7 research outputs found

    A time-based approach for multi-GHz embedded mixed-signal characterization and measurement /

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    The increasingly more sophisticated systems that are nowadays implemented on a single chip are placing stringent requirements on the test industry. New test strategies, equipment, and methodologies need to be developed to sustain the constant increase in demand for consumer and communication electronics. Techniques for built-in-self-test (BIST) and design-for-test (DFT) strategies have been proven to offer more feasible and economical testing solutions.Previous works have been conducted to perform on-chip testing, characterization, and measurement of signals and components. The current thesis advances those techniques on many levels. In terms of performance, an increase of more than an order of magnitude in speed is achieved. 70-GHz (effective sampling) on-chip oscilloscope is reported, compared to 4-GHz and 10-GHz ones in previous state-of-the-art implementations. Power dissipation is another area where the proposed work offer a superior solution compared to previous alternatives. All the proposed circuits do not exceed a few milliWatts of power dissipation, while performing multi-GHz high-speed signal capture at a medium resolution. Finally, and possibly most importantly, all the proposed circuits for test rely on a different form of signal processing; the time-based approach. It is believed that this approach paves the path to a lot of new techniques and circuit design skills that can be investigated more deeply. As an integral part of the time-based processing approach for GHz signal capture, this thesis verifies the advantages of using time amplification. The use of such amplification in the time domain is materialized with experimental results from three specific integrated circuits achieving different tasks in GHz high-speed in-situ signal measurement and characterization. Advantages of using such time-based approach techniques, when combined with the use of a front-end time amplifier, include noise immunity, the use of synthesizable digital cells, and circuit building blocks that track the technology scaling in terms of area and speed

    National Neuroinformatics Framework for Canadian Consortium on Neurodegeneration in Aging (CCNA)

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    The Canadian Institutes for Health Research (CIHR) launched the “International Collaborative Research Strategy for Alzheimer's Disease” as a signature initiative, focusing on Alzheimer's Disease (AD) and related neurodegenerative disorders (NDDs). The Canadian Consortium for Neurodegeneration and Aging (CCNA) was subsequently established to coordinate and strengthen Canadian research on AD and NDDs. To facilitate this research, CCNA uses LORIS, a modular data management system that integrates acquisition, storage, curation, and dissemination across multiple modalities. Through an unprecedented national collaboration studying various groups of dementia-related diagnoses, CCNA aims to investigate and develop proactive treatment strategies to improve disease prognosis and quality of life of those affected. However, this constitutes a unique technical undertaking, as heterogeneous data collected from sites across Canada must be uniformly organized, stored, and processed in a consistent manner. Currently clinical, neuropsychological, imaging, genomic, and biospecimen data for 509 CCNA subjects have been uploaded to LORIS. In addition, data validation is handled through a number of quality control (QC) measures such as double data entry (DDE), conflict flagging and resolution, imaging protocol checks1, and visual imaging quality validation. Site coordinators are also notified of incidental findings found in MRI reads or biosample analyses. Data is then disseminated to CCNA researchers via a web-based Data-Querying Tool (DQT). This paper will detail the wide array of capabilities handled by LORIS for CCNA, aiming to provide the necessary neuroinformatic infrastructure for this nation-wide investigation of healthy and diseased aging

    Low-power low-voltage high-speed delta-sigma analog-to-digital converters

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    The increasingly stringent requirements of today's communication systems and portable devices are imposing two challenges on the design of Analog-to-Digital Converters (ADC) and delta-sigma modulators (DeltaSigmaM) architecture in particular.The first is the extension of the input frequency range to include applications where the input bandwidth exceeds the 1 MHz range.This challenge in extending the operational speed of DeltaSigmaM is further rendered more complicated by the ever shrinking transistor dimension. As predicted by the Semiconductor Industry Association (SIA) Roadmap for CMOS technology, the transistor dimension will reach 0.05 mum in 2011. With this dramatic shrink in the transistor length, and as a result in the supply voltage, device modelling becomes ambiguous and circuit non-idealities more pronounced. The design of the main analog building blocks that minimize the time-to-market is therefore becoming very complicated.These two issues will be addressed in this thesis, namely a new design method that will minimize the design cycle of delta-sigma analog-to-digital converters (DeltaSigma ADCs) intended for high-speed applications. This method will be demonstrated efficient in the implementation of two state-of-the-art modulators in terms of performance using a widely adopted figure of merit.The validity of the top-down design methodology was verified through the fabrication of two prototype integrated circuits (ICs), both in TSMC 0.18 mum CMOS technology. In the first chip, a single-bit, fourth-order DeltaSigma ADC was implemented achieving more than 12-bit resolution. The second chip further validated the methodology to include higher resolution, in the range of 13 bits, multi-bit DeltaSigma ADCs. The experimental results from both prototype ICs closely mimic the system-level behavior of the designed modulator

