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Finally, the model outputs for several samples compared with experimental data to evaluate precision of model.
This data was obtained by placing various weights on a fabric mat just after it had been wet out by hand.
This test apparatus gave a fabric flow area of 161 cm2 to reduce scatter in the data caused by the random variation in permeability.
At each point, the differential pressure was recorded throughout the test with a data logging multi-meter.
To get around this, data from separate compressibility tests were used along with the uncompressed thickness as recorded before the test.

The analysis on concrete acoustic emission technology We have done sound emission data receiving of the concrete cracking process through sound emission receiver apparatus, and have got the sound emission data curve, and through which judge the destructive condition of the concrete, and adopted the reinforcement measures of the concrete according to the results we’ve got, thus we have to analysis the data we received.
However, the sound emission phenomenon of the concrete material is a very complex process, the development situation of the inner crack is also very complex, which need a large amount of data for the study and establish the sound emission data model and formula.
The sound emission technology data curve of the concrete should be improved In the process that we apply the sound emission technology to the testing of practical engineering concrete material, the noise will occur, which would disturb the sound emission data curve, thus we have do get rid of the noise before we analyze the sound emission curve, the sound emission data we got will reflect the real condition of the concrete material.
Researchers had done little work on the processing work of concrete sound emission data.
The researchers should adopt many ways to get rid of the noise of the concrete sound emission signals, and compare which one is will eliminate the noise effectively, the curve after noise reduction would truly reflect the stress effect of the real constructions, and can establish the computer software programme by the results and provide service for the actual engineering data.

Fast access to data and manufacturers resources is desirable.
Ease of manufacturing is possible by products complexity reduction.
Data and groups of data are organized in fields as entities (objects, events) and records (attributes of objects or events) on datasheets.
Entities represent elements for which data should be stored.
Data for all tools, inserts and machines are stored.

The data in each unit were updated as the construction process progressed.
This data-accumulating process is easy to understand by imagining that the units continuously flow down the network from the top process, upstream of the excavation, to the bottom process of ship loading, collecting new data during each step of the construction.
The data concerning the blasting are also recorded on the information units to be used afterward for a ground evaluation.
The data recorded in the subsystem includes spatial information, and thus, all the recorded data are organically unified on three-dimensional GIS, enabling the analysis of various types of information.
These effects created enough time for the engineers to make accurate decisions, based on the large and favorable data.

For the statistical processing of the experimental data the VH5 hardness values of the studied materials were considered.
Generally, a technological process can be described by a mathematical model and is characterized by two types of parameters or variables: independent parameters (input data) and dependent parameters (output data) [6,7,8].
Empirical methods of the mathematical modeling used in regression analysis by passive experiment allow statistical analysis of the experimental results by using the variation of the input data to different levels.
Experimental data As experimental materials, three compositions of iron-copper alloys having different additional elements made by PM route were used (Table 1).
Table 1 Alloy compositions [wt%] and experimental conditions For the statistical analysis of the experimental data the hardness values of the analyzed materials are presented in Table 2.

Many new challenges in data quality were also exposed.
The quality of available data was often exceedingly poor or entirely absent.
Data quality is another challenge in supply chain management.
International Journal of Disaster Risk Reduction, 102983
To Fight Pandemics, We Need Better Data.

But the artificial neural network needs a large number of sample data, and the information processing system is complicated.
But for the objective weighting method, the collected data has a great influence on the results.
Once the data has some deviation, the results might differ greatly from the actual weight.
Data acquisition and processing of the case.
In this paper, the energy consumption data comes from a public building.

Several data were gotten by proximate analysis with considering indexes of volatile matter, fixed carbon, sulfur content, heat value and ash.
The regression equations of the data were gotten through regression analysis for the relationship between blend ratios of corn stalk(BRCS) and proximate analysis data(PAD)．The result showed that there was linear relation between PAD of the blend fuel and BRCS, and linear equation slope absolute value of volatile matter, fixed carbon, sulfur content, heat value and ash were 8.49,7.64,5.45,4.85,3.97, respectively.
Some characteristics of blend fuel about corn stalk and coal were found, which can provide some data for utilization of blend fuel of biomass and coal.
PAD and calorific value of corn stalk, coal and blend fuel was gotten by an Automatic Proximate Analyzer (5E-KCIII/MAC/GIII, China), ultimate analysis data was gotten by an Automatic Ultimate Analyzer (EA3000, Italy), low heat value were gotten on the base of calorific value and ultimate analysis data.
Some characteristics of blend fuel about corn stalk and coal were found, which can provide some data for utilization of blend fuel of biomass and coal.

The X-Ray diffraction study coupled with the Rietveld refinement of XRD data showed that sample crystallize in a rhombohedral structure with space group of R-3C.
The AC-susceptibility data obtained at different frequencies confirmed the presence of a frequency–dependent freezing temperature around room temperature.
By fitting the experimental data with mentioned models the possibility existence of superparamagnetic/spin glass states were considered.
By fitting the experimental data from ac susceptibility of sample (Figure 4), we have found unphysical low values for τ0 (Table 2) in comparison to the values of 10-9-10-13 s for SPM systems.
Yusuf, Effect of size reduction on the ferromagnetism of manganite La1-xCaxMnO3 (x=0.33), New J.

Data Transformation.
Since raw data is not useful unless it is reduced and transformed into information and knowledge for responsive actions, data mining tools for data reduction, representation and prediction adopted for plant floor data need to be developed [14].
There will be a local evaluation of the data.
For example, reducing data into useable information would be easier when transmitting large data on a particular bandwidth.
In overall, it is a concept and set of systematic methods that attempts to control the product information which contains of several data (specification data, Life cycle data and Meta data).