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In data processing, various data analysis methods are also implicated, for example, the frequency spectrum analysis method[2], coherence function[3], and various other data analysis methods.
At present, the interior noise of domestic corresponding models is around 75dB at 120km/h, fluctuating within 2dB.The test vehicle reaches above 80dB. so the noise reduction measures would be necessary.
The collected noise data at constant speed was analyzed with the 1/3 times frequency spectrum, as shown in fig. 1.
The structural characteristics of the body are modified. 4 Summary Upon the loud interior noise problem in a newly developed vehicle sample, profound analysis is carried out on every experimental data; the main sources of the vehicle interior noise are identified.
Glazing for vehicle interior noise reduction [ C ] (SAE Paper ,200220121993).

Experimental data indicate that the proposed method does not negatively affect to the surface integrity and the process validity has been verified.
Moreover,conventional methods of delivering grinding fluid, i.e. flood delivery via a shoe or jet delivery tangential to the wheel via a nozzle, are not believed to fully penetrate this boundary layer and, thus, the majority of the grinding fluid is deflected away from the grinding zone[2].Therefore, the flood delivery of a grinding fluid not only increases hydrodynamic lift force, results in reduction in the depth of cutting, and increases grinding wheel spindle distortion, but also entails high costs in production and creatse several techno-environmental problems, biological problems, and soil contamination during disposal.
The drastic reduction or even the complete elimination of this fluid can undoubtedly lead to higher temperatures in the process, causing reduced cutting tool output, loss of dimensional and geometrical precision of the workpieces and variations in the machine thermal behavior.
When abrasive tools are used, a reduction in grinding fluid may make it difficult to keep the grinding wheel pores clean, favoring the tendency for clogging and thus strongly contributing to the aforementioned negative factors[3].

Dependencies between the initial characteristics of a metal and characteristics, formed during the drawing, proceeding only from the data about standard mechanical characteristics, chemical composition, microstructure, etc., have not found adequate consideration in the literature and periodicals.
Route parameters Input parameter of the wire rod, [mm] Drawing velocity, [m/s] No. of the block 1 2 3 4 5 6 7 Route No.1 Diameter of the wire, mm 5.5 8…14 4.68 3.99 3.42 2.95 2.56 2.24 1.98 Reduction, % 27.6 27.31 26.53 25.60 24.69 23.44 21.87 Die angle, degrees 12 12 12 12 12 12 12 Route No.2 Diameter of the wire, mm 5.5 8…14 4.76 4.17 3.68 3.28 2.95 2.69 2.48 Reduction, % 25.1 23.25 22.12 20.56 19.11 16.85 15.00 Die angle, degrees 12 12 12 12 12 9 12 Table 2.
Route parameters Input parameter of the wire rod, [mm] Drawing velocity, [m/s] No. of the block 1 2 3 4 5 6 7 8 9 Route No.1 Diameter of the wire, mm 2.48 10…14 2.26 2.07 1.90 1.77 1.66 1.57 Reduction, % 16.95 16.11 15.75 13.22 12.04 10.55 Die angle, degrees 12 9 9 9 9 9 Route No.2 Diameter of the wire, mm 2.48 12…18 2,22 1,99 1,79 1,64 1,50 1,39 1,30 1,23 1,17 Reduction, % 21,15 19,65 19,09 16,06 16,34 14,13 12,53 10,48 9,52 Die angle, degrees 12 12 12 9 9 12 9 9 9 Route No.3 Diameter of the wire, mm 1.98 17…20 1.78 1.6 1.46 1.34 1.24 1.15 1.08 1.03 0.98 Reduction, % 20.79 19.20 16.37 15.76 14.37 13.99 11.80 9.04 9.47 Die angle, degrees 12 12 9 12 9 9 9 9 9 Route No.4 Diameter of the wire, mm 1.98 20…24 1.73 1.52 1.34 1.19 1.07 0.98 0.9 0.83 0.77 Reduction, % 25.18 22.80 22.28 21.14 19.15 16.11 15.66 14.95 13.94 Die angle, degrees 12 12 9 12 12 9 9 9 9 Route No.5 Diameter of the wire, mm 1.98 12…18 1.79 1.64 1.50 1.39 1.30 1.23 1.17 Reduction, % 18.27 16.06 16.34 14.13
Statistical processing of the obtained data revealed characteristic approximating functions of the parameters from the specimen drawing ratio.
(6) where is value of hardening index for , i.e. for 2.71-time reduction of the initial cross-sectional area, – the value of hardening index for .

The biomimetic highly-efficient drag reduction surface can be directly replicated by shark skin as biological template, and the pre cured micro-embossing technology is put forward aiming at the thermosetting materials.
Fig.3 Biological scale and particular cross section curve Fig.4 Corresponding negative template and cross section curve In accordance with the data in the above pictures, the handled curves are shown in figure 5.
By the available data, the replication-precision on the horizontal direction is almost 100%, and the replication-precision of the two different grooves on the vertical direction is about 98.2% (10.4495/10.645) and 93.8% (10.92559/11.6457) respectively.
According to the pictures, carrying out the relevant data of corresponding single scale and negative template, the handled curves can be received, as shown in figure 8, the maximum of the replication error on the vertical direction is 0.85um, and the replication precision on the horizontal direction is almost 100%.
The measured distances of different scales are shown in figure 11 and figure 12, and the corresponding distances of different scales are signed in the two pictures, the data of distances and replication error are shown in Table 2.

