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The wind induced responses are calculated from these wind load datum from above three tests considering the coupling of mode shapes.
Wind tunnel test and model summary The wind tunnel test with simultaneous surface pressure measurement was carried out in TJ-2 atmospheric boundary layer wind tunnel in the state key laboratory for disaster reduction in civil engineering in Tongji University.
In order to describe the changed wind load more clearly, four rectangular section high-rise building models’ test datum were taken as compared ones.
Summaries In this paper, a wind tunnel test with simultaneous surface pressure measurement was carried out and the relevant data analysis was done.
A new force balance data analysis method for wind response predictions of tall buildings.

In the marine engine room, there are a variety of equipment, such as main propelling engine, diesel generator set, air blower, pump, air compressor, air conditioning unit, steering gear, other auxiliary machineries, reduction gear box, and transmission system.
The Bluetooth technology has a data transfer rate of 1M/s, which can make the vibration waveform not be distorted and can make the computer analyze the spectrum and conduct fault diagnosis accurately.[2][3] The Bluetooth technology has been widely used in office automation and communications, such as Bluetooth keyboard, Bluetooth printer, Bluetooth cell-phone and Bluetooth headset.
In the special module, the electric signal is amplified by the amplifier, transformed by the integral converter, compensated by the equalizer, changed into digital signal by the analog to digital converter, turned into serial data by special circuit, linked to the Bluetooth application module by the RS-232 interface, and sent by the transmitter of Bluetooth application module.
With the help of relay function, the computer in the engine control room receives the signal. [4-8] Fig.2 The structure of the vibration sensor with wireless transmission system The system structure of wireless vibration monitoring device The real-time vibration monitoring system in the engine room can offer helpful information for fault diagnosis, offer references for troubleshooting, and offer data for testing the repair result.

PLSRM was achieved through actual measurement data and calculation results of geo-stress, then fitting data was ready.
(2) calculated covariance matrix V of standardized data matrix X, V is the correlation coefficient matrix of X
The data was extracted as dependent variable Y for subsequent calculation.
The independent variable data matrix would be written as E, the dependent variable data matrix as F.
Usually due to cost constraints, the measured sample points were relatively few and valid data obtained from tests was very limited.

In this paper, we use the well-known model proposed by [3] which has a linear decay and is given by (1) c determines the white phase noise floor of the oscillator. a gives the phase noise level near the center frequency up to . b is the steepness of noise reduction with increasing frequency distance up to where the noise floor becomes dominant.
The whole steps are shown below: Step1: Coarse data estimate 1) LS estimation at pilot subcarriers to obtain pilot frequency responses. 2) Linear interpolation at time domain between adjacent symbols. 3) Linear interpolation at frequency domain to get all frequency responses. 4) Coarse data estimation utilizes the frequency response coefficients.
Step2: ICI cancellation 1) Construct ICI channel matrix by Taylor’s expansion. 2) Substract the ICI coefficient of received data. 3) And then update the received data.
Step3: Fine data estimation and decision feedback 1) LS estimation and linear interpolation at both the frequency and time domain from the update received data to get ICI free data. 2) Using the decision feedback procedure with ICI free data, get the feedback data.
Step4: Update the phase noise vector by relation between feedback and received data of present time.

The data obtained from the experiment is shown in Table 1.
The diagram of curves Fig. 3 shows the relationship between the processing speed and roughness of workpiece surface refereed to the experiment data.
The data obtained from the experiment is shown in Table 2.
The diagram of curves Fig. 4 shows the relationship between the magnetic field intensity and roughness of workpiece surface refereed to the experiment data.
Conclusion The experimental data from Table 1 to Table 3 are measured by 80 orders for abrasive particle size.

In this paper, the design of smart state machine and various data processing module.
Constantly from the frame, on the other hand, the cache to retrieve data, is in accordance with the prescribed format output.
The FPGA as the logic control chip, responsible for identifying the source signal, the image data according to certain format writing frame cache, while at a fixed rate of reading data from the frame buffer, and generate the corresponding sync signal, sent to the DAC together; Block and EEPROM used in active serial mode of the FPGA configuration on electricity.
The image processing system design based on FPGA Image processing system should be implemented based on FPGA and external to communicate with other systems, or receive the output image data, cache the image data, and meet the requirement of algorithm, and thus to hardware algorithm processing of images, and have certain ability of the advanced treatment of image.
After the completion of the system configuration, video acquisition device for video images, each frame by the analog-to-digital conversion generated image data into preprocessing module, after preprocessing the image data into SDRAM memory, the subsequent processing of the image by the Nios II processor and control, after processing of the image by digital to analog conversion on the monitor real-time display.

According to the simulation experience and related data, the maximum number of iterations is 20, water content tolerance is 0.0001, pressure head tolerance is 0.1, upper optimal iterative range is 7, the lower optimal iterative range is 3, upper time step multiplication factor is 0.33, the lower time step multiplication factor is 1.3.
Water flow parameters.According to the Van Genvchten-Mualem model and software unique experience of soil parameters database, combined with the experimental measured data, set up the moisture migration parameters are shown in table 1.
In combination with the determination of the actual test data at the same time, compared with the simulation results, found the simulated data and experimental data have the same change trend, as shown in figure 1 ~ figure 3, the simulation accords with actual situation, software reliability is verified.
Fig.1 Ammonia nitrogen simulation data and test data comparison chart Fig.2 Nitrite-nitrogen simulation data and test data comparison chart Fig.3 Nitrate-nitrogen simulation data and test comparison chart Analysis.
Initial interactions with two autotrophic nitrification occurs under the action of bacterial nitrification, ammonia nitrogen under the action of nitrite bacteria is converted into nitrite-nitrogen, nitrite nitrogen under the action of nitrate bacteria is converted into nitrate-nitrogen, this will cause the reduction of ammonia nitrogen, nitrate on the rise.

The system management including system maintenance and data maintenance function.
The function of the data layer is to realize the integration of the data; The function of the functional layer is to realize the data transmission and processing; The presentation layer's function is to realize the display of data.
System data layer is the lowest level of the system, which stores all data of the system.
The safety monitoring system for pork product is a pork data chain as the core system, so there is only one topic as pork food data chain link.
The security design system database is mainly manifested in the following aspects: a) Data backup and recovery: Using the backup server, data backup, disaster recovery and other measures, establish the database backup and recovery mechanism.

The data were analyzed with the Kolmoforov-Smith test, One-way ANOVA and Tukey’s test.
Statistical Analysis The distribution of the data was calculated by the Kolmoforov-Smith test and the variables were analyzed using One-way ANOVA.
[2] Goldberg, A.J., Vanderby, R., Jr., and Burstone, C.J.: Reduction in modulus of elasticity in orthodontic wires, J.
[9] Siriwat Chamnunphol, Influence of reduction ratio of cross sectional area in drawing stainless steel wire for orthodontic use, 2008

The GM(1,1) developed by converting the original data series into a monotonically increasing data series through a preliminary transformation is called accumulated generating operation (short for AGO).
Using the AGO technique to reduce the noise of the original data series efficiently, and the new data series generated will approximately exhibit exponential behavior.
Applying grey system theory and based on data processing to put forward accumulated or inverse accumulated generating operation, the randomness of data sequence is weaken by generating, thus converting to relative regular data sequence, that is the process of converting stochastic process to grey process [4-6].
If applying accumulated generating operation for data processing, let (2) Then get the new data sequence (3) The randomness of this new data sequence will be weaken, which can process n times.
——new data sequence, which are obtained by using original data in accumulated generating process.