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The numerical models were validated with experimental data obtained from the scientific literature.
On the contrary, the damage is more extensive in the back face sheet of the sandwich structure as a result of the reduction in the velocity produced by the presence of the foam core.
Thus the inclusion of the core in the sandwich plate cannot be considered effective in terms of increment of the ballistic limit, but a significant contribution of the foam core to the reduction of residual velocities and damaged area.
Results show very good comparison between the numerical predictions obtained from the FE models and experimental data.
Comparison of numerically obtained residual velocity versus impact velocity with experimental data from the literature Conclusions The energy absorption of different composite sandwich plates with aluminium foam core subjected to high velocity impact was analyzed using a 3D finite element model in ABAQUS/Explicit.

The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data.
Forest fire disaster area prediction based on genetic algorithm and support vector machine is presented in the paper.Genetic algorithm is used to select appropriate parameters of support vector machine[3,4].The computation process of the parameters of support vector machine by using genetic algorithm is given.The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data,where the forest fire disaster area data in Jiangxi Province from 1970 to 1989 are used to select the parameters of support vector machine and train the proposed GA-SVM model,and the forest fire disaster area data in Jiangxi Province from 1990 to 1997 are used to test the proposed GA-SVM model.
Experimental Analysis As shown in Fig.1, forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data.
Forest fire disaster area data in Jiangxi Province from 1970 to 1997 Fig.2.
The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data.The comparison of the forest fire disaster area forecasting results between the proposed GA-SVM model and the SVM model indicates that the proposed GA-SVM model has more excellent forest fire disaster area forecasting results than the SVM model.

Conventional GM (1, 1) model for long-term data to predict accuracy is not high, but metabolism GM (1, 1) model can be made up for conventional GM (1, 1) model of this one defect [1].
In the practical modeling process, when the system produce the new data, we will take out the most old data in original system and reestablish a GM (1, 1) model.
Continuously add new information while remove the old data in time, and this kind of model is the information renewal model.
The conventional GM (1, 1) model just has high accuracy in the recent data, to the further development, the model prediction accuracy is weak [5].
The monitoring group should closely communicate with the construction party, in the time, they should measure in time and ensure the accuracy of data to avoid the faults because of unnecessary artificial reasons.

Yet there are still not many systems can compute enough pedestrian data to analyze, due to the bottleneck of the computer.
It’s useful for separating image data into constitutive parts.
Thus, each sample data vector can be approximated by a linear combination of the columns of B, weighed by the elements of F.
Each column vector of F can be viewed as a new data representation of the corresponding sample data vector of X.
If the basis can discover the intrinsic structure of data, a good approximation can be achieved.

To use the quick and easy method, it is essential that the necessary data are easily accessible.
It is a simply and easy way to describe current manufacturing data and physical material flow [5].
The AVSM requires a few additional data compared to the VSM but gives a much more detailed picture on the current situtation of an manufacturing situation.
Since up to 90% of the time and costs for industrial manufacturing process is not productive (because the customer does not pay for it [5]), it is assumed that the reduction of 40% is a achievable limit [1].
Starting from AVSM we introduce the data directly into the PCT and we can display curves of the evolution of manufacturing cost and time.

Harries and Ritchie [11] measured vertical temperature profiles in mine waste dumps and used the data to calculate the heat flow and consequently the rate of pyrite oxidation in the laboratory.
These anaerobic biogeochemical processes in mine waste are poorly understood and reaction rate data are not available.
Data are from [27, 28].
Primarily cultivation techniques have been used to enumerate prokaryotes involved in oxidation and reduction processes in sulfidic mine waste dumps [10, 20, 30, 31].
The data show that Bacteria dominate over Archaea and Eukarya and that Acidithiobacillus is the most abundant Fe(II)+++ +++ +++++++ ++ Acidithiobacillus spp.

Also, for naturally ventilated buildings located in the tropical regions in Indonesia, Feriadi and Wong [7] gathered 525 sets of data through an extensive field survey.
The data analysis revealed that the PMV equation had predicted warmer thermal perception as compared to what people actually felt.
The dataset consists of 30,000 buildings (10,000 office buildings for each of the three major climatic zones) with their detailed constructional and operational data and of their simulation outputs.
With a suitable scheme of neutral temperature and comfort air speed, reduction of energy consumption of the central chiller plant may surpass the additional energy requirement of the air side equipment, then both energy saving and thermal comfort can be achieved for the entire air-conditioning system.
Table 3 lists the percentage reductions of the primary energy demand achievable with a dual set point with dead band with reference to the three single set point PMV=0, PMV = +0.5, PMV= –0.5.

Kn is designed to achieve the desired reduction in base shear.
Hence, the NSD and structure assembly has a strength reduction factor, Roy’ =Fo/Fy’ of 5.
The strength reduction factor Ryy’ should not be greater than 4 due to safety considerations.
These cycloidal pulses and recorded ground motion data are used to test the performance of the ANSS.
“Retrofit of a hospital through strength reduction and enhanced damping.”

The data can be stored by means of a specialized magnetic write head [3].
Diameter reduction is performed within 0.75 s, followed by a 0.45 s lasting calibration phase when diameter reduction is finished and roundness as well as dimensional accuracy is improved.
Fig. 5: Test setup (left) Calibration Data (right) During the calibration procedure, the piezo tube is loaded with different maximum pressure forces with the help of a compression testing machine.
In order to discuss the course of the data with regard to maximum forces, an incremental analysis approach will be pursued.
Fig. 7: Axial force peaks from experimental data Positive and negative force flanks show a maximum deviation of about 6 %.

Reductions in micropipe and dislocation densities, inclusions, and other structural defects in substrates, and the associated reduction in substrate-induced epitaxial defects, have increased the useful wafer area and improved fabrication yield.
The reduction in JFET inverter current from 3.6 A to 3.39 A over the same temperature range is attributable to a decrease in the watt-loss characteristic of the magnetic material used for transformer fabrication and thus, an increase in transformer efficiency.
This was in agreement with the STW45NM50 data sheet temperature derating factor of 2.08 W/o C, increase in RDS,ON, observed Hbridge VDS data increases of 1.2 V to 2.1 V, and the fact that MOSFET on-resistance is reduced 25% when operated at the current levels of this experiment.
Fig 5 illustrates the calculation of static loss components for the power switches, as a function of temperature, from the measured waveform data.
In each case, the offstate power dissipation is seen to be invariant with temperature, consistent with the data of Fig. 6, and is a negligible fraction of the total loss even at 300o C.