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The data show that the surface energy of the dielectric after the repair process strongly depends on the process conditions like OMCTS flow, substrate temperature and choice of additives.
The surface energy data not only give information about the effectiveness of the repair process but can mainly be used to predict whether or not the material shows a good wettability.
Fig. 2: Dispersive, polar and total surface energies of the low-k dielectric in pristine condition, after etching and after application of different repair processes Fig. 3: Differences in total surface energies of the dielectric after repair and the studied cleaning solutions The data show that in most cases large energy differences occur, especially if solution C is applied on the dielectric after a repair process which distinctly lowered the polar energy contribution.
An effective repair process leads to a decrease of the polar energy part of the solid and a reduction of the total surface energy.

This article should collect 30 frames noise reduction image with no fault, then average process for the 30 frames image, and finally we can get a frame standard image.
In this paper, the acquisition of image is based on VC++ and transmits data using on-line network interface, and design the foundation platform，through the combination of flexibility in C++ and MFC wrapper class [3].
Then, collect image data and process data to display in interface.

Introduction Magnesium alloy as one of the lightest metal structural materials in engineering application，it has many structure and performance advantages and will be widely used for weight reduction, performance improvement and environmental protection in automobile industry[1].
Flow/ thermal analysis parameters Whether to perform flow analysis Whether to perform thermal analysis Whether to perform analysis of shrinkage Whether to consider the influence of gas Yes Yes Yes Yes Free surface model Flow data output frequency Temperature data output frequency Termination temperature 1 2 2 200 Results of the Numerical Simulation of Impeller’s Filling and Solidification Process.
According to the actual production data and the material properties of AZ91D magnesium alloy, the physical parameters of AZ91D and H13 have shown in Table 2[4], the combination of the die-casting process parameters: pouring temperature is 660℃, mold initial temperature is 200℃, punch injection speed is 1.5m/s, the ProCAST software was applied to simulate the filling and solidification processes of impeller.

We made test pieces using sandblasting under several conditions, and surveyed the roughness of the surface and the reduction of sphericity caused by the process.
The top-left one is a cylindrical gauge, which is used to check the diameter and cylindricity calculated from measurement data in large volume.
The top-right one is a concentric truncated cone gauge, which is used to check the concentricity of each cone and cone angle from the measurement data.
The bottom-right one is a cylindrical step with round corner, which is used to check the corner radius fitted to the measurement data with optical digitizers.

Method The measured data were used as the basis for the simulation analysis in this study.
The data were analyzed in the CFD simulation.
Simulated Concentration at Monitor Points in Area A and B According to the result of simulation in area A, the data showed significant changes (refer with: Fig. 4).
However, as shown in the cross-section view of points 1 to 9, as the conduction direction of air flow changed, the concentration of suspended aerosol particles in this region had no significant reduction, points 4, 5 and 6 showed an increasing effect.

The results have been compared with measured data from 300 K to 573 K, and applied to predict the device performance up to 773 K.
As the temperature increases, there is a reduction in saturation drain current IDS and transconductance gm, to IDS=0.149 mA and gm=1.52 mS/mm at 773 K.
The simulation results have been compared with the measured data from 300 K to 573 K, and applied to predict the device performance up to 773 K in Fig. 2 (b).
The results have been compared with measured data from 300 K to 573 K, and applied to predict the device performance up to 773 K.

The networks are always busy and they tend to increase the chance of data colliding and latency in data delivery.
If such thing happens for ordinary data, the impact wouldn’t be much of thing to consider but if this is the case for an important data then the data would be lost half way or delayed, which might cause serious damages to the system and also affects the safety of the people working in the industry.
It transmits the data to the sink in shortest possible way.
Data packet 100bytes 6.
The initial energy of each node is 100 joules, after that there is energy reduction seen as time passes.

Collection of data about the influence of the stiffness of the individual layers by an angle promotion rod and durability allow the optimal folding of the reinforcing layers and the type of reinforcement and matrix.
The reliability of the approximate theory of layered twisted rods checked by comparison with the known for some special cases the decisions and results are compared with experimental data [3].
Results for computing on the linear relations are in better agreement with the experimental data than the existing literature linearized dependence [3].
Table 1 Data of epoxide and carbon fiber.
Collection of data about the influence of the stiffness of the individual layers by an angle promotion rod and durability allow the optimal folding of the reinforcing layers and the type of reinforcement and matrix.

Least-squares statistical regression on densities and viscosities data from each of the biodiesel/diesel blend sets revealed highly linear relationships (R2 > 0.99).
The experimental data were correlated as a function of biodiesel fraction by empirical linear equation.
As seen in Table 2, it is clear from the correlation coefficients; Eq.(1) fits the data so good that it is not needed to use higher-degree equations: D= ax+b, (1) where D is density (g/cm3), a and b are coefficients and x is biodiesel fraction.
The viscosity data were correlated as a function of biodiesel fraction by empirical second-degree equation.
Because, a linear equation does not fit the data well, then it is needed to use higher-degree equation.

Established an interaction theory model of the buildings foundation and ground, used the model could calculate the changes of internal force and deformation of surrounding buildings caused by foundation pit excavation by selecting the reasonable foundation settlement equation or using the measured settlement data.
Hsieh and Ou through nineteen pit monitoring data statistical studies had also drawn a triangle settlement distribution curve (Fig.1 (a)) and groove shape settlement distribution curve (Fig.1 (b))[4, 5].
The deformation of buildings and ground reaction force distribution law Depending on the amount of measured data, caused by excavation of building deformation failure and surface deformation size, structure stiffness, properties of foundation soil, building the surface location and so on, the building deformation and ground reaction force distribution law characteristics were as follows
In addition, it could be directly calculated numerical solution of the ground additional force, the additional internal force and the additional deformation of buildings by the measured settlement data after foundation pit excavation.
The internal force and the deformation of theory of solution or numerical solution the effect of foundation pit excavation on buildings through by selection of reasonable ground foundation deformation equation or using the measured settlement data.