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Three questionnaires were used for different purposes: (1) the first data set was used to subject degree analysis, any index with low subject degree will be rejected; (2) the second data set was aimed to find indexes with higher value of application.
Valid data is rooted in the third questionnaire.
They provided business data of the first quarter of 2010.
Empirical study was conducted by subject degree analysis, importance analysis and AHP based on large sample data from questionnaires of experts in this industry.
The methodology uses subject degree analysis, the importance analysis and AHP to ensure the scientificity of the data processing

As the microstructure changes with ρt, the grain size increases from d = 130nm to 500nm due probably to the reduction of pore dragging effect.
4444 10101010----5555 90909090 65656565 70707070 85858585 75757575 80808080 95959595 90909090 65656565 70707070 85858585 75757575 80808080 95959595 Relative Density, Relative Density, Relative Density, Relative Density, ρρρρtttt (%)(%)(%)(%) Effective Stress, Effective Stress, Effective Stress, Effective Stress, σσσσeff ((((MPaMPaMPaMPa)))) 100100100100 1000100010001000 500500500500 200200200200 100100100100 1000100010001000 500500500500 200200200200 D e n sific atio n R ate , D e n sific atio n R ate , D e n sific atio n R ate , D e n sific atio n R ate , ρρρρtttt ((((ssss ---1111)))) D e n sific atio n R ate , D e n sific atio n R ate , D e n sific atio n R ate , D e n sific atio n R ate , ρρρρtttt ((((ssss ---1111)))) 1175117511751175°°°°C C C C ---- 80MPa80MPa80MPa80MPa 1.01.01.01.0 2.02.02.02.0 4.04.04.04.0 : Raw Data
: Raw Data: Raw Data: Raw Data : Corrected Data : Corrected Data : Corrected Data : Corrected Data Fig. 2 Densification rate ρt (=(1/ρt)(dρt/dt)) plotted as a function of the effective stress σeff [11].

Force data came from a 3D (X, Y, Z) Piezo-electric multicomponent dynamometer type YDM-III99 with control unit for dynamometer with built-in charge amplifier type YE5850.
Data acquisition card is a PC I9118 with maximum acquisition rate of 250,000 samples per second.
The digital data is acquired with 15,000 samples per second, which proved to be high enough to give reliable information during one revolution of the end mill.
The data is processed in Microsoft Excel 2000.
The cutting force data is downloaded from the oscilloscope and information on cutting force signatures are stored onto a floppy disk and post processing of the cutting force data analysis is performed using software.

The normalized results for “the-smaller-the-better” characteristics, which are applied to groove width and HAZ width in this study, can be calculated as (1) In the case of groove depth which is ‘the-larger-the-better’ characteristic, the original data can be normalized as (2) where xio(k), xi*(k), i and k are the original data, normalized data, the number of experiments, and the total number of data observations, respectively.
The Grey relational coefficients ranging from 0 to 1 are calculated to provide the relationship between the ideal, which equals 1 for the best value, and the normalized data.
The Grey relational grade indicates the degree of correlation between the reference and comparability, and becomes 1 when the two data are identical.
Experimental and Grey relational analysis data.
Although further reduction of the thermal effect can be reduced, this will be at the cost of the other performance characteristics.

NiGa, CoGa, AuCd, or AuZn were intensively investigated due to the availability of convenient radioisotopes, see for example the respective handbook on diffusion data [6].
The experimental data along with a linear fit in coordinates of the logarithm of the diffusion coefficient vs. the inverse temperature are presented in Fig. 3.
The agreement of the two independent data sets is impressive both with respect to the activation enthalpy and the absolute diffusivities.
Thus, these data represent true volume diffusion of Ni in equiatomic NiTi.
Mehrer et al.: Diffusion in Solid Metals and Alloys, Landolt-Börnstein, Numerical data and functional relationships in Science and Technology, Vol.26 (1990)

Build response objective functions with the use of forming limit drawing and acquire corresponding data through Latin hypercube design, so as to build response surface model of response objectives and design parameters.
However, objective functions of forming quality are generally complicated higher-order functions, and there may frequently be relative great errors[6] with the use of primary or quadratic polynomial regression model, which may cause that optimized data calculated under approximate model may not be optimal data in practical work.
It delivers experimental results of the previous step to the next step with narrowed sample space and to continue to experiments, and design points of this sample space possess features of random sampling, so as to guarantee substantial reduction of entire simulation times.
Give initial height data of drawbeads, conduct minimum-value optimization towards response objective function through trust region model, adopt relative change rate of response objective function as the termination criterion, and acquire optimal height data of drawbeads through iterating for eight times: 35.4, 20.5, 22.1, 30.8, and 22.9 mm.

Interpretation of Structure Model (“ISM”) is used to design a tailor made data model.
Serious city problems, such as carbon dioxide emission, traffic jam, and reduction of arable land, are more and more influencing people’s daily life.
Analysis of Influencing Factors by the ISM model Interpretative structure model (ISM) is the most commonly used tool to build up a structured data model.
The main characteristic is to separate complex system data into several subsystems (elements) data, make use of people’s time experience and specific knowledge, run large amount of calculation by computer, and finally constitute a hierarchical structure model [6].
Nominating as the Reachable Set; as the Former Set; as the joint part of both the Reachable Set and Former Set; use to represent different element classes from high to low, use P to represent an element collection within this data group and generate Formula (2) and Formula (3):

The velocity data is used as a feedback to control system during MR damper control evaluation.
A Date Acquisition System (PXI-4472B) is used with LabVIEW software to record the acceleration data and control the MR damper.
Based on the results shown in Fig. 6, compare with the OEM suspension system, a sprung mass acceleration reduction of 50% can be created by the MR damper system under on-off skyhook control.

But Doppler causes mismatch in processing of phase-coded signals when matched filtering and correlation processing is used to realize compression. [3] Pulse integration is a good way to enlarge the detection range, however methods based on pulse train transmission have ambiguous problems and false peaks of the cross-correlation output can cause an erroneous decision.[4][5] So sidelobe reduction is important in a pulse integration radar system.
Fig. 8 shows the sampling data of radar echo and range processing.
Sampling data of radar echo and range processing Fig.8 (a) is range processing when SNR=20 and fig. 8 (b) is the zoomed vision for the two neighboring targets.

This is probably the result of a temporary reduction of the surface recombination velocity on exposure to the laser light.
All data are shown with the full permission of our customers but we will not reveal the names of the vendors.
We have observed very large variations in PL and XRD data within-wafer, wafer-to-wafer and vendor-to-vendor.