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In this case the maximum average grain size 〉〈D lim should not exceed (1−2)h, which was supported by the experimental data on Ge films [4].
In contrast, the experimental data on grain growth in films with 3D microstructure are very rare and not systematic enough.
Grain growth is assumed to evolve because of reduction in the total grain boundary area.
The initial grain size distribution was taken from the experimental data [10] for sputtered Ag film with 0〉〈D ≅33.9 and h=80 nm.

That causes some problems, which mostly behaves in these terms: (1) it engrosses too much bandwidth and refrains other applications; (2) some P2P software could get through the existed fire wall and security agent, opens a loophole of an enterprise network from inside, and then various virus will get into the enterprise easily, meantime the private data will be leaked; (3) the harmful content in the P2P traffic may pollute the network; (4) some resource that has intellectual property is diffused without restraint.
Literature [1] for the first time abstracts P2P total traffic as a computing process of the M/G/∞ Queuing System, which divides net traffic into there parts: short-time-traffic, ACK long-time-traffic and data micro-long-traffic.
File-sharing P2P traffic prediction model Generally, the resources shared in the File-sharing P2P network are video files and software, and the total traffic is made of the traffic generated in the stage of searching resource (signaling traffic) and downloading resource (data traffic).
Reduction of Quality (RoQ) attacks on structured peer-to-peer networks.

Generally the noise could be defined as undesired pattern incorporated in a desired data space.
Historically, it was employed for purposes of data compression.
For such predominantly noisy subtrees, a reduction in the magnitude of the noisy scaling coefficient would suppress some of the noise.
As seen in row (2), if we simply apply the generalized fractal-wavelet coding of the noisy image, at the (k:, k;) = (4,5), (with no effort to compress the data, i.e.. quantization of coefficients), a significant amount of noise is suppressed.

Efficiency factor of bearing capacity is also known as reduction factor of bearing capacity or efficiency factor of strength.
The design parameters of columns, soil, cushion, and platform were the test data of model tests on multi-element composite foundation of concrete column and lime column.
Some parameters were determined by inverse from the test data in paper [7].
Some parameters of the soil were the test data of model tests on multi-element composite foundation of concrete column and lime column.

Recently, a new robust statistic method named as Canonical Correlation Analysis (CCA) [13] was successfully applied to face recognition and facial expression recognition because of their special abilities on analyzing pair data sets.
Overview of Canonical Correlation Analysis (CCA) Considering a set of multivariate random vector data {,t=1,..
For ease of representation, the experiment is also named as Gm/Pn which means that the random images per expression are sleeted for training data and the remaining images for testing of the same expression.
Conclusion In this paper, a novel algorithm ICCA has been proposed for feature fusion and dimensionality reduction.

For data acquisition, K type thermocouples were located at the inlet and outlet of the mini-channel to measure the fluid inlet and outlet temperatures.
Hydraulic diameter μm Inner width mm Inner depth mm Heated length mm Channel wall thickness mm Inlet temperature ºC Mass flux kg/(m2·s) Heat flux kW/m2 Working pressure 1454 8.0 0.8 80 0.54 25 22.4, 44.8 5.95~10.12 1atm Data Reduction Heat loss.
Data show that only part of the applied heat flux is used for evaporation.

