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Yamagishi [9] carried out a study on numerical analysis of the circumferential motion over a cylinder with textured grooves on which external face in large Reynolds number case, and found the cavitation occurred at the inner of texturing groove, simultaneously, the transition of cavitation was assigned from laminar to turbulent boundary layer, the reduction of the friction coefficient of texturing surface was performed.
The width w and depth hp of micro-groove have effect on load supporting capacity and friction reduction, here numerical results for them are showed in the name of net calculating forces, dynamic pressures, wall shear stress and related mean friction coefficient.
However, those datum don't offer us supporting for an explicit analysis based on various structures of micro isosceles trapezoid-grooves, thus a mathematic method of surface integral is used here.
The data of mean coefficient of friction for various micro arc-grooves are obtained by the mathematic method of surface integral for wall shear stress τ and total pressure pt loaded on sliding surface, which were shown in Fig. 6.

These actions cause more difference in breathing sounds and are usually associated with a reduction in blood oxygen saturation.
The "local maxima" plot can reveal the location of this kind of disturbance in the input data.
The "local maxima" plot can reveal the location of this kind of disturbance in input data.
Suresh Kumar from Vijaya Health Centre, Chennai, for helping us in data acquisition.

In order to study the catalytic effect of Pd nanoparticles on the thermal degradation kinetics of nylon 6, TGA data at various heating rates were introduced to Flynn & Wall equation.
These kinetic data would be used in the recycling of the wasted condensation polymers.
TGA data for Nylon 6/Pd Nanocomposites with Various Exposure Time to Pd(acac)2.
Straight lines for various α were created by the relationships between log β and T-1 data from Table 2, as displayed in Fig. 4, and the activation energy for each α was calculated from the slope of the each straight line, as listed in Table 3.
These results were very different from the data of neat nylon 6 and it was due to the catalytic activity of Pd nanoparticles on the depolymerization of amide group in nylon 6, as was explained in Fig. 2.

According to our approach, SPM is used as the on-chip main memory to contain the data with high frequency of use.
Core data or code will be partitioned as different slices.
Both of SPM and cache fetch data from off-chip memory (main memory).
Cache is controlled by hardware and data will be fetched from main memory.
SPM and main memory have no same data commonly.

Analysis and calculation show that the predictions agree well with the experimental data.
According to the application of noumenon sampling method to test the strength of concrete structures in winter construction, the strength data of different curing time was obtained.
The noumenon sampling strength data of different curing time for C30 concrete are given in Table 1.
From Table 3, it is obvious that the prediction value is very close to the real data, that is to say, the model can well reflect the development trend of the concrete entity strength.
Curing Time Real Data Simulated Data Absolute Error - Relative Error 2 3 4.8 5.81 -1.01 21.04% 3 5 6.6 6.85 -0.25 3.79% 4 7 8.7 8.07 0.63 7.24% 5 9 10.1 9.51 0.59 5.84% 6 11 11.4 11.21 0.19 1.67% 7 13 13.1 13.21 -0.11 0.84% 8 15 15.2 15.56 -0.36 2.37% We can get the incidence degree from Eq. 15 and Eq. 16 as = 0.6300.

In the present work DEA (data envelopment analysis) coupled with Taguchi method has used for optimization in process parameters of hot turning operation.
Sadhu and Chakraborty studied data envelopement analysis as a selection tool in non-traditional machining process.
Fig. 1 Experimental set up of hot turning Methodology Data Envelopment Analysis (DEA) Data Envelopment Analysis (DEA) was developed by Charnes Cooper and Rhodes (CCR) in the year 1978.
First experimental data is normalized using the criteria of the responses [14]
Chakraborty, Non-traditional machining process selection using data envelopment analysis (DEA), Expert Systems with Applications, 38 (2011) 8770-8781

Because of PNN application need enough sample data that is due to probabilistic density function.
The reduction gear ratio was 1/60.
Fig. 4 Data acquisition and processing system.
Classification is performed by flaw signal data itself through BPNN classifier and PNN classifier.
Because of PNN application need enough sample data that is due to probabilistic density function.

Through the parameter analysis, the predicted value of the dissimilar joint’s tensile strength was calculated to be 209.7 MPa, which is in close proximity to the experimental data (219.6 MPa) with 4.5% error.
Taguchi method is a powerful and preferable design of experiments tool to solve many engineering problems with significant reduction in time and cost [5][6].
Raw data and S/N ratio for L9 orthogonal array No.

Corresponding epitaxial growth experiments were done and the obtained experimental data was in good agreement with the simulation results.
This tensile stress may affect the strain in the PMOS channel and lead to a reduction of the channel stress if h is higher than 10 nm.
This experimental data is in good agreement with the simulation results.

Through measuring the physical characteristics of the 152 canoeists taking part in the Chinese Fifth Intercity Games and analyzing the data with factor analysis model, the most important factor of canoeists’ physical characteristics, degree of brawniness, was found, and the first ten indexes which can perfectly represent the physical characteristics of canoeists were identified.
Introduction Athletes’ specific physical characteristics has always been the important indicators for sports selection and training monitoring, but due to data and other reasons, now, in our country, in-depth researches on canoeists’ physical characteristics are still few.
Factor analysis is often used in data reduction to identify a small number of factors that explain most of the variance observed in a much larger number of manifest variables.
Generally, the first m factors, of which the cumulative variance contribution rate is greater than 85% of the raw data, are taken as principal factors.
The data of the common parameters, such as body height, body weight, etc. indicates those sportsmen have good physique characteristics for this game.