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(2) (3) Where f and are the friction factors in the pipe and the specific weight of the water, the friction factor (f) is the main data we wanted to observe.
We analyzed our data by using Numerical Curve fitting in the exponential function [12], resulting in a new equation
From the calculations illustrated in Fig.4, we defined the hypothesis trend line of experiment data as an exponential function.
We then analyzed our data by curve fitting technique using the exponential function [12], to find the relationship between flow rate in a pipe and level of water.
From data of this study, when we using polymer solution in difference concentration in pipe flow at turbulent condition, we can increase flow rate in pipe because friction between pipe wall and fluid are decrease follow the hypothesis of Drag reduction effect, in this research can show the data in Fig.7, that is a relationship of friction factor (f) in y-axis and Reynolds number (Re) in x-axis, the result show effect of polymer solution can decrease friction factor immediately by this experiment best of polymer concentration is in 30 to 100 wppm because these friction factor are decrease in closely number compare with pure water, by percentages are 35, 45, 44 and 44 % at polymer concentrations are 10, 30, 50, 100 wppm.

The collected vibration signal can be used for data mining as well as obtaining fault rule based on the rough set theory.
Vibration data mining based on Rough Set theory 60 vibration signal of the rotor experimental platform sample data were analyzed, and the normalized energy as condition attributes, using fault types as decision attribute to form fault diagnosis data tables.
So we chose 80% of the data as training samples, 16 samples of each fault samples, and take the remaining 20% of the data as a test sample.
Data partition is obtained according to the above method(Table 3).
The table 4 shows that the reduction produces 37 diagnosis rules. 

Reduction of anatase started just below 900ºC whilst rutile underwent reduction below 800ºC.
Positions of the peaks were taken from the ICDD database, however, peaks for the mixed valance TinO2n-1 phases where n>3 were only present up to 2θ = 50.2º and the data for these has taken from the paper by Bowden et al [16].
The onset of reductive mass loss in rutile system occurs at ~770ºC, about 100ºC lower than for anatase system Beyond the initial mass loss due to desorption, it is difficult to compare the curves in Fig.1, therefore the data has been differentiated so that the stages become more clearly defined.
Further heating to 1380ºC resulted in completing the reduction.
The reduction of rutile started at ~770ºC whereas reduction of anatase began about 900ºC.

In order to prove the numerical simulation validity, the simulation data was compared with that of the experiments, which shows that the vibration prediction error is lower than 15% and the noise prediction error is about 5 dB(A).
The sound absorption material was pasted on the bulkhead of cabins, and the average noise reduction level achieved to 7 dB(A).
Then, the single-layer vibration isolation system was designed for the diesel engines, the average noise reduction level achieved to 5 dB(A).
So the noise reduction measures for meeting room should be carried out.
The noise level in high frequency is reduced obviously after the treating and the average noise reduction level achieves to 7 dB(A).

Noise mixed in the recorded seismic signals often affects the data analysis result.
In addition, the higher sampling frequency of seismic record, resulted in massive monitoring data, the application of split-based FFT algorithms to do spectral analysis of the data, reduce computation and improve the speed of data analysis than base 2FFT and base 4FFT, thereby improving the timeliness of the seismic monitoring system.
A Wavelet Packet Decomposition Technique Principle In the field acquisition of seismic data it was inevitable to contain some regular or irregular interference noise, which would have a significant impact on the geological data interpretation.
Fig4 and Fig5 were data of two channels and the denoising datas.
Fig4 Data processing of channel one Fig5 Data processing of channel two Acknowledgment This work was supported by Team funded projects of the Central Universities basic research expenses and special funds innovative projects (ZY20120101) References [1] RenXueping,Ma Wensheng, XiaoLongsong.

Reliability-Based Assessment of Bridges Using Long-Term Monitoring Data Y.Q.
From the monitoring data the bridge managers want to get answers to the serviceability and reliability issues: (i) has the load capacity or resistance of the structure changed?
As consistent with reliability analysis, the structural damage is first identified using a probabilistic approach from the monitoring data, so that the damage identification results account for uncertainty and randomness inherent in the measurement data and the structure.
The uncertainty in measured modal data is assumed as normally distributed uncorrelated random variables with known statistical properties.
In this example, the simulated stress measurement data (history) for each member is obtained by applying the random loads V to a finite element model of the structure.

Applied-information technology in fusion SVM partial least squares analysis of experimental data in the body of PET Xian Zhou, Ying Xiong, Wangping Xiong, Lingzhu Xiong Jiang Xi University of Traditional Chinese Medicine, NanChang, JiangXi, China Corresponding author: Wangping Xiong xiaoxiongxwp@126.com Keywords: Partial Least Squares; SVM; PET; Data Mining; Nonlinear Data Abstract.
But in the data acquisition process, often unnoticed or be some subtle surprises.
Observational data can not contain a gross error, otherwise the result is not reliable.
The reason is because there is a variable data from the data recording abnormality, when this happens, there will be a natural component of the selected offsets, thereby affecting the results of the regression.
A modified PLSR method in prediction[J],Data Science，2006,4:257-274

The numerical model of the seat frame has been developed and the numerical results were validated against experimental data obtained during static loading tests.
The mass reduction verified by the introduction of the new topologies is shown in Table 3.
Table 3 – Mass Reduction associated to the changes suggested Component designation Mass Reduction (kg) rotary foot 3.09 backrest 0.97 cushion 0.41 The global mass reduction associated to the suggested changes is approximately 4.47 kg.
The good concordance between the numerical results and the experimental data is an important point to highlight.
It is expected that the proposed changes to the current car seat frame are directly linked with a substantial reduction of mass.

Its calculation procedure is shown as below: Step1: Confirm the reference sequenceas a record in standard fault sets and comparative sequence, process the data being dimensionless.
Step2: calculate difference sequence, whereas comparative sequence which is unknown pattern, as reference sequence, which is history diagnosis data sequence.
Select the record in reduced diagnosis knowledge database as reference sequence, the data observed which transform to reduced space as comparative sequence.
Part of the data that sampled repeatedly and modeled by AR time-series in normal and wear state is shown in Table1.
Use 10 of 20 data acquainted with known state construct the learning samples data sets, the other 10 data as test data, after the original data normalized, Use respectively the grey relational analysis(method 1)and rough set based weighted grey diagnosis method(method 2) to recognize their status.

Figure 1 shows an eye-diagram of a Pulse Amplitude Modulation (PAM)-4 data transmission on a micro-strip line.
To calculate the data at twice the symbol rate, the transmit data is held for T sec by a delay element.
Figure 4 shows the simulation results of a PAM-4 data transmission using DTHP at 2 GS/s (Symbol/sec) on a 1-m-long micro-strip line.
The transmitter data can be demodulated at receiver by using modulo reduction.
Yuminaka, “Double Rate Equalization Using Tomlinson-Harashima Precoding for Multi-Valued Data Transmission,” Proc.