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These three temperatures in the previous section are theoretical data of the maximum adiabatic temperature of hydration heat in concrete mix proportion.
Table 2 Theoretical calculated data of hydration heat of different ages in sample 2 age[d] 3 7 14 28 0.68 0.66 0.49 0.20 [] 27.57 39.13 42.88 43.14 [] 33.75 40.83 36.01 23.63 [] 21.75 28.14 25.45 18.51 As is shown in Table 2, based on the theoretical calculated data of hydration heat at different ages in sample 2, the maximum temperature difference between the maximum temperature and the surface temperature is 12.69˚C, no more than 25˚C.
Then 200-hour temperature data were collected and analyzed with a JTRG-II model temperature collecting system.
Temperature data were collected for 680 hours successively.
Layout drawing of temperature-measuring point Based on the temperature data obtained on the locale, it is estimated that the maximum temperature rise is 40.1˚C, which is close to the theoretical calculated data of hydration heat 40.83˚C.

In the ideal case test data are available for both states.
It is well known that low frequency vibration test data or static response data are not very well suited for detecting and quantifying localized small size damage.
Data acquired with scanning laser vibrometers may be used but also test data from static tests.
Examples for both types of data, modal data extracted from laser vibrometer measurements as well as static influence line data measured from a slowly moving load will be presented later in this paper.
In damage assessment it is well known that low frequency vibration test data or static response data are not very well suited for detecting and quantifying localized small size damage unless high spatial resolution of the response data is available.

Data Processing This paper selected the data of China from 2001-2010.
Because the various indicators of the evaluation index system have different dimensions, we use non-dimensional formula as to obtained the standardized data which ensure the data is not influenced by the dimensions, whereis original data, is the mean of original data, is the correction for the standard deviation of the original data.
And we got two common factors of input indicators about environment-friendly, where for pollution reduction factor, for environmental factor.
According to factor score matrix, the factor scores can be calculated by using regression and the original index data.
There are five input indexes: -------resource consumption factor；-------economic contribution factor； -------elastic coefficient factor； ------- pollution reduction factor； -------environmental factor.

Data evaluation is crucial for gaining information from sensor networks.
ML is a suitable approach for the evaluation of sensor data [4].
Hence, agents can carry learned models separating code (ML algorithms) and data.
Fortuna1, Using Machine Learning on Sensor Data.
Kosina, Learning Decision Rules from Data Streams.

The computational analysis quantifies the number of operations required for each speckle reduction method.
Very many ways to de-noise an image or a set of data exists.
In the existing the OSRAD method is considered the best suitable of those considered for clinical application, based on consideration of its performance on both simulated and clinical data, and also evaluation of its computational requirements [2].
In the existing the OSRAD method is considered the best suitable of those considered for clinical application, based on consideration of its performance on both simulated and clinical data, and also evaluation of its computational requirements.
-B., and Kadah Y.,(2002) “Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion,” IEEE Trans.

The reduction effect of water pressure is more and more obvious from the tunnel crown to the elevation where the drainage holes are provided.
The reduction effect of water pressure is more and more obvious from the tunnel crown to the elevation where the drainage holes are provided.
Generally, for the invert is closer to the drainage hole, it enjoys better reduction effect regarding to the water pressure behind the lining walls than tunnel crown.
Nevertheless, for the water pressure behind the walls at the tunnel crown represents the overall characteristic of the water load reduction around the segment lining, it is still recommended to take the water pressure behind the walls at the tunnel crown as the reference for evaluating the reduction effect.
It is worth mentioning that: the quantitative data in this paper is gotten under special physical mechanics parameters for water head and wall rock, which can only be used as the reference for similar projects rather than for direct design.

The comment set of {excellent，good，medium，poor，very poor} corresponds to the scores of {(o.8-1),(0.6-0.8),(0.4-0.6),(0.2-0.4),(0-0.2)}. 1) reduction of attributes by rough set The paper uses a rough set analyzing software, the ROSETTA, to analyze the data, which proceeds according to the following steps. ①Open the set of experimental data in decision table. ②Apply frequency division algorithm (Equal Frequency) to discretize data.
Each of two adjacent breakpoints contains equal attribute values. ③Reduce the attribute by Johnson algorithm, the reduction set is: [d11,d13,d22,d23,d24,d33,d34,d44,d45,d51,d52,d53,d54,d55,d61,d62,d73] 2) Supporting vector machine regression ①Training set and testing set selection The experimental data is divided into two parts, training set and testing set.
This paper chooses the former 24 groups of data as a training set and the latter 6 groups of data as a test set to verify the training results. ②Experimental data processing This paper uses Svmdark to make support vector machine evaluation.
Firstly, transform the experimental data format, input value by Svmdark is . ③When select the parameter of ，，, MSE should be minimized as .
Error analysis in Table 1 reveals that Support Vector Machine regression model based on rough set attribute reduction achieves a high precision.

The experimental data were measured in transmission and reflection arrangement.
The measured data are corrected, normalised and the experimental pole figures are calculated.
The experimental data were measured in transmission or reflection arrangement.
The measured data are corrected for absorption, irradiated volume, and they are normalised.
The experimental data processed in this manner are used to calculate the coefficients of expansion to express the measured direct pole figures using spherical functions.

Weight reduction at wheels is important due to its unsprung mass and the associated reduction of fuel consumption and the better ride-and-handling comfort.
Especially in the front of the car, a weight reduction is necessary to ease the critical mass distribution at the front axle and therefore increase driving safety.
Final product Back to modify Fig.2 Flow chart of metal liquid simulation The procedure includes: open pre-processing module (anyPRE), imported in CATIA have built a 3D model of STL files, setting the casting parameters, and set the simulation end condition, then save the file as *. gsc format, Start anySOLVER calculation, and finally open the results analysis module anyPOST, to observe the results, including process data, simple contraction and micro-structure prediction three parts, process analysis specifically with filling time, solidification time, filling the order, solidification order, the order of gas volume.
Fig.3 Simulation results of process data Fig.4 Simulation results of simple shrink Fig.5 Simulation results of microstructure prediction Summary This research concentrated on development of the process method for automobile parts and prediction of the optimal casting conditions that were applied to the casting of an actual product shape.

GBPS results suggest that the signs of right ventricular dysfunction in PE are: the reduction in its stroke volume, as well as reduction in the peak filling and ejection rate.
The state of the right ventricle was assessed using equilibrium GBPS data.
The results obtained agree with published data on the dissociation between the amount of vascular bed lesions in PE and the degree of the increase in pulmonary vascular resistance [10].
The consequence of prolonged increase in pulmonary vascular resistance is usually dilatation of the right heart compartments and reduction of its contractile function [6].
Conclusion Gated blood pool SPECT with radionuclide technetium 99m-labelled sodium diphosphate decahydrate reveals signs of right ventricular dysfunction (reduction of its stroke volume and peak ejection and filling rate) even with only a small amount of pulmonary hypoperfusion in patients with thromboembolism of pulmonary artery branches.