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After that, selected samples were cold rolled to 30 and 75 % reduction.
Figure 2a shows the microhardness data of PA samples measured after aging at 100 °C versus aging time up to 6 days.
Figure 3 shows the DSC curve obtained at the heating rate of 10 °C/min for the cold rolled (to 30 and 75 % reductions) materials.
Figure 4 shows the microhardness data of both the deformed materials measured after ageing at 100 °C versus aging time up to several days.
Figure 4 The microhardness data of both the deformed materials measured after ageing at 100 °C versus aging time.

Then on the basis of that, proceeded the noise analysis of the turbocharger compressor, which provides theory basis for the design of turbocharger compressor noise reduction.
Fig3: Compressor Grid Model Flow field Simulation 2.1 Boundary conditions and associated Settings This article USES the air inlet boundary conditions for quality inflow boundary conditions, the air outlet boundary USES is the pressure outlet boundary conditions, and the specific data for table 1 shows the measured data.
Table 1 A certain type of turbocharger measured data Working point speed（rpm） Inlet pressure （kPa） Outlet pressure（kPa） Flow (m3/s) 1 26880 0 200 3.45 2 32000 0 230 3.92 2.2 The calculation and analysis of stress field After about 15000 times after iterated convergence residual, calculating the time is about 28 hours.
Fluent 6.3 fluid analysis software can do better in the noise evaluation of turbocharger compressor, the result can provide reference for the design of noise reduction.

Further, data on electron beam (EB) welding and solid state welding process like friction welding are scarce.
However, data on high energy density processes such as electron beam (EB) welding are scarce.
Hardness reduction is predominant at high tempering temperatures.
Tempering resulted reduction in hardness.
a) 10000C b) 10500C c) DA Table 5: Impact properties of parent metal and EB welds in different heat treated conditions X-ray diffraction data summarized in Table 10 suggests that a - phase (martensite) is present in all the conditions while; g-phase in conjunction with a is present only in the as-received parent metal, in the as-welded and HT/400 condition of the weld.

Incomplete data set usually cause bias due to differences between observed and unobserved data.
A straightforward approach to deal with this problem is to ignore the missing data and to discard those incomplete cases from the data set.
Types of problems that are usually associated with missing values are [1] 1) loss of efficiency; 2) complications in handling and analyzing the data; 3) bias resulting from differences between missing and complete data (bias estimates) and; 4) reduction of statistical power (inefficient estimates).
The equation of coefficient of determination (R2) is given as follows [3]: (15) where N is the number of imputations, Oi is the observed data points, Pi is the imputed data point,is the average of imputed data, is the average of observed data, is the standard deviation of the imputed data and is the standard deviation of the observed data.
Since the data used is a real data set, comparison was made by fitting the Gamma distribution to the data.

Fourier transform infrared spectrometer (FTIR) and electron dispersive spectrometer (EDS) data suggested that the hybrid material were composed of Au, AgCl and PPy.
The catalytic reduction and oxidation of H2O2 by Au nanoparticle-AgCl@PPy was investigated.
It can be seen in Fig.5 that the reduction peak currents of Au nanoparticle-AgCl@PPy increased 1.5 µA on addition of 20 µM H2O2 (curve a and b), demonstrating that Au nanoparticle-AgCl@PPy can catalyze the reduction of H2O2 more efficiently than AgCl@PPy.
After adsorbing large amounts of electrons, the Au nanoparticles turn from electron acceptors to electron donors, indicating that Au nanoparticles-AgCl@PPy can catalyze both the oxidation and reduction of H2O2 efficiently. 4.
After the incorporation of Au nanoparticles, AgCl@PPy showed a greatly improved catalytic activity on the reduction and oxidation of H2O2.