This allows to compare two different damage parameters, the crack density and the stiffness reduction over the life of the specimens.
All data presented here were derived after analyzing each area.
Acknowledgement The data presented here have been obtained in the frame of the German Research Foundation (DFG) Focus Project SPP1123 "Textile Composites" under the grant number HO2122/6-3 References [1] S.

This ZnO reaction pattern is following the data model referring to the Crystallography Open Database (COD) number 9004182.
The model data has ZnO lattice parameters, namely a = b = 3.2316 Å and c = 5.2051 Å.
Meanwhile, position 2θ 37.46o (111) is a diffraction pattern of Au according to the Open Database Crystallography (COD) data model number 9013044, lattice parameter a = b = 4.2500 Å, and space group Fm-3m.
The reduction in energy bandgap is due to the agglomeration of Au nanoparticles [16].
The resulting reduction and oxidation peaks are related to the interconversion of the PANI layer's oxidation level in the electrolyte [36].

What should also be prevented is the user being unnecessarily confronted with two systems, especially as production data are also quality data.
The result is a reduction in message dialogs, interfaces are avoided and there is greater acceptance on the part of the users.
The design of software use c++ network library to realize agile and effective network communication, and with SPC theory to achieve effective on-line monitoring of the production process, The whole system has intelligent data acquisition, effective data management, process capability index, drawing process control charts and abnormal condition automatic early warning function.
In MES, the integration of production and quality management means that all relevant data can be clearly displayed within an application [3].
Quality information center must cover the following areas: quality historical data management; quality report forms; quality cost account.

Field trails in the headentry, and by analyzing the rock pressure monitoring data, field tests showed that the effect of supporting is good.
The immediate roof is siltstone, with horizontal bedding, fracture developed fully, the bearing capacity is bad; partial is mudstone, and it rapidly became expansion and argillization after it met water, exacerbated its reduction in the intensity
Partition of anchor drilling water tricking roof of coal roadway and measured results Parameters Water tricking area Water gushing area Weak Medium Strong Weak Medium Strong Drench water standard(mL/s) [0,10] (10,50] (50,100] (100,150] (150,300] (300,+∞） Measured water spray(mL/s) [0,8] [14,42] [72,96] [126,143] Length(m) 21 18 37 24 0 0 Test roadway bolting with wire mesh for weak gushing and tricking conditions, mainly to prevent under the joint action of water tricking and gushing penetration and surrounding rock stress, from the reduction of the bearing capacity of the surrounding rock, reducing the strength of the support system, leading to the destabilization of surrounding rock deformation.
According to observation data collected from the three observation stations set in test roadway, we got that the largest displacement of test roadway roof is 151mm, the maximum displacement of sides is 112mm, the test roadway was in a stable state.

Digital audio watermarking technology can realize owner identification, copy control and data authentication functions by hiding extra information into the audio products.
In order to guarantee the robustness and good imperceptibility of the algorithm, the watermark is embedded in the low frequency components of wavelet transform domain, and at the same time, the algorithm adopts the quantization scheme [3], the extraction of the watermark doesn't need original signal, which greatly enhance the practical application of the algorithm. 1 Digital Watermarking Embedding 1.1 Watermark image preprocessing The preprocessing algorithm includes scrambling encryption, dimensional reduction, and adding synchronous code sequence before the watermark is embedded.
This paper adopts the watermark with the size of , if it is embedded in the audio signal, it is needed to be converted to one dimension signal, that is, (2) V is the watermarking sequences after dimension reduction, W is the watermark image after scrambling
(3) Structure of the embedded data.
(2) Establish a SVM training samples and train, generate a fixed {0, 1} sequence and form a map relationship with part of the coefficients extracted in step 1, establish the training data of SVM: (3) Then use SVM to train samples, get classification model SVM '

The loss in the mutual information between X and Y caused by the (probabilistic) clustering X can be viewed as the average of this distortion measure: , , , , ( ) ( ) ( ; ) ( ; ) ( , , )log ( , , )log ( ) ( ) x x y x x y p x y p y x I X Y I X Y p x x y p x x y p x p y − = − ∑ ∑ (5) In order to find a clustering that causes minimum reduction of the mutual information between the objects and the features, we minimize the functional ( )min ( ; ) ( ; ) p x x I X Y I X Y− (6) In order to minimize the over all information loss caused by the clustering, classes are merged in every step such that the loss in the mutual information caused by merging them is the smallest.
After observing data x , the posterior probability of the cluster ic is 1 ( ) ( ) ( ) , 1,2,..., ( ) ( ) i i i K k k k p c p x c p c x i K p c p x c = = = ∑ (8) Where ( )ip x c is the probability of the data x given the cluster ic .
Schwarz [11] showed that for sufficiently largen , the number of observations, the best model is the one which maximize BIC: ( ) 2log ( )i BIC k p x c = (10) In order to find a clustering that causes minimum reduction of the mutual information between the objects and the features in information bottleneck method, we defined ( , ) ( ) 2log ( ) log ( , ) after i before I X Y BIC k p x c I X Y λ = + (11) The meaning of the above definition is that a good cluster model should as far as possible preserve the intrinsic mutual information.
The data set consists of more than two hours of various types of video sequences.