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Physical and chemical properties of cotton plant, its chemical composition and fractional make-up are determined by laboratory testing in compliance with the GOST 19222, GOST 25820-2000, as well as reference and literatory data [1 - 22]. 5.
Therefore, the contraction process ovelapped the creep process that exacerbated the analysis of the experimental data.
Thus, if compared with porous lightweight concretes, creep of porous arbolit is significantly lower that leads to the reduction of creep deformation while maintaining the same stress level.
At the age of 28 days, the deformation curves are changed, there observed reduction of mortar fraction deformation due to the strength growth of sulfur-containing arbolit (fig. 2).

The need to determine physicochemical data in these models is also described.
Second, few and uncertain data, restricted to the 550°C-780°C Fig. 3.
Determination of iron physicochemical data in liquid Pb-Bi.
More data must be gained to confirm these results.
However, data, such as solubilities and diffusion coefficients of metallic species are necessary to use these models.

Therefore, it has important significance of guiding practical production to conduct quantitative and qualitative tests for surface characteristics of the paper and analyze the test data.
Table 1 Data of glossiness test Sample Glossiness (average value) Gold card paper 31.2 Coated paper 3.9 Vacuum aluminized paperboard 45.2 2.1.3 Analysis on test results Data in Table 1 show that glossiness of vacuum aluminized paperboard is the highest, far greater than that of gold card paper and coated paper.
Table 2 Data of smoothness test Sample Smoothness (average value) (s) Gold card paper 920 Coated paper 365 Vacuum aluminized paperboard 1820 2.2.3 Analysis on test results Data in Table 2 show that smoothness of vacuum aluminized paperboard is extremely high, which is several times more than that of other paper.
Table 3 Data of ink absorbency test Sample Ink absorbency value (%) Gold card paper 12 Coated paper 20 Vacuum aluminized paperboard 10 2.3.3 Analysis on test results Data in Table 3 show that K&N value of vacuum aluminized paperboard is quite low and almost has no absorption capacity.
Conclusion Through test data about paper surface characteristics, this paper analyzed particularity of surface characteristics of vacuum aluminized paperboard in detail.

Introduction Frequent itemset mining is a traditional and important problem in data mining.
Second, we split the stream data into sections, and build data synopsis with a 3-tuple data structure, through which we can merge partial results into the final results; thus, an incremental update is implemented. 3.
AMFIoDS Algorithm In this section, we will introduce the data structure and the detailed algorithm. 3.1 Data Structure We employ a 3-tuple list to store the data synopsis, in which i represents the itemset, s is the support, and t refers to the itemset type.
[5] D.Lee, and W.Lee, Finding Maximal Frequent Itemsets over Online Data Streams Adaptively, in: Proc.
Online Mining(Recently) Maximal Frequent Itemsets over Data Streams, in: Proc.

Objectives The overall objective of this study was to develop and adapt existing computational methodologies to produce an engineering tool that is capable of predicting the effects of rocket plumes on ejection seat aerodynamic characteristics.The developed methodology utilizes a rocket nozzle and plume computational method coupled with an existing computational environment for ejection seat flows.Specific objectives of this study were:1/development of boundary condition modules for controllable propulsion.2/implementation of local grid refinement for improved plume resolution,3/validation of methodologies against 2D and 3D rocket plume data,and 4/perform a demonstration calculation for 4th Generation Ejection Seat with rocket power.
Two sets of basic validation data were chosen.The first data set was taken from a 0.036 scale B-1 escape capsule test[9].The data set consisted of calibration measurements of model plume shapes for the escape capsule rockets at different jet to free-stream pressure ratios.Excellent agreement between the predicted and measured plume shapes was obtained for all three pressure ratios.The second set of experimental data was chosen from the works of Fearn and Roth.
Comparison of Measured and Computed Nozzle Thrust Profiles In Fig. 6,the thrust versus pintle position profiles predicted by the series of CFD solutions is compared to the profiles derived from the Aerojet test data.The equilibrium and frozen chemistry simulations predict almost identical thrust profiles,and both compare well with the test data.Both the CFD and test results produce a nearly linearly thrust profiles as a function of pintle position.At the lower thrust settings,the CFD simulations tend to over predict the nozzle thrust.This phenomenon was also reported in the Aerojet analysis[13]and was attributed to thermal expansion and ablation of the nozzle throat.
Computational Grid at Symmetry Plane for Multi-Domain, Many-to-One Gridof Upper Rocket Geometry Including Exit.reduction in the normal force coefficients when the rockets are on.These predictions are consistent with previous wind tunnel test findings[15]The reason for the increase in the force coefficients is due to the lower pressure zones created at the back of the seat by the inward direct rocket plumes.In Fig. 10,the pressure contours on the surface of the seat and at the symmetry plane for the multi-domain grid for both the rockets-off and rockets-on test cases is presented.
Acknowledgments The authors of this report would like to thank Dr.Anatha Krishnan of CFERC for his support in adapting CFD-ACE to perform equilibrium simulations of ejection seat rocket plumes,and Mr.Matt Thomas for providing information on the composition and properties of solid propellants.The authors would also like to thank Mr.Joe Morris and Mr.Bill Barnette of Aerojet for their full cooperation in providing detailed geometry and test data on the PEPS system.

The real time monitoring data characterize the different spatial and time domains is the information carrier of structural health.
Therefore, the data acquisition and processing system are the bridge connected to monitoring systems hardware and software systems[6-8].
Besides, it should consider the time interval of data acquisition, data standardization, measurement uncertainty, purification of data and other problems.
Data analysis and processing is that extract the structural performance and damage state characteristic factor from the signals of acquisition system[9].
On-line temperature monitoring systems for aluminum reduction based on fiber bragg grating [J].

This set is a data source for the intensive statistical analysis and evaluating the bounds of confidence intervals.
Results from the bootstrap simulation (10000 times) before postprocessing (raw data) and after postprocessing (trimmed data – 250 values cut off from both tails).
In the next step, the data were processed: values were sorted, 250 values were cut off from both tails and then the minimum and maximum values were found.
They were assigned as bounds of 95% confidence intervals (Table 3 – trimmed data).
Piekos, Modeling of recrystallization using Monte Carlo method based on EBSD data, in: D.N.

These terminals uninterruptedly collect data and information to related objects, and promptly upload to the network layer.
Network layer includes WEB, application servers, and data servers.
Next, the vehicle exhaust in north China is to be monitored and tracked, meanwhile the data should be collected and coped timely.
Comprehensive monitoring system that is the combination of fixed data collection points and movable data collection points can be used during the IOT establishment of air pollution monitoring.
By deepening the data layer and evaluating comprehensively, we can build a more unified center for data monitoring and a service platform for data sharing of atmospheric environment in north China.

The data is illustrated together with previously reported data as shown in Fig. 2.
The reproducibility of the measured data in this work agrees well with the previously reported data.
The results were compared with phase equilibrium data of CO2 rich gas hydrate in the presence of pure water.
Burgass, Equilibrium data and thermodynamic modeling of nitrogen, oxygen, and air clathrate hydrates, Chem.
Data. 48 (2003) 612-616

(b) The TGA/DTA data for s-ANTs.
The Langmuir-Hinshelwood model was used to fit the data to  C /C0  et / where the parameter is the time required for 67% dye reduction and was used to compare the results.
The complete photocatalytic data is presented in Fig. 3.
Table 1 summarizes the results of the Raman data.
The commercial software that came with the instrument was used to smooth the data.