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The data obtained by evaluating the real performance function allow usually constructing and refining the surrogate model.
Kriging Approximation The construction of a Kriging approximation model is based on data acquired from a computer experiment.
The likelihood of the data is maximized with respect to the parameters (β, θ, σz2).
These points are considered as pilot data and no simulation has been carried out.
The statistical properties and the structural data are given in Tables 3 and 4, respectively.

Interstitial Oxygen Concentration [Oi] (1017 cm-3) 4 5 6 7 8 9 10 Nt*/ Ndop (10 -16 cm 3/µs) 10-2 10-1 ~[Oi]1.9 Figure 4: Normalized defect concentration Nt* on the interstitial oxygen concentration [Oi] (data taken from Ref. 21).
Furthermore, the scatter in the data of Glunz et al. has been much larger, making these results less reliable.
After TD formation, they measured a pronounced reduction in the metastable defect concentration by up to a factor of 3, giving an indirect confirmation of the proposed dimer model.
MCz-Si 1.2 Ωcm [Oi] = 1.5 ppm P-dop.Cz-Si 0.6 Ωcm [Oi] = 16 ppm Figure 7: Measured carrier lifetimes of of B-, Ga-, and P-doped Cz-Si and B-doped MCz-Si before and after light soaking (data taken from Refs. 12, 36).
For comparison, cell efficiencies obtained on conventional B-doped Cz-Si before (white boxes) and after (black boxes) light degradation are shown (data taken from Refs. 34-39).

These results are necessary for comparison of conditions of zonal desintegration manifestation with geodynamic data that were obtained in mines of Ukraine.
Further growth of pressure is followed by reduction of rocks volume.
Theories about Physical Processes around Mine Workings From 1925 to 1938, data about rock pressure manifestations during underground mining had been accumulated.
Kommerell Austria 1912 Parameters of the stable equilibrium dome Calculation is executed according to the natural data 2.
Savost'yanov Ukraine 1974 Theory of destruction of the layered massif and formation of abutment pressure zones Empirical dependences according to natural data of research III.

MBD definition model In the mid 90's 737-NX project, by using the DCAC/MRM technology system, the Boeing company makes the 737 series of product drawings of all models come ture,and the use of PDM system makes the data into a configuration management system, which makes the data consistency and traceability in the design, production and inspection, maintenance link.
The successful application of DCAC/MRM in the development cycle has shorten the 50% aircraft, change the cut in half, cost reduction of 25%,which greatly improves the user satisfaction.
（3）Put forward higher requirements for the quality of enterprise application personnel MBD data integration is the single product data source of the product life cycle development procession .Three-dimensional design tool is the main means to create it, this requires a greater range of engineering, technology, equipment, quality control and management personnel to understand the connotation of MBD technology, and can use the corresponding 3D design tools. 2.
These multimedia technology data and 3D digital products, tooling data completely replaced the 2D engineering drawings and paper process instruction, multimedia information technology training for workers, as well as in the technical basis for guiding workers of the production site. 4.
management, MBD data application, to develop MBD application software based on KBE, so as to develop the greatest potential of MBD technology. 4.4 Training MBD applied talents MBD data integration is the single product data source transferring the information in the product life cycle development.

When passing the hub through the network, the data packet will be intercepted both by the auditing system and the firewall.
A. firewall’s filtration In the method, the data packets are judged by firewalls ( process S1~S5).
B. auditing system’ process to the data packet Router transmits the data packet by processed, swift, advanced distributed exchange or other ways.
In the process of disassembling and assembling the data packet, the logic, upon which auditing system decides to send the blocking request or not, is that: when disassembling and assembling the data packet, its result will be matched with the rules that has been set.
Data disassembly, reduction and distributed processing: key words’ match Data Collection Packet Analysis, Features Extraction semantic analysis Monitor and process the images extract and process the features of the screen block the harmful information and DNS data management document library of harmful informatiom monitoring strategies and the blacklist library Figure 1.

The DSEMS is a loosely coupled and data-driven system, in which all the modules are independent with each other.
Besides, the communication module transfers the data receiving from the sockets, the IRRCs and the remote sever to the data module in order to execute further processing.
Data Module.
Data module is a database which provides the interface to meet the data request requirements of the communication module, the algorithm module and the interface module.
If other module processes the relevant data in the data module and modifies the data, the data module should be informed immediately to alter the corresponding data synchronously.

