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So a novel passive detection model based on three-dimensional hyperbeam forming (3D-HBF) and fuzzy support vector data description (FSVDD) is proposed, where these advantages of beam width reduction and side lobe suppression for 3D-HBF and excellent target-detection capability for FSVDD are combined.
For this problem, a new data domain description technique, referred to as SVDD, has recently been presented [5].
Actually, because each input data point may not be fully assigned to one class, it is very difficult for SVDD to correctly detect the development process of motional target from remote range to nearby range.
Fuzzy Support Vector Data Description The sketch of the support vector data description (SVDD) is shown in Fig. 5.
Engineering Applications In order to verify the validity of the passive detection model for the UHSST, the background noise data and the radiated noise data of UHSST are acquired by the plane array in a lake trial.

Test Data Processing and Analysis To verify the performance of the propose method in this paper for impulsive noise, GPS measurement data in an aircraft test is used to process.
The time domain wave of the data is shown in Fig.3.
From Fig.3 can see the data is interfered with impulsive noise.
Fig.3 The measurement data Fig.4 De-noising by SVD combined with WNN From the data processing result, it can see that, the de-noising by SVD combined with wavelet neural network (WNN) can eliminate the impulsive in the measurement data effectively.
For the GPS measurement data processing, this method is effective to obtain satisfaction results.

Selective catalytic reduction (SCR) aftertreatment system has been applied to reduce Nitrogen Oxides (NOx) as a key technology.
The simulation data were shown in table 1: Table1, Simulation Data and Results M N NO2(ppm) NO(ppm) NH3(ppm) NOx conversion efficiency NH3 slip(ppm) 1 5 1 50 250 300 91.% 14 2 7 1 37.5 262.5 300 90.% 15 3 9 1 30 270 300 91.4% 12 4 9 0.8 30 270 240 76.4% 8 5 9 1.1 30 270 330 93.4% 49 Through the results of the simulation, can analysis the two factors influence on the NOx conversion efficiency and NH3 slip intuitively, the changes of m has not influence on the NOx conversion efficiency and NH3 slip, however, the changes of n has a great influence on them.
The NOx conversion efficiency has a significant reduction.
[2] Ming-Feng Hsieh, ”Control of Diesel Engine Urea Selective Catalyst Reduction Systems”.
Diesel SCR NOx Reduction and Performance on Washcoated SCR Catalysts [C].SAE, 2004-01-1293

An experimentally verified FE model provides a baseline that can be compared with data collected from an in-service testing on the same structure to determine whether the structure is in a healthy condition.
In recent years, many methods have been proposed to locate and assess structural damage from measured data.
A reduction coefficient for each finite element is defined and later found to indicate stiffness reduction in that particular element.
For an undamaged structure, all reduction coefficients are zeroes, i.e. δj = 0, j = 1, …, l.
After only 7 iterations, all damaged elements and the extent of their stiffness reductions are clearly identified.

Then, the pretreated sample data using rough set attribute reduction method to delete redundant attributes.
Rough Set theory is based on a simplified indistinguishability of ideas and knowledge methods, while maintaining the ability to classify the same premise, through knowledge reduction, the logical inference rules from the data in the system as a model of knowledge.
Using rough sets to avoid the loss of information caused by discrete data in a data processing process, through the rough set attribute reduction, greatly reducing the training process of neural networks[3-4].
Fault diagnosis method proposed neighborhood rough sets and neural networks using neighborhood rough set to avoid the loss of information caused by discrete data in a data processing process, through the rough set attribute reduction, greatly reducing the neural network training process.
[8] Yulig Y, Ye SH, Rough set reduction for hybrid data based on genetic algorithm, Journal of harbin institute of technology. 2008,40(5):683-687

By integration analysis of monitoring data of typical section, curves of horizontal and vertical displacement with time were drawn, shown in Figure 3.
Based on the observation results of typical section and the cumulative horizontal and vertical displacement variation, as well as integration analysis of the data, curves of horizontal and vertical displacement rate with time are drawn, shown in Figure 4.
By integration analysis of monitoring data of typical inclinometer hole, deep displacement curves with depth were drawn, shown in Figure 5.
Fig.11 Plastic strain contours Fig.12 Changing curves of side deformation with reduction factor (3) Based on the penalty function contact of pile soil and the surface of rock mass, the three-dimensional numerical model of coupling of seepage and strain has been established, the measured value of 55.3mm, numerical simulation of 56.1mm through analyzing and comparing with field test data of slope.
Slope Stability Analysis by Strength Reduction FEM [J].

