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Publicações

2015

Batched Evaluation of Full-Sharing Multithreaded Tabling

Autores
Areias, M; Rocha, R;

Publicação
LANGUAGES, APPLICATIONS AND TECHNOLOGIES, SLATE 2015

Abstract
Tabling is a technique that overcomes some limitations of traditional Prolog systems in dealing with redundant sub-computations and recursion. When tabling is combined with multithreading, we have the best of both worlds, since we can exploit the combination of higher declarative semantics with higher procedural control. To support this combination, the Yap Prolog system has, at engine level, multiple designs that vary from a No-Sharing design, where each thread allocates fully private tables, to a Full-Sharing (FS) design, where threads share the complete table space. In this work, we propose an extension to the table space data structures, which we named Private Answer Chaining (PAC), as way to support batched scheduling evaluation with the FS design. Batched scheduling is one of the most successful tabling scheduling strategies, known to be useful when a tabled logic program requires an eager propagation of answers and/or do not requires the complete set of answers to be found. Experimental results show that PAC is a good first approach, since with it the FS design remains quite competitive.

2015

Validation of percutaneous puncture trajectory during renal access using 4D ultrasound reconstruction

Autores
Rodrigues, PL; Rodrigues, NF; Fonseca, JC; Vilaca, JL;

Publicação
MEDICAL IMAGING 2015: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING

Abstract
Background: An accurate percutaneous puncture is essential for disintegration and removal of renal stones. Although this procedure has proven to be safe, some organs surrounding the renal target might be accidentally perforated. This work describes a new intraoperative framework where tracked surgical tools are superimposed within 4D ultrasound imaging for security assessment of the percutaneous puncture trajectory (PPT). Methods: A PPT is first generated from the skin puncture site towards an anatomical target, using the information retrieved by electromagnetic motion tracking sensors coupled to surgical tools. Then, 2D ultrasound images acquired with a tracked probe are used to reconstruct a 4D ultrasound around the PPT under GPU processing. Volume hole-filling was performed in different processing time intervals by a tri-linear interpolation method. At spaced time intervals, the volume of the anatomical structures was segmented to ascertain if any vital structure is in between PPT and might compromise the surgical success. To enhance the volume visualization of the reconstructed structures, different render transfer functions were used. Results: Real-time US volume reconstruction and rendering with more than 25 frames/s was only possible when rendering only three orthogonal slice views. When using the whole reconstructed volume one achieved 8-15 frames/s. 3 frames/s were reached when one introduce the segmentation and detection if some structure intersected the PPT. Conclusions: The proposed framework creates a virtual and intuitive platform that can be used to identify and validate a PPT to safely and accurately perform the puncture in percutaneous nephrolithotomy.

2015

GPU-based computing for nesting problems: The importance of sequences in static selection approaches

Autores
Rocha, P; Rodrigues, R; Miguel Gomes, A; Alves, C;

Publicação
Operations Research and Big Data: IO2015-XVII Congress of Portuguese Association of Operational Research (APDIO)

Abstract
In this paper, we address the irregular strip packing problem (or nesting problem) where irregular shapes have to be placed on strips representing a piece of material whose width is constant and length is virtually unlimited. We explore a constructive heuristic that relies on the use of graphical processing units to accelerate the computation of different geometrical operations. The heuristic relies on static selection processes, which assume that a sequence of pieces to be placed is defined a priori. Here, the emphasis is put on the analysis of the impact of these sequences on the global performance of the solution algorithm. Computational results on benchmark datasets are provided to support this analysis, and guide the selection of the most promising methods to generate these sequences.

2015

Preliminary results on soil-emitted gamma radiation and its relation with the local atmospheric electric field at Amieira (Portugal)

Autores
Lopes, F; Silva, HG; Barias, S; Barbosa, SM;

Publicação
ELECTROSTATICS 2015

Abstract
The atmospheric electric field near the Earth's surface is dominated by atmospheric pollutants and natural radioactivity, with the latter directly linked to radon (Rn-222) gas. For a better comprehension on the temporal variability of both the atmospheric electric field and the radon concentration and its relation with local atmospheric variables, simultaneous measurements of soil-emitted gamma radiation and potential gradient (defined from the vertical component of the atmospheric electric field) were taken every minute, along with local meteorological parameters (e.g., temperature, atmospheric pressure, relative humidity and daily solar radiation). The study region is Amieira, part of the Alqueva lake in Alentejo Portugal, where an interdisciplinary meteorological campaign, ALEX2014, took place from June to August 2014. Soil gamma radiation is more sensitive to small concentrations of radon as compared with alpha particles measurements, for that reason it is more suited for sites with low radon levels, as expected in this case. Preliminary results are presented here: statistical and spectral analysis show that i)the potential gradient has a stronger daily cycle as compared with the gamma radiation, ii) most of the energy of the gamma signal is concentrated in the low frequencies (close to 0), contrary to the potential gradient that has most of the energy in frequency 1 (daily cycle) and iii) a short-term relation between gamma radiation and the potential gradient has not been found. Future work and plans are also discussed.

2015

Mídia social em contexto de hibridismo e multimodalidade: o percurso da experiência na formação de mestres e doutores

Autores
Schlemmer, E;

Publicação
Revista Diálogo Educacional

Abstract
Este artigo se contextualiza no Grupo de Pesquisa Educação Digital (GPe-dU Unisinos/CNPq), vinculado à linha de pesquisa Educação, Desenvolvimento e Tecnologias, do Programa de Pós-Graduação em Educação da Unisinos e parte da problemática: Como as mídias sociais podem contribuir com o processo de formação de professores-pesquisadores em contexto de hibridismo e multimodalidade? Seu objetivo consiste em compreender e discutir os significados construídos em relação à docência para a formação do professor-pesquisador em contexto de hibridismo e multimodalidade, quando um dos espaços disponibilizados para a prática pedagógica é uma mídia social. A pesquisa, exploratória e qualitativa, é inspirada no método cartográfico e faz uso da observação; de textos e fotografia digitais; de discursos; e de acompanhamento da experiência (trilhas). Para a análise dos dados utiliza a análise textual discursiva. Os principais resultados evidenciam que as mídias sociais podem contribuir com a formação do professor-pesquisador tanto por meio da criação de grupos no âmbito das atividades acadêmicas curriculares quanto no âmbito da prática de pesquisa e da orientação. Os dados indicam que um número significativo de sujeitos continua interagindo nos grupos, mesmo após seu término, o que contribui para que se constitua enquanto uma comunidade virtual de aprendizagem e de prática, além disso, a cada novo semestre, novos sujeitos passam a integrar essa comunidade, o que enriquece as trocas, dando origem a um processo de formação continuada.

2015

Artificial Neural Network-based Methodology for Short-Term Electric Load Scenario Generation

Autores
Vagropoulos, SI; Kardakos, EG; Simoglou, CK; Bakirtzis, AG; Catalao, JPS;

Publicação
2015 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP)

Abstract
In this paper a novel scenario generation methodology based on artificial neural networks (ANNs) is proposed. The methodology is able to create scenarios for various power system-related stochastic variables. Scenario reduction methodologies can then be applied to effectively reduce the number of scenarios. An application of the methodology for the creation of short-term electric load scenarios for one day up to seven days ahead is presented. Test results on the real-world insular power system of Crete present the effectiveness of the proposed methodology.

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