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On the other hand is the limitation effect on the signal and propagation, including attenuation and disturbance, lead to the reduction of communication rate and reliability, and various functions of error.
The key of propagation prediction is the accumulation of measured data about the time and space characteristics of medium, so can research and grasp the change rule of the medium parameters, then we can build reasonable medium model.
Finally, on the basis of the medium model and the measured statistical data, based on the channel transfer function of simplified analytical or numerical simulation, we can establish the utility of signal field strength prediction model.
A more sophisticated model is not warranted because of a lack of data.

It is essential that an experimental design methodology be economical for extracting the maximum amount of complex in- formation, a significant reduction in experimental time, saving both material and personnel cost.
RSM approach consists of designing experiments to provide adequate and reliable measurements of the response, developing a mathematical model having the best fit to the data, obtained from the experimental design, and determining the optimal value of the independent variables that produces a maximum or minimum response.
Experimental data have been optimized in order to find every parameters synergy law to SiO2 extracting rate and relevant process mathematics model will be established to provide scientific basis for industrial production.
The analysis of variance (F-value) shows that the quadratic model is well adjusted to the experimental data.

For inlet type in the other hand, external data is needed.
The data of boundary layer velocities, kinetic energy and turbulent dissipation for different Reynolds number are extracted from wind tunnel measurement by Allegrini et al. [1].
These data are then saved as profile type and extracted to FLUENT.
Viewing from building aspect, the ratio of wind velocity at backwind building to upwind building decreased with the reduction of aspect ratio and Reynolds number.

This technique, known as Low Voltage Near-Field Electrospinning (LVNFES), allows for a more dramatic reduction ofjet instabilitiesand increases patterning and dimensional control of the fibers [5].Figure 2shows aschematic of the LVNFES setupwith theperturbation free electrospinning jet.
Preliminary data on controlled oxygen plasma etching havebeen collected on carbonizedpolyacrylonitrile (PAN) nanofibers, which are deposited using FFES and suspended on the SU-8 electrodes shown in Figure 4.
The data collected from the SEM imager are plotted in Figure 7c, which shows the carbon nanofibers etching rate at a constant power of 70W.
Preliminary data at 70W.

Photos of failure simples in different condition (a) 0°simple, (b) 90°simple, (c) ±45°simple Prediction of Strength The off -axis tensile strength data versus temperature obtained from experiment are presented in Fig. 4.
An attempt was made to forecast the strengths at other elevated temperature by fitting the data except ±45° lay-up using the method of least-squares linear.
Major reduction in transverse tensile (E2), shear (G12) modulus and transverse tensile (Y) were observed with temperature in the research.
According to the experiment data, assuming longitudinal and transverse strength has linear relationship with temperature, we forecast the values of strength at 350°C.

Off-road vehicle stability and the reduction of injuries related to off-road vehicle rollovers were areas addressed by many researchers [2—4].
The main functions of these modules are described as follows: Data Input.
It is a starting module which help users to establish an input data file (interactive mode) or specify an existing data file (batch mode) that contains all information of the system.

The data acquisition system was consisting of personal computer and Unilog datalogger of Seba Hydrometry, and data were logged at the interval of 2 minutes.
Particle Size distribution curve The moisture content was measured with Imko TDR, the TDR consist of 2 rods with 10cm of the depth, and these TDRs were connected to another Globelog datalogger for data acquisition and same this was logged after 2 minutes.
Although the toe of the slope is sensitive to rainfall, but the failure can be initiated at upper parts of the slope as well, this was due to reduction of shear strength with increasing of moisture content.

We also need to feature dimension reduction and feature selection to obtain the optimal feature subset.
The decision level fusion is to extract feature information of single-mode first, input the appropriate classifier, get single-mode state recognition results, and then use rules to fuse the single-mode experimental data to get the final recognition results.
The main parameters data is shown in Table 2.
Table 2 Main experimental data of characteristic parameters Emotional Category Duration Rate Energy Pitch average Pitch range Forman range Calm 0.74 5.43 1.75 287.45 160.73 2117.16 Happy 0.88 4.45 3.27 291.54 213.95 2122.41 Surprise 0.82 4.87 7.16 296.52 190.68 2114.61 Sad 0.93 4.31 2.93 282.52 232.05 2128.37 anger 0.61 6.54 2.15 294.16 175.69 2131.35 For each training speech sample, extract the prosody parameters, and change into a 10-dimensional feature vector.

The data presents broadening of the main peak occur at around at 2q=27.54° without any indication of diffraction peaks associated with crystalline precipitation.
The data shows that the localized minimums of FTIR spectra are observed at 524, 744, 899 and 1090 cm-1.
The data presenting the highest optical band gap of glass obtained from 5SF sample was 3.20 eV.
This reduction of band gap could be described by the highly active impurity, which occurs when SF is incorporated into Na2O-CaO-P2O5 lattice, and acts as a donor [14].

The data points are listed in table 1, in which is a stability factor, is slenderness ratio.
Table 1 The data points of Q460 equal angle steel’s column curve 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 176.855 125.312 102.330 88.649 79.131 70.304 61.252 43.791 29.499 0 Based on this data points, Least Squares of Nonlinear Function were employed to fit the column curve of Q460 equal angle steel.
The statistical analysis show that using the column curve calculated by Eq.(1) and Eq.(2) and the following formula for the Calculation of reduction factor is reasonable.