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Data source The main data for years 2001-2008 was obtained from the Annual TPC Operation Statistics [10].
The data used in the DEA estimation comprised information for 7 DMUs during 8 years for a total of 56 observations.
[5] Dyckhoff, H. and Allen, K., Measuring ecological efficiency with data envelopment analysis (DEA).
[6] Korhonen, P., L CO2uptacik, M., Eco-efficiency analysis of power plants: An extension of data envelopment analysis.
[8] Liu, C.H., Sue J., Lewis, C., Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis.

Big data-driven hybrid model for operation optimization of thermal power units 3.1.
How to analyze these data effectively is clearly of importance.
With the exergy analysis in Section 2, big data analytics emphasis the huge volume of data and imply that the collected data set covers almost the whole population as well.
In this paper fuzzy rough set (FRS) is selected to perform big data analytics.
Table 1 Data sets description Data set Load range （MW） Ambient temp. （℃） Coal quality* （MJ/kg） Samples Original attributes Num.

Yeager et al. [1]-[4] studied the reaction kinetics in the oxygen reduction reaction to found that the two-electron reduction and the four-electron reduction goes simultaneously.
And the set values of the parameters are reasonable, for the data from the calculation are within the effective range.
The simulation data shows that the bond between O1 and Pt breaks when the H3 is close to O1.
Electrocatalysts for O2 reduction, Electrochim Acta. 29 (1984) 1527-1537 [2] Miah R, Ohsaka T.
Recent advances in the kinetics of oxygen reduction.

Based on a two-week benchmark data log, the result shows a total energy reduction from 210 kWh to 71 kWh, representing a saving of 65%.
Table 1 lists the technical data of all the lamps in the system.
Power is computed from voltage and current data logs.
Figure 1 Typical half hour power consumption plot This part of the research involves capturing live data from the system by the aid of a data logger to get a clear understanding of the usage pattern.
As the demand was not uniform, it was inevitable to go for long term data capturing and monitoring.

Algorithm based on wavelet was studied for noise reduction of data cloud, and one volume calculation model was raised.
Wavelet and Riemann algorithms were used to reduce noise of measured data and volume calculation.
Comparison Experiment And Data Analysis To verify the measuring method discussed above, comparison experiment system was designed.
Because the data from laser scanning method is arranged by linear array, the B-spline or NURBS was used to reconstruct the surface of horizontal tank shell.
Zhao: 3D Laser Scanner Data Acquisition System Developed (In Chinese).

Fig. 1 X-ray diffraction data for the mixture of Fe2O3-Ca MA powders as a function of total milling time.
Fig. 4 X-ray diffraction data for the mixture of Fe2O3-Ca MA powders ball-milled for various time intervals and subsequently heat treated up to 600°C.
Fig. 4 shows the X-ray diffraction data for the mixture of Fe2O3-Ca MA powders ball-milled for various time intervals and subsequently heat treated up to 600°C.
Hence, the magnetic data of Fe2O3-Ca MA powders can supply a better understanding of the evidences for the solid state reduction process of Fe2O3-Ca system, as well as the amount of magnetic phase and microstructures.
The X-ray diffraction and magnetic data have been discussed simultaneously in order to achieve a better understanding of the solid state reduction induced by MA.

It provides a theoretical basis for the implement of liquid core heavy reduction rolling mill. 2.
Simulation conditions: rolling reduction is 70mm, line speed is 0.9m/s, and materials are 2Cr12NiMoWV and 5Cr4W5Mo2V.
Simulation conditions: rolling reduction is 70mm, line speed is 0.9m/s, material is 5Cr4W5Mo2V.
Simulation conditions: rolling reduction is 90mm, line speed is 1.09m/s, material is 5Cr4W5Mo2V.
[4] Lu Huimin, Shen Yunyuan: Mechanical Engineering Material Properties Data Manual.

Then, the Hadamard transform is performed to reduce the correlation of the input data sequences.
Finally, data signals are successfully received after the P/S conversion.
CCDF denotes the probability that the PAPR of a data block exceeds the threshold value.
PAPR Reduction Technique Hadamard Transform is a precoding technique that reduces the correlation of the input data.
The data sequencesafter the Hadamard transform can be represented as: (5) Partial Transmit Sequence Scheme.In the PTS scheme, an input data block of N symbols is partitioned into several disjoint subblocks.

A newly developed response prediction technique has been successfully used for the identification of more detailed information from limited sets of data.
They are written as follows Simple Vibration Test Upgrade and Optimization Response Prediction Structure Limited Data Full Field Response Data { }{ } { }{ } { }{ } { }{ } { }{ } { }{ } 2 T n n 2 2 T T n n n n U v RU v MAC= U v U v RU v RU v                  
Conclusion With the response prediction technique, the full field response data can be deduced from the limited data obtained by simple vibration test instead of conducting full-size test, which can present reference for the succeeding upgrade and optimization in dynamic design.
References [1] Chipman,C, Expansion of Real Time Operating Data [D],Master's Thesis,University of Massachusetts Lowell,May 2009 [2] P.Pingle, C.Niezrecki, P.Avitabile.
Real Time Operating Data Expansion for Dynamic Stress and Dynamic Strain Fatigue Accumulation [A].

Most recently, wavelet analysis stands out to be a powerful tool for signal processing including data compression, data transmission and denoising.
The data are acquired spirally at the sampling interval of 1 mm.
Fig. 7 shows a sampled data of thickness.
SMA, Gauss WMA and Haar WT are applied on that sample data to study their performance of noise reduction.
In other word, the noise account about 10% of measured data.