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This study is based on data from 2010.
During data acquisition the needed information of energy and production systems will be collected.
For the usage of renewable energy at the production site, information of climate data and data of possible power generation equipment are gathered [18].
On the other side energy data of the production system will be acquired.
The acquired data are used in the next step to identify solutions.

The stent is found to exhibit a fatigue life reduction with the increase of the expansion diameter due to ratchetting strain.
Therefore, the fatigue behaviour of the stent must be a main design consideration to prevent in-service rupture while keeping competitive advantages and achieving manufacturing cost reductions.
This law is defined as an additive combination of a linear term and a relaxation term, which introduces the non-linearity: α=Cσ0σ-αεp-γαεp (4) where is the equivalent plastic strain rate, and C and γ are the material parameters that are normally calibrated from cyclic test data.
This model is based on the Smith-Watson-Topper (SWT) relation, given in Bannantine et al.[34], and expressed as: FP= ∆ε2σmax+J∆γ∆τ (7) where the symbol denotes the MacCauley bracket (i.e., ), is the fatigue parameter, is the normal strain range, is the maximum normal stress, is the shear strain range, is the shear stress range, and is a load- and material-dependent constant and is obtained from traction/torsion test data.
On the contrary, when the width of the strut is decreased the reduction in constraint is promoted by the low number of grains of harder orientation and the apparition of softer zones, characterised by a stress raiser area, is privileged.

With the data obtained from these tests and in order to analyze the results obtained from the models, a methodology based on four points is proposed: First, the uncertainty of the dataset obtained from the DoE is analyzed in order to evaluate to which degree the experimental data define the problem.
Third, the accuracy of the generated models is checked using an additional — previously unused — set of data.
Finally, the best models obtained for each machine learning technique are tested and compared to actual data to assess the accuracy are the models.
Prior to generating the regression models, the data obtained from the DoE was normalized between 0 and 1 to improve the quality of these models.
Hall, Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, Elsevier Inc, 2011.

Data was analyzed by using Spss data processing software, and the correlation coefficient matrix between the feeling of wearing Introduction As the knitted fabric has good elasticity and extensibility, the kinds of fabric has been used for more and more types of tight and sports garment.
Physiological data were measured including height, thigh, waist and hip circumferences, knee circumference.
The physiological data are shown in table 2.
After the wearing state, according to table 3, tester assessed the clothing pressure comfort and other related feeling in the range of values within 1-5, and the corresponding records were made by the experimenter in the wearing pressure comfort subjective assessment questionnaire calculated subjective evaluation data of each wearer, and a total of 80 group wearing sensation value were achieved. data was analyzed by using Spss data processing software, and the correlation coefficient matrix between the feeling of wearing sstretch pants were obtained.
Results and discussion After the subjective evaluation experiment ended, we The correlation coefficient is a quantity to show how close the relationship is between two experimental data, usually represented by the letter R.

The real-time NURBS curve fitting process consists of (1) the reading discrete points, (2) curve segmentation and data reshaping, (3) curve fitting, and (4) local and global modulation.
The well developed NURBS curve fitting method along with a given set of data points by least-squares approach is applied to fit each segment in this stage [1].
(2) Access the discrete data points Q , j=0,1,…...
The detailed process will be mentioned in parts of curve segmentation and data reshaping
Fig. 1 The flow chart of optimum NURBS curve fitting method Curve segmentation and data reshaping The input datum will be separated into different segments according to the proposed algorithm shown in Fig. 4.

Data received from sensors is delivered to a sensor interface using CAN communication.
The data transmitted is composed of message processing which classifies the data from the different sensors and the data processing which processes the data for use in monitoring.
The data which has been processed is transmitted to an Android system through a mobile communication interface and the data can then be retransmitted to a remote android device using mobile communication included in the android system for remote monitoring.
Data displayed on the remote monitor was transferred to control the panel manuals of existing leisure vessels.
Receiver interface of the remote monitoring system The display is designed to be composed of an upper main data display, a middle sub-data display, and a lower warning display.

The collected data were compared with the ICDD data.
Results of the bend test data.
Shore D Hardness data.
Vicat softening data.
HDT data of the composites.

Then by fitting angle-dependent reflectivity data to modeling theory, the arrangement of the director and some importance parameters of liquid crystal cell are obtained.
Results and discussions The multilayer optics [5] and continuum elastic theory of nematics are used, and the reflectivity data are fitted to a model giving the full director profiles within the cell with different voltages.
Comparison of experimental data with theoretical reflectivity curve for ITN-Cell with external potential of 0 Vrms (1kHz) at 632.8nm wavelength: (a) the polarization-conserving signal Rss; (b) the polarization-conversion signal Rps.
Comparison of experimental data with theoretical reflectivity curve for ITN-Cell with external potential of 6Vrms (1kHz) at 632.8nm wavelength:(a) the polarization-conserving signal Rss; (b) the polarization-conversion signal Rps.
Using multilayer optical theory to fit the angle-dependent reflectivity data, the director full profile and the material parameters of the cell are obtained, as shown in Table 1.

Finite element simulations of the brazing process have been performed to evaluate the expected residual stress reduction near the metal-carbon interface.
In this work another route for the reduction of residual stresses in PFCs has been preliminary explored; it entails the use of high strength and high thermal conductivity, but low CTE or graded CTE interlayers, to be brazed in between the low CTE protective material and the high CTE heat sink.
The easiness of industrialization and the costs reduction of the brazing process could be completely exploited.
Finite Element Modeling Finite Element Modeling (FEM) has been used in order to calculate the expected residual stress reduction near the metal-carbon interface with respect to the pure Cu compliant layer.
Zolti: Materials Data, NET Int.

Energy Dispersion X-ray (EDX) analysis revealed that there was 1.02% reduction of Ru in the Ru/Mn/Ce (5:35:60)/Al2O3 used catalysts compared to fresh catalysts.
Introduction Recently, the increasing demand for natural gas and the reduction of greenhouse gases have became more promising.
The diffractogram was collected over the range of 2θ from 10o to 80o and the data obtained were analyzed by a PC interfaced to the diffractometer using the Diffrac Plus.
EDX analysis reveals that there was 1.02% reduction of Ru in the Ru/Mn/Ce (5:35:60)/Al2O3 of used catalyst compared to fresh catalyst.
The reduction was possibly due to the migration of Ru into porous support during the reaction.