Search results for "algorithms"
showing 10 items of 1716 documents
Estimation of sea surface temperature from SEVIRI data: algorithm testing and comparison with AVHRR products
2006
Three surface temperature (ST) algorithms for Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data are developed and tested. A general split window algorithm for ST estimation, a sea surface temperature (SST) algorithm and a nonlinear algorithm (NLSST) developed for SEVIRI data. The test was carried out by comparing SEVIRI data with two types of data: (a) in situ and (b) obtained with the NLSST algorithm applied to Advanced Very High Resolution Radiometer (AVHRR). The field campaign was carried out over sea using a thermal radiometer. The algorithms were applied to SEVIRI images in coincidence with the field campaign and the results show an rms error lower than 0.7 K. The comparison …
Comparison of stereo vision techniques for cloud-top height retrieval
2007
This paper presents an ongoing study for the estimation of the cloud-top height by using only geometrical methods. In agreement with some recent studies showing that it is possible to achieve reliable height estimations not only with the classical methods based on radiative transfer, this article includes a comparison of performances of a selected set of vision algorithms devoted to extract dense disparity maps or motion fields from Infra Red stereo image pairs. This collection includes both area-based techniques and an optical flow-based method and the comparison is accomplished by using a set of cloudy scenes selected from the Along-Track Scanning Radiometer (ATSR2) database. The first gr…
Maintaining Dynamic Minimum Spanning Trees: An Experimental Study
2010
AbstractWe report our findings on an extensive empirical study on the performance of several algorithms for maintaining minimum spanning trees in dynamic graphs. In particular, we have implemented and tested several variants of the polylogarithmic algorithm by Holm et al., sparsification on top of Frederickson’s algorithm, and other (less sophisticated) dynamic algorithms. In our experiments, we considered as test sets several random, semi-random and worst-case inputs previously considered in the literature together with inputs arising from real-world applications (e.g., a graph of the Internet Autonomous Systems).
Nonlinear Optical Characterization of InP@ZnS Core-Shell Colloidal Quantum Dots Using 532 nm, 10 ns Pulses
2021
InP@ZnS core-shell colloidal quantum dots (CQDs) were synthesized and characterized using the z-scan technique. The nonlinear refraction and nonlinear absorption coefficients (γ = −2 × 10−12 cm2 W−1, β = 4 × 10−8 cm W−1) of these CQDs were determined using 10 ns, 532 nm pulses. The saturable absorption (β = −1.4 × 10−9 cm W−1, Isat = 3.7 × 108 W cm−2) in the 3.5 nm CQDs dominated at small intensities of the probe pulses (I ≤ 7 × 107 W cm−2) followed by reverse saturable absorption at higher laser intensities. We report the optical limiting studies using these CQDs showing the suppression of propagated nanosecond radiation in the intensity range of 8 × 107–2 × 109 W cm−2. The role of nonline…
Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition with Spatial Sparsity Constraint
2022
Tucker decomposition can provide an intuitive summary to understand brain function by decomposing multi-subject fMRI data into a core tensor and multiple factor matrices, and was mostly used to extract functional connectivity patterns across time/subjects using orthogonality constraints. However, these algorithms are unsuitable for extracting common spatial and temporal patterns across subjects due to distinct characteristics such as high-level noise. Motivated by a successful application of Tucker decomposition to image denoising and the intrinsic sparsity of spatial activations in fMRI, we propose a low-rank Tucker-2 model with spatial sparsity constraint to analyze multi-subject fMRI dat…
Approximation algorithm for constrained coupled-tasks scheduling problem
2014
International audience; We tackle the makespan minimization coupled-tasks problem in presence of compatibility constraints. In particular, we focus on stretched coupled-tasks, i.e. coupled-tasks having the same sub-tasks execution time and idle time duration. In such context, we propose some complexity results according to several parameters and we design an efficient polynomial-time approximation algorithm.
An approximate/exact objective based search technique for solving general scheduling problems
2018
Abstract In this paper, we analyze single machine scheduling problems under the following minimization objectives: the maximum completion time (makespan), the total completion time and the maximum lateness, including fundamental practical aspects, which often occur in industrial or manufacturing reality: release dates, due dates, setup times, precedence constraints, deterioration (aging) of machines, as well as maintenance activities. To solve the problems, we propose an efficient representation of a solution and a fast neighborhood search technique, which calculates an approximation of criterion values in a constant time per solution in a neighborhood. On this basis, a novel approximate/ex…
CAMLearn : a semantic context-aware recommender system architecture : application on m-learning domain
2015
Given the rapid emergence of new mobile technologies and the growth of needs of a moving society in training, works are increasing to identify new relevant educational platforms to improve distant learning. The next step in distance learning is porting e-learning to mobile systems. This is called m-learning. So far, learning environment was either defined by an educational setting, or imposed by the educational content. In our approach, in m-learning, we change the paradigm where the system recommends content and adapts learning follow to learner's context.
Image-based MRI Gradient Estimation
2017
In order to reduce geometric distortion phenomena in MR images, every MRI system main magnet undergoes a shimming process. Since this process aims at optimizing magnetic field homogeneity within a so-called uniformity sphere, image quality outside this sphere is neglected. Since the fields vary smoothly in space, MR signal-to-noise ratio is still non-zero just outside the uniformity region, but correction of MR image distortion fails due to lack of magnetic field knowledge outside it. We propose a novel algorithm for measuring all the fields involved in the generation of images. Our proposal is based on exploitation of the distortion which can be observed in images of a known phantom. The p…
Fitting linear models and generalized linear models with large data sets in R
2009
We present an estimating algorithm to fit linear and generalized linear models not involving the QR decomposition. Some new R functions are presented and discussed. For large data sets, comparisons with respect to the well-known lm() and glm(), as well as to biglm() and bigglm() from the package biglm, show that the proposed functions speed up computation while preserving numerical stability and accuracy