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The test object used as a model was based on experimental research [1] and produced in the form of a beam with 15 cm x 30 cm x 220 cm dimensions and observed to possess the specification data indicated in Table 3.
Data on BBSN-20 fiber-reinforced foam concrete material Parameter Formula Value Unit Reference Compressive strength f’c -27,6 MPa [1] Density of lightweight concrete Wc 1.729 Kg/m3 [1] Modulus of Elasticity Ec = wc1,5(0,043)fc' 16.252,39 MPa [8] Poisson Ratio µ 0,2 [6] Tensile Strength 2,952 MPa [1] Fracture Energy by Vos (1983) 0,000074 MN/m [6] Critical compressive displacement -0,0005 m [6] Plastic Strain εcp = fc'Ec -0,0017 [6] Reduction of comp. rc,lim 0,8 [6] Fail Surface eccentricity e 0,52 [6] Direction of flow β 0 [6] Density ρ 0,017 MN/m3 [1] Thermal expansion α 0,000012 [6] Fixed crack model 1 [6] Results and Discussion Load and Deflection Relationship.
Data on BN-25 normal concrete material Parameter Formula Value Unit Reference Compressive strength f’c -23,6 MPa [1] Modulus of Elasticity Ec = 22.822,12 MPa [8] Poisson Ratio µ 0,2 [6] Tensile Strength 2,381 MPa [1] Core Values of Fracture Energy Gfo (Interpolation) 0,037 N/mm [7] Fracture Energy Gf=Gfofcmfcmo0,7 0,000067 MN/m [7] Critical compressive displacement -0,0005 m [6] Plastic Strain εcp = fc'Ec -0,00103 [6] Reduction of comp. rc,lim 0,8 [6] Fail Surface eccentricity e 0,52 [6] Direction of flow β 0 [6] Density ρ 0,024 MN/m3 [1] Thermal expansion α 0,000012 [6] Fixed crack model 1 [6] (a) (b) Fig. 2 Graph of load-deflection relationship: (a) BBSN-20 beam (b) BN-25 beam Crack Pattern and Failure Mode.
Meanwhile, no reduction was observed in the numerical analysis as indicated with the horizontal line because the concrete material is theoretically considered to be homogeneous and this means no cracks occurred.

Next step is comparison of the machining time of milling process with results from paper Reduction of milling time by using CAQ technologies [6].
The Results includes comparing simulation results of roughing for selected shape of forging die based on two models from scanning data by optical 3D scanner and evaluation of hard facing layer quality, detection welding defects and finally, hardness measurement.
The data analysis showed that the scanning precision was satisfactory not only for assessment of deformations, but also to reveal the details of the weld joints.
The 3D scanner provide a sufficient amount of input data for the analysis of weldment’s deformation and it is able to accurately determine the size and direction of the weldment distortion.
Reduction of milling time by using CAQ technologies.

Optimization and Means of Urban Traffic Structure Chaocheng Zheng1, 2, a, Xinren You1, 2, b 1Nanjing Communications Institute of Technology, Nanjing 211188, China; 2Jiangsu Engineering Technology Research Center for Energy Conservation and Emission Reduction of Transportation, Nanjing 211188, China.
Cever has collected data about transport development in typical cities in US, fitting a positive correlation between low-density dispersed layout and car travel [9].
Evidently, this model predict the general trend of traffic demand in a strong description, however, deviation always exit between forecast and actuality, therefore, could reflect the influence of government rules, regulations, policies on travel mode, especially, with the improvement of people's living standards, the number of trips, trip frequency has increased, restraining its large scale application due to lots of tedious data to be dealt with.
Based on this, the disaggregate model is more popular due to the effective improvement in not the merely average data to indicate each trip activities, it is the possible values of a travel behavior.
Policies for the promotion of sustainable mobility and the reduction of traffic-related air pollution in the cities participating in the EpiAir2 project.

