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The calculation is good agreement with the experimental data and the theory, we obtained that the calculated data are validated.
Experimental method and data.In the experiment we use synthetic natural gas, the mole fraction is 0.9141 methane, 0.0570 ethane, 0.0289 propane.
In the group of data, we can see the bubble radius and the outer radius of hydrate changing with time-varying in Fig. 4.
In the group of data, we can see the bubble radius and the outer radius of hydrate changing with time-varying in Fig. 5.
The calculation is identical with the experimental data and the theory, so the calculate data we obtained are validated.

Reduction of nitrogen and phosphorus content in piggery water with algal culture Ying Shen1, a, Jing Wang2, Wei Chen1, Xiangyang Lin2 1 College of Mechanical Engineering and Automation, 2 College of Biological Science and Technology, Fuzhou University, Fuzhou, Fujian, 350000, China ayshen@fzu.edu.cn Keywords: Algae, nitrogen, phosphorus, biomass, Scenedesmus obliquus Abstract.
All the samples were duplicated in the same culture conditions, and the data presented in this paper were the average of two samples.

This data indicates that autogenous shrinkage is not only an issue in HPC and UHPC, but can be an issue in currently used normal strength mixtures as well.
The reduction of surface tension can be realised by adding shrinkage reducing admixtures (SRA’s).
Code values for drying shrinkage were based on experimental data from the past.
The data are presented in Table 3.
In experimental data on drying shrinkage of mixtures with w/c > 0.4, which had formed the basis for codes values for drying shrinkage, autogenous shrinkage has often been ignored.

Traditional collaborative filtering recommendation system put emphasis on data but ignores the users.
Introduction With the development of information technology, Internet data is becoming increasingly huge.
As a result, in the case of a very sparse data, there will be missing mistakes when generating user nearest neighbor set.
The quality of system recommendation depends largely on the historical data sets.
The user similarity study tend to find similarity among several users from the point of view of macro data, while ignoring the fact that each user is unique .In web2.0 era, which is people-oriented, user-centered, users in the use of the Internet will leave a lot of personal data.

Population demographic data is a comprehensive presenting of the total number of population in certain districts.
Spatial distribution of the demographic data can be inverted as population distribution in certain moments and in certain geographic space through population demographic data with a combination method of qualitative and quantitative methods.
According to the idea of spatial distribution of the demographic data of.
Figure 2 Xi'an population density Figure 3 The spatial distribution histogram of Xi'an population density Spatial Distribution of Population Census Data with GIS.
Analyzing influence range of park with service radius of 2000m based on GIS software,and then,overlay the data with population density distribution data,we can get population density data.( Figure 5) Figure 4 Analysis of spatial distribution and service radius all the existing park as the disaster prevention park Figure 5 Population density space distribution of all the park cluster in service radius Taking population density multiplide by the number of cells of different ,Wedensity, We can get the data of population of park in service radius.

Size-related effects like the reduction of the melting temperature and displacement of the phase boundaries can be predicted.
Right panel: observed (red dots), calculated (black line) and difference pattern (indigo line) of a typical neutron data collection on ZrO2 nanocrystals.
The mechanism of the tetragonal to monoclinic phase transition occurring in pure micrometric zirconia was recently analyzed within the Landau theory framework [17] In micrometric zirconia crystals, accurate data, obtained by neutron diffraction, were used to monitor this first order reconstructive phase transition as a function of the temperature during both heating and cooling.
The effective activation energy extracted from the experimental data Ea for boundary migration is about 0.4 eV.
The best fit of these experimental data gives ϕt = 54 nm and σ = 2 nm.

The encouraging results include significant increase in tool life by MQL mainly through reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interaction.
The drastic reduction in tool life is considered as the only significant drawback of the hard-milling process.[2,3] Lot of research work has been and is being done in order to find the optimal combination of tooling, cutting, and environment parameters for enhancement of tool life, without compromising the high values of material removal rate offered by the high-speed milling(HSM) process.
The ratio of maximum tool life value to the minimum one was 3.70, which was large enough for data transformation to be applied.

Introduction With the reduction of natural resources and the development of detection techniques, the purity detection of gem has become the main research content of gem mining areas [1].
According to the above way, it is possible to extract the feature vectors of spectrum in the detection wave, and calculate the correlation coefficient between these characteristic parameters, so as to filter the unrelated information to the purpose of purity detection of gem, providing accurate data base for purity detection of gem.
The experimental environment are constituted by the embedded Window operating system, Labview simulation software, Java programming language, the signal transmitter, and the spatial data acquisition.

At every stepwise reduction, the system is equilibrated for 5 ps after which the required data is extracted.
In our simulation study, we base our observations on the volume data instead of density and observe that volume minimum occurs at a temperature of 275 K (Fig. 3).

Literature [4] proposed a method that using the secondary star sensor to modify the primary star sensor output, but it only takes advantage of the data from secondary star sensor which compensate the lower accuracy of primary star sensor’s information, while other information is lost.
(8) Dealing with the star sensors’ observation model Star sensor’s output quaternion is obtained from the star sensor’s observation vector by data processing.
Superfin: Filtering Methods for Error Reduction in Spacecraft Attitude Estimation using Quaternion Star Trackers[C].