509 research outputs found
Multifractional processes with random exponent
Multifractional Processes with Random Exponent (MPRE) are obtained by replacing the Hurst parameter of Fractional Brownian Motion (FBM) with a stochastic process. This process need not be independent of the white noise generating the FBM. MPREs can be conveniently represented as random wavelet series. We will use this type of representation to study their Hölder regularity and their self-similarity
A process very similar to multifractional Brownian motion
In Ayache and Taqqu (2005), the multifractional Brownian (mBm) motion is
obtained by replacing the constant parameter of the fractional Brownian
motion (fBm) by a smooth enough functional parameter depending on the
time . Here, we consider the process obtained by replacing in the
wavelet expansion of the fBm the index by a function depending on
the dyadic point . This process was introduced in Benassi et al (2000)
to model fBm with piece-wise constant Hurst index and continuous paths. In this
work, we investigate the case where the functional parameter satisfies an
uniform H\"older condition of order \beta>\sup_{t\in \rit} H(t) and ones
shows that, in this case, the process is very similar to the mBm in the
following senses: i) the difference between and a mBm satisfies an uniform
H\"older condition of order ; ii) as a by product, one
deduces that at each point the pointwise H\"older exponent of is
and that is tangent to a fBm with Hurst parameter .Comment: 18 page
Pathological Cluster Identification by Unsupervised Analysis in 3,822 UK Biobank Cardiac MRIs
International audienceWe perform unsupervised analysis of image-derived shape and motion features extracted from 3,822 cardiac Magnetic resonance imaging (MRIs) of the UK Biobank. First, with a feature extraction method previously published based on deep learning models, we extract from each case 9 feature values characterizing both the cardiac shape and motion. Second, a feature selection is performed to remove highly correlated feature pairs. Third, clustering is carried out using a Gaussian mixture model on the selected features. After analysis, we identify 2 small clusters that probably correspond to 2 pathological categories. Further confirmation using a trained classification model and dimensionality reduction tools is carried out to support this finding. Moreover, we examine the differences between the other large clusters and compare our measures with the ground truth
Hydrographic network extraction and watersheds delimitation software of the South Oran (North Wester Algeria)
The development of space technology has allowed a better understanding and effective use of water resources through the use of Digital Terrain Models (DTM) Mapping the river system from DTM has two objectives, namely identifying first topography descriptors like hills, ridges and valleys of watersheds and second hydrological parameters to map areas of runoff recovery for a more efficient development and also a better representation of the actual land occupation. Our work is part of a methodological approach to satellite imagery processing and mapping of topographic and hydrographic parameters of watersheds. Thus, from DTM one was able to extract the full river system of the region. The results show a remarkable evolution of human activities and especially in areas of high water recovery capacity.Keywords: remote sensing, DTM, network hydrology, geographic, steppe, west of Algeria
Information-Theoretic Active Learning for Content-Based Image Retrieval
We propose Information-Theoretic Active Learning (ITAL), a novel batch-mode
active learning method for binary classification, and apply it for acquiring
meaningful user feedback in the context of content-based image retrieval.
