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The removal of the data correlation is the obvious characteristics of wavelet transform which makes it become the mainly theoretical basis of the wavelet threshold shrinkage method.
Table.1 PSNR comparison by application of different denoising threshold functions Performance indicators Hard threshold Soft threshold Improved threshold PSNR(db) 80.2977 85.5973 86.4144 The data in Table 1 shows that the peak signal-to-noise ratio is higher than the application of traditional soft and hard threshold results.
Table.2 MSE comparison by application of different denoising threshold functions Performance indicators Hard threshold Soft threshold Improved threshold MSE 2.6439×10-4 1.7921×10-4 1.4857×10-4 The data in Table 2 shows that the mean squared error is lower than the application of traditional soft and hard threshold results.
Compared to the application of the traditional soft and hard threshold function noise reduction, the application of improved threshold function could get a better peak signal-to-noise ratio, mean square error and noise reduction effect.
[7] D.L.Donoho,Nonlinear Wavelet Methods for Recovery Signals,Densities,and Spectra from Indirect and Noisy Data[J].Proc.of Symp,1993,100:173-205 [8] D.L.Donoho, I.M.Johnstone.

Abdeen Mustafa Omer (2007) thought that we should be energy conservation and emissions reduction.
After reviewing and collecting relevant data, consulting relevant experts and carrying out other methods, we implement the preliminary screening of these indicators on the basis of the actual situation.
Specific building process, the first is the indicator reduction and filtering.
Rough set theory cannot deal directly with continuous indicator, so before the application of rough set methods of indicator screening, we should first through continuous indicator data discretization processing into discrete indicator data.
After scoring data preprocessing, we can get the evaluation indicator information table (see table 2).

Based on literature data[23], formation of W2C due to the reaction between the produced W and C at the cathode is spontaneous above 973 K in thermodynamic conditions.
A distinct reduction wave appeared at a potential of -0.41 V, which was attributed to the reduction of tungsten ion to metallic tungsten.
This confirmed that the reduction of tungsten ion was a one-step process.
Ag/AgCl), which corresponds to the reduction of tungsten ion.
Che,Manual of inorganic thermodynamic data.Shenyang: Northeastern university Press,Shenyang,1994

The Database of Facilities Asset Management Application in the Disaster Reduction – Case Study of Ching Yun Building in Ching Yun University Ruei-Hung Shiu1, a, Po-Hsun Sung2,b, Jyh-Dong Lin2,c, Hao-Hsien Chen3,d and Li-Rung Jeng1,a 1No.229, Jianxing Road, Zhongli City, Taoyuan County, Taiwan, R.O.C. 2No.300, Zhongda Road, Zhongli City, Taoyuan County, Taiwan R.O.C. 3Department of Civil Engineering, National Ilan University, Taiwan, R.O.C.
Asset management system demands data such as the goals set in the opening, the list of assets to create and manage systems, and performance indicators and final set of program planning and evaluation, etc.
To assess management platform is vulnerable or not, and improve the risk assessment about the software and hardware. [4] First, the study combines the business information systems and related inventory data of Ching Yun University.
Second, the important meetings of competent department confirm the priority order aim on the important system or data analysis.
Center, "Disaster risk management and vulnerability reduction: protecting the poor," 2001

Nearly monodisperse Au NPs with mean diameters of 2-6 nm are acquired via the reduction of HAuCl4 by NaBH4 in the presence of tri-n-octyl amine and dodecanethiol in solvent of toluene.
Data for Gold Nanoparticles Num HAuCl4/Toluene (mmol/ml) NaBH4/Water (g/ml) Mean diam and Deviation (nm) a 20/10 0.020/ 0.5 2.2±1.25(56.8%) b 20/10 0.010/ 1 2.0±0.75(37.5%) c 20/10 0.0025/ 1 7.6±6.81(89.6%) Figure 1 shows TEM images and UV-vis spectra of Au NPs prepared by varing concentration of the reducing agent.
Generally, increasing temperature can accelerate the solution diffusion and the reduction of gold ions because molecular collision frequency increases.
As chance for Au atoms aggregating is in corresponding with the speed of the reduction, the mean particle size grows with the increase of the reduction speed.

This study shows that the smaller pores contained in the composite results in sharp reduction of thermal conductivity, when the porosity is up to 2.66 vol.%, the thermal conductivity of composite is found to decrease by about 9.02%.
On comparison, the results obtained from the FEA are closer to the measured values of effective thermal conductivity for composites with low porosity (roughly below 6%), when exceeding this value, the FEM predictions are slightly higher than experimental data.
And the other possible reason is that the pores congregate preferentially to the interfaces between Al and SiCp, which lead to a marked reduction of the interfacial bonding and introduces additional thermal barriers, resulting in the reduction for the measured composite conductivity.
FEA shows that the pores contained in the composite results in sharp reduction of thermal conductivity.

In aprotic solvents like unbuffered DMSO, AQDS undergoes two reductions in the cathodic scan (peaks C1 and C2) corresponding to two single electron reductions to give mono- and di-anions (AQDS à AQDS. - à AQDS2-) and two corresponding oxidations in the anodic scan (peaks A1 and A2), which involve the loss of an electron in each one (AQDS2- à AQDS.- à AQDS) (7, 8).
The values of E½ vs SCE, for the first and second reduction stages (estimated from the mean values of the CV peaks were -0.801 V and -1.249 V respectively, which are in agreement with the literature (8).
The difference between reduction potentials peaks (EC1 – EC2) corresponding to AQDS. - and AQDS2- formation, respectively, (and also their counterparts EA1 – EA2), was approximately 0.44 V.
Ep values of Peak 2, corresponding to monoanion reduction (AQDS.- to AQDS2-) show a shift towards the most negative potentials, and a similar behaviour is observed in its anodic counterpart.
Summary of electrochemical data.

The simplified model is obtained through modal reduction to form the controlled plant of the active control.
The essential of modal reduction is that those modes with subordination contribution are eliminated and those modes with bigger contribution are reserved.
Basic data employed in the numerical study are as follows: the material density is , the elasticity module is , the Poisson ratio is 0.3, the dynamical friction coefficient is 0.15 and the bolt pretightening displacement is 0.5mm, the direction of which goes along the bolt shank.
Then modes reduction is processed through selecting the three main modes in PSD curves.
b) A simplified model is obtained to make up the controlled plant after model reduction.

However, a lot of potential and valuable data are not been integrated, shared, used and analyzed.
The pretreatment of process data.
The data used for model building is from the actual production data of pharmaceutical factory.
In this paper, the rank of data matrix X is 3, so the number of effective components is 2.
Data source.

OA-capped Cu nanoparticles as an additive in PAO10 perform good anti-wear and friction-reduction properties.
It is well known that several kinds of methods have been used to synthesize Cu nanoparticles, such as thermal reduction, chemical reduction, ion implantation, vacuum vapor deposition, two-phase method.
For each sample, three identical tests were performed so as to minimize data scattering.
The CO and CO2 enwrapping the nanoparticles forms reduction ambience.
So the addition of OA- capped Cu nanoparticles can effectively improve the friction-reduction properties of PAO10.