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The BET data show at higher calcinations temperature cause the reduction number of surface area of the sample.
Increasing calcination temperature causes the reduction intensity of the zeolite peak this due to the rapture of the structure of zeolite.
From BET analysis show the increasing of the calcinations temperature cause in reduction of the surface area of the sample, meanwhile the XRD data analysis show the existing of the zeolite compound in the sample of natural granite Acknowledgment The authors would like to thank the Ministry of Education Malaysia for financial support via Fundamental Research Grant Scheme (FRGS).

In order to minimise reduction of oxides by silicon or carbon the Si3N4/SiC composites with Al2O3 and Y2O3 were prepared also via chemical deposition of aluminium and yttrium hydroxides on nanosized Si3N4/SiC particles, produced by plasma chemical synthesis.
The crystallite size, dcryst,. of SiC is calculated from the XRD data (hkl 200,220) using the Scherrer formula.
It means that at least partial reduction of oxides occurs in the plasma process and it should lead to formation of silicon oxynitride and possibly sialon type phases.
From data of Table 1 it follows that the typical average particle size, d, of the nanocomposites produced is in the range of 30-50 nm and the crystallite size dcryst. of SiC is from 27 nm to 42 nm.
The nucleus of Al2O3 and Y2O3 or TiN can be enclosed in the layer of SiC and Si3N4 as well as of Si2ON2 regarding partial reduction of oxides by silicon.

According to relevant data, the appropriate temperature for the foot is 24℃ and that for the head is 20℃.
The heating load is reduced which means the reduction of consumption and saving of energy [2].
Third, the reduction of the temperature should be gradual when the system is closed.
There is no exact geological research data for recharge temperature of geothermal water.
Reduction of recharge temperature improves the efficiency of geothermal energy and solves thermal pollution to some extent.

Introduction At the Copenhagen summit in December 2009 , the committee in the Climate Change of the United Nations Intergovernmental Panel claims,carbon dioxide and other greenhouse gases have become the main reasons for global warming, energy efficiency and emission reduction should be paid more attention by human beings the future[1].In 2009,China's President Hu Jintao pointed out that Chinese new energy efficiency and emission reduction plan will be served as an important direction of our development strategy in the summit of the United Nations Climate Change, which shows that China will greatly reduce carbon emissions in the future, and reduce the consumption of fossil fuels.
Low carbon and energy saving of the brand construction are snapped up in Hangzhou, the systems of the entire building energy which use low carbon emissions throughout its life cycle, and then 250 million KWH of electricity, 830 million tons of standard coal, 2.48 billion tons of carbon dioxide emissions and reduction emissions will be saved in this project.
According to the Figure 6, the life cycle of the building 's carbon emissions data have to be dealt with normalized rating, it comes to a score from the four stages which is divided by the highest score, then the final value is normalized: 0.85,0.6,0.8,0.9 .Evaluation of the analytic hierarchy process which comes from the proportion of the four stages, according to the normalized data and specific gravity which are multiplied and summed to arrive at a final score.

Introduction BOF process contains a very complex multiphase high-temperature reaction, it is a cyclical warming carbon reduction process.
Basic theory Multi Neural Network Model In this paper, using the pedigree clustering method to divide the input data, and then train the BP neural network to each group, ultimately generate the corresponding BP neural network prediction model.
Fig.1 Flowchart of multiple neural network prediction model Training model algorithm is as follows: (1)Pretreatment; (2) Pedigree cluster method, all the data is divided into K classes {C1, C2, ...
Take the top 561 furnace data for predicted model training, the latter 50 furnace date used for prediction.
Fig.3 Endpoint temperature prediction Fig.4 Endpoint carbon content prediction Simulation of the second sample group Take the top 186 furnace data for predicted model training, the latter 50 furnace date used for prediction.

Fortunately, The PCA is an effective data dimensionality reduction technique that by making use of orthogonal transformation the PCA could make the selected features irrelevant and give full play to the role of each feature [9].
The PCA is a powerful tool for data dimensionality reduction widely used in a variety of applications.
As a result, the FKNN has ability to deal with problems where pattern data overlap.
The vibration data were acquired under heavy-load with 660 rpm of the motor speed.
Then, the PCA was used to reduce the data dimensionality.

For the studies on influence of high temperature ageing on the J-R curves of SS 316(N) weld, the fracture tests at room temperature were carried out using unloading compliance method for crack length estimation, while those at high temperature were carried out using multiple specimen method as well as normalization data reduction technique.
For 643 K, DCPD was used for as-welded & 823 K/1000 h aged specimens and normalisation data reduction as well as multiple specimen method for 923 K/4200 h aged specimens.
Fig.7: Variation of (a) J0.2 and (b) % reduction in area for 316 (N) welds tested at 298 K with duration of ageing at different temperatures.
Subsequent reduction in toughness is due to the transformations taking place in the d ferrite regions of the weld metal.
It is the formation of a¢ phase that leads to reduction in toughness.

Comparison of the calculated results with experimental data for Pb(Mg1/3Nb2/3)O3– PbTiO3 ceramics is presented. 1.
Decreasing results in the reduction of polarization value at saturation field of the sample and also in the reduction of hysteresis loop steepness. 3.
The XRD data indicates that most of matrix grains were well-oriented and there were almost negligible residual randomly-oriented matrix grains.
The experimental data on hysteresis loops of these PMN–PT-xBT ceramics, , and results of calculations are presented in Figs.9–11.
Comparison of the calculated results with experimental data for Pb(Mg1/3Nb2/3)O3– PbTiO3 ceramics.

Some alloying elements, which tend to segregate, make the as-solidified dendritic microstructure prone to hot cracking and then require well-controlled cross-reductions during subsequent rolling or thermal-mechanical treatment to homogenize microstructure and get optimum properties.
The reduction in the grain size with each hot rolling reduction stage also facilitates the distribution of impurities.
This value coincides with the 20mm of thin slab half-thickness according to the data presented in Fig.12.

This paper chooses ZigBee technology to realize the data communication among the wireless sensor network.
Once a detecting node send data to the gathering nodes or receive command from the gathering nodes, an optimal path should be established between these two nodes in order to reduce the energy consumption during the data transmission.
The routing protocol of ZigBee technology is responsible for transmitting data from the source node to the destination node, and mainly includes two main functions, one is to find the optimal route between the source node and the destination node, the other is to transmit data along the optimal route correctly.
The routing node only need to realize the data emitting and receiving wirelessly, no analogue hardware collection and transform circuit are needed relatively to detecting node, and the power supply is based on battery power. 2.2 The hardware design of gathering node The gathering node receive data from all nodes in the WSN, use wavelet transform and support vector machine to recognize the type of power quality disturbance, store data of each detecting node, realize the agreement conversion between WSN and GPRS, realize the remote monitoring on each detecting node’s power quality.
The main components of Tiny OS include network protocol, distributed server, sensor driver stage data recognization, support the data sending, receiving and collection of wireless sensor node. 2.4 System software process In the system software design, the important one is the wireless sensor network communication mechanism between nodes in the network, how to design the reasonable receiving and transmitting data mechanism between nodes is the key problems must be solved during the whole design scheme.The software function mainly includes data acquisition and processing, the implementation of routing algorithm and the wireless transmission.