequence variations of the represented dance styles. For specifically assessing the metric hypothesis, we compare the captured dance sequences with repetitive sequences of a fixed dance motion pattern, synthesized at different metric resolutions for both dance styles. In order to evaluate the hypothesis of variability, we compare the same repetitive sequences with others synthesized with variability, by generating and concatenating stochastic variations of the represented dance pattern. The observed results validate the proposition that different dance styles of repetitive gestures might require a minimum and sufficient metric resolution to be fully represented by the proposed representation model. Yet, these also suggest that additional information may be required to synthesize variability in the dance sequences while assuring the naturalness of the performance. Nevertheless, we found evidence that supports the use of the proposed dance representation for flexibly modeling and synthesizing dance sequences from different popular dance styles, with potential developments for the generation of expressive and natural movement profiles onto humanoid dancing characters. © 2012 Oliveira et al; licensee Springer.

Nogueira P.A.,Artificial Intelligence and Computer Science Laboratory LIACC | Nogueira P.A.,University of Porto | Nogueira P.A.,University of Western Ontario | Rodrigues R.,INESC Porto | And 4 more authors.
Web Intelligence | Year: 2015

With the rising research in emotionally believable agents, several advances in agent technology have been made, ranging from interactive virtual agents to emotional mechanism simulations and emotional agent architectures. However, creating an emotionally believable agent capable of emotional thought is still largely out of reach. It has been proposed that being able to accurately model human emotion would allow agents to mimic human behaviour while these models are studied to create more accurate theoretical models. In light of these challenges, we present a general method for human emotional state modelling in interactive environments. The proposed method employs a three-layered classification process to model the arousal and valence (i.e., hedonic) emotional components, based on four selected psychophysiological metrics. Additionally, we also developed a simplified version of our system for use in real-time systems and low-fidelity applications. The modelled emotional states by both approaches compared favourably with a manual approach following the current best practices reported in the literature while also improving on its predictive ability. The obtained results indicate we are able to accurately predict human emotional states, both in offline and online scenarios with varying levels of granularity; thus, providing a transversal method for modelling and reproducing human emotional profiles. © 2015 - IOS Press and the authors. All rights reserved.

Correia F.L.,Artificial Intelligence and Computer Science Laboratory LIACC | Amaro R.F.S.,Artificial Intelligence and Computer Science Laboratory LIACC | Sarmento L.,University of Porto | Rossetti R.J.F.,University of Porto
Proceedings of the 5th Iberian Conference on Information Systems and Technologies, CISTI 2010 | Year: 2010

The main objective of this paper is to describe a project named AllCall, created to help researchers organize their publication schedule. The technology herein presented intends to be able to automatically extract conference's relevant information - conference name, important dates, location, conference sites and topics - from emails and conveniently present it on a web interface. Differently from other tools, to the best of our knowledge no other application is able to do this sort of information extraction automatically. This paper reports on the first approach of the project and presents the results so far.

Oliveira J.L.,INESC Porto | Oliveira J.L.,Artificial Intelligence and Computer Science Laboratory LIACC | Gouyon F.,INESC Porto | Martins L.G.,Research Center for Science and Technology in Art | Reis L.P.,Artificial Intelligence and Computer Science Laboratory LIACC
Proceedings of the 11th International Society for Music Information Retrieval Conference, ISMIR 2010 | Year: 2010

This paper describes a tempo induction and beat tracking system based on the efficient strategy (initially introduced in the BeatRoot system [Dixon S., "Automatic extraction of tempo and beat from expressive performances." Journal of New Music Research, 30(1):39-58, 2001]) of competing agents processing musical input sequentially and considering parallel hypotheses regarding tempo and beats. In this paper, we propose to extend this strategy to the causal processing of continuous input data. The main reasons for this are threefold: providing more robustness to potentially noisy input data, permitting the parallel consideration of a number of low-level frame-based features as input, and opening the way to real-time uses of the system (as e.g. for a mobile robotic platform). The system is implemented in C++, permitting faster than real-time processing of audio data. It is integrated in the MARSYAS framework, and is therefore available under GPL for users and/or researchers. Detailed evaluation of the causal and non-causal versions of the system on common benchmark datasets show performances reaching those of state-of-the-art beat trackers. We propose a series of lines for future work based on careful analysis of the results. © 2010 International Society for Music Information Retrieval.

Da Silva G.A.,University of Porto | Nogueira P.A.,Artificial Intelligence and Computer Science Laboratory LIACC | Rodrigues R.,INESC Porto
CHI PLAY 2014 - Proceedings of the 2014 Annual Symposium on Computer-Human Interaction in Play | Year: 2014

"Generic Shooter 3000" is a First-Person shooter with semi-realistic interaction, where actions such as firing a gun or diving through underwater sections are performed with your own body- through the use of biofeedback technology. This prototype is the idealised version of a research game developed for a master's thesis project on "biofeedback interaction in video games". © 2014 ACM.

Santiago C.B.,University of Porto | Santiago C.B.,INESC Porto | Oliveira J.L.,INESC Porto | Oliveira J.L.,Artificial Intelligence and Computer Science Laboratory LIACC | And 5 more authors.
International Journal of Computational Intelligence Systems | Year: 2012

We propose an online sensorimotor architecture for controlling a low-cost humanoid robot to perform dance movements synchronized with musical stimuli. The proposed architecture attempts to overcome the robot's motor constraints by adjusting the velocity of its actuators and inter-changing the attended beat metrical-level on-the-fly. Moreover, we propose quantitative metrics for measuring the level of beat-synchrony of the generated robot dancing motion and complement them with a qualitative survey about several aspects of the demonstrated robot dance performances. Tests with different dance movements and musical pieces demonstrated satisfactory beat-synchrony results despite the physical limitations of the robot. The comparison against robot dance sequences generated without inter-changing the attended metrical-level validated our sensorimotor approach for controlling beat-synchronous robot dancing motions using different dance movements and facing distinct musical tempo conditions. © 2012 Copyright the authors.

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