2018
Authors
Simões, DA; Lau, N; Reis, LP;
Publication
2018 International Joint Conference on Neural Networks, IJCNN 2018, Rio de Janeiro, Brazil, July 8-13, 2018
Abstract
2018
Authors
Iria, J; Soares, F; Matos, M;
Publication
APPLIED ENERGY
Abstract
2018
Authors
Caetano Pereira, JP; Bernardes, G; Penha, R;
Publication
DAFx 2018 - Proceedings: 21st International Conference on Digital Audio Effects
Abstract
We present MusikVerb, a novel digital reverberation capable of adapting its output to the harmonic context of a live music performance. The proposed reverberation is aware of the harmonic content of an audio input signal and ‘tunes’ the reverberation output to its harmonic content using a spectral filtering technique. The dynamic behavior of MusikVerb avoids the sonic clutter of traditional reverberation, and most importantly, fosters creative endeavor by providing new expressive and musically-aware uses of reverberation. Despite its applicability to any input audio signal, the proposed effect has been designed primarily as a guitar pedal effect and a standalone software application. Copyright
2018
Authors
Abuter, R; Amorim, A; Bauboeck, M; Berger, JP; Bonnet, H; Brandner, W; Clenet, Y; du Foresto, VC; de Zeeuw, PT; Deen, C; Dexter, J; Duvert, G; Eckart, A; Eisenhauer, F; Schreiber, NMF; Garcia, P; Gao, F; Gendron, E; Genzel, R; Gillessen, S; Guajardo, P; Habibi, M; Haubois, X; Henning, T; Hippler, S; Horrobin, M; Huber, A; Jimenez Rosales, A; Jocou, L; Kervella, P; Lacour, S; Lapeyrere, V; Lazareff, B; Le Bouquin, JB; Lena, P; Lippa, M; Ott, T; Panduro, J; Paumard, T; Perraut, K; Perrin, G; Pfuhl, O; Plewa, PM; Rabien, S; Rodriguez Coira, G; Rousset, G; Sternberg, A; Straub, O; Straubmeier, C; Sturm, E; Tacconi, LJ; Vincent, F; von Fellenberg, S; Waisberg, I; Widmann, F; Wieprecht, E; Wiezorrek, E; Woillez, J; Yazici, S;
Publication
ASTRONOMY & ASTROPHYSICS
Abstract
We report the detection of continuous positional and polarization changes of the compact source SgrA* in high states ("flares") of its variable near-infrared emission with the near-infrared GRAVITY-Very Large Telescope Interferometer (VLTI) beam-combining instrument. In three prominent bright flares, the position centroids exhibit clockwise looped motion on the sky, on scales of typically 150 mu as over a few tens of minutes, corresponding to about 30% the speed of light. At the same time, the flares exhibit continuous rotation of the polarization angle, with about the same 45(+/- 15) min period as that of the centroid motions. Modelling with relativistic ray tracing shows that these findings are all consistent with a near face-on, circular orbit of a compact polarized "hot spot" of infrared synchrotron emission at approximately six to ten times the gravitational radius of a black hole of 4 million solar masses. This corresponds to the region just outside the innermost, stable, prograde circular orbit (ISCO) of a Schwarzschild-Kerr black hole, or near the retrograde ISCO of a highly spun-up Kerr hole. The polarization signature is consistent with orbital motion in a strong poloidal magnetic field.
2018
Authors
Valle, OT; Budke, G; Montez, C; Moraes, R; Vasques, F;
Publication
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
Abstract
The use of wireless sensor network nodes to support reliable communication exposes some challenging issues. For instance, the reduced available bandwidth combined with an error-prone communication medium impairs the provision of reliable communication services. Network coding techniques can be useful to mitigate some of these issues, where multiple message groups can be combined into single messages and retransmitted to their destinations, improving the network reliability and reducing the bandwidth consumption. However, an effective use of network coding requires the availability of wireless sensor network nodes able to encode/decode messages within the required timing constraints. This paper reports an experimental assessment of commercial off-the-shelf wireless sensor network nodes, running a set of network coding encoding/decoding tasks. The assessed nodes range from the high-performance ARM Cortex-M7 to the low capability Arduino Uno platforms, including some of the most popular ARM Cortex and ATMEL AVR processors. The performed experimental assessment demonstrates that highly complex network coding techniques (with fields as large as F28) can be efficiently implemented on a wide range of wireless sensor network nodes, including ARM Cortex, ATMEL AVR, and Arduino Uno platforms, smoothing some relevant reliable communication implementation issues.
2018
Authors
Campaniço, AT; Valente, A; Serôdio, R; Escalera, S;
Publication
Motricidade
Abstract
The study explores the technical optimization of an athlete through the use of intelligent system performance metrics that produce information obtained from inertial sensors associated to the coach's technical qualifications in real time, using Mixed Methods and Machine Learning. The purpose of this study is to illustrate, from the confusion matrices, the different performance metrics that provide information of high pertinence for the sports training in context. 2000 technical fencing actions with two levels of complexity were performed, captured through a single sensor applied in the armed hand and, simultaneously, the gesture’s qualification through a dichotomous way by the coach. The signals were divided into segments through Dynamic Time Warping, with the resulting extracted characteristics and qualitative assessments being fed to a Neural Network to learn the patterns inherent to a good or poor execution. The performance analysis of the resulting models returned a prediction accuracy of 76.6% and 72.7% for each exercise, but other metrics indicate the existence of high bias in the data. The study demonstrates the potential of intelligent algorithms to uncover trends not captured by other statistical methods. © Edições Desafio Singular.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.