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The reduction of natural frequency could be used to evaluate the fatigue damage of structures.
Figure 2 shows the setup of the experiment system including Y51150 electrodynamic shaker, specimens and fixtures, and data acquisition system.
The reduction of natural frequencies of type Ⅱ begin earlier than that of type I, but the rate of reduction of type I is faster and achieved 5% default failure threshold firstly.
The reduction of natural frequency can be used to evaluate the structural fatigue damage.
[8] Gao Zhentong: Fatigue Test Design and Data Treatment.

Effects of Reduction f Percent of Template (HMI) and Time of Static Synthesis on the Structure of MCM-22 Zeolite Everton R.
Federal University of Campina Grande, 58109-970 Campina Grande - PB, Brazil, aeverton.ufcg@gmail.com, bromulo_fas@yahoo.com.br, caeciob@hotmail.com, dherve@deq.ufcg.edu.br emeiry@deq.ufcg.edu.br Keywords: reduction, HMI, time, MCM-22.
This paper focuses on the synthesis of MCM-22 to determine the effect of reduction of percent of template (HMI) and time of static synthesis on the production of high purity MCM-22 zeolite.
According to the data in Table 1 verify that the synthesized MCM-22 (P) and MCM-22 showed a high percentage of silicon oxide (SiO2) and a reason SiO2/Al2O3 characteristic of the MWW framework [8], and a reason SiO2/Al2O3 lower when compared with the MCM-22 [3], after the calcination those ratios can be submitted to small reductions [5].
These results agree with the previously reported data [3] to the static synthesis.

Hydrogeology and Groundwater Hydrology Drilling data analysis.
Groundwater usage and groundwater level observation data.
Firstly, steady state simulation is conducted, and various hydrological parameters, and other input data, of the model are adjusted by the groundwater level observation data of the eight self-recording wells around the area.
As shown in Figure 5, the simulation results are fairly consistent with the groundwater level observation data.
The annual groundwater level of the STSP is 6 m from the historical data.

Through the analysis of measured data, significant economic benefits had been brought about by using the heat pump water heating system.
The waste heat recovery is an effective measure of energy saving and emission reduction.
The data is in table1.
Table 1 Comparison of operation cost data Test time Daily steam consumption (t) Average power consumption (kWh) Steam price (RMB/t) Power price (BMB/kWh) Daily operation cost (RMB) Steam water heating system 2012.2.24~ 2012.3.7 227.2 ____ 273 0.8 62000 Heat pump water heating system 2012.3.26~ 2012.4.7 188 5772 273 0.8 56000 It can be seen that the daily operating cost of 6000 RMB was saved, and operating cost of 2.19 million RMB was saved average a year by using the heat pump water heating system with waste heat recovery.
The effect of energy efficiency and emission reduction is obvious, so the heat pump water heating system with waste heat recovery has good development prospect.

Virtual honeynets architecture Honeynet architecture has three key elements: data control, data capture acquisition and data analysis.
The data control is the attacker attack behavior of the system outside the Honeynet limited mechanisms for reducing the deployment of the safety risks posed by the Honeynet.Data capture all acts that is monitored and recorded an attacker within the Honeynet.The data analysis is the attack captured data integration and analysis methods,with auxiliary safety researchers found that one of the attack methods, tools and purpose.Using data mining methods for data analysis in this paper, which we need to treat the analysis of data processing format to facilitate data mining, which requires the introduction of data processing.
Data capturing and processing In order to protect the normal operation of the data capture,The introduction of a multi-layer data capture mechanism,From system layer to the network layer,Including firewall capture of baotou data, covering command parser get keystroke information, flow data reorganization get attack tools intrusion detection system caught the attack information warning and binary data packet, data capture, purpose and data format to be different from each other.
The standardization of data processing Through the network packet capture collect is the original binary data.
The selection of these characteristic, both to be able to mark out the characteristics of data, and to do as far as possible concise, make these attributes have representative and save system resources, and improve the efficiency of the data processing.The network connection record some attributes on the final data mining result is no influence, these attributes in terms of security can't provide the desired value, and if these attributes to join characteristics focus will greatly influence the mining efficiency, even may cause the deviation of the results of data mining.Therefore, the original data effectively simplified is very necessary.Data reduction is in the mining purpose and data is the only expression characteristics under the premise of maximum lean data quantity.Through experiment and summary, this paper mainly selected datagrams characteristics are: service, src_IP, dest_IP, src_port, dest_port, flag and timestamp.

