1,177 research outputs found
Crucial role of sidewalls in velocity distributions in quasi-2D granular gases
Our experiments and three-dimensional molecular dynamics simulations of
particles confined to a vertical monolayer by closely spaced frictional walls
(sidewalls) yield velocity distributions with non-Gaussian tails and a peak
near zero velocity. Simulations with frictionless sidewalls are not peaked.
Thus interactions between particles and their container are an important
determinant of the shape of the distribution and should be considered when
evaluating experiments on a tightly constrained monolayer of particles.Comment: 4 pages, 4 figures, Added reference, model explanation charified,
other minor change
Nurses\u27 Alumnae Association Bulletin, September 1958
Committee Reports
Digest of Alumnae Meetings
Graduation Awards - 1957
List of Wrong Addresses
Marriages
Necrology
New Arrivals
Physical Advances at Jefferson
President\u27s Message
School of Nursing Repor
Fusion of basic algorithms for detection and localization of vehicle plate numbers
Institut des Systèmes Intelligents et de Robotiqu
A systematic review of randomised controlled trials in rheumatoid arthritis: the reporting and handling of missing data in composite outcomes.
BACKGROUND: Most reported outcome measures in rheumatoid arthritis (RA) trials are composite, whose components comprise single measures that are combined into one outcome. The aims of this review were to assess the range of missing data rates in primary composite outcomes and to document the current practice for handling and reporting missing data in published RA trials compared to the Consolidated Standards of Reporting Trials (CONSORT) recommendations. METHODS: A systematic search for randomised controlled trials was conducted for RA trials published between 2008 and 2013 in four rheumatology and four high impact general medical journals. RESULTS: A total of 51 trials with a composite primary outcome were identified, of which 38 (75Â %) used the binary American College of Rheumatology responder index and 13 (25Â %) used the Disease Activity Score for 28 joints (DAS28). Forty-four trials (86Â %) reported on an intention-to-treat analysis population, while 7 trials (14Â %) analysed according to a modified intention-to-treat population. Missing data rates for the primary composite outcome ranged from 2-53Â % and were above 30Â % in 9 trials, 20-30Â % in 11 trials, 10-20Â % in 18 trials and below 10Â % in 13 trials. Thirty-eight trials (75Â %) used non-responder imputation and 10 (20Â %) used last observation carried forward to impute missing composite outcome data at the primary time point. The rate of dropout was on average 61Â % times higher in the placebo group compared to the treatment group in the 34 placebo controlled trials (relative rate 1.61, 95Â % CI: 1.29, 2.02). Thirty-seven trials (73Â %) did not report the use of sensitivity analyses to assess the handling of missing data in the primary analysis as recommended by CONSORT guidelines. CONCLUSIONS: This review highlights an improvement in rheumatology trial practice since the revision of CONSORT guidelines, in terms of power calculation and participant's flow diagram. However, there is a need to improve the handling and reporting of missing composite outcome data and their components in RA trials. In particular, sensitivity analyses need to be more widely used in RA trials because imputation is widespread and generally uses single imputation methods, and in this area the missing data rates are commonly differentially higher in the placebo group
Information fusion and adaptation for on-line text recognition
In this paper, we present a new writer independent system dedicated to the automatic recognition of
on-line hand-printed texts. This system uses a very large French lexicon (200000 words), which covers numerous fields
of application. The recognition process is based on the activation-verification model proposed in perceptive psychology.
A set of experts encodes the input signal and extracts probabilistic information at several levels of abstraction
(geometrical and morphological). A neural expert generates a tree of segmentation hypotheses. It is explored by a
probabilistic fusion expert that uses all the available information (geometrical, morphological and lexical) in order to
provide the best transcription of the input signal. We experiment several strategies of self-supervised writer-adaptation
on this system. The best one, called “dynamic self-supervised adaptation”, modifies the recognizer parameters
continuously. It gets recognition results close to supervised methods. These results are evaluated on a database of
90 texts (5400 words) written by 38 different writers and are very encouraging as they reach a recognition rate of 90%.Dans cet article nous présentons un nouveau système de reconnaissance de textes manuscrits scripts en
mode omni-scripteur. Ce système utilise un lexique français de très grande taille (200 000 mots), qui couvre
de nombreux champs d'application. Le processus de reconnaissance repose sur le modèle d'activationvérification
proposé en psychologie perceptive. Un ensemble d'experts code le signal d'entrée et extrait des
informations probabilistes à différents niveaux d'abstraction (géométrique, morphologique). Un expert de
segmentation neuronal génère un treillis d’hypothèses qui est exploré par un expert de fusion probabiliste qui
utilise toute l’information disponible (géométrique, morphologique et lexicale) afin de fournir la meilleure
retranscription du signal d’entrée. Nous avons expérimenté plusieurs stratégies d'adaptation non supervisée
au scripteur. La meilleure, appelée « adaptation non-supervisée dynamique» agit en continu sur les
paramètres du système. Elle permet d'atteindre des performances proches de l’une adaptation supervisée.
Les performances, évaluées sur une base de données comportant 90 textes (5 400 mots) écrits par 38 utilisateurs
différents, sont très encourageantes car elles atteignent un taux de reconnaissance de 90%
Nurses\u27 Alumnae Association Bulletin, May 1960
Accreditation of Programs in Nursing
Alumnae Meetings, 1959
Committee Reports
Greetings from the President
Highlights from first issue of Alumnae Bulletin
Living in the new nurses residence
Lost Members
Marriages
Necrology
New Arrivals
Notices
Personal Items of Interest
Report of the School of Nursing and Nursing Services
Staff Nurses Association
Student Activities
Year of tremendous growth and expansio
Combinaison de classifieurs pour la localisation de visage
Dans cette communication, nous présentons une méthode de localisation de visages dans des images couleurs combinant trois détecteurs respectivement anthropomorphique (détecteur basé sur un modèle d'apparence neuronal), géométrique (détecteur d'ellipse utilisant une Transformée de Hough Généralisée sur l'image des orientations de gradient) et colorimétrique (détecteur de teinte chair utilisant un seuillage dans l'espace CbCr). La combinaison linéaire de ces trois détecteurs produit une carte de probabilités. La localisation du visage dans l'image correspond au maximum absolu de cette carte. Nous montrons l'apport de la combinaison sur le taux de localisation des détecteurs pris isolément
Détection de visages sur des images fixes par combinaison de classifieurs discriminants et de modèles
- Cette communication présente une technique de détection de visages sur des images fixes couleur quelconques applicable à l'indexation de séquences vidéos ou à des bases d'images. Les méthodes exposées sont sans segmentation (globale) combinant une étape par modélisation (fusionnant deux classifieurs) et une étape discriminante exploitant la modélisation. On observe une très bonne capacité à détecter des visages d'orientation variée sur un fond quelconque, même avec des résolutions faibles
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