The flow stress data from a Gleeble machine, obtained both below β transus temperature in two phase α+β region as well as above β transus temperature in β phase region, were directly used in the FEM simulation of extrusion process, eliminating the need for any assumptions regarding material plastic flow law.
From such information, the necessary design specifications and data are obtained for optimization of the design of dies and the prediction of mechanical properties of extruded product.
For optimizing the values for heat transfer coefficient and friction coefficient for Zr-based alloys and tool steel interface, multiple combinations of convective heat transfer and friction coefficient were adopted for simulation and the ones which gave ram force profile that conformed to the actual experimental data obtained from the shop floor were taken as the optimum values.
Reduction ratio Reduction Ratio 6 (a) Reduction Ratio 8 (b) Reduction Ratio 10 (c) Reduction Ratio 12 (d) Reduction Ratio 14.4 (e) Reduction Ratio 20 (f) Figure 3: The temperature profile is seen to change with change in reduction ratio.
Effect of reduction ratio Intuitively, increasing reduction ratio should result in increase in required ram force.

The anode is made by carbothermal reduction of an enriched TiO2 slag.
Data obtained by XRF analysis and given in weight %.
Data obtained by XRF analysis and given in weight %.
This is due to an "incomplete" carbothermal reduction process.
Martinez, Electrochemical Society Transactions, 16 (49) (2009) p. 229 [15] Landolt-Börnstein in Phase Equilibria, Crystallographic and Thermodynamic Data of Binary Alloys, Springer-Verlag (1998) [16] D.M.

Aerodynamic Drag Reduction Design of Concept Sports Car Ying-chao Zhang1, a, Fang Zhao1, b, Shu-xin Shao1, c and Guang-yin Jin2, d 1State Key Laboratory of Automotive Simulation and Control, Jilin University, China 2China FAW Company Limited R&D Center, Jilin, China ayingchao@jlu.edu.cn, bzfzhaofang@gmail.com, cshaoshuxinjlu@163.com, dgabrielking@126.com Keywords: Sports car, shape optimization, CFD, Aerodynamics, drag reduction.
The aim is to provide the experimental data for researches of drag reduction and aerodynamics theory. [2] 2 Model 2.1 Basic Theories.
(3) Comparison with the foregoing analysis, you can see basically the fingerprint consistent with tabular data analysis.
All show that the optimization of spoiler and body results obviously, the reduction of grill wind resistance coefficient mainly due to the reduced area of small grid on both sides.

Therefore, this paper presents a modified algorithm based on Nesta algorithm to reduce the amount of data sampled of power quality signal, the complexity of the algorithm to improve the algorithm’s speed.
Compressed sensing algorithm is in the process of data sampling is completed while the compression process, then the resulting signal is then compressed in the terminal for data reduction process.
The core content of the compressed sensing algorithm can be seen in three aspects: First, the sparse representation, its main role is the traditional sparse sampling data base by converting a sparse signal in order to remove redundant data signals traditional, with less the amount of data representation signal; Second, the measurement matrix, and its main role is to mapping x N-dimensional signal to the M-dimensional signal y, mainly to ensure that information is not lost; Third reconstruction algorithm, the main role is from M-dimensional signal y matrix through a non-linear projection regain N-dimensional signal.
Fig. 1 1600 bit timing simulation data image, (a) the voltage sag signal, (b) the voltage liter signal simulation, (c) the voltage interruption signal, (d) the voltage pulse signal Power Quality Signal Compression Sensing Algorithm.
Nesta Reduction Algorithm.