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排序方式: 共有160条查询结果,搜索用时 15 毫秒
1.
Sigal Gottlieb Julia S. Mullen Steven J. Ruuth 《Journal of scientific computing》2006,27(1-3):271-287
The weighted essentially non-oscillatory (WENO) method is an excellent spatial discretization for hyperbolic partial differential equations with discontinuous solutions. However, the time-step restriction associated with explicit methods may pose severe limitations on their use in applications requiring large scale computations. An efficient implicit WENO method is necessary. In this paper, we propose a prototype flux-implicit WENO (iWENO) method. Numerical tests on classical scalar equations show that this is a viable and stable method, which requires appropriate time-stepping methods. Future study will include the examination of such methods as well as extension of iWENO to systems and higher dimensional problems.Sigal Gottlieb - The work of this author supported by NSF grant DMS-0106743.Steven J. Ruuth - The work of this author was partially supported by a grant from NSERC Canada. 相似文献
2.
Micha Livne Leonid Sigal Nikolaus F. Troje David J. Fleet 《Computer Vision and Image Understanding》2012,116(5):648-660
It is well known that biological motion conveys a wealth of socially meaningful information. From even a brief exposure, biological motion cues enable the recognition of familiar people, and the inference of attributes such as gender, age, mental state, actions and intentions. In this paper we show that from the output of a video-based 3D human tracking algorithm we can infer physical attributes (e.g., gender and weight) and aspects of mental state (e.g., happiness or sadness). In particular, with 3D articulated tracking we avoid the need for view-based models, specific camera viewpoints, and constrained domains. The task is useful for man–machine communication, and it provides a natural benchmark for evaluating the performance of 3D pose tracking methods (vs. conventional Euclidean joint error metrics). We show results on a large corpus of motion capture data and on the output of a simple 3D pose tracker applied to videos of people walking. 相似文献
3.
Discriminative regression models have proved effective for many vision applications (here we focus on 3D full-body and head pose estimation from image and depth data). However, dataset bias is common and is able to significantly degrade the performance of a trained model on target test sets. As we show, covariate shift, a form of unsupervised domain adaptation (USDA), can be used to address certain biases in this setting, but is unable to deal with more severe structural biases in the data. We propose an effective and efficient semi-supervised domain adaptation (SSDA) approach for addressing such more severe biases in the data. Proposed SSDA is a generalization of USDA, that is able to effectively leverage labeled data in the target domain when available. Our method amounts to projecting input features into a higher dimensional space (by construction well suited for domain adaptation) and estimating weights for the training samples based on the ratio of test and train marginals in that space. The resulting augmented weighted samples can then be used to learn a model of choice, alleviating the problems of bias in the data; as an example, we introduce SSDA twin Gaussian process regression (SSDA-TGP) model. With this model we also address the issue of data sharing, where we are able to leverage samples from certain activities (e.g., walking, jogging) to improve predictive performance on very different activities (e.g., boxing). In addition, we analyze the relationship between domain similarity and effectiveness of proposed USDA versus SSDA methods. Moreover, we propose a computationally efficient alternative to TGP (Bo and Sminchisescu 2010), and it’s variants, called the direct TGP. We show that our model outperforms a number of baselines, on two public datasets: HumanEva and ETH Face Pose Range Image Dataset. We can also achieve 8–15 times speedup in computation time, over the traditional formulation of TGP, using the proposed direct formulation, with little to no loss in performance. 相似文献
4.
Colin B. Macdonald Sigal Gottlieb Steven J. Ruuth 《Journal of scientific computing》2008,36(1):89-112
Diagonally split Runge–Kutta (DSRK) time discretization methods are a class of implicit time-stepping schemes which offer
both high-order convergence and a form of nonlinear stability known as unconditional contractivity. This combination is not
possible within the classes of Runge–Kutta or linear multistep methods and therefore appears promising for the strong stability
preserving (SSP) time-stepping community which is generally concerned with computing oscillation-free numerical solutions
of PDEs. Using a variety of numerical test problems, we show that although second- and third-order unconditionally contractive
DSRK methods do preserve the strong stability property for all time step-sizes, they suffer from order reduction at large
step-sizes. Indeed, for time-steps larger than those typically chosen for explicit methods, these DSRK methods behave like
first-order implicit methods. This is unfortunate, because it is precisely to allow a large time-step that we choose to use
implicit methods. These results suggest that unconditionally contractive DSRK methods are limited in usefulness as they are
unable to compete with either the first-order backward Euler method for large step-sizes or with Crank–Nicolson or high-order
explicit SSP Runge–Kutta methods for smaller step-sizes.