Isakov,” Cutting Data for turning of steel,” Industrial Press,Inc. 989 Avenue of the Americas New York, NY 10018, pp.316, 2009, ISBN 978 – 0 – 8311- 3314-6 [4] E.D.
Pandová: Natural zeolite-clinoptilolite - raw material serviceable in the reduction of toxical components at combustion engines noxious gases.
[11] J.R.Wolberg,“ Data analysis using the method of least squares: extracting the most information from experiments,“ Springer Berlin Heidelberg New York, pp.250,2006, ISBN 978-3-540-25674-8 [12] J.R.DAVIS,” Materials.
ASM Specialty Handbook,” ASM International, Materials Park,Ohio, pp.501,1998, ISBN 0-8170-545-1 [13] J.R.Wolberg,“ Data analysis using the method of least squares: extracting the most information from experiments,“ Springer Berlin Heidelberg New York, pp.250,2006, ISBN 978-3-540-25674-8 [14] K.Vasilko,“ Analytical theory of splinter machining,” Prešov FVT, pp. 338, 2007, ISBN 978-80-8073-759-7 [15] M.Neslušan.et.al.,“ Experimental methods in splinter machining,” EDIS ŽU Žilina, pp.343,2007, ISBN 978-80-8070-711-8 [16] STN ISO 3685: Tool-life testing with single-point turning tools, 1999

The transmission system consists of an 11 reduction ratio gear reducer with two plastic gears, a solid shaft driving the wings flap, a hollow sleeve , two metal ball bearings, three iron rods (rod 1 and rod 2) and two plastic rods (rod 3) as shown in Fig. 2.
Four pairs of wings tested and their geometric data and weights are listed in Table 3.
Table 3 Geometric data of the wing models tested Wing model ID A B C D Length of beam 1 [cm] 3.1 3.8 3.8 4.8 Length of beam 3 [cm] 6.6 6.6 7.6 8.6 Single wing area [cm2] 17.1 23.1 25.1 38.1 Single wing mass [g] 0.26 0.27 0.32 0.39 Table 4 Averaged lift in different motor input voltage and angle of attack for wing model B Test ID 1 2 3 4 5 6 7 8 Motor input voltage [V] 2.0 2.5 Attack [°] 0 10.6 20.0 31.8 0 10.6 20.0 31.8 Averaged lift [g] 0.47 2.06 2.79 1.40 0.54 3.16 4.08 2.90 Wing load [g·cm-2] 0.02 0.09 0.12 0.06 0.02 0.14 0.18 0.13 Table 5 Averaged lift in different wing models and motor input voltage as angle of attack is 20 deg Test ID 1 2 3 4 5 6 Motor input voltage [V] 3.0 3.8 Wing model ID A B C D B C Averaged lift [g] 4.12 4.40 4.73 3.05 7.64 7.97 Wing load [g·cm-2] 0.24 0.19 0.19 0.08 0.33 0.21 It is shown from Table 4 and 5 that the effects of wing area (spanwise length), angle of attack and motor input voltage on averaged lift are obviously for four tested wing models
In the future, design of geometric data and structural flexibility of flapping rotary wings is important to improve aerodynamic performance of MAV.

Introduction Recently, much attention has been drawn to the problem of recovering low-dimensional structure in high-dimensional signal or data from linear measurements [1, 2].
It has a lot of applications, such as: medical imaging [3] and computer vision [4, 5], especially in the field of dimensionality reduction [6] and video surveillance [7].
Suppose a large data matrix M may be decomposed as M=L0+S0+N0, where L0 has low-rank, S0 is sparse and N0 is a small perturbation.
If the data is contaminated by a little noise, the rank of the recovered low-rank matrix will increase vastly, as it shows in Fig.1 (the rank (average of experiments repeated 100) of recovered low-rank matrix by PCP-ADM (The maximum iteration number kmax=200) under different level of noise.

The calculation to find the specific vibration frequency of the body frame structure has studied and it is a part of the field of noise vibration control and reduction in cars [1, 3, 4].
Therefore, in order to accurate depict the car body framework, to be convenient for calculating and processing data, the structural fragmentation techniques was used.
The finite element modeling of the entire car body shell structure is performed on HyperMesh by meshing and processing the generated geometric model links through the transfer of model image data from Catia software to Hypermesh software.
Table 2 Statistics data of finite element model of the car body Element type Node Quadrilateral Triangle CWELD RBE2 Quantity 170860 650 5825 182 182762 Triangle element occupies 0.38 [%] After completing finite element modeling, define the material properties in the body structure.