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♦ Oferta de empleo. Titulado Superior
Se buscan candidatos para un contrato de Titulado Superior en el área de Tecnología Electrónica y de Comunicaciones, asociado al Proyecto de Investigación MARAGDA (Aproximación multi-nivel al diseño orientado a la fiabilidad de circuitos integrados analógicos y digitales).  [+ info] »
Facultad de Física (Universidad de Sevilla).
18 Noviembre 2016
- La seguridad no está sólo en tu clave, sino también en tus
  microchips.
  Antonio José Acosta Jiménez y Erica Tena Sánchez.
- Visión artificial: Una revolución tecnológica silenciosa.
  Jorge Fernández Berni.
7 Noviembre 2016
La Dra. Adoración Rueda, profesora de la Universidad de Sevilla e investigadora del IMSE-CNM, ha sido galardonada con uno de los Premios FAMA destinados a reconocer y divulgar los méritos acumulados por los profesores durante una trayectoria investigadora de excelencia desarrollada en la Universidad de Sevilla. Los premios fueron entregados en el Paraninfo de la Universidad el 25 de octubre de 2016.
El Ministerio de Economía y Competitividad publicó el pasado día 27 de septiembre la Propuesta de Resolución Provisional de los Proyectos I+D+i Excelencia y los Proyectos I+D+i Retos 2016. El Instituto de Microelectrónica de Sevilla ha obtenido la aprobación de los cinco proyectos presentados a ambas convocatorias, lo que supondrá una captación de fondos cercana a un millón de euros. Los proyectos, desarrollados por equipos de investigación mixtos pertenecientes a la Universidad de Sevilla y el CSIC, se centrarán en el diseño de circuitos microelectrónicos y su uso en aplicaciones espaciales, microelectrónica para seguridad y sistemas biomédicos.

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7-20 Noviembre

El Mundo de los Chips

Oferta de servicios basados en el sistema automático de test ATE Agilent 93000

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Últimas publicaciones
Trivium hardware implementations for power reduction  »
This paper describes the use of parallelization techniques to reduce dynamic power consumption in hardware implementations of the Trivium stream cipher. Trivium is a synchronous stream cipher based on a combination of three non-linear feedback shift registers. In 2008, it was chosen as a finalist for the hardware profile of the eSTREAM project. So that their power consumption values can be compared and verified, the proposed low-power Trivium designs were implemented and characterized in 350-nm standard-cell technology with both transistors and gate-level models, in order to permit both electrical and logical simulations. The results show that the two designs decreased average power consumption by between 15% and 25% with virtually no performance loss and only a slight overhead (about 5%) in area.

Journal Paper - International Journal of Circuit Theory and Applications, first online, 2016 JOHN WILEY & SONS
DOI: 10.1002/cta.2281    ISSN: 0098-9886    » doi
J.M. Mora-Gutiérrez, C.J. Jiménez-Fernández and M. Valencia-Barrero
Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation  »
Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organization have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure and function, have been successfully applied to visual recognition and classification tasks. In addition, implementations on neuromorphic hardware have enabled large-scale networks to run in (or even faster than) real time, making spike-based neural vision processing accessible on mobile robots. Neuromorphic sensors such as silicon retinas are able to feed such mobile systems with real-time visual stimuli. A new set of vision benchmarks for spike-based neural processing are now needed to measure progress quantitatively within this rapidly advancing field. We propose that a large dataset of spike-based visual stimuli is needed to provide meaningful comparisons between different systems, and a corresponding evaluation methodology is also required to measure the performance of SNN models and their hardware implementations. In this paper we first propose an initial NE (Neuromorphic Engineering) dataset based on standard computer vision benchmarksand that uses digits from the MNIST database. This dataset is compatible with the state of current research on spike-based image recognition. The corresponding spike trains are produced using a range of techniques: rate-based Poisson spike generation, rank order encoding, and recorded output from a silicon retina with both flashing and oscillating input stimuli. In addition, a complementary evaluation methodology is presented to assess both model-level and hardware-level performance. Finally, we demonstrate the use of the dataset and the evaluation methodology using two SNN models to validate the performance of the models and their hardware implementations. With this dataset we hope to (1) promote meaningful comparison between algorithms in the field of neural computation, (2) allow comparison with conventional image recognition methods, (3) provide an assessment of the state of the art in spike-based visual recognition, and (4) help researchers identify future directions and advance the field.

