Artificial Intelligence and Computer Science Laboratory LIACC

United States

Artificial Intelligence and Computer Science Laboratory LIACC

United States
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Freitas F.,University of Aveiro | Ribeiro J.,University of Aveiro | Ribeiro J.,Polytechnic Institute of Leiria | Brandao C.,University of Porto | And 4 more authors.
Advances in Intelligent Systems and Computing | Year: 2018

One of the first precautions that a consumer/user has when acquiring a new product is related to how to use it. In this context, the user manuals can be assumed as one of the main communication channels between the companies that develop the products and the user. Regarding the use of software packages, literature indicates that one of the decisive factors for user’s dissatisfaction is related to the difficulty in learning how to work with a software. In this context, Qualitative Data Analysis Software (QDAS) enterprises are increasingly looking to develop features that can decrease user’s learning curve of their tools. In this way, this chapter illustrates a comparison of user support features, such as: support and typology of the User Manual; Training; Tutorials; Forums; Frequently asked questions (FAQ’s); Workshops. Through a systematic exploration of the native sites guided by a dedicated checklist, it was sought to identify the singularities of the resources to support (self)learning of the different software packages. In order to systematize the offers that each user can find, enabling him/her to choose the package that provides the solutions that best respond to his/her learning style. It was concluded that among the different software packages there are no noteworthy disparities, only in two packages analysed there were shortcomings in the offer of formative and autonomous learning. © Springer International Publishing AG 2018.

Nogueira P.,Artificial Intelligence and Computer Science Laboratory LIACC | Nogueira P.,University of Porto | Urbano J.,Artificial Intelligence and Computer Science Laboratory LIACC | Urbano J.,University of Porto | And 8 more authors.
Advances in Intelligent Systems and Computing | Year: 2017

With the rise in wearable technology and “health culture”, we are seeing a rising interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals’ quality of life. On one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health. In this paper, we evaluate the current state of the art in physiological therapy (biofeedback) along with the existing medical grade and consumer grade hardware for physiological research. We provide a comparative analysis between these two device grades and also discuss the finer details of each consumer grade device in terms of functionality and adaptability for controlled (laboratory) and uncontrolled (field) studies. © Springer International Publishing AG 2017.

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.

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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