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1.
P. K. Yeung S. C. Kot 《International journal for numerical methods in engineering》1985,21(5):929-939
A body-fitted curvilinear co-ordinate system is used to solve the equations of two-dimensional incompressible laminar flow over bluff obstructions by finite differences. Arbitrary conditions at the corner are removed by this method. Results for a backward-facing step are in reasonable agreement with those obtained with conventional mesh systems, and the differences are explained. A treatment of a channel expansion, in comparison with empirical data, is also included. The capability of the present method to handle arbitrary two-dimensional geometries is stressed and demonstrated, using a triangle and a semi-circle as examples. 相似文献
2.
Based on a decimation-in-time decomposition, a fast split-radix algorithm for the 2D discrete Hartley transform is presented. Compared to other reported algorithms, the proposed algorithm achieves substantial savings on the number of operations and provides a wider choice of transform sizes 相似文献
3.
Sinha Swati Shaw Siddharth Biswas Kunal De Debashis Das Samir Chandra Sarkar Angsuman Bandyopadhyay Jaya 《Microsystem Technologies》2021,27(11):4087-4100
Microsystem Technologies - Single-Walled Carbon Nanotubes (SWCNTs) are widely used as potential carriers in drug delivery systems. The objective of this work was to observe the effects of pristine,... 相似文献
4.
Eigenfeature regularization and extraction in face recognition 总被引:3,自引:0,他引:3
Jiang X Mandal B Kot A 《IEEE transactions on pattern analysis and machine intelligence》2008,30(3):383-394
This work proposes a subspace approach that regularizes and extracts eigenfeatures from the face image. Eigenspace of the within-class scatter matrix is decomposed into three subspaces: a reliable subspace spanned mainly by the facial variation, an unstable subspace due to noise and finite number of training samples and a null subspace. Eigenfeatures are regularized differently in these three subspaces based on an eigenspectrum model to alleviate problems of instability, over-fitting or poor generalization. This also enables the discriminant evaluation performed in the whole space. Feature extraction or dimensionality reduction occurs only at the final stage after the discriminant assessment. These efforts facilitate a discriminative and stable low-dimensional feature representation of the face image. Experiments comparing the proposed approach with some other popular subspace methods on the FERET, ORL, AR and GT databases show that our method consistently outperforms others. 相似文献
5.
The Journal of Supercomputing - Hpcfolder is a user-friendly high-performance computing tool that can be used to analyze the performance of algorithms parallelized using MPI. It is possible to view... 相似文献
6.
Kunal Sain Abhishek Dasgupta Utpal Garain 《International Journal on Document Analysis and Recognition》2011,14(1):75-85
Performance evaluation of mathematical expression recognition systems is attempted. The proposed method assumes expressions
(input as well as recognition output) are coded following MathML or TEX/LaTEX (which also gets converted into MathML) format. Since any MathML representation follows a tree structure, evaluation of
performance has been modeled as a tree-matching problem. The tree corresponding to the expression generated by the recognizer
is compared with the groundtruthed one by comparing the corresponding Euler strings. The changes required to convert the tree
corresponding to the expression generated by the recognizer into the groundtruthed one are noted. The number of changes required
to make such a conversion is basically the distance between the trees. This distance gives the performance measure for the
system under testing. The proposed algorithm also pinpoints the positions of the changes in the output MathML file. Testing
of the proposed evaluation method considers a set of example groundtruthed expressions and their corresponding recognized
results produced by an expression recognition system. 相似文献
7.
8.
We study dynamic routing in store-and-forward packet networks where each network link has bounded buffer capacity for receiving
incoming packets and is capable of transmitting a fixed number of packets per unit of time. At any moment in time, packets
are injected at various network nodes with each packet specifying its destination node. The goal is to maximize the throughput, defined as the number of packets delivered to their destinations.
In this paper, we make some progress on throughput maximization in various network topologies. Let n and m denote the number of nodes and links in the network, respectively. For line networks, we show that Nearest-to-Go (NTG), a
natural distributed greedy algorithm, is
-competitive, essentially matching a known
lower bound on the performance of any greedy algorithm. We also show that if we allow the online routing algorithm to make centralized decisions, there is a randomized
polylog(n)-competitive algorithm for line networks as well as for rooted tree networks, where each packet is destined for the root
of the tree. For grid graphs, we show that NTG has a competitive ratio of
while no greedy algorithm can achieve a ratio better than
. Finally, for arbitrary network topologies, we show that NTG is
-competitive, improving upon an earlier bound of O(mn).
An extended abstract appeared in the Proceedings of the 8th Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005, Berkeley, CA, USA, pp. 1–13, Lecture Notes in Computer Science, vol. 1741, Springer, Berlin.
S. Angelov is supported in part by NSF Career Award CCR-0093117, NSF Award ITR 0205456 and NIGMS Award 1-P20-GM-6912-1.
S. Khanna is supported in part by an NSF Career Award CCR-0093117, NSF Award CCF-0429836, and a US-Israel Binational Science
Foundation Grant.
K. Kunal is supported in part by an NSF Career Award CCR-0093117 and NSF Award CCF-0429836. 相似文献
9.
This work proposes a method to decompose the kernel within-class eigenspace into two subspaces: a reliable subspace spanned
mainly by the facial variation and an unreliable subspace due to limited number of training samples. A weighting function
is proposed to circumvent undue scaling of eigenvectors corresponding to the unreliable small and zero eigenvalues. Eigenfeatures
are then extracted by the discriminant evaluation in the whole kernel space. These efforts facilitate a discriminative and
stable low-dimensional feature representation of the face image. Experimental results on FERET, ORL and GT databases show
that our approach consistently outperforms other kernel based face recognition methods.
相似文献
Alex KotEmail: |
10.