The concept of alternative energy that will use is relates to sustainability, renewability, and pollution reduction.
Besides, it also can protect the environmental especially in term of carbon dioxide (CO2) emissions reduction.
The data has been recorded on 3rd and 4th April 2013.
Based on the data that analyzed, the best system that will produce energy is the PV system because it suitable for condition in Melaka area in term of radiation of sunlight in daylight.
Vijayagowri, Hybrid PV/Wind system for reduction of harmonics using artificial intelligence technique. (2012) 303–308

This construction contributed to a significant reduction in the vibrating elements’ weight when maintaining high rigidity of the inducing system.
Analyzed model was simplified, not including the radius in the place of diameter reduction of the sample [as seen in figure].
These data (relating to material non-linear properties) were imported from JMatPro program.
Then these data were loaded into FEM analysis using bi-linear material model with linear strengthening after plastic deformation.
These data confirmed the FEM results analysis showing the potential region of crack initiation to be in near the depth 1.5-1.8 mm from the surface.

Most of facial data sets currently in use are captured in a visible light spectrum[2].
Dimensionality Reduction For Face Recognition KLT-based dimensionality reduction for face images was first proposed by Sirovich and Kirby[4].
Since then, eigenface based dimensionality reduction has been used widely in face recognition.
,k. 5: Output: identity(y)=arg miniri(y) Before classifying a given test sample, we must initial decide if it is a valid sample from one among the classes within the data set.
Figure 6: Test data(having occluded and pose varied images) Figure 6 shows the test dataset.

With respect to the data given in Table 1, the significant decreases in the values of both the ionic conductivity and apparent diffusion coefficient of triiodide are observed in the electrolyte of PEO(750).
transfer resistance Rct of triiodide reduction according to the reaction Eq. 4 on the counter-electrode gives rise to improving the Jsc and FF.
The data on the DSCs with the conventional nanocrystalline TiO2 electrode is illustrated for comparison.
The stead-state voltammograms for the reduction of I3− in the Electrolyte A and Electrolyte B are depicted in Fig. 18.
The decreases in the conversion efficiency about 2.1 and 3.9% after heat- treatments at 100C for 30 and 120 min, respectively, are evaluated from the data listed in Table 3.

Further XRD data analysis revealed that the magnetite has a lattice parameter of 8.38 Å.
The circle symbol represents the XRD data, while the solid line represents the calculated pattern after Rietveld analysis.
SANS data and fitting analysis of the Fe3O4 magnetic fluid Table 1.
Results of the data analysis of the Fe3O4 magnetic fluid, after Rietveld analysis of the XRD data [Fig. 2] and fitting analysis of the SANS data [Fig. 3] Fe3O4 a = b = c [Å] x [nm] ξ [nm] D XRD 8.38 12.7 - - SANS - 7.6 45.3 1.2 Figure 3 shows that the experimental data scattering for all q range is in good agreement with the theoretical model calculation.
The solid line and circles symbol correspond to the theoretical model calculation and experimental data, respectively.

The reduction of critical load after post-annealing was believed due to diminution in mechanical properties of the substrate derived from the Co deficit in WC-Co substrate.
The interlayer thickness was controlled by sputtering time considering our back-data of thickness vs.
The large reduction of critical load after post-annealing at 600�in Fig. 3 is believed due to a reduction in mechanical properties of WC-Co substrate near surface region [20], which is believed derived from a deficit of Co content in WC-Co substrate due to Co diffusion into Ti interlayer.
Thus, no reduction of critical load in Fig. 7 happened after post-annealing at high temperature.
The reduction of critical load after post-annealing was believed due to a diminution in mechanical properties of the substrate derived from the Co deficit in WC-Co substrate.

Generally, since some random data being existed, the output original data of the system has no rules.
Fig.2: Comparison before and after data processing The reversion of the grey accumulated generating series into the forecast value of initial data is called grey inverse accumulated reduction.
And after the forecasting value of the new data is obtained, the grey inverse accumulated reduction operation would be applied to obtain the forecasting value of the original data. 3.2 Modeling for blast furnace gas forecast Based on the grey RBF neural network model, the amount of gas for short-term and multi-step forecast algorithm flow chart is shown in Fig.3.
The experimental data is the blast furnace gas production amount data which comes from WISCO 4# blast furnace.
These data is employed as the training data to train the network.