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Robustness against local property changes and spatial scattering requires distributed sensing and appropriate data mining and data fusion techniques, allowing to reduce data redundancies and to save only the useful information.
Distribute sensing means many sensors and a huge amount of data to handle.
Indeed, nodes are provided with an onboard processor; therefore, every node, instead to send "crude" data to the nodes responsible of the data gathering, can just carry out simple elaborations and transmit required and already processed data [5].
As it will be shown later, Data Mining is useful not only for handling redundant experimental data but also as powerful aid in case of stochastic model updating.
However, the realized part represents a good starting point for future upgrades: supposing future applications, it's possible to expect to enclose new algorithms for data generation and analysis and for the handling of structure properties data and model data too.

The reduction of fatigue limit under 5% NaCl environments was much larger than that under high humidity environment.
One of the effective ways to reduce gas emissions is weight reduction of the vehicles.
Figure 4 shows corrosion pit nucleation life and crack nucleation life of AZ61 in the form of an S-N plot along with the fatigue life data under high humidity [11].
As shown in Table 2, the reduction rates of fatigue strength due to 5%NaCl environment were 0.77 for AZ80-T5, 0.85 for AZ61 and 0.53 for AZ31.
The significant reduction in the fatigue strength by the NaCl environment was attributed to the formation of corrosion pits.

Rough Set Theory Rough set theory is an excellent tool for handling incomplete and inconsistent data.
Under the condition of unchanged classification abilities, attribute reduction is to delete irrelative or unimportant knowledge.
The property data represents risk investment projects is regarded as a information of the research object, where risk investment projects have m indexes (columns), namely the property value set has n risk investment projects.
Step 2, Discredited of information table data, we get the total index A as well as all sets of each properties.
And finally, the data is verified to show the excellent performance of the model.

Those peaks were denoted as the reduction peak which means that Se(IV) was reduced two times.
Overall, the higher concentration will increase the reduction peak current.
The determination of the concentration of selenite is based on the first reduction peak.
This data indicates the adsorption of Se(IV) on the surface of the copper amalgam working electrode.
This supports the data that the redox reaction on the surface of the electrode is controlled by the adsorption process.

The system uses a USB interface chip with micro-controller and the data are transmitted into computer by USB interface.
This system also allows users to query the historical data by different ways and supports printing functions.
Image Noise Reduction.
So this paper introduces the algorithm of total variation which is used for image noises reduction.
Compared with the traditional measurement methods, this scheme not only inherits the advantages of CCD imaging system, but also makes full use of computer’s powerful data processing capability.

These stresses of different modules obtained from the finite element analysis were compared and the considerable reduction of weight occurred was found and also the values are compared with the theoretical values.
Table 1 Required Input data for spur Gear design (Steel C45 material) Description Gear Pinion Material Steel C45 Steel C45 Number of teeth(Z) 44 17 Young’s Modulus(E) 2.10*105 N/mm2 2.10*105 N/mm2 Speed (N) 635rpm 1500 Power (P) 25 25 Poisson Ratio 0.3 0.3 Normal Module (M) 6 mm 6 mm The gear design problem are taken as, a pair of spur gears with pinion 17 teeth to transmit 25 kW at 1500 rpm.
Table 2 Required Input data for spur Gear design (Steel 40Ni 2Cr1Mo28 material) Description Gear Pinion Material Steel 40Ni 2Cr1Mo28 Steel 40Ni 2Cr1Mo28 Number of teeth(Z) 44 17 Young’s Modulus(E) 2.15*105 N/mm2 2.15*105 N/mm2 Speed (N) 635rpm 1500 Power (P) 25 25 Poisson Ratio 0.3 0.3 Normal Module (M) 5 mm 5 mm Normal Pressure Angle 20o 20o Table 3 Results obtained as per AGMA Standard for spur Gear design Description Formula Used Steel C45 Steel 40Ni 2Cr1Mo28 Pitch Diameter (D) m*z1 102mm 85mm Circular Pitch (Pc) πd1/Z1 18.84mm 15.70mm Diameter Pitch (Pd) Z1/d1 0.16666 0.16666 Gear Ratio (i) Z2/Z1 2.58 2.58 Centre Distance (a) mZ1+Z22 183mm 152.5mm Pitch Line Velocity (v1) πd1N160 8.011m/sec 6.675m/sec Force exerted (Ft) pv*ko 3120.67N 3745.31N Transverse Force (Fr) Ft*tan∅ 1135.83N 1363.18N Addendum 1m 6mm 5mm Dedendum 1.25 m 7.5mm 6.25mm Minimum total depth 2.25 m 12mm 11.25mm Bottom Clearance 0.25 m 1.5mm 1.25mm Fillet Radius at Root 0.4 m 2.4mm 2mm Module (m) 2C/(Z1+Z2)
The results clearly shows that, reduction of weight for about 22% occurs in Steel 40Ni 2Cr1Mo28 when compared to Steel C45.
H., Bar, I., 2001, “Multiobjective optimal Design of Cylindrical Gear Pairs for the Reduction of Gear Size and Meshing Vibration”, JSME International Journal, Vol.44, No. 1, pp 291-292 [6] Prof.

