9,415 research outputs found
An AER handshake-less modular infrastructure PCB with x8 2.5Gbps LVDS serial links
Nowadays spike-based brain processing emulation is
taking off. Several EU and others worldwide projects are
demonstrating this, like SpiNNaker, BrainScaleS, FACETS, or
NeuroGrid. The larger the brain process emulation on silicon is,
the higher the communication performance of the hosting
platforms has to be. Many times the bottleneck of these system
implementations is not on the performance inside a chip or a
board, but in the communication between boards. This paper
describes a novel modular Address-Event-Representation (AER)
FPGA-based (Spartan6) infrastructure PCB (the AER-Node
board) with 2.5Gbps LVDS high speed serial links over SATA
cables that offers a peak performance of 32-bit 62.5Meps (Mega
events per second) on board-to-board communications. The
board allows back compatibility with parallel AER devices
supporting up to x2 28-bit parallel data with asynchronous
handshake. These boards also allow modular expansion
functionality through several daughter boards. The paper is
focused on describing in detail the LVDS serial interface and
presenting its performance.Ministerio de Ciencia e InnovaciĂłn TEC2009-10639-C04-02/01Ministerio de EconomĂa y Competitividad TEC2012-37868-C04-02/01Junta de AndalucĂa TIC-6091Ministerio de EconomĂa y Competitividad PRI-PIMCHI-2011-076
Mobihealth: mobile health services based on body area networks
In this chapter we describe the concept of MobiHealth and the approach developed during the MobiHealth project (MobiHealth, 2002). The concept was to bring together the technologies of Body Area Networks (BANs), wireless broadband communications and wearable medical devices to provide mobile healthcare services for patients and health professionals. These technologies enable remote patient care services such as management of chronic conditions and detection of health emergencies. Because the patient is free to move anywhere whilst wearing the MobiHealth BAN, patient mobility is maximised. The vision is that patients can enjoy enhanced freedom and quality of life through avoidance or reduction of hospital stays. For the health services it means that pressure on overstretched hospital services can be alleviated
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Fast volume reconstruction from motion corrupted stacks of 2D slices
Capturing an enclosing volume of moving subjects and organs using fast individual image slice acquisition has shown promise in dealing with motion artefacts. Motion between slice acquisitions results in spatial inconsistencies that can be resolved by slice-to-volume reconstruction (SVR) methods to provide high quality 3D image data. Existing algorithms are, however, typically very slow, specialised to specific applications and rely on approximations, which impedes their potential clinical use. In this paper, we present a fast multi-GPU accelerated framework for slice-to-volume reconstruction. It is based on optimised 2D/3D registration, super-resolution with automatic outlier rejection and an additional (optional) intensity bias correction. We introduce a novel and fully automatic procedure for selecting the image stack with least motion to serve as an initial registration target. We evaluate the proposed method using artificial motion corrupted phantom data as well as clinical data, including tracked freehand ultrasound of the liver and fetal Magnetic Resonance Imaging. We achieve speed-up factors greater than 30 compared to a single CPU system and greater than 10 compared to currently available state-of-the-art multi-core CPU methods. We ensure high reconstruction accuracy by exact computation of the point-spread function for every input data point, which has not previously been possible due to computational limitations. Our framework and its implementation is scalable for available computational infrastructures and tests show a speed-up factor of 1.70 for each additional GPU. This paves the way for the online application of image based reconstruction methods during clinical examinations. The source code for the proposed approach is publicly available
The hunt for submarines in classical art: mappings between scientific invention and artistic interpretation
This is a report to the AHRC's ICT in Arts and Humanities Research Programme.
This report stems from a project which aimed to produce a series of mappings between advanced imaging information and communications technologies (ICT) and needs within visual arts research. A secondary aim was to demonstrate the feasibility of a structured approach to establishing such mappings.
The project was carried out over 2006, from January to December, by the visual arts centre of the Arts and Humanities Data Service (AHDS Visual Arts).1 It was funded by the Arts and Humanities Research Council (AHRC) as one of the Strategy Projects run under the aegis of its ICT in Arts and Humanities Research programme. The programme, which runs from October 2003 until September 2008, aims âto develop, promote and monitor the AHRCâs ICT strategy, and to build capacity nation-wide in the use of ICT for arts and humanities researchâ.2 As part of this, the Strategy Projects were intended to contribute to the programme in two ways: knowledge-gathering projects would inform the programmeâs Fundamental Strategic Review of ICT, conducted for the AHRC in the second half of 2006, focusing âon critical strategic issues such as e-science and peer-review of digital resourcesâ. Resource-development projects would âbuild tools and resources of broad relevance across the range of the AHRCâs academic subject disciplinesâ.3 This project fell into the knowledge-gathering strand.
The project ran under the leadership of Dr Mike Pringle, Director, AHDS Visual Arts, and the day-to-day management of Polly Christie, Projects Manager, AHDS Visual Arts. The research was carried out by Dr Rupert Shepherd
Autonomous monitoring framework for resource-constrained environments
Acknowledgments The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub, reference: EP/G066051/1. URL: http://www.dotrural.ac.uk/RemoteStream/Peer reviewedPublisher PD
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