The hot-rolled plates were symmetrically cold rolled to 65-95% reductions in thickness and then asymmetrically warm rolled to 20-40% reductions by one pass at 473 K with a roll speed ratio of 1.5.
To reveal a change in texture during solution treatment, the area fraction of representative orientations were determined from EBSD data by using the samples annealed at 813 K for some short periods within 90 s and immediately water-quenched.
The near-{111}<110> recrystallization texture, which has a peak in the center of a {111} pole figure, is formed at relatively low reductions of AWR, while the {111} orientations hardly develop at all CR reductions under the condition of 40% AWR reduction and the main component is expressed by {013}<631>.
Here C90A25 means cold rolling to 90% reduction and asymmetric warm rolling to 25% reduction.
Fig. 10 Optical micrograph in longitudinal section for AZ31Mg sheet hot rolled to 30% reduction and asymmetrically hot rolled to 20% reduction. 50μm Fig. 11 (0001) pole density distribution for AZ31Mg sheets hot rolled to 30% reduction, asymmetrically hot rolled to 20% reduction and annealed at 573 K for 1800 s.

It can get the core of attributes by reducing redundant samples from the current data set, and then use the core as decision rules to classify the observed or measured imperfect data.
Unfortunately, the Rough Set Theory can only deal with such data sets that only contains discrete attributes while the reality is that most data sets contains both discrete and consecutive attributes at the same time.
The essence of discretization is to treat some consecutive data points as indistinguishable, and use an uniform symbol to instead all of them.
References [1] Zhao Jun, Data discretization methods based on rough set theory, Journal of Chinese Computer System, 25(1) (2004) 60-64
[8] Liu Kai, Wang Yi-Nao, Pang Yan-Jun, Data discretization methods based on clustering neural network, Computer Science, 28(5) (2001) 136-137,168

If there is no statistic data available, s data referenc as shown in Table 1[7].
Table 3 W0 data reference Maximum gravel size（mm） 16 20 25 31.5 W0(kg/m3) 235 215 210 205 Table 4 △h data reference Slump(mm) 150～180 200～220 $220 △h 0.04 0.06 0.08 The ratio of new type of high efficient water-reducing(CSP) agent to binding material should be 1%(Measured by solid). 3.7 Trial mixing for a proposal of reference mix proportion Trial mixing is carried out at a calculated mix proportion as above, by use of materials and mixing method for an involved construction project, so as to verify the mixture performance.
One of the figures is reference mix proportion, and the other two are an addition or a reduction of cement quantity by 20kg respectively, with a simultaneous reduction or addition of mineral admixture by 20kg.
One of the figures is reference mix proportion, while two of the figures are an addition or a reduction of cement quantity by 20kg respectively, with a simultaneous reduction or addition of GGBS by 20kg.
The last two figures are a reduction or an addition of GGBS by 20kg respectively, with a simultaneous addition or reduction of fly ash in equivalent quantity.

Factor Decomposition of Regional Carbon Emissions from Energy Consumption for China Ya-wei QI 1, a 1 School of Information Technology, Jiangxi Key Laboratory of Data and Knowledge Engineering, Jiangxi University of Finance & Economics, Nanchang, China a616321570@qq.com Keywords: Carbon Emissions from Energy Consumption; Factor Decomposition; LMDI; Regional Economic Development.
Data is from the IPCC (2006) and Energy Research Institute of the National Development and Reform Commission(2007).
According to the above formula, this paper calculated carbon dioxide emissions arising from energy consumption in China's 30 provinces and cities from 2000 to 2010 (Tibet is beyond the scope of inspection because of incomplete data).
According to the residual-value of index factor decomposition results and the zero-value problems of data processing, Ang further put forward Logarithmic Mean Divisia index factor decomposition method(LMDI 1).
Technical effect is the main force of reduction in carbon emission.

A piezoelectric combustion pressure sensor (Kistler, 6125) and a data acquisition board are installed to measure the in-cylinder pressure.
A Kistler crank angle encoder (0.25oCA resolution) is fixed on the crankshaft which is used to clock pressure data acquisition.
The pressure data saved was fed to the Engine Combustion Pressure (ECP) analysis software to determine the Heat release rate, Temperature, etc.
During experiments, in-cylinder pressure data was acquired for 150 consecutive cycles.
The calculation of heat release energy from engine cylinder pressure data.