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H2 consumption and Tmax (temperature of maximum of the reduction profile) positions were recorded by a TCD.
Before analysis, an pre-reduction of CuO phase to Cu0 was performed in a flow mixture of 5%H2-N2, raising the temperature at a heating rate of 10 ℃/min from room temperature up to 290 ℃.
Cu0 surface area was calculated from N2O decomposition data using the following equation .
Additionally, the reduction profiles are unimodal curves, indicating the reduced material is only CuO because ZnO would be reduced in H2 atmosphere above 600 ℃.
Additionally, (CuZn)5(OH)6CO3 in the precursors of Cu catalysts leads to more active Cu0 compared with the other precursors after calcination and reduction.

The LabVIEW program controls data acquisition card, which realizes real-time data acquisition, display and storage etc.
Data Collection Card.
acquisition, data analysis, data calculation, and data storage etc.
The principle and program shown in Fig. 2 are used to test data.
With the solar cells output current reduction, the voltage difference decreases.

The aim of this paper is to introduce a new design as well as to compare the stiffness, load capacity and weight reduction of composite material with that of steel leaf spring.
In addition, steel spring causes a reduction in the level of comfort provided, due to the continuous running of the small loader car.
In order to obtain great weight reduction, improve comfort ride quality and safety for the passenger, the present paper is mainly focused on the implementation of composite materials by replacing conventional steel leaf spring.
Within the limits of the physical problem, the processing of the data is usually done.
While the post processing offers information for acceptance or rejecting of the data analysis of the model [8].

It can get the core of attributes by reducing redundant samples from the current data set, and then use the core as decision rules to classify the observed or measured imperfect data.
Unfortunately, the Rough Set Theory can only deal with such data sets that only contains discrete attributes while the reality is that most data sets contains both discrete and consecutive attributes at the same time.
The essence of discretization is to treat some consecutive data points as indistinguishable, and use an uniform symbol to instead all of them.
References [1] Zhao Jun, Data discretization methods based on rough set theory, Journal of Chinese Computer System, 25(1) (2004) 60-64
[8] Liu Kai, Wang Yi-Nao, Pang Yan-Jun, Data discretization methods based on clustering neural network, Computer Science, 28(5) (2001) 136-137,168

The surface area was calculated from data obtained and shown in Fig 3.
Fiber surface area and SEM micrograph of circular and worm-like PP fiber The fiber surface area data from image-J software revealed that the surface area of worm-like fiber was higher than circular fiber (24%) for ZnO free fibers.
Bacterial reduction percentage of worm-like composite fiber from ASTM E2149-10 Sample The number of bacteria CFU/ml (3 h.) % reduction Pure + 0.01% wetting 3.4 x 105 - W 0.5% SP + 0.01% wetting 1.0 x 104 97.05 W 1.0% SP + 0.01% wetting 2.4 x 105 29.41 W 2.0% SP + 0.01% wetting 2.5 x 105 26.47 W 3.0% SP + 0.01% wetting 2.3 x 105 32.35 W 1% ZnO + 0.01% wetting 1.6 x 105 52.94 W 3% ZnO + 0.01% wetting 4.0 x 104 88.23 For modified chitosan (SP) at 0.5% had the reduction percentage of 97% compared with ZnO (3% loading) at 88.23% reduction.
As modified chitosan (SP) loading percentage increased, the reduction percentage decreases.
Especially modified chitosan-PP fiber showed excellent antibacterial activity against the tested germs at 0.5wt% loading (97% reduction) which notably lower loading than ZnO for the same reduction percentage.

It has been well established that there are two major mechanisms of softening during the dynamic restoration, one is dynamic recovery and the other is dynamic recrystallization. data on the high temperature deformation behavior of the stainless steels are sufficient, but most of them are on wrought, only few on as-cast steels[4-6].
Hot ductility tensile curves for two steels temperature above 700 o C with the strain rate غ =0.005 s-1, (a) stress against the testing temperature curve, (b) reduction of area against the testing temperature curve.
In order to understand the hot ductility behavior of two stainless steels, the Gleeble hot ductility data under investigation were used through the hot tensile and compression testing methods.
The curves of the reduction of area and stress against the testing temperature for tensile testing are shown in Fig.1.
For the steels B, the reduction of area values using the heating method 2 was much greater than that of the method 1 at the strain rate of 0.005 s-1 in the temperature range 1000 to 1150 o C ( Fig.2(b)).

(2) The data reduction module.
Clock Management 250MHz differential clock after DCM processed to produce a single 250MHz clock, and divided by 2 to generate a clock signal of 125MHz, DCM also 250MHz signals 180 degree phase shift, for subsequent data speed reduction processing and storage.
(3) High-speed data access High-speed data storage and retrieval, is a focus of high-speed data acquisition card is also a difficulty[5].
High-speed data stored procedure shown in Figure 5: Figure.5.
Design PXI FPGA-based data acquisition system.

The chip reduction coefficient (CRC) and von Mises stress (VMS) were the output responses.
Subsequently, the chip reduction coefficients (ratio of formed and un-deformed chip thicknesses) were determined.
Data for the mean response Level Speed, (N) Feed, (f) DOC, (d) 1 -5.1277 -8.6458 -6.5573 2 -5.1142 -5.8871 -4.5501 3 -6.2072 -1.9162 -5.3417 Delta, (max-min) 1.093 6.7296 2.0072 Rank 3 1 2 It is seen that the optimal solution is attained at N2 f3 d2 i.e., at (0, 1, 0) (Table 7).
Validation of data obtained by Taguchi-FIS simulation.
Therefore, it is evident that the data obtained by the Taguchi-FIS simulation is validated.

Introduction Data compression was an important preprocessing step while massive point cloud data processing.
Octree topology partitioning of massive point cloud data It was scattered that the state of original cloud data point.
(a) (b) (c) (d) (a)original cloud data (b)the surface reconstructed in original data (c) streamlined cloud data (l=4) (d)the surface reconstructed in streamlined data Figure 3.
Comparison of original data and streamlined data It was shown that the original cloud data and the streamlined cloud data using this algorithm, in the Fig3.
More details were retained with a higher reduction rate.

BATC survey data of 15 intermediate-band filters offer excellent opportunity to study low spectral resolution SED for thousands of point sources in the field simultaneously.
However, they have much superior photometric accuracy than spectroscopic data and still represent general outlines of optical SEDs.
Title of Publication (to be inserted by the publisher) BATC Multiband Data The BATC (Beijing-Arizona-Taipei-Connecticut) color survey is optical imaging survey for approximately 500 target fields [2].
The left panel shows detailed spectra for each spectral type and the right panel is for BATC SEDs Data Reduction In order to sample faintest sources at an increased S/N, we combined hundreds of images from the same filter.
The BATC data of multiple intermediate filters are indeed useful in constructing SED curves for many thousands of sources accurately.