Instead of combining different heuristics such as uncertainty, diversity, or
density, our method is based on maximizing the mutual information between the
predicted relevance of the images and the expected user feedback regarding the
selected batch. We propose suitable approximations to this computationally
demanding problem and also integrate an explicit model of user behavior that
accounts for possible incorrect labels and unnameable instances. Furthermore,
our approach does not only take the structure of the data but also the expected
model output change caused by the user feedback into account. In contrast to
other methods, ITAL turns out to be highly flexible and provides
state-of-the-art performance across various datasets, such as MIRFLICKR and
ImageNet.Comment: GCPR 2018 paper (14 pages text + 2 pages references + 6 pages
appendix
DIAMS revisited: Taming the variety of knowledge in fault diagnosis expert systems
The DIAMS program, initiated in 1986, led to the development of a prototype expert system, DIAMS-1 dedicated to the Telecom 1 Attitude and Orbit Control System, and to a near-operational system, DIAMS-2, covering a whole satellite (the Telecom 2 platform and its interfaces with the payload), which was installed in the Satellite Control Center in 1993. The refinement of the knowledge representation and reasoning is now being studied, focusing on the introduction of appropriate handling of incompleteness, uncertainty and time, and keeping in mind operational constraints. For the latest generation of the tool, DIAMS-3, a new architecture has been proposed, that enables the cooperative exploitation of various models and knowledge representations. On the same baseline, new solutions enabling higher integration of diagnostic systems in the operational environment and cooperation with other knowledge intensive systems such as data analysis, planning or procedure management tools have been introduced
Imaging of non-operated cholesteatoma: Clinical practice guidelines
SummaryMiddle ear cholesteatoma is an aggressive form of chronic otitis media requiring surgical therapy. The surgical strategy depends on the location of the lesion, its extensions to the middle ear and mastoid, the anatomical conformation of the tympanomastoid cavities and the health status of the patient (as well as his or her interest in aquatic leisure activities). For several years, imaging of the ear has been a routine test in the preoperative work-up of the disease. National guidelines for the topic “Imaging of non-operated middle ear cholesteatoma” were prepared in October 2010, for the annual congress of the French Society of Otolaryngology Head and Neck Surgery (SFORL), by a panel of experts from the SFORL, represented by the French Association of Otology and Neuro-otology (AFON), and the French Radiological Society (SFR), represented by the French Society of Head and Neck Imaging (CIREOL). These guidelines are presented in the present article
Effects of Transcranial Direct Current Stimulation on Information Processing Speed, Working Memory, Attention, and Social Cognition in Multiple Sclerosis
Multiple Sclerosis (MS) is a chronic inflammatory disease of the central nervous system. Cognitive impairment occurs in 40–65% of patients and could drastically affect their quality of life. Deficits could involve general cognition (e.g., attention and working memory) as well as social cognition. Transcranial direct current stimulation (tDCS), is a novel brain stimulation technique that has been assessed in the context of several neuropsychiatric symptoms, including those described in the context of MS. However, very rare trials have assessed tDCS effects on general cognition in MS, and none has tackled social cognition. The aim of this work was to assess tDCS effects on general and social cognition in MS. Eleven right-handed patients with MS received two blocks (bifrontal tDCS and sham, 2 mA, 20 min, anode/cathode over left/right prefrontal cortex) of 5 daily stimulations separated by a 3-week washout interval. Working memory and attention were, respectively, measured using N-Back Test (0-Back, 1-Back, and 2-Back) and Symbol Digit Modalities Test (SDMT) at the first and fifth day of each block and 1 week later. Social cognition was evaluated using Faux Pas Test and Eyes Test at baseline and 1 week after each block. Interestingly, accuracy of 1-Back test improved following sham but not active bifrontal tDCS. Therefore, active bifrontal tDCS could have impaired working memory via cathodal stimulation of the right prefrontal cortex. No significant tDCS effects were observed on social cognitive measures and SDMT. Admitting the small sample size and the learning (practice) effect that might arise from the repetitive administration of each task, the current results should be considered as preliminary and further investigations in larger patient samples are needed to gain a closer understanding of tDCS effects on cognition in MS
Correlations between the mechanical loss and atomic structure of amorphous TiO2-doped Ta2O5 coatings
<p>Highly reflective dielectric mirror coatings are critical components in a range of precision optics applications including frequency combs, optical atomic clocks, precision interferometry and ring laser gyroscopes. A key limitation to the performance in these applications is thermal noise, arising from the mechanical loss of the coatings. The origins of the mechanical loss from these coatings is not well understood.</p>
<p>Recent work suggests that the mechanical loss of amorphous Ta2O5 coatings can drop by as much as 40% when it is doped with TiO2. We use a combination of electron diffraction data and atomic modelling using molecular dynamics to probe the atomic structure of these coatings, and examine the correlations between changes in the atomic structure and changes in the mechanical loss of these coatings. Our results show the first correlation between changes in the mechanical loss and experimentally measured changes in the atomic structure resulting from variations in the level of TiO2 doping in TiO2-doped Ta2O5 coatings, in that increased homogeneity at the nearest-neighbour level appears to correlate with reduced mechanical loss. It is demonstrated that subtle but measurable changes in the nearest-neighbour homogeneity in an amorphous material can correlate with significant changes in macroscopic properties.</p>
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