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Meanwhile, disorder degree of the materials increases, as leads to the reduction of the mean free path of phonon.
However, the ionic theory of slag results show that, as the temperature increases, the network structure of slag is gradually cut off [12], the degree of disorder gradually increased so as to cause the reduction of phonon mean free path.
The data from Table 2[14] may also illustrate this point.
Because B is trivalence and Si is quadrivalent, replacing SiO2 by B2O3 will lead to the reduction of slag overall bond density.
Kunugi, et al., in: Handbook of Glass Data, edited by O.V.

Analyzing the obtained noise data from measuring noise of all activity and the noise produced by chiselling operation (Figure 2), one can observe that in the measurement points S1 and S2, the equivalent sound weighted levels are close for both measurement, but there is a big difference between the levels recorded in points 1- 6.
Typically, reductions up to 10 dBA can be achieved for A-weighted sound pressure levels.
Polishing process – linear equivalent noise pressure level for all three configurations (blue – configuration 1, red – configuration 2, green – configuration 3) After this set of measurements it was observed that for polishing process good results were obtained while for the chiselling process the data are inconclusive, so supplementary measurements were preformed (figure 6 shows grater level of noise in configuration 3).
The noise reduction obtained for this set of measurements is presented in the Table 1 and Figure 10.
Noise reduction obtained with the artificial sound source Figure 10.

Therefore, the data from first and second step need to make dimensionality reduction by factor analysis in this step and multiple standards will be condensed, extract and transform into smaller number of standards. 4) Make weighted distribution of impact factors: Retain several impact factors of evaluated design program.
Moreover, factor analysis belongs to areas of multivariate statistical analysis techniques and its main purpose is to condense data.
It basically achieves the purpose of data simplification, and determines the number of factors and communalities for each variable.
Moreover, compare each program tender process and feedback with the result of data analysis, which shows a high-degree match of each item.
Furthermore, modify the short-board factors of the feedback in tender process and data analysis, and balance them in next round of program tender.

In the case of Kallend and Davies we could actually from their own data detect a texture difference between copper and brass already at 20% reduction.
Typically this texture component first appears at about 60% reduction, reaches its maximum at about 80% reduction, then decreases with further reduction and disappears at very high reductions (higher than 95%).
Nevertheless the final texture after high reduction is a reasonably normal brass-type texture in both cases.
The experimental observations point at a composite deformation pattern at intermediate reductions.
As mentioned earlier there is a transition from MA to PSA with increasing reduction, increasing flatness of the grains.

Curves obtained by mathematical processing of the experimental data are shown in Fig. 4.
The data of Fig. 4 prove significant reduction in the intensity of wear of carbide tool with designed NMCC Ti-TiN-(ZrNbTi)N as compared with the same figure for an uncoated tool or a tool with standard coating TiN.
As it can be seen from the above data, the nature of development of wear centres on rake and flank faces of CI with NMCC Ti-TiN-(ZrNbTi)N is characterized by evenly-balanced pattern, with no visible chips and cenres of brittle fracture.
Following the analysis of the data presented in Fig. 9, it is possible to note that the pattern of change in the content of the main chemical elements (N, O, Zr, Nb, Ti, W) in NMCC Ti-TiN-(ZrNbTi) relates to a significant growth of oxygen content and reduction of nitrogen content in the areas of through cracks in zones 1, 2 and 3 (see Fig. 8).
Following the analysis of the data obtained, it is possible to note the following.

The work was started with the data collection of production and rejection report of the industry.
Current State Mapping: The production and rejection rate data was collected for three months of a particular component.
From the observed data it was found that, the product consists of around 15% as the total rejection for three months as given in Table 1.
Based on the location analysis the data was collected to know about the number of defects for eight days and given in Table 3.
Balakannan et al., Selection and evaluation of supplier by decision model of hybrid data envelopment analysis, Int.

Fuzzy C-means clustering algorithm In the fuzzy C-means clustering method, each data belongs to a cluster center according to certain fuzzy membership functions.
Objective function J is calculated as[8]: (2) Where, is the distance between the two vectorsand , is the k th samples of data, is the i th clustering prototype, i = 1，2,…, c； k = 1, 2,…, n, is weighting exponent, the objective function J is the square sum of the weighted distance between a variety of data and the corresponding cluster center.
The fault diagnosis system for bearings and data collection The developed fault diagnosis system for rolling element bearings is composed of sensors, signal treatment modules and a micro-computer.
The data converting device is a ADVANTECH PCI-1711 A/D board。
Each type of bearing has 10 groups of repeatedly collected data and each group contains 10000 sampling points.

Data reduction.
Numerical data reduction.
Data given by the simulation software isn’t in a form that permits us to extract directly the convection coefficient and the friction coefficient.
In order to extract the needed data calculation must be done using the data given in the form of temperatures, mass flow and pressures.
Fig 7 Model deviation from experiment a. pressure drop; b. friction coefficient Results and discussions After finishing the simulations and making the necessary data reduction we have obtained the Colburn number and friction coefficient for all the studied designs, the results are shown in graphical form below: Fig 8 Results: a.

The empirical research dataset includes 322 accidents data on a 15.27km continuous downgrades segment.
The accident data structure is listed in Fig. 1.
Further data analysis would be necessary before countermeasures.
Data preparation is implemented by SPSS Modeler.
Statistical and Econometric Methods for Transportation Data Analysis.

The reduction gear structure, as shown in Fig. 4.
I 2C bus interface for the two-wire interface: one clock line SDA, the second is the data line SCL.
Software design, the most important is to ensure the reliability of data storage, in the system, in addition to the hardware guarantees, the software used to save many times the data, read out the 22 when compared, and then find out the correct value of the method treatment.
Through experiments show that there are vast majority of single-store data errors during the power supply from the storage instability.
Through this treatment, even if there is a data storage error, the CPU chip, the role of monitoring, the microcontroller reset to re-run, the total allowed to deliver the correct data, multiple store data errors are minimal.