Journal Paper - Frontiers in Neuroscience, vol. 10, article 496, 2016 FRONTIERS RESEARCH FOUNDATION
DOI: 10.3389/fnins.2016.00496    ISSN: 1662-453X    » doi
Q. Liu, G. Pineda-Garcia, E. Stromatias, T. Serrano-Gotarredona and S.B. Furber
Introduction to the special issue on SMACD 2015  »
Abstract not avaliable

Journal Paper - Integration, the VLSI Journal, vol. 55, pp 293-294, 2016 ELSEVIER
DOI: 10.1016/j.vlsi.2016.09.001    ISSN: 0167-9260    » doi
G. Dundar, N. Horta and F.V. Fernandez
Hairiness: the missing link between pollinators and pollination  »
Functional traits are the primary biotic component driving organism influence on ecosystem functions; in consequence, traits are widely used in ecological research. However, most animal trait-based studies use easy-to-measure characteristics of species that are at best only weakly associated with functions. Animal-mediated pollination is a key ecosystem function and is likely to be influenced by pollinator traits, but to date no one has identified functional traits that are simple to measure and have good predictive power. Here, we show that a simple, easy to measure trait (hairiness) can predict pollinator effectiveness with high accuracy. We used a novel image analysis method to calculate entropy values for insect body surfaces as a measure of hairiness. We evaluated the power of our method for predicting pollinator effectiveness by regressing pollinator hairiness (entropy) against single visit pollen deposition (SVD) and pollen loads on insects. We used linear models and AICC model selection to determine which body regions were the best predictors of SVD and pollen load. We found that hairiness can be used as a robust proxy of SVD. The best models for predicting SVD for the flower species Brassica rapa and Actinidia deliciosa were hairiness on the face and thorax as predictors (R2 = 0.98 and 0.91 respectively). The best model for predicting pollen load for B. rapa was hairiness on the face (R2 = 0.81). Accordingly, we suggest that the match between pollinator body region hairiness and plant reproductive structure morphology is a powerful predictor of pollinator effectiveness. We show that pollinator hairiness is strongly linked to pollination -an important ecosystem function, and provide a rigorous and time-efficient method for measuring hairiness. Identifying and accurately measuring key traits that drive ecosystem processes is critical as global change increasingly alters ecological communities, and subsequently, ecosystem functions worldwide.

Journal Paper - no. e2433v1, PeerJ Preprints, 2016 PEERJ
DOI: 10.7287/peerj.preprints.2433v1    » doi
J.R. Stavert, G. Liñán-Cembrano, J.R. Beggs, B.G. Howlett, D.E. Pattemore and I. Bartomeus
Comparative Analysis of Projected Tunnel and CMOS Transistors for Different Logic Application Areas  »
In this paper, five projected tunnel FET (TFET) technologies are evaluated and compared with MOSFET and FinFET transistors for high-performance low-power objectives. The scope of this benchmarking exercise is broader than that of previous studies in that it seeks solutions to different identified limitations. The power and the energy of the technologies are evaluated and compared assuming given operating frequency targets. The results clearly show how the power/energy advantages of TFET devices are heavily dependent on required operating frequency, switching activity, and logic depth, suggesting that architectural aspects should be taken into account in benchmarking experiments. Two of the TFET technologies analyzed prove to be very promising for different operating frequency ranges and, therefore, for different application areas.

Journal Paper - IEEE Transactions on Electron Devices, first online, 2016 IEEE
DOI: 10.1109/TED.2016.2616891    ISSN: 0018-9383    » doi
J. Núñez and M.J. Avedillo

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