We also present stage order conditions for DSRK methods and show that the observed order reduction is associated with the
necessarily low stage order of the unconditionally contractive DSRK methods.
The work of C.B. Macdonald was partially supported by an NSERC Canada PGS-D scholarship, a grant from NSERC Canada, and a
scholarship from the Pacific Institute for the Mathematical Sciences (PIMS).
The work of S. Gottlieb was supported by AFOSR grant number FA9550-06-1-0255.
The work of S.J. Ruuth was partially supported by a grant from NSERC Canada. 相似文献
5.
6.
7.
Sigal Meirovitch Zvi Shtein Tal Ben-Shalom Shaul Lapidot Carmen Tamburu Xiao Hu Jonathan A. Kluge Uri Raviv David L. Kaplan Oded Shoseyov 《International journal of molecular sciences》2016,17(9)
The fabrication of cellulose-spider silk bio-nanocomposites comprised of cellulose nanocrystals (CNCs) and recombinant spider silk protein fused to a cellulose binding domain (CBD) is described. Silk-CBD successfully binds cellulose, and unlike recombinant silk alone, silk-CBD self-assembles into microfibrils even in the absence of CNCs. Silk-CBD-CNC composite sponges and films show changes in internal structure and CNC alignment related to the addition of silk-CBD. The silk-CBD sponges exhibit improved thermal and structural characteristics in comparison to control recombinant spider silk sponges. The glass transition temperature (Tg) of the silk-CBD sponge was higher than the control silk sponge and similar to native dragline spider silk fibers. Gel filtration analysis, dynamic light scattering (DLS), small angle X-ray scattering (SAXS) and cryo-transmission electron microscopy (TEM) indicated that silk-CBD, but not the recombinant silk control, formed a nematic liquid crystalline phase similar to that observed in native spider silk during the silk spinning process. Silk-CBD microfibrils spontaneously formed in solution upon ultrasonication. We suggest a model for silk-CBD assembly that implicates CBD in the central role of driving the dimerization of spider silk monomers, a process essential to the molecular assembly of spider-silk nanofibers and silk-CNC composites. 相似文献
8.
We consider the modified conjugate gradient procedure for solving A
=
in which the approximation space is based upon the Krylov space associated with A
1/p
and
, for any integer p. For the square-root MCG (p=2) we establish a sharpened bound for the error at each iteration via Chebyshev polynomials in
. We discuss the implications of the quickly accumulating effect of an error in
in the initial stage, and find an error bound even in the presence of such accumulating errors. Although this accumulation of errors may limit the usefulness of this method when
is unknown, it may still be successfully applied to a variety of small, almost-SPD problems, and can be used to jump-start the conjugate gradient method. Finally, we verify these theoretical results with numerical tests. 相似文献
9.
Sigal L Sclaroff S Athitsos V 《IEEE transactions on pattern analysis and machine intelligence》2004,26(7):862-877
A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling, and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24 percent is observed in 17 out of 21 test sequences. In all but one case, the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation. 相似文献
10.
Dagan Hadar Sigal Gelkop Livne Vaserman Dr. Miriam Amiram 《Chembiochem : a European journal of chemical biology》2021,22(8):1379-1384
Site-specific incorporation of unnatural amino acids (uAAs) bearing a bioorthogonal group has enabled the attachment – typically at a single site or at a few sites per protein – of chemical groups at precise locations for protein and biomaterial labeling, conjugation, and functionalization. Herein, we report the evolution of chromosomal Methanocaldococcus jannaschii tyrosyl-tRNA synthetase (aaRS) for the alkyne-bearing uAA, 4-propargyloxy-l -phenylalanine (pPR), with ∼30-fold increased production of green fluorescent protein containing three instances of pPR compared with a previously described M. jannaschii-derived aaRS for pPR, when expressed from a single chromosomal copy. We show that when expressed from multicopy plasmids, the evolved aaRSs enable the production – using a genomically recoded Escherichia coli and the non-recoded BL21 E. coli strain – of elastin-like polypeptides (ELPs) containing multiple pPR residues in high yields. We further show that the multisite incorporation of pPR in ELPs facilitates the rapid, robust, and nontoxic fluorescent labeling of these proteins in bacteria. The evolved variants described in this work can be used to produce a variety of protein and biomaterial conjugates and to create efficient minimal tags for protein labeling. 相似文献