At present, the common measuring method includes Fuzzy Comprehensive Evaluation, Analytic Hierarchy Process (AHP), Data Envelopment Analysis method, and Neural Network (NN), etc.
This index reflects the GM data management situation of the enterprise, and it is difficult to quantify. (6) Anticipation to social environmental projects.
The data are gathered from the Internet, including the corporate portal website, related news and reports [9,10,11].
And the standardized data are shown in Table 3.
Because the input data are between [0, 1], the transfer function for the hidden layer is Logsig, and for the output layer is Purelin.

Using the model to indentify the natural frequency of bearing rotor under different parameters, then compare identification value with experimental values shows that projections in good agreement with the experimental data.
SVM achieved data reduction.
In order to give full play to the good characteristics of SVM, we must choose specific data sets for SVM parameters.
Concrete data are shown in Table.1and Table.2: Table1: Standard input 1 2 3 4 5 6 7 8 9 2.16 2.16 2.16 2.16 2.16 2.16 2.16 2.16 2.16 7800 7800 7800 7800 7800 7800 7800 7800 7800 0.02126 0.05345 0.06029 0.09242 0.11319 0.13273 0.15754 0.17357 0.18916 0.03792 0.08874 0.09864 0.13681 0.15642 0.18511 0.21039 0.24223 0.2911 0.03991 0.05533 0.07633 0.08488 0.11204 0.13079 0.14621 0.16141 0.19165 0.2424 0.53322 0.7971 0.9644 1.121 1.3247 1.5558 1.6024 1.9018 0.22476 0.31964 0.4526 0.63948 0.84893 1.0029 1.0961 1.2341 1.3611 0.2581 0.41908 0.76388 0.95073 1.0367 1.3355 1.5853 1.7033 1.8386 20 20 20 20 20 20 20 20 20 Table2: Standard output 1 2 3 4 5 6 7 8 9 4.0957 3.7861 3.3013 3.4227 2.4099 2.4684 1.9517 1.6133 1.6367 65.4413 37.172 25.02 21.35 14.646 14.347 11.205 8.8576 9.3318 Meanwhile, in order to meet the needs of support vector machine model and have a better performance , this paper normalized the experimental data ,so that the data fall in [0,1].
Concrete data are shown in Table.3: Table 3: Error comparison of the analyzed results NO.

Some high-throughput tests combining nanoindentation tests with EPMA technology to test alloys have proven to be efficient, and a large number of compositions and performance data can be obtained just by testing a small number of materials [5, 8].
At the same time, some scholars use statistical methods such as principal component analysis [10, 11] to analyze the test data of the obtained materials, which has sped up the new material research.
Then the principal component analysis method and the alloy equivalent method are used to perform a dimensionality reduction analysis on the composition at different indentation respectively, integrating multiple composition data into specific parameters.
As shown in Table 4, the first two components contain 87.654% (>85%) of original data and corresponding eigenvalues 4.075 and 1.184 are greater than 1, indicating that the two components actually cover most information of these six elements content.
In summary, the data of composition and performance at multiple indentations can be used to establish some atlases through the method of principal component analysis, thus helping optimizing alloy composition to obtain higher or lower E and H values.

（a）1-d wavelet decomposition （b）2-d wavelet decomposition Fig.1 wavelet decomposition diagram （a）original image （b）1-d wavelet decomposition （c）2-d wavelet decomposition (d) low frequency component Fig.2 face image wavelet decomposition Eigenface method Eigenfaces is a statistical method based on the overall intensity and description for face images [5] that built on Principal Component Analysis (PCA), its purpose is that put face image from high-dimensional image space to map into low-dimensional feature space, then classification and recognition after amount of image data dimensionality reduction.
Face recognition based on wavelet transform and improved Eigenface From the above methods analysis, we can conclude that eigenface method achieve the purpose of dimensionality reduction, but the calculation also large and it didn't consider the training sample category information, so first reduce the data amount through two-dimensional wavelet transformation.