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However, hardly any data are available for these types of materials.
Data reduction The global force-displacement data and the actual crack length values were used to calculate the tearing energy values.

The experimentation can provide useful data for disaster prevention and mitigation research and actual construction.
It is of great significance for various geotechnical problems research, also a significant reality for analysis and evaluation of the soil project quality and disaster prevention and reduction.
After getting a great deal of useful data, the principal of the displacement in different times and in different locations under different water load can be obtained by drawing displacement curves, consequently the experimentation can provide useful data for disaster prevention and mitigation research and actual construction.

In addition, these preliminary data indicated that the maximum achievable growth rate corresponding to the good surface morphology may be noticeably larger for the CH3Cl+SiH4+H2 growth system.
The process conditions of the growth experiments were selected to provide deliberately non-homogeneous growth rate along the gas flow direction in order to increase the experimental diversity and, consequently amount of data points (e.g., for the surface morphology versus the growth rate) available from each growth run.
The trend of the growth rate change in the direction parallel to the gas flow indicates that further reduction of the carrier gas flow is going to be beneficial for achieving the optimal homogeneity, which is opposite to the trend of the silane-propane growth.
In addition, the preliminary data indicates that the maximum achievable growth rate resulting in good surface morphology may be noticeably higher for the CH3Cl+SiH4+H2 growth system.

In this paper, we revisit Tseng’s security proof and show that the reduction in the proof is invalid.
The shared key may be subsequently used to achieve some cryptographic goals such as confidentiality or data integrity.

Such traditional prediction models have been developed with a fixed equation form based on the limited number of data and parameters.
But theses equation forms are not stable and should update for if new data is quite different from original data.
Artificial neural network (ANN) does not need such a specific equation form, only needs sufficient input–output data, and it can continuously re-train the new data easily.
Experimentation and Collection of Data Specimen Preparation The cement was Portland cement, grades P.C 325&P.O 425 (Chinese standard).
Distribution of test points · Though one data was get on one test point, there were 16 data for every specimen.

This has been the frame of image data in RGB format.
Line real-time data will be converted into the standard 30-bit RGB data, and sample for subsequent display and image process.
The acquisition of one camera outputs 30-bit RGB format data.
But in memory the data must be stored in the form of 32-bit.
Random feature is that data is not linear storage.

Formability of tube in elevated temperature is essential data to design the warm hydroforming process parameters, such as tube diameter, forming temperature and die geometries.
Since the quantitative data of forming limit can be used to predict the failure on forming process, formability data available on the FE analysis is one of the very important information for the optimum design.
Formability of tube in elevated temperature is essential data to design the warm hydroforming process parameters, such as tube diameter, forming temperature and die geometries.
Since quantitative data of forming limit could predict the failure on forming process, forming limit data available on the FE analysis is one of the very important information to design the process variables.
And, thermal properties of Al6061 were used material data from DEFORMTM.

Both the experimental data and the theoretical formulations proposed in this paper stem out from the inter-university collaboration developed as part of the EU funded EnCoRe Project (www.encore-fp7.unisa.it).
Moreover, it is worth mentioning that although the proposed formulations are calibrated on experimental data achieved from tests performed on single particles (i.e., MIP and CT tests), they can be easily extended to a bigger sample of aggregates.
The experimental data obtained from temperature measurements were employed for scrutinising the hydration process which took place in the concrete specimens tested in compression.
This parameter can be useful for describing the reduction in compressive strength due to the replacement of NAs by RCAs.
Fig. 5a shows that all the points (w/ceff-Rc,max/r*) can be aligned on a curve that can be analytically expressed by the well know Abram´s law and, particularly, it assumes the following expression: (12) in which the values of AR and BR can be assumed to be equal to 265 and 9.5, respectively, based on the aforementioned experimental data.

Fig. 2 System functional structure 2 Three-dimensional pipe network data model 2.1 Characteristics of Data of Comprehensive Pipe Network Compared with other GIS data, underground pipe network data possessed its own distinct characteristics.
So, we took full account of the characteristics of the data of pipe network and designed the data which fitted for pipe network data model and data structure.
The data of underground pipe network was different from the data of general network.
Underground pipeline data as GIS data consisted of two parts: spatial data and attribute data.
It also provides necessary assistant decision-making for city's sustainable development and disaster prevention and reduction.

Performance Comparison of Energy-aware task scheduling with GA and CRO algorithms in Cloud Environment Lin Wu1 , Yujing Wang1 , Chaokun Yan （1.School of Computer and Information Engineering, Henan University, Kaifeng, Henan, 475004） Keyword: Cloud Computing, Task Scheduling, Energy-awareness, CRO algorithm, GA algorithm Abstract: With energy problem of cloud data center is becoming more and more serious, the BoT scheduling algorithm only considering the timespan is not applicable to the cloud computing environment.
Experimental evaluation indicators are as follows: (1) Makespan value; (2) Energy consumption reduction rate. 3.2 Results and analysis Scene I, the scheduling results of the two algorithms are shown in Table 4.
The above data shows that increasing the number of resources that can be given more expanded scope of task scheduling.
Saving Energy in Data Center Infrastructures [C].
Proceedings of the First International Conference on Data Compression, Communications and Processing, 2011:265 – 270