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It is extremely meaningful to optimize the parameters for wear reduction to extend the mold life.
The Determination of Level Data.
According to the theoretical ranges of processing parameters listed in Table 1, the data package for CWR experiments are listed in Table 2, which considers three parameters, three levels[7].
C2, the radial reduction at second level, which .
The stretching angle is the prior considered factor for mold wear reduction , which should be as small as possible.

The reduction of pure WO3 and Ce/WO3 has been studied by using temperature programmed reduction (TPR) and X-ray diffraction (XRD) analysis.
The reduction behavior were examined by non-isothermal reduction up to 900 ºC then continued with isothermal reduction at 900 ºC for 45 min under (40% v/v) carbon monoxide in nitrogen (CO in N2) atmosphere.
The completeness of the reduction of the powder was analyzed by temperature programmed reduction (TPR) method.
For identification purposes of crystalline phase composition, diffraction pattern obtained were matched with standard diffraction data (JCPDS) files.
Catalysts Characterization after Reduction by XRD.

In this study, to evaluate the reduction effects of urban heat reduction of water-retentive pavement, surface temperature of pavement, air temperature, wind speed and albedo were measured for 3 years(2008~2010, summer period).
Experimental results indicated that water-retentive was effective to reduction of air temperature by decreasing of surface temperature of pavement compare to other pavements.
This increasing of impervious area was caused the urban dryness and destruction of water cycle and heat cycle by reduction of evaporation that is reduced from 42% in 1962 to 25% in 2002 [7].
In this paper, effect of urban heat reduction of water-retentive pavement was studied compare with existing rigid pavement.
(a) Thermo-couple (b) Data logger (c) Net-radiometer/albedometer Fig. 2 Thermal environmental measurement equipment Also, sensible heat flux is calculated using measured data by a measuring instrument machine.

The parameters of the spring model have been determined, based on the experimental data.
The mathematical model developed may be applied in the design of passive, semi-active, and active vibration reduction systems, as well as in the synthesis of adaptive smart vibration reduction systems.
Shape memory alloys are also used as actuators in active vibration reduction systems.
This article discusses the use of SMA springs in vibration reduction systems.
Et=cA2ω202πωcos2ωtdt=cA2ωπ (7) Therefore, the damping coefficient may be determined on the basis of formula (8), where energy Et has been determined on the basis of experimental data.

Problem statement There are quantitative differences in the experimental data presented by a number of authors [2, 4, 6, 8, 11, 15, 19] as to the effect of elevated temperatures on the characteristics of the mechanical properties of heavy concrete.
The research results The experimental data obtained from the first short-term heating of concrete prove the existing in literature generalized dependences of concrete strength during axial compression on elevated temperature value and duration of its effect.
Fig. 1 and 2 show the comparison of newly and previously obtained experimental data of strength characteristics of various strength concrete classes.
The results prove the data provided by the authors mentioned and signify of the maximum reduction of concrete strength during the first short-term heating up to +90°…+100°C which can make 20-35% in compression (Fig. 1).
Experimental data: - [8] - [13] - [4] - [15] - [17] - [2] - [19] Theoretical values: – calculations according to formulas [4] – according [22] 1, 3 – short-term heating 2, 4 – long-term heating (Т = 90 days) long-term heating short-term heating Fig. 2.

The oxide thickness was estimated using ellipsometry and CV data.
Fig. 2 shows the density of interface states near the SiC conduction band edge extracted from CV data.
For comparison, TDRC data for the samples depicted in Fig. 1 is presented in Fig. 3.
Fig. 3b) shows similar data for the sample exposed to potassium.
The plot is extracted from the data in Fig. 3.

The classical metal-organic Frameworks CuBTC showed remarkable low temperature activity in selective catalytic reduction of NO with NH3 (NH3-SCR).
The nature of the active Cu species among CuBTC in NH3-SCR based on the activity data were characterized by TEM, XPS, XRD, EPR and IR.
In this paper, CuBTC was synthesized by hydrothermal method and used for selective catalytic reduction of NO with NH3.
The activity data was recorded when the catalytic reaction practically reached steady-state condition at each temperature.
Conclusions The CuBTC catalysts showed remarkable low temperature activity in selective catalytic reduction of NO with NH3.

They reported that the porosity of iron changes from 20 to 62% upon reduction.
However, it is possible to make a reasonable approximation to explain the experimental data.
Thermal diffusivity changes with the progress of NiWO4 reduction.
Summary of data on time dependence of diffusivity changes Temperature, K Initial diffusivity, α0 x 106 cm2s-1 Final diffusivity, αt x 106 cm2s-1 Time to completion, min Incubation time, min 973 0.0058 0.0141 120 22 1048 0.0053 0.0161 110 14 1123 0.0051 0.0161 98 6 1198 0.0038 0.0159 49 2 1273 0.0036 0.0159 41 2 The activation energy of the reduction of NiWO4 was calculated by an Arrhenius plot using the isothermal reduction rates, which can be represented by the change in thermal diffusivity, at different temperatures.
Arrhenius plot for the reduction of NiWO4.

It can provide a method and data for search energy saving and CO2 reduction potentials in iron and steel industry by LEAP model.
With its flexible data structures, LEAP allows for analysis as rich in technological specification and end-use detail as the user chooses.
The data is actual data of devices used in iron and steel industry in 2010.
The data in 2040 is a forecast data which is the ratio of device used in iron and steel industry.
Specific data is shown in Tab.1.

In this way, vibration fault data table meets the requirement of rough sets data analysis.
Thus, fault information which hidden in huge signal data is extracted.
As rough sets can only deal with data of discrete attribute, those original fault data of continuous attribute must be discretized.
Table1 is extracted experimental data which is after envelopment analysis.
Then we have discretizated data table 3.