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In comparison, the same amount of data can be send through 2-D OCDMA system.
The signals are sum of temporal spreading data of users carried on the wavelength and expressed as .
Where is the data bit of the user and Fu is the number of users.
High data transmission rate increases in BER, requires high effective power and deteriorate the system performance.
The 2-D PDC, 1-D MDW and 2-D MDW with 1.1Gbps and 2.5Gbps data rate suffer high power penalty lost due to high transmission data rate.

The human body's dynamic and static data show that the parameter of detail parts specification has great changes, while the parameter of control parts' specification parameter has small changes.
Experimental Size measurement and variable analysis under body static condition Through data collation and variable analysis, dynamic parameters of the human body is obtained, which provides data reference for the restructuring of sheath dress and suitability inspection
The experiment rules out individual differences of limiting the movements due to physical factors in order to ensure the relative stability of the measurement data
Data collection, reduction and analysis Due to initial data collection may overload, after finishing and analysising the variables and parameters, only study and analyse the body surface of related position which may influence the suitability of the sheath dress pattern, which can provide data reference for detail structure of sheath dress pattern of elastic fabric based on dynamic change.
According to the data both under static and dynamic condition, the change of body surface extension parameter of detail specification is larger under moving condition, while there is no obvious change in control parts (see Table 1).

Control of their accuracy parameters is complicated task consisting from some high requirements needed for rotation, positioning, signal processing, object adjustment and data processing.
During the process of calibration the results of measurements are collected and accumulated data is analyzed by information system.
Data management of mechatronic system The amount of data generated by such systems is usually vast in an average complexity of the system.
Adding information entropy parameters helps to determine the uncertainty of performed measurements, therefore improving the accuracy of data processing. 5.
Data processing and information assessment in scales measurement simulation, in: Proceedings, XVII IMEKO World Congress, 2003, pp. 1053–1056

ArcGIS software is applied involving in data collection, data management, data analysis and evaluation process expressing.
The primary detrimental effects of Seawater intrusion are reduction in the available freshwater storage volume and contamination of production wells, whereby less than 1% of seawater (250 mg/l chloride) renders freshwater unfit for drinking.
Fig2 Information value accumulated curve Fig3 Hazard evaluation and evaluation test The precision of the model was validated by the monitoring data of the mean concentration of Cl- from 2011.6 to 2011.10,which are acquired from 18 automatic monitoring stations.
According to the standard of seawater intrusion evaluation, the data of the 18 well can be divided into 3 kinds: no intrusion well(Cl- < 250 mg/L), intrusion well(250 mg/L < Cl- < 1000 mg/L) and serious intrusion well> 1000 mg/L).

Table 3 Demand pattern & Wind generation pattern Demand pattern & wind generation pattern Peak time Scenario 1 Spring 2~6p.m (4h) Scenario 2 Summer 1~5p.m (4h) Scenario 3 Fall 1~5p.m (4h) Scenario 4 Winter 8~12a.m (4h) 3.2 Input data for carrying out case study A chart of input data for carrying out REC weight analysis in the already selected peak time slot can be made as follows.
Therefore, KRW 500 million was reflected in the input data for the additional installation cost of ESS after 10 years.
Application of different weight to peak time slot is meaningful in the respect that it is a factor that can motivate the renewable power producers to use ESS, and can be utilized as baseline data of incentive provision method of government that aims at peak reduction and the peak coincident factor improvement of renewable energy source.
Peak time slot was determined through system load pattern and renewable power generation pattern analysis, and was utilized as input data for assessing REC weight through life cycle cost analysis according to each assessed scenario.
REC weight assessment is meaningful in the respect that it is a factor that can motivate the renewable power producers to use ESS, and can be utilized as baseline data of incentive provision method of government that aims at peak reduction and the peak coincident factor improvement of renewable energy sources.

