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Data analysis.The use of Microsoft Excel to process and analyze the data of simple.
Analysis of data processing and result.Design according to the test method in this experiment, by dilute acid concentration, temperature, reaction time, particle size, solid to liquid ratio of these five factors on the corn straw was pretreated, and measured the OD value of saccharification liquid, into the glucose standard curve of reduced sugar quality, and calculate the content of reducing sugar in sugar solution.
Data processing.As the five graphs in Fig.2 shows, including (1) for dilute sulfuric acid concentration on the corn stalk sugar producing effect, (2) as the ratio of solid to liquid of corn stalk sugar producing effect, (3) as the time of corn stalk sugar producing effect, (4) particle fineness of corn stalk sugar producing effect, (5)as the temperature of corn straw to produce sugar effect
Conclusions In this paper, by dilute sulfuric acid pretreatment the conclusion of corn straw under different factors, taking into account the impact on energy consumption and other factors[6], differences and also on the basis of the data obtained in the experiment shows, given the highest sugar yield test conditions for dilute sulfuric acid concentration 5%, ratio of solid to liquid was 1:10, reaction time is 80min, particle fineness of 120 mesh in the lowest energy consumption, reaction temperature, 100 ℃, this group of conditions of pretreatment of corn stalks is more reasonable, conducive to further for further processing of corn straw.
References [1] Palmowski L，Muller J．Influence of the size reduction of organic waste on their anaerobic digestion．In：11 International．Symposium on anaerobic digestion of solid waste[J]．Barcelona．1999，6：137—144

Firstly, sonar data flow collected by multi-beam sonar is processed by median filter to reduce noise.
Firstly, the sonar image display and image filter pre-processing were completed using sonar data.
Sonar Data Collection The sonar we used for collecting the data throughout this paper is P450E imaging sonar from BlueView Technologies.
The distance and relative bearing of object Experiment and Result We have tested the underwater object detection and localization system on real sequences of sonar data.
The ability of the system has been demonstrated on real sonar data collected by P450E multi-beam sonar.

The results of the numerical analysis were calculated using data from the material library of AUTODYN.
More accurate and various data are needed to achieve a further detailed description.
The reference material data of the hydro tensile limit for glass were applied in the simulation.
The numerical analysis based on reference data did not display the dynamic damage accurately.
When experimental data were provided as feedback data for the simulation, a more detailed description was possible.

The experimental data on the elongation of Cu2O islands agree with the energetic calculations based on the balance between surface/interface energies and the elastic strain relief in the three dimensional islands.
There is a reduction of the width to its optimal width, α0.
A comparison of Tersoff and Tromp's model with our data shows good agreement for the size evolution of the island.
With its continued elongation, there is a reduction in the island width.
The kinetic data on the volume evolution of the islands agree well with the model of surface diffusion of oxygen.

Machining and cooling parameters Feed rate 0.05 mm/rev Cutting speed 15 m/min Drilling depth 15 mm Air pressure* 5.76 bar Air Flow* 32 l/min Drill air outlet temperature* 17.3 ºC *Only in refrigerated test Equipment for processing and data acquisition For data collection, the equipment shown in Table 3 has been used.
The considerable temperature reduction of almost 150 °C is noteworthy.
Diameter A whisker diagram Fig. 10 has been made with the results obtained from the three-pointer micrometer measurement, in addition to which the data obtained can be seen in Table 4.
Roughness The roughness data obtained are shown in Table 5.
As for the temperature data obtained at the tip of the cutting tool, we can see that in the cooled test the tool seems to reach a stationary temperature range of over 200 ºC.

The symptom causes a significant reduction of the hand-eye coordination and memory abilities.
Also, through the RFID and Internet facility, the training data can be fed into remote database servers for medial references and analyses. 2.
Data retrieved during the gaming will be stored in the SQL Server database, which later on can be used for training effectiveness analysis.
The stored data can be used later on for training effectiveness analysis. 3.
Moreover, the introduction of RFID technology allows online collection of rehabilitation data, such as training date and time of use, for later analyses.

While the test data nearby the threshold district can be appropriately characterized using a statistical distribution for the factor range data at a given FCGR level and the case is similarly for the test toughness data.
And then, delta K is evaluated by the following equation [12] (1) (2) FCGR (da/dN ) data can be yielded by taking a differentiation to the a-N data and then, da/dN-delta K data can be gotten by combining the da/dN data and the a-delta K data. da/dN-delta K data for GR specimens and TH specimens are shown in Fig. 6.
While the test data nearby the threshold district can be only characterized using a statistical distribution for delta K data at a given da/dN level and the case is similar for the test KIC data.
It reveals that test data in stage II can be reasonably described by employing a statistical distribution for the FCGR data at a given delta K level.
While the test data nearby the delta Kth district can be appropriately characterized using a statistical distribution for delta K data at a given FCGR level and the case is similarly for the test KIC data.

The fusion data on the one hand is further used with object’s complex status and safety logic that have been set in advance to propel the lights, on the other hand, it is projected to the plan of airfield which display the real-time traffic situation for air traffic controller.
The reduction of surveillance range increase the reliability, performance and expandability.
From the perspective of update rate of surveillance data, radar equipment such as ASDE needs 1 second to update[16].Currently, the development of the high performance of intelligent video hardware increase the accuracy and processing rate which now descend to millisecond.
Eventually, the data can be used as surveillance data to propel automatic RWSL or as a backup or complementary surveillance equipment.
The evaluation index of data source the video processing technology provide In 2000,a set of Runway Incursion Prevention System(RIPS) whose data source include ASDE,1090MHz multilateration system,ADS-B and SSR was installed in Dallas-Fort Worth international airport.

In this research, the historical data of defect rate from in-mould decoration gathered in October 2017-June 2018 shown as averaged baseline is 7.9%.
Improve Phase As a result of data analysis from ANOVA in Fig. 8, there are 4 factors that significantly influence to the adhesive strength of PET film including drying time, adhesive transparent layer, PET film thickness, and oven drying temperature.
In order to find the optimal setting for maximum adhesive strength [7], further data analysis is required to be done by same experimental design of 4 factors to increase adhesive strength and improve quality of in-mould decoration process.
Data monitoring for defect rate comparison of in-mould decoration.
Regarding result monitoring of new lots after implementing the new parameter setting and updated control plan, the result from data monitoring for defect rate comparison over a one-month period after improvement is shown in Fig. 11.

The travelling data of one certain demonstration running EVs are adopted as an example to test the calculation mode, and the rationality of the mode is verified.
A detailed description can be obtained from the data in one demonstration running EV company.
Fig. 1 Operation condition statistical data of Evs As can be seen from the frequency histogram, the EVs’ operation characteristics approximately obey normal distribution.
By analyzing the EV’s operation data of demonstration running company above, some coupling relationship can be found among the various factors of driving characteristics.
For the extracting of EVs’ operation data, the multivariate joint distribution function must be used in order to reflect the original characteristics of the users’ driving.