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In this paper, a novel force-gradient explicit symplectic finite-difference time-domain (SFDTD) algorithm based on the type Hamiltonian decomposition is derived to investigate the propagation characteristics of electromagnetic waves, in which Maxwell's equations are numerically integrated by third-order symplectic map combined with force gradient in the time direction. The numerical...
The performance of automated analysis of cellular images is heavily influenced by the features that characterize cells or cell nuclei. In this paper, an exhaustive set of features including morphological, topological, and texture features are explored to determine the optimal features for classification of cells and cell nuclei. The optimal subset of features are obtained using popular feature selection...
This paper addresses the problem of efficient and effective parameter variation modeling and sampling in computer architecture simulations. While there has been substantial progress in accelerating simulation time for circuit designs subject to manufacturing variations, these approaches are not generally suitable for architectural studies. Toward this we investigated two complementary avenues: (1)...
This work investigates the lower bounds of wireless localization accuracy using signal strength on commodity hardware. Our work relies on trace-driven analysis using an extensive indoor experimental infrastructure. First, we report the best experimental accuracy, twice the best prior reported accuracy for any localization system. We experimentally show that adding more and more resources (e.g., training...
The openness of the lower-layer protocol stacks in cognitive radios increases the flexibility of dynamic spectrum access and promotes spectrally-efficient communications. To ensure the effectiveness of spectrum sharing, it is desirable to locate primary users, secondary users, and unauthorized users in a non-interactive fashion based on limited measurement data at receivers. In this work, we present...
There has been an increasing interest recently in identifying subcellular proteins from cellular images in order to understachind subcellular activities of cells. However, accuracies of the prediction tend to decrease with the number of protein subcellular localization classes. Therefore in this paper, we introduce a multiple-cell model with a higher-order Markov random fields (MRF) to combine predictions...
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