These models contribute to increase the stability and efficiency of the reduction process [1, 2].
The high generalization capability also provides robustness to the model when data or examples are under the effect of noise [7].
This database was separated three subsets, 70% of data for training, 15% for the validation phase and 15% for testing.
This demonstrates that the model exhibits a good agreement in simulating the phenomenon of silicon incorporation, since the mathematical model in different periods of operation showed a good agreement with the actual data.
The developed mathematical model showed excellent agreement with the actual data of the reduction process in blast furnaces, because the ANN were able to accurately predict silicon content in hot metal.

Synthesis of ceramic materials from waste residues Sabrina Portofinoa, Sergio Galvagnob, Anna De Girolamo Del Mauroc , Enzo Calòd Unità Tecnica Tecnologie Portici (UTTP), ENEA P.le Enrico Fermi 1 – 80055 Portici (NA) asabrina.portofino@enea.it, bsergio.galvagno@enea.it, canna.degirolamo@enea.it, denzo.calo@enea.it Keywords: rice shell, carbothermal reduction, silicon nitride, SEM, XRD Abstract.
The synthesis products were characterized by X Ray Diffraction (XRD) and scanning electron microscopy (SEM) and the data confirmed the production of ceramic silicon nitride (Si3N4) at high yield and purity, under the adopted process parameters.
Synthesis reactions have been performed both on the original rice husk (without any pre-treatment) or after size reduction.
The chars have been characterized and the proximate analysis data are reported in Table 2.
Table 2, Proximate analysis of char from rice husk pyrolysis [% w/w] Volatile 32.9 Fixed carbon 29.6 Ash 37.5 According to the experimental data, the carbon/silica weight ratio of the char is nearly 0.8 (considering that the ash is just silica); such a value is definitely higher than the stoichiometric value of the two reagents of reaction (2) (which is 0.4), but is certainly adequate to allow high conversion rates.

The quad search tree can be applied to all the two-dimension data.
It is characteristic of large quantity of data and information.
Quad Tree Quad Tree for Spatial Data.
This quad search tree can be applied to all the two-dimension data excellently, including data of both spatial and non-spatial.
Suppose that R is a two-dimension data point given arbitrarily, we make a comparison on it with another two-dimension data point S.

For obtaining fatigue limit and dealing with censored data, the" pair- life -weighted” is proposed in this paper.
Because of the time and budget constraints, fatigue experimental data is often quite limited and incomplete (such as censored data).
Gao Zhentong proposes pairing dichotomy to calculate fatigue limit with test data of the up-down method, which has become a conventional method.
In the reference [5], contrasted test data of "destroy" and "non-destroy" at adjacent stress levels (,) can be taken as a pair (Figure 1).
"Destroy" means the life of a tested sample is less than 107 and "non-destroy" means the life is over 107, which can be as a data of the conventional method

Efficiency Enhancement through Decision Support Based on Data Mining S.
a. s_aghvami@yahoo.com, b. htshandiz@shahroodut.ac.ir, c.jahedmr@iust.ac.ir Keywords: Data Mining, Clustering, Boiler, Operating Data, Efficiency Abstract.
Data Mining entrance to this field happened in parallel with the expansion of using DCS, Distributed Control Systems that provide data warehouses of the process operating data as historical trends or reports [8].
DATA PREPERATION We have implemented this idea on the operating data of a gas fired boiler serving a petrochemical company by providing 90 Tones per Hour 42 Bar pressure superheated steam.
The following processes on these data samples have been done, just as usual steps toward solving any other data analyzing problem: a.