36,440 research outputs found
Analytical considerations of flow boiling heat transfer in metal-foam filled tubes
Flow boiling in metal-foam filled tube was analytically investigated based on a modified microstructure model, an original boiling heat transfer model and fin analysis for metal foams. Microstructure model of metal foams was established, by which fiber diameter and surface area density were precisely predicted. The heat transfer model for flow boiling in metal foams was based on annular pattern, in which two phase fluid was composed by vapor region in the center of the tube and liquid region near the wall. However, it was assumed that nucleate boiling performed only in the liquid region. Fin analysis and heat transfer network for metal foams were integrated to obtain the convective heat transfer coefficient at interface. The analytical solution was verified by its good agreement with experimental data. The parametric study on heat transfer coefficient and boiling mechanism was also carried out
Reduction of -Regular Noncrossing Partitions
In this paper, we present a reduction algorithm which transforms -regular
partitions of to -regular partitions of .
We show that this algorithm preserves the noncrossing property. This yields a
simple explanation of an identity due to Simion-Ullman and Klazar in connection
with enumeration problems on noncrossing partitions and RNA secondary
structures. For ordinary noncrossing partitions, the reduction algorithm leads
to a representation of noncrossing partitions in terms of independent arcs and
loops, as well as an identity of Simion and Ullman which expresses the Narayana
numbers in terms of the Catalan numbers
Charmless two-body B decays: A global analysis with QCD factorization
In this paper, we perform a global analysis of and decays
with the QCD factorization approach. It is encouraging to observe that the
predictions of QCD factorization are in good agreement with experiment. The
best fit is around . The penguin-to-tree ratio of decays is preferred to be larger than 0.3.
We also show the confidence levels for some interesting channels: , and , . For decays, they are expected to have smaller branching ratios with
more precise measurements.Comment: 20 pages, 4 figures, version to appear in Phys. Rev.
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks
Recently, Convolutional Neural Networks (ConvNets) have shown promising
performances in many computer vision tasks, especially image-based recognition.
How to effectively use ConvNets for video-based recognition is still an open
problem. In this paper, we propose a compact, effective yet simple method to
encode spatio-temporal information carried in skeleton sequences into
multiple images, referred to as Joint Trajectory Maps (JTM), and ConvNets
are adopted to exploit the discriminative features for real-time human action
recognition. The proposed method has been evaluated on three public benchmarks,
i.e., MSRC-12 Kinect gesture dataset (MSRC-12), G3D dataset and UTD multimodal
human action dataset (UTD-MHAD) and achieved the state-of-the-art results
- …