MAUD v2.94 Rietveld refinement software are used to simultaneously refine the diffraction data by varying the spherical harmonic texture parameters [18-20].
Result and Discussion Fig. 1 shows the sample data reduction and curve fitting which shows a good agreement between reduced data (blue) and pseudo-Voigt fit (red).
Total of eleven data of each azimuth angle (φ) were reduced, fitted, and evaluated by sin2ψ – σ plot as shown in Fig. 2.
Fig. 3(a) shows the 2D xy-offset data plot from φ=0° to φ=90°, one can clearly see is that all the major peaks are increase with φ (maximum at 90°).
The sequential Rietveld refinement shows a good agreement between observed and calculated data (Fig. 3(c)), but there is over (600 cts) and under (-740 cts) fit shown in residual fit (Fig. 3(d)) due to the limitation to model the actual data.

Measurement setup During the whole experiment measurement data from all the sensors applied to the construction were constantly collected, with predefined intervals, using distributed network data acquisition system.
Magnetic field and earth field acceleration data were sampled with a sampling frequency of 2 Hz.
Sensors were transmitted measured data over CAN network to the cRIO controller (NI 9853 module).
Sampled data were send from the computer to the database of the system over TCP/IP network.
There were no significant difference of the standard deviation of the measured displacement between the data obtained using reference camera and the camera the data computed after rectification.

The reductions in building envelope heat losses combined with optimized material configuration and the proper amount of thermal insulation and thermal mass in the building envelope help to reduce the building cooling and heating energy demands and building related CO2 emission into the atmosphere.
a) Free convection: The heat transfer by free convection is given by the equation where the constants “C” and “n” are determined by the correlation of experimental data.
Conclusion In the rapidly changing scenario in building sector, architects, and builders are looking for new materials and technologies to adopt in future constructions that benefits like energy efficiency, life cycle cost reduction and durability.
The reductions in building envelope heat losses combined with optimized material configuration and the proper amount of thermal insulation in the building envelope help to reduce the building cooling and heating energy demands and building related CO2 emission into the atmosphere.
Wong, Handbook of Essential Formulae and Data on Heat Transfer for Engineer, Longman Group Limited, London, (1977)

Freecod-data collector, dynamics GPS and the sensors of steering degree was utilized to study the rule of driver steering velocities, the relationships between maximum steering velocities and distance, and as well as maximum steering velocities and driving velocities were eastablished.
Data Acquisition and Processing Data Acquisition Test of driver’s steering characteristics under emergency was done in a pilot plant of Ministry of Transportation.
The data of maximum steering velocity and distance under different velocities Distance to obstacle D(m) 41.9 40.462 41.214 40.972 51.783 51.524 50.913 50.037 Turning speed (o/s) v=75km/h 445.8 418 408 397.27 374 408.4 408 416.8 v=70km/h 441.8 448 448 445.93 303.6 345.4 347.4 398.8 v=60km/h 413.8 404 404 407.27 378 364 344 328.67 v=50km/h 286.6 378.4 443.2 369.4 210 185.6 199.2 198.27 v=40km/h 310.4 292.8 237.2 213.47 236.4 248.4 221.4 218.73 After linear regression analysis of Sample data in Table 2 get the regression curve in Figure 5.
Figure 5 on the left is the data point and the regression curve, the right frame box is the regression line coefficient and the correlation coefficient, test number.
On the left, is the data point and the regression curve, the right frame box is the regression line coefficient and the correlation coefficient, test number.

Thus the coking enterprises urgently need a coke prediction method using many blend coal- related data.
Support Vector Machine [3] (SVM) is a new machine learning methods developed on the basis of the statistical learning theory, just to solve the prediction of such a small sample data. 1.Support Vector Machine Theory In 1995, on the basis of the statistical learning theory, Vapnik proposes the SVM theory.
The basic idea of support vector machine regression is that by a nonlinear mapping, data is mapped to a high dimensional feature space, and linear regression is got in this feature space。
Coal vitrinite reflectance [6] distribution could correctly reflect substantial change degree of coal, so coal vitrinite reflectance distribution is considered as an important indicator of the coke forecast, but reflectivity distribution is combined by 60 data, in order to facilitate the calculation, the data is divided into six parts.
Data Mining and Knowledge Discovery，2003，2( 2) : 121-167