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The first two indices were derived by the side surfaces data, while the wall heights were derived from the top surfaces.
This section presents the results of the analyses, first discussing the thermocouple data and then the surfaces’ geometry.
Thermal data.
Thermocouples data are summarized in Fig. 5, which presents the signals of TC2 (Fig. 1), the closest to the wall.
Surface data.

Five isotherm models were used to describe the isotherm data.
The removal of NH4+ ion from aqueous solution using the ammonium ion-exchange material was studied in PH range from 3 to10, and the data obtained were plotted in Fig.3.
The other parameters are different isotherm constants, which can be determined by regression of the experimental isotherm data.
A lower S.E. value and higher R2 value are considered to represent goodness of conformity between measured and estimated NH4+ exchanged data.
The comparison of their reported ammonium adsorption capacities data is given in Table2.

Noise data was collected simultaneously with the traffic volume survey conducted from 8:00 am to 8:00 pm.
The geographic coordinates of the locations were generated using GPS, where noise and traffic data was collected.
Buffers of diameter 300m centered at the coordinates of noise meter, were made on “Google Earth Pro” to extract the land use data of these locations as [8] had taken data for 200m diameter.
The change in the methodology was due to the change in site selection [8] had collected data for different sections whereas this data was collected at intersections.
The noise data collection devices used (cell phones) lacked the ability to distinguish between different sources of noise.

Considering the failure event in the statistical analysis, the data reduction technique proposed in [14] is used for fatigue limit estimation.
As can be seen a scatter of FCG data is observed especially at low crack length.
Crack length vs. number of cycles curve (CT specimen no. 3) FCG data analysis.
Rilly, A practical method for statistical analysis of strain-life fatigue data, Int.
Mood, A method for obtaining and analyzing sensitivity data, J.

The objective of this work is to filter the data obtained from measurements of the anemometer at NRP Sagres, with the purpose of reducing the previously mentioned errors.
In this project we have used some data base available in [23] relatively to an anemometer from NRP Sagres.
These data were provided to the author of [23].
However, data classification was considered carried out perfectly suited to the scope of this work, having been necessary to import only “Speed” variable.
Notice that the data is expressed in the usual unit of wind speed, the knot (nautical mile per hour = 0.51 m sec-1 = 1.15 mph).

Usually we can clarify hierarchical data and geometric data with a collection of feature data.
Here it will first introduce the link between the attribute data and objective data.
Cache Management component can be used to store the geographical data of the mechanical manufacturing obtained from the server, retrieve cached spatial data in the client, select out and update the cache data.
In a word, data storage, this is because the format of spatial data storage plays a vital role in the cache of system port.
Data mining technology in the application of cost control work With the development of computer data mining technology, data mining tools have been more and more widely applied in the information system.

Data flow is shown in Figure 1.
Fig.1 Data flowing in system Pipeline Property Database.
Pipeline attribute data comprises underground pipeline length, diameter data, depth, construction age, period of use, the type of pipe, the basic purpose, pipes and other relevant attribute data.
Table 1and 2 are part of the pipeline design table of data.
The MetaDatabase manages various data, through the integration and management to data storage, which can accurately describe the data content, quality condition and other functions, MetaDatabase structure of organizations include the establishment of the identity of the metadata, data quality, data maintenance, space representation, distribution and information content.

However, many samples and long time are required in the reliability test, while no special reliability tests are made in the shooting range, so that it is difficult to obtain the reliability data of the electronic equipment in guided missile and also the amount of the data is small.
Also, the geometric figure of grey prediction is a relatively smooth curve, and the predication values fluctuate and the prediction accuracy if it is applied to the prediction of the data with great stochastic volatility.
If the time series data of the prediction problems is fit with the GM (1, 1) to find out the change tendency, the grey model can make up for Markov chain prediction, while the Markov prediction on the basis of the grey prediction can make up for the imperfection of the low data series prediction accuracy with the great stochastic volatility [2].
The modeling method for (GM (1, 1) is as follows: (1) the original data series is processed with accumulative generation to weaken its randomness, and then the generated data series is fit using the first-order differential equation to get the grey prediction model, and then the discrete solution is obtained for the equation, and finally the future development trend of the system is predicted after the accuracy is tested for meeting the accuracy requirements [3].
It is assumed that features the approximate exponential rule, and a differential equation is established for the accumulative data series for changing differential to difference, so the grey differential equation is obtained as follows: a is development coefficient, and its value reflects the growth speed of data series; b is a grey action.

It have the functions for collecting and analysing real-time data, controlling data and history data.
The following functions are the important ones: · Collecting and analysing data.
It restores the historical data and provides query function.
Also, it can do query operation for production data and print the report forms
For example, cutting length, measuring length and speed, weight, forecasting data and tracing data

Data Modeling and Data Storage  Here it mainly involves the modeling and storage of data information on backup devices’ technology and relevant process.
Data storage: In the process of data storage we should take the following three points into accounts: Ensure the independence of modules, so as to improve the storage efficiency; Reduce data redundancy, saving storage costs; Take the safety and integrity of the data into consideration. 2.
Data Management Data management mainly includes data update after executing the operation “add”, “modify” or “delete” and “query” the management of some important information.
Background Data Layer: the data mainly include system data, static and dynamic data of backup devices, process information and auxiliary management information.  
Data sever: data manipulations on the background data layer should completed on MySQL database server.