    The Canadian Dementia Imaging Protocol: consistency of resting-state fMRI connectivity in a traveling human phantom, Connectivity Maps Dashboards

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    <p>The Canadian Dementia Imaging Protocol (CDIP) was developed to harmonize acquisition parameters of various imaging sequences across MRI vendors and acquisition sites.  We evaluated the consistency of brain connectivity maps generated using resting-state functional magnetic resonance imaging (rsfMRI) across 18 visits of a single individual: 3 sessions separated by several months and 6 scanning sites (3 Philips, 3 Siemens). Single time point inter-vendor consistency was also analysed using all previous sites and new ones (in total, 4 Philips, 7 Siemens and 2 GE). </p> <p>Provided in these dashboards are the connectivity maps of both parts of the study. Using NIAK (Bellec et al. 2011) we computed for each rsfMRI scan, voxel-wise connectivity maps associated with each of the 7 network templates extracted from a group-level functional brain atlas, namely, the Multiresolution Intrinsic Segmentation Template (MIST) atlas generated from 200 healthy subjects (Urchs et al. 2017).</p

    LORIS (Longitudinal Online Research and Imaging System)

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    &lt;h2&gt;What's Changed&lt;/h2&gt; &lt;ul&gt; &lt;li&gt;[media] React Warning on Upload Tab by @skarya22 in https://github.com/aces/Loris/pull/8721&lt;/li&gt; &lt;li&gt;[issue_tracker] Do not display inactive users in issue form by @charlottesce in https://github.com/aces/Loris/pull/8841&lt;/li&gt; &lt;li&gt;[LINST] skip metadatafields for surveys by @zaliqarosli in https://github.com/aces/Loris/pull/8961&lt;/li&gt; &lt;li&gt;[dictionary] Fixes for correct displaying &quot;Data Type&quot; column for the enumeration type in the &quot;Data Dictionary (Beta)&quot; table by @yagurdmitriy in https://github.com/aces/Loris/pull/8976&lt;/li&gt; &lt;li&gt;[tools] Fix efficiency of fix_candidate_age script by @CamilleBeau in https://github.com/aces/Loris/pull/8992&lt;/li&gt; &lt;li&gt;[media] fixes issue when media module try to instantiate a non existing instrument. by @racostas in https://github.com/aces/Loris/pull/8903&lt;/li&gt; &lt;li&gt;[instrument_list] Fix deprecation warning by @driusan in https://github.com/aces/Loris/pull/8867&lt;/li&gt; &lt;li&gt;[LINST] fix survey and date issues by @ridz1208 in https://github.com/aces/Loris/pull/8858&lt;/li&gt; &lt;li&gt;[JSX] Modal Width Prop by @skarya22 in https://github.com/aces/Loris/pull/8893&lt;/li&gt; &lt;li&gt;[libraries] Get examiner sites by UserID by @CamilleBeau in https://github.com/aces/Loris/pull/8994&lt;/li&gt; &lt;li&gt;[genomic_browser] Download button not showing up in the Files tab by @ridz1208 in https://github.com/aces/Loris/pull/8480&lt;/li&gt; &lt;li&gt;[issue_tracker - raisinbread/tools] Fix issue tracker history wrong module ID by @zaliqarosli in https://github.com/aces/Loris/pull/8677&lt;/li&gt; &lt;li&gt;[Issue Tracker] Issue Change Notifications by @skarya22 in https://github.com/aces/Loris/pull/8885&lt;/li&gt; &lt;li&gt;[behavioural_qc] fixes visitLevel feedback not showing up. by @racostas in https://github.com/aces/Loris/pull/8900&lt;/li&gt; &lt;li&gt;[battery_manager] Update Test Plan by @skarya22 in https://github.com/aces/Loris/pull/8782&lt;/li&gt; &lt;/ul&gt; &lt;h2&gt;New Contributors&lt;/h2&gt; &lt;ul&gt; &lt;li&gt;@yagurdmitriy made their first contribution in https://github.com/aces/Loris/pull/8976&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Full Changelog&lt;/strong&gt;: https://github.com/aces/Loris/compare/v25.0.1...v25.0.2&lt;/p&gt;If you use this software, please cite it using these metadata
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