48,807 research outputs found
B\"{a}cklund transformations for the constrained dispersionless hierarchies and dispersionless hierarchies with self-consistent sources
The B\"{a}cklund transformations between the constrained dispersionless KP
hierarchy (cdKPH) and the constrained dispersionless mKP hieararchy (cdmKPH)
and between the dispersionless KP hieararchy with self-consistent sources
(dKPHSCS) and the dispersionless mKP hieararchy with self-consistent sources
(dmKPHSCS) are constructed. The auto-B\"{a}cklund transformations for the
cdmKPH and for the dmKPHSCS are also formulated.Comment: 11 page
Exact Algorithms for Maximum Independent Set
We show that the maximum independent set problem (MIS) on an -vertex graph
can be solved in time and polynomial space, which even is
faster than Robson's -time exponential-space algorithm
published in 1986. We also obtain improved algorithms for MIS in graphs with
maximum degree 6 and 7, which run in time of and
, respectively. Our algorithms are obtained by using fast
algorithms for MIS in low-degree graphs in a hierarchical way and making a
careful analyses on the structure of bounded-degree graphs
Stray field and superconducting surface spin valve effect in LaCaMnO/YBaCuO bilayers
Electronic transport and magnetization measurements were performed on
LaCaMnO/YBaCuO (LCMO/YBCO) bilayers
below the superconducting transition temperature in order to study the
interaction between magnetism and superconductivity. This study shows that a
substantial number of weakly pinned vortices are induced in the YBCO layer by
the large out-of-plane stray field in the domain walls. Their motion gives rise
to large dissipation peaks at the coercive field. The angular dependent
magnetoresistance (MR) data reveal the interaction between the stripe domain
structure present in the LCMO layer and the vortices and anti-vortices induced
in the YBCO layer by the out-of-plane stray field. In addition, this study
shows that a superconducting surface spin valve effect is present in these
bilayers as a result of the relative orientation between the magnetization at
the LCMO/YBCO interface and the magnetization in the interior of the LCMO layer
that can be tuned by the rotation of a small . This latter finding will
facilitate the development of superconductive magnetoresistive memory devices.
These low-magnetic field MR data, furthermore, suggest that triplet
superconductivity is induced in the LCMO layer, which is consistent with recent
reports of triplet superconductivity in LCMO/YBCO/LCMO trilayers and LCMO/YBCO
bilayers.Comment: 14 pages, 3 figure
Real-time motion data annotation via action string
Even though there is an explosive growth of motion capture data, there is still a lack of efficient and reliable methods to automatically annotate all the motions in a database. Moreover, because of the popularity of mocap devices in home entertainment systems, real-time human motion annotation or recognition becomes more and more imperative. This paper presents a new motion annotation method that achieves both the aforementioned two targets at the same time. It uses a probabilistic pose feature based on the Gaussian Mixture Model to represent each pose. After training a clustered pose feature model, a motion clip could be represented as an action string. Then, a dynamic programming-based string matching method is introduced to compare the differences between action strings. Finally, in order to achieve the real-time target, we construct a hierarchical action string structure to quickly label each given action string. The experimental results demonstrate the efficacy and efficiency of our method
Competition between Hidden Spin and Charge Orderings in Stripe Phase
The correlation between charge and spin orderings in hole-doped
antiferromagnets is studied within an effective model of quantum strings
fluctuating in an antiferromagnetic background. In particular, we perform the
direct estimation of the charge and spin long-range-order parameters by means
of the quantum Monte Carlo simulation. A hidden spin long-range order is found
to be governed by a competition between the two trends caused by increasing
hole mobility: the enhancement of the two-dimensional spin-spin correlation
mediated by hole motions and the reformation of a strong stripe order.Comment: 4 pages, 8 figures. Accepted for publication as a Rapid Communication
in Physical Review
Charmless decays and new physics effects in the mSUGRA model
By employing the QCD factorization approach, we calculate the new physics
contributions to the branching radios of the two-body charmless and
decays in the framework of the minimal supergravity (mSUGRA) model.
we choose three typical sets of the mSUGRA input parameters in which the Wilson
coefficient can be either SM-like (the case A and C) or has
a flipped-sign (the case B). We found numerically that (a) the SUSY
contributions are always very small for both case A and C; (b) for those
tree-dominated decays, the SUSY contributions in case B are also very small;
(c) for those QCD penguin-dominated decay modes, the SUSY contributions in case
B can be significant, and can provide an enhancement about to
the branching ratios of and decays, but a
reduction about to decays; and (d) the
large SUSY contributions in the case B may be masked by the large theoretical
errors dominated by the uncertainty from our ignorance of calculating the
annihilation contributions in the QCD factorization approach.Comment: 34 pages, 8 PS figures, this is the correct version
A system for learning statistical motion patterns
Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction
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