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Introduction Since the demand for the data service of use equipment (UE) has grown highly.
We perform autocorrelation calculation between PSS data in time domain and the received wireless frame data and find the maximum value.
And we just need to store only 1024 words for each group of data .So the storage memory space of local PSS is only 2048 word.
We adopt real-time data processing in order to solve problems of the massive memory needed to be created.
It means that we perform correlation calculations while receiving data at the same time, which requires that we should have accomplished the processing of the prior received data before the later data arrives.

Etch trend data for etch rate, sidewall profile angle and depth uniformity.
B) Cu masked samples etch data, varying SF6 flow at constant source and bias powers with low process pressure.
C) Cu masked samples etch data, varying process pressure at constant source and bias powers with low SF6 flow.
Etch trend data for etch rate, sidewall profile angle and depth uniformity.
B) Cu-masked sample data for variable process pressure with SF6 held at 100% of max and constant source and bias powers.

To investigate the discrete degree of the effective principal compositions in cement and the reliability of data, the cement specimens with bottom ash added were analyzed.
With reference to Chebyshev’s theorem and the empirical rule, we concluded those data within the intervals with the specific standard deviations from the average.
In this regard, there were 75% (or 95%) of data within the interval with 2 standard deviations from the average by Chebyshev’s theorem (or by the empirical rule) and 89% (or 99.7%) of data within the interval with 3 standard deviations from the average by Chebyshev’s theorem (or by the empirical rule).
Based on the data collected in this study to recognize and analyze any error, the credibility of data in the sample set is investigated and checked here according to the Empirical Rule by which there are 95% of data at least within the interval with 2 standard deviations from the average.
The analytic results indicate the test data is credible because of 100% of data distributed within this interval.

The results show monitoring data is stable, reliable, and the problem of high water content of lube in the steel industry is solved.
According to the level of abstraction, Oil data collection and identification fusion is divided into three groups: data-level integration, feature level fusion and decision level fusion.
Data-level integration is the direct integration from the same level of the raw sensor data (temperature).
Information about a particular quantity of interest Wi therefore comes not only from the properties of those data which directly depend on it, but also from the properties of the population of parameters W as a whole, inferred from the data as a whole, summarized by the hyper parametersη.
Fig.4 Fault diagnosis based on lubes data fusion of neural network The system application in metallurgy, power industry is shown in Fig. 5.

Computer simulation technology is a very complicated professional technology, data acquisition system using data acquisition card generally is expensive and difficult to exactly match with the actual demand.
Sound card as the data acquisition card has the advantages of low cost, easy development and system flexibility.
(2) the simulation modeling aspects: in addition to adapt to the development of computer software and hardware environment and constantly research new algorithms and the development of new software, modern simulation technology adoption model separation technology with the experiment, namely the model data driven (data driven).
Data validity Problem of entity To verify the simulation results A simulation model checking The simulation model The conceptual model Design entity Validation of the conceptual model Figure 2 VV & A and M & S along with the development of reliability research in recent years and puts forward the simulation test and evaluation (hereinafter referred to as the T & E) [10], reliability and use it as a organic whole, referred to as reliability assessment.
[2] Balaji Raghavan, Liang Xia, Piotr Breitkopf, Towards simultaneous reduction of both input and output spaces for interactive simulation-based structural design [J].

According to the damage statistics data of several past earthquakes of China in recent years, the difference of damaging phenomenon and rate of earthquake damage of earthquake fortification and non-earthquake fortification masonry buildings in highly and lowly seismic regions are discussed and analyzed.
Awareness of higher level of life safety and damage reduction was improved after the catastrophic 1976 Tangshan earthquake and some codes were promulgated successively.
The typical seismic damage of earthquake fortification and non-earthquake fortification masonry buildings are analyzed and the causes are illustrated, which are based on a large number of earthquake disaster survey data of Ms8.0 Wenchuan earthquake, Ms6.4 Baotou earthquake and Ms7.8 Tangshan earthquake and so on.
Table 1 was statistical data of earthquake damage in the Baotou Ms6.4 earthquake.
4.3 26.1 17.4 0.0 Non-earthquake fortification 27.6 10.3 31.0 27.6 3.5 Table 2 and table 3 were statistical data of earthquake damage of masonry buildings in Tangshan and Tianjin Cities in the Tangshan earthquake.

A set of data can make this clear.
The process does not need to re-traverse data. 2.
Data processing The paper uses data set which has 13 fields, and there are 1000 records.
Data preprocessing model is shown in Fig 1.
Fig.1 Data Pre-processing Model 2.

Then a life cycle inventory was worked out and the data was characterized and normalized by CML analysis method.
The reliability, objectivity, rationality and timeliness of the data quality are very important.
Data Sources and Cut-off.
Data types include company fills, tripartite testing, post-measurement [14-15], sampling simulations, adjusted data, time averaging, and spatial averaging.
With a Fuzhou enterprise 2019 data research and later data integration, the main raw materials procurement and transportation data for the production of 1kg automobile laminated glass was obtained Table 1 is the input and output list of 1 m2 automobile laminated glass products.

Analytic results are shown as follows：Firstly, the soil consolidation settlement model is built by the estimated soil parameters using the data of soil exploration.
We adopted the embankment data because of the integrated recorders.
The monitoring data from PR6-10 bridge pier subsidence was shown in Figure 2.
In order to facilitate data analysis, the settlement amount before June 5, 2003 (48.1cm) returns to zero. 98.4.23 Figure 3 Settlement curve in PR6-10 Figure 4 Settlement in phase 10 Analysis settlement.
We got conclusions are as follows basing on various soil parameters, construction conditions and monitoring data, and application of the Plaxis program: 1.

This allows to obtain the Preisach distribution function, without any special conditioning of the measured data, owing to the filtering capabilities of the neural network interpolators.
The model is validated through comparison and prediction of data collected from a typical Terfenol-D transducer.
This allows to obtain both Everett integrals and the Preisach distribution function, without any special conditioning of the measured data, owing to the filtering capabilities of the neural network interpolators.[4] The model is able to reconstruct both the magnetization relation and the Field-strain relation.
The model is validated through comparison and prediction of data collected from a typical Terfenol-D transducer.
The importance of reliable climatic data in the energy evaluation.