Search results for " projection"
showing 10 items of 203 documents
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
Cognitive Overload and Orthographic Errors: When Cognitive Overload Enhances Subject–Verb Agreement Errors. A Study in French Written Language
1994
Three experiments were carried out to test the hypothesis that cognitive overload enhances the occurrence of subject-verb agreement errors in French. Highly educated adults were presented orally with sentences they were required to write down. The sentences were of the types “N1 de N2 V” (Noun 1 of Noun 2 Verb: Le chien des voisins arrive/The neighbours’ dog is arriving) versus “Prl Pr2 V” (Pronoun 1 Pronoun 2 Verb: Il les aime/He likes them). In these sentences, N1 (Pr1) and N2 (Pr2) matched or mismatched in number. In the three experiments, the sentences had to be recalled either in an isolated condition (i.e. every presented sentence had to be immediately recalled) or with a concurrent …
Constraining Uncertainty in Projected Gross Primary Production With Machine Learning
2020
The terrestrial biosphere is currently slowing down global warming by absorbing about 30% of human emissions of carbon dioxide (CO2). The largest flux of the terrestrial carbon uptake is gross primary production (GPP) defined as the production of carbohydrates by photosynthesis. Elevated atmospheric CO2 concentration is expected to increase GPP (“CO2 fertilization effect”). However, Earth system models (ESMs) exhibit a large range in simulated GPP projections. In this study, we combine an existing emergent constraint on CO2 fertilization with a machine learning approach to constrain the spatial variations of multimodel GPP projections. In a first step, we use observed changes in the CO2 sea…
Kaon femtoscopy in Pb-Pb collisions at √sNN=2.76 TeV
2017
We present the results of three-dimensional femtoscopic analyses for charged and neutral kaons recorded by ALICE in Pb-Pb collisions at √ s NN = 2.76 TeV. Femtoscopy is used to measure the space-time characteristics of particle production from the effects of quantum statistics and final-state interactions in two-particle correlations. Kaon femtoscopy is an important supplement to that of pions because it allows one to distinguish between different model scenarios working equally well for pions. In particular, we compare the measured three-dimensional kaon radii with a purely hydrodynamical calculation and a model where the hydrodynamic phase is followed by a hadronic rescattering stage. The…
Deaf readers benefit from lexical feedback during orthographic processing
2019
Published: 23 August 2019 It has been proposed that poor reading abilities in deaf readers might be related to weak connections between the orthographic and lexical-semantic levels of processing. Here we used event related potentials (ERPs), known for their excellent time resolution, to examine whether lexical feedback modulates early orthographic processing. Twenty congenitally deaf readers made lexical decisions to target words and pseudowords. Each of those target stimuli could be preceded by a briefly presented matched-case or mismatched-case identity prime (e.g., ALTAR-ALTAR vs. altar- ALTAR). Results showed an early effect of case overlap at the N/P150 for all targets. Critically, thi…
The time course of orthography and phonology: ERP correlates of masked priming effects in Spanish
2009
Abstract One key issue for computational models of visual-word recognition is the time course of orthographic and phonological information during reading. Previous research, using both behavioral and event related brain potential (ERP) measures, has shown that orthographic codes are activated very early but that phonological activation starts to occur immediately afterward. Here we report an ERP masked priming experiment in Spanish that investigates this issue further by using very strict control conditions. The critical phonological comparison was between two pairs of primes having the same orthographic similarity to the target words but differing in phonological similarity (e.g., conal-CA…
Time trends and short term projections of cancer prevalence in France
2018
IF 2.888 (2017); International audience; BackgroundThis study analyzes time trends in cancer prevalence in France and provides short-term projections up to the year 2017. The 15-year prevalence for 24 cancers was estimated from the French cancer registries network (FRANCIM) incidence and survival data.MethodWe estimated prevalence using the P = I × S relationship, with flexible modeling of incidence and survival. Based on observations of the incidence and survival up to 2010, different scenarios for evolution up to 2017 were studied, combining stable and dynamic incidence and survival. The determinants of variations in prevalence (incidence, survival and demography) were quantified.ResultsA…
Effects of masked repetition priming and orthographic neighborhood in visual recognition of words.
1996
Summay.-The role of orthographic neighborhood (neighborhood size and neighborhood Erequency) in visual-word recognition was analyzed using the masked repetition-priming paradigm. Specifically, we varied stimulus-onset asynchrony (33, 50, and 67 msec.) and type of prime (identical, unrelated, unprimed) in a lexical-decision task. Analyses show additive effects of repetition and stimulus-onset asynchrony. Further, the unrelated condition overestimated the repetition effects relative ro an unprimed condition. Fachtatory effects of neighborhood size and inhibitory effects of neighborhood frequency were also found. The results are interpreted in terms of current models of visual-word recognition…
Dual-Energy CT Material Density Iodine Quantification for Distinguishing Vascular From Nonvascular Renal Lesions: Normalization Reduces Intermanufact…
2019
OBJECTIVE. The purpose of this study was to determine whether a single, uniform normalized iodine threshold reduces variability and enables reliable differentiation between vascular and nonvascular renal lesions independent of the dual-energy CT (DECT) platform used. MATERIALS AND METHODS. In this retrospective, HIPAA-compliant, institutional review board-approved study, 247 patients (156 men, 91 women; mean age ± SD, 67 ± 12 years old) with 263 renal lesions (193 nonvascular, 70 vascular) underwent unenhanced single- energy and contrast-enhanced DECT scans. One hundred and six nonvascular and 38 vascular lesions were scanned on two dual-source DECT (dsDECT) scanners, and 87 nonvascular and…
Virtual Unenhanced Images at Dual-Energy CT: Influence on Renal Lesion Characterization
2019
Background Dual-energy (DE) CT allows reconstruction of virtual noncontrast (VNC) images from a single-phase contrast agent-enhanced examination, potentially reducing the need for multiphasic CT to characterize renal lesions. However, data regarding diagnostic performance of VNC images for the characterization of renal lesions are limited. Purpose To determine whether renal mass CT performed by using VNC images allows for reliable identification of renal lesions and differentiation of contrast-enhanced from unenhanced lesions, compared with unenhanced images. Materials and Methods This is a retrospective study of 293 patients (105 women [mean age, 65 years; age range, 18-91 years] and 188 m…