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Data Collection We construct the conditions for the simulation model based on the company's current operating processes, orders, and resource allocation gathered during data collection: a) The sequence of the work process.
Production line model using FlexSim Model Validation We use system simulation to input the order data from the previous month (February 2020) into the model to verify if the output data aligns with actual results: a) The workflow is synchronized with the simulation system.
b) Independent sample T-test: measures significant differences between two data sets that are independent of each other.
Orders from February to November 2020 were used as the primary data set for the simulation.
Although we can observe the values, we cannot determine the statistically significant effects based on the raw data alone.

RSSI Data Processing Based on the Gauss Distribution Function On the Gauss Distribution Function.
The Data Processing Method of Gauss Model.
Record of the Test Data and Results.
Record of the test data is shown as in Table 1.
Record of the test data.

Fig. 4 shows experimental data on the distribution of aluminum along the radius of the sample in its median plane (along the x-axis) for different infiltration pressures.
The infiltration is accompanied by densification of porous SHS skeleton, reduction of pore volume and, consequently, decreasing the aluminum content.
The skeleton densification manifests itself as a reduction in size of the SHS compacted samples.
Experimental data for average concentration of aluminum and hardness of the composites as functions of the pressure of infiltration are presented in Fig. 5.
The actual reduction of the aluminum content is dictated by densification of the porous SHS skeleton and reduction of the pore volume.

These data processing methods dominate the accuracy of prediction models.
It has high requirement for the smoothness of the original data array.
The power function conversion is presented to improve the smoothness of the original data array by processing the original data array.
The data generated by AGO should be in the nature of index properties that can fit by the differential equations.However , accumulated data series generating by the negative time series may not have index rule.under this circumstances the power function conversion is presented to improve the smoothness of the original data array by processing the original data array.
Assuming the original data series is is not a smooth discrete data series,then using power function to transform the original data series ,a new more smooth data series is obtained as (T≥v), using the new obtained data series for the following prediction ,finally employed the formula to transform the data type from the prediction output to the original state.

Burk [7]) The ongoing quality improvement in SiC bulk crystal growth reaching wafer diameters up to 2 inch, enabled a higher degree of material utilization and further cost reduction.
No data have been published about inter-wafer or run-torun homogeneity as well as to reproducibility.
The key data are listed in Table 1, too.
Table 2 shows some key data of our 2" cold- and hot-wall multi-wafer CVD equipments.
Further improvements in uniformity and run-to-run reproducibility, particularly on 3" diameter substrates, continued the trend of productivity enhancement and cost reduction for SiC epitaxial materials.

Flood and drought, especially serious flood and drought will be bound to result in a significant reduction in grain-based agricultural products, with a large number of reduction in agricultural productions, and the reproduction of the agricultural disaster areas coming to a standstill[1] Xie Yonggang.
Here the national statistical series of data of food production was used to be analyzed.
Study on Cultivated Land Reduction in the Course of Nanjing's Urbanizations with Gray Theory.
Comparative sequence： m is the sequence number ，m=1，2，3……8 Reference sequence：；n is the years，n＝1，2 ……7 The second step: Normalize the raw data, namely divide each value of sequence by the initial value of sequence to generate initialization sequence.
Taking the actual rainstorm occurrence and the data acquisition into account, the largest rainstorm of 3 days added weight in typical stations were selected as the influence factor, were made correlation analysis.

However, due to the fact that the disaster situation data series in county unit are always relatively short, available data are often not sufficient for disaster risk analysis.
However, due to the fact that the disaster situation data series in county unit are always relatively short, available data are often not sufficient for disaster risk analysis.
To partly fill the gap caused by incomplete data, the simplest technique is to change observations into normal fuzzy sets.
Each has its advantages and disadvantages and is more suitable for certain types of data than others.
CURAM can manage the attribute data and spatial data uniformly, and establishes the contact between them.

The gear ratio of the reduction gear-box is 10.
Post-processing of experimental data was carried out as follows.
During the test, the tensile force and elongation of specimen’s gauge were recorded, followed by computer processing of the data.
Hodgson, A heuristic model selection scheme for representing hot flow data using the hot torsion test results.
Pavlov, Control and experimental data processing in torsion testing with variable acceleration.

Benefits of grain refinement of the billet on extrusion were found to be a slight increase in the size of the operating window, and a reduction of the grain size in the extrudate.
However, the effect of the reduction in extrudate grain size due to refinement of the billet was small compared with the amount of grain refinement obtained due to recrystallisation on extrusion.
This is because in Mg alloys the final grain size is critical to the mechanical properties because the Hall-Petch coefficient is very high [1], hence a substantial reduction in grain size leads to a large increase in strength.
Critical to the success of this trial was the determination of the level of Mn that can be tolerated when grain refining with zirconium, as there is little data available as to its tolerable level.

Material characterization indicates potential RDSon reductions of up to 15% or 30% for advanced 1200V SiC MOSFETs and JFETs.
A 24% RDSon improvement for 650V SiC MOSFETs has been demonstrated, with potential reductions of up to 30% for next-generations 1200V SiC MOSFETs.
Such a strong reduction of RDSon is close to what can be expected during the transition from a given device generation to the next one.
The lifetime data (see Fig.12) exhibit an exponential term as expected from the CIPS 2008 [17] as a major driving term.