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As the rolling reduction increases, the balance can be broken.
The Rex texture calculated from the data by the SERM model was the (441) Fig. 3 Figures for explaining that {111}<112> rolling texture can change to (a) {111}<112> and (b,c) {111}<110> recrystallization textures [4].
r d 10]1//[10]1TD//[ r d //[001]3]11AMSD//[ r d //[110] [332] r d //[118]2]11RD//[ r d ]1//[44 ND//[111] orientation is represented by the Gauss type scattering with a half width angle of 12°, the calculated result is as shown in Fig. 4(b), which is in good agreement with the measured data in Fig. 4(c), where the highest intensity poles are the same as those of the Goss orientation, even though it is not real Goss orientation.
The activities of the four slip systems are the same at ε33 = 4.25 (98.6% reduction in thickness).

In order to make the measurements comparable the attenuation coefficient range, ring artefact reduction and beam hardening were kept constant in all samples.
The green coloured structures illustrate the binder/conductive additive mixture, since due to the small difference in X-ray absorption the polymeric binder and the conductive additives cannot be clearly distinguished in the current tomographic data.
A reduction of the material free space is visible, since the aged electrodes seem to be more dense that the cathode with SOH 100.
To quantify these effects the reconstructed tomographic data was binarized and quantitatively analyzed.

., strength reduction factor) for the design of pultruded FRP compression member since its cross-sectional configuration is similar to that of structural steel.
Specimens were tested at a rate of 1mm/min with load and strain being recorded automatically by the computer controlled data acquisition system.
Specimens were tested with a loading speed rate of 1mm/min and load, displacement, and strain are measured and recorded automatically by the computer controlled data acquisition system.
Therefore, if we use the form factor (strength reduction factor) obtained by the finite element analysis in the structural design of the member, it may be resulted in conservative design.

Measuring apparatus: KISTLER dynamometer; computer data acquisition and processing system.
The grinding force is changed to electric signal by the KISTLER dynamometer, then the signal is amplified by the signal amplifier and sent to computer data acquisition and processing system.
By reducing the grain size in a grinding layer, the number of grains increases by the square of the grain size reduction.
The big enhancement of the higher number of active grains means a reduction of the mechanical treatment by each single grain, because the same material is removed by a higher number of active grains.

The safety parameters of thermal decomposition for storage conditions include parameters, such as isothermal time to maximum rate (TMRiso), total energy release (TER), and time to conversion limit (TCL) [9–11], and in addition, the thermal hazard properties of thermal reactive materials that could be applied as a reduction of loss prevention for safer design during storage lifetime conditions and relevant operations, which all usefully data will be obtained by modelling method.
Approximately 0.9–1.1 mg of the sample was used to acquire the GP experimental data.
Conclusions These results could be applied toward energy reduction and safer designs for storage of thermal reactive materials.

In this paper, the aforementioned commodity is interpreted as data packet.
Machine-to-Machine (M2M) is a set of technologies that enables data communications between machines, devices, systems, and people [1, 2].
The algorithm contains the generation and reduction of a small-world route map and the selection of an optimal route.
Small-World Route Map Reduction Algorithm This sub-section presents an algorithm, developed by Chou et al. [6], that can reduce a SWRM generated from Section A.

The data were then transmitted to the ShadeEye View software and expressed in terms of three coordinate values (L, a, b), which were established by CIE for the purpose of quantifying the appearance of an object.
The data was statistically analyzed by the SPSS 13.0 Program (SPSS Inc.
These changes in L, a and b values were consistent with a study that as the dentin ceramic thickness increased, significant reductions in L values were recorded by Ozturk et al [7].
As the ceramic thickness increased, significant reductions in L values and significant increases in both a and b values were recorded.

In many cases, the quality control process is carried out selectively with respect to a representative group of elements selected randomly from the batch (which does not ensure sufficient knowledge of the level of defective and causes only a reduction in the probability of their occurrence).
In addition, the use of a universal vision system will allow to: · developing a universal housing adapted to most items, · elaborating one model that can be developed in the form of the standard [10] with variable structural properties depending on varying applications (overall dimensions), · increasing the versatility of elaborated machine, · reducing the time needed to prepare the testing of a new item, · reducing the number of sensors used to detect the presence of the object, · simplification of the control subsystem (possible resignation from Programmable Logic Controllers or programmable relays), · acquisition of measurement data (in form of photographic documentation), · the ability to connect to arbitrary industrial network, · reducing the impact of external interference from magnetic fields, stray currents, etc.
All of presented assumptions should be consistent with the preventive maintenance model [3] which includes several meaningful guidelines, among other things: risk reduction, failure avoidance, the continuous improving of the reliability of the considered system, defects elimination (with attention focused on minimization of the time needed for the detection of error sources and their elimination), maximization of a productivity combined with decreasing of the total production costs, with continuous improvement of the quality level [11].
Krenczyk, Data transformation for production planning and control systems integration.

Introduction The ball mill is one of the most common grinding equipments, it has been widely used in mineral processing for particle size reduction.
In this paper, we use the related data obtained from the DEM simulation of ball mill and then combine theoretical and empirical models to get the main parameter values of mill performance.
According to the actual mill length, it will take a number of days to complete the simulation, so such a reduction is necessary to make the simulation time feasible.
Combining the data from DEM simulation such as the relative normal impact velocities distribution for grinding media to ore particle and theoretical or empirical models such as breakage probability model, the related parameter values of mill performance including throughput, power consumption and operational stability were got.

Diagram for calculating metal cutting when grinding Vw – The removed volume of workpiece (mm3); Vs - The wear volume of the grinding wheel (mm3); For the radial grinding process, the wear volume of the grinding wheel is calculated as follows: Vs = pdsDrsb (2) where: Drs - Reduction in radius of the grinding wheel (mm); N=2400rpm ds - The average value of radius of the grinding wheel before and after the wear occurred (mm); Figure 2.
Grinding Experiment and Data Collection Experimental grinding process is carried out as shown in Fig. 2 with the following grinding conditions: - Grinding wheel: MBcBN grinding wheel with a diameter of f = 10mm and length L = 12mm manufactured by electroplating method in Vietnamese laboratory [2-6].
Experimental results and calculated grinding ratio after 500 grinding stokes   M1 M2 M3 M6 Japanese wheel Measured cut thickness after (mm) 4.995 4.989 4.996 4.995 4.996 Theoretical cut thickness (t=0,01mm) (mm) 5.000 5.000 5.000 5.000 5.000 Reduction in radius of the grinding wheel (mm) 0.005 0.011 0.004 0.005 0.004 Removed volume of workpiece (mm3) 2247.750 2245.050 2248.200 2247.750 2248.200 Wear volume of the grinding wheel (mm3) 1.571 3.456 1.257 1.571 1.257 Grinding ratio G 1430.96 649.66 1789.06 1430.96 1789.06 Figure 7.
Roughness data Japan Sample Figure 8.