The wind pressure data of roofs are obtained by using the synchronous multi-pressure scanning technique.
Using the wind pressure data measured simultaneously by wind tunnel test, can study the influence of characteristics of wind pressure, wind angle, landforms type or other factors on the partial area of the roof in-depth.
The test of the saddle roof was carried out in the TJ-2 atmospheric boundary wind tunnel of the State Key Laboratory for Disaster Reduction in Civil Engineering at Tongji University, China.
The wind pressures were measured substantially simultaneously with the sampling frequency of 312.5 Hz by using the DSM-3000 data acquisition system.
Kim: Wind load identification using wind tunnel test data by Inverse analysis.

The transistor data is summarized in Table 1.
Instead we use the field effect mobility data and compare it with the effective mobility data for Si devices.
The broken line shows best line fit to the Si data of Takagi et al [5].
Also shown is effective mobility data of Takagi et al for n-channel Si MOSFETs [5].
The broken line is a best fit to the Si data.

It can easily making base surface figure, data point bitmap, classification data figure, contour mapping, line block diagram, terrain landform figure, trend figure, vector figure and 3Dcurve figure; and provides 11 species data network grid methods, which are all popular calculation methods of data statistics.
Firstly, the raw data file with corresponding data format (normally the text file format as three columns of data, respectively X-Y-Z),Z stands for the value of points (x,y), in which the first column is X coordinate and the second column is Y coordinates, the third column is Z value on (x,y).And then convert to the data file as *.grd file format which is read able for Surfer to draw the contours.
The plane grid data file (XYZ format data files) is gained by using the noise distribution software.
The gridding is an interpolation methods of interpolate and encrypt data from sparse, irregular distributed data into regular distributed one which fits the drawing needs.
Surfer offers 11 ways of data gridding, Kriging method is applied within this paper.

According to the characteristics of environment emergency responding, attention should be paid to the following three points with respect to water environment model selection: 1)First, as emergency responding is pressing and complex, the decision makers must make relatively proper first response at the preliminary stage, and must get accurate pollution information later, so there must be a model system consisting of both quick engineering model and fine scientific model to meet the needs in different phases of emergency responding. 2)After an accident, the data required for model calculation such as the hydrological data, water quality data and pollution source data are not complete at first, but will be gradually obtained during the responding process.
Aiming at the characteristics of water pollution change, this paper uses a model of base state with amendments to build the space-time data model, and uses AcrSDE to realize management of the space-time data.
Basic Correction Model 2.4 Integration of water environment model and GIS The methods and degree of integration of water environment model and GIS depend on the complexity of the model objective, the requirement of the model for GIS functions of the base data, the practicability of the interface, the compatibility of the data model, the hardware environment, the system structure of GIS model software [12,13], and so on.
Pollution Situation in Scenario 3 The pollution data at the Baishiyao section in three scenarios are entered into the system for comparison analysis, as shown in Figure 6.
Comparison of Cadmium Concentration Change at Baishiyao Section in the Three Scenarios The comparison of the pollution data in Scenario 3 and the actually measured data (as shown in Figure 7) shows that the two change processes match very much, indicating that this study can accurately forecast and simulate pollution change after implementation of various emergency responding actions and can be used for actual emergency responding.