426 research outputs found
SemCW: Semantic Collaborative Writing using RST
No full textDuring collaborative writing each author works on a copy of the shared document. These copies are then merged to produce the final document. This asynchronous work is supported by several collaborative writing tools. While these tools are excellent at merging and detecting syntactic conflicts, they are not able to easily recognise semantic inconsistencies. This hinders the coherence of the document because while each individual copy might be well constructed, they may not be after the merge. To address this, we investigate the combination of the Rhetorical Structure Theory with Operational Transformation approach. In this paper, we define a data model, a set of operations to manipulate the RST structures and a set of transformation functions. A validity checker alerts the authors to areas in the text with possible semantic lapses in the merged documents
Causal Broadcast: How to Forget?
No full textCausal broadcast constitutes a fundamental communication primitive of many distributed protocols and applications. However, state-of-the-art implementations fail to forget obsolete control information about already delivered messages. They do not scale in large and dynamic systems. In this paper, we propose a novel implementation of causal broadcast. We prove that all and only obsolete control information is safely removed, at cost of a few lightweight control messages. The local space complexity of this protocol does not monotonically increase and depends at each moment on the number of messages still in transit and the degree of the communication graph. Moreover, messages only carry a scalar clock. Our implementation constitutes a sustainable communication primitive for causal broadcast in large and dynamic systems
How accurate is MOLLI T1 mapping in vivo? Validation by spin echo methods.
No full textT1 mapping is a promising quantitative tool for assessing diffuse cardiomyopathies. The purpose of this study is to quantify in vivo accuracy of the Modified Look-Locker Inversion Recovery (MOLLI) cardiac T1 mapping sequence against the spin echo gold standard, which has not been done previously. T1 accuracy of MOLLI was determined by comparing with the gold standard inversion recovery spin echo sequence in the calf muscle, and with a rapid inversion recovery fast spin echo sequence in the heart. T1 values were obtained with both conventional MOLLI fitting and MOLLI fitting with inversion efficiency correction. In the calf (n = 6), conventional MOLLI fitting produced inconsistent T1 values with error ranging from 8.0% at 90° to 17.3% at 30°. Modified MOLLI fitting with inversion efficiency correction improved error to under 7.4% at all flip angles. In the heart (n = 5), modified MOLLI fitting with inversion correction reduced T1 error to 5.5% from 14.0% by conventional MOLLI fitting. This study shows that conventional MOLLI fitting can lead to significant in vivo T1 errors when not accounting for the lower adiabatic inversion efficiency often experienced in vivo
MOLLI acquisition and data fitting: a) Simulated longitudinal magnetization during MOLLI acquisition (T<sub>1</sub> = 1000 ms, T<sub>2</sub> = 30 ms, readout flip angle = 30°, echo train length = 64, heart rate = 60 bpm).
No full text<p>Note the complex pattern of the underlying magnetization evolution due to mixed periods of bSSFP readout and free relaxation. MOLLI data are sampled at 11 inversion times marked; b) Conventional MOLLI fitting approximates the rearranged MOLLI data with a mono-exponential function to derive an apparent T<sub>1</sub>, which is then corrected according to Eq.1.</p
Example of T<sub>1</sub> maps (in ms) obtained with IR-SE, conventional MOLLI fitting and MOLLI fitting with inversion correction in the calf muscle at 30° flip angle.
No full text<p>Example of T<sub>1</sub> maps (in ms) obtained with IR-SE, conventional MOLLI fitting and MOLLI fitting with inversion correction in the calf muscle at 30° flip angle.</p
Example of myocardial T<sub>1</sub> maps (in ms) obtained with IR-FSE, conventional MOLLI fitting and MOLLI fitting with inversion correction at a 30° flip angle.
No full text<p>The IR-FSE image was taken in a separate breath-hold than the MOLLI and therefore it is at a slightly different position. Blood has been segmented out to minimize distraction due to the blood T<sub>1</sub>: IR-FSE spoils the blood signal and is not able to fit for blood T<sub>1</sub>, however MOLLI is able to fit for T<sub>1</sub> in the blood.</p
Comparison of T1 values obtained in the calf muscle (n = 6) and myocardium (n = 5) of healthy volunteers using conventional MOLLI fitting (Eq.1) and MOLLI fitting with inversion correction (Eq.2) at various flip angles (FA).
No full text<p>P values are given for comparison with the gold standard IR-SE method (calf) or IR-FSE method (myocardium).</p><p>Comparison of T1 values obtained in the calf muscle (n = 6) and myocardium (n = 5) of healthy volunteers using conventional MOLLI fitting (Eq.1) and MOLLI fitting with inversion correction (Eq.2) at various flip angles (FA).</p
SWOOKI: A Peer-to-peer Semantic Wiki
No full textInternational audienceIn this paper, we propose to combine the advantages of semantic wikis and P2P wikis in order to design a peer-to-peer semantic wiki. The main challenge is how to merge wiki pages that embed semantic annotations. Merging algorithms used in P2P wiki systems have been designed for linear text and not for semantic data. In this paper, we evaluate two optimistic replication algorithms to build a P2P semantic wiki
SWOOKI: A Peer-to-peer Semantic Wiki
No full textInternational audienceIn this paper, we propose to combine the advantages of semantic wikis and P2P wikis in order to design a peer-to-peer semantic wiki. The main challenge is how to merge wiki pages that embed semantic annotations. Merging algorithms used in P2P wiki systems have been designed for linear text and not for semantic data. In this paper, we evaluate two optimistic replication algorithms to build a P2P semantic wiki
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