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Product-ion Measurement method of fuel saving technology for automobiles GB/T14951-2007 Evaluation, test method, experimental data processing and evaluation project.
The survey data were obtained from a number of large and medium-sized road transport enterprises.
Through the calculation of the average, the statistic data was shown in table2.
The R2(R square) was used to describe the degree of data fitting the model.
It has important meaning for energy conservation and emission reduction about transportation industry.

We replaced them by 14-bit data acquisition card (DAQ).
Using external trigger chain allows to use digitizers with lower data throughput (USB, LAN) and relieve data processing part from work on rapid signal parts.
First, a simple command line utility to set up the ADC card and acquire data into a file was developed.
Data were evaluated using MePASto software [9].
Rosinger: Computerized Data Reduction and Analysis in Positron Annihilation Coincidence Doppler Broadening Spectroscopy, American Journal of Undergraduate Research, Vol. 2 (2003), p. 13 [10] Informational website of SourceForge Group, [online] SourceForge.

Finally, Gleeble specimens were subjected to hardness tests to compare FE prediction of hardness with experimental data.
The available data set has been divided into three parts: training, validation and testing data.
The ANN model has been trained using 80% of the total data randomly selected, while the remaining data 10% has been used for validation and the other 10% for testing.
A measurement of how well neural network has fit the data is the regression analysis and the error histogram.
The blue bars represent training data, the green bars represent validation data, and the red bars represent testing data.

Network data sending flow chart as shown in figure.3.
Send data to all the node.
Data check is conducted After final package is sent out.
Capture data display Through many times test data packet capture, packet loss rate is very low, the network transmission is efficiency and stable.
Motioncompensated temporal prefiltering for noise reduction in a video encoder .

According to the preceding surveys on relative algorithms, one of the key features of pattern generation technology is the ability to obtain a holistic view of a system function as well as to isolate and focus on component-specific reliability issues, incorporating statistical and probability theory in addition to data processing, dimensionality reduction by compression and transformations, and feature extraction.The signals of the transducer element are analyzed and recorded as shown in Fig. 3 and Fig. 4.
With the available and historical information stored in host processor, feature extractions of data from the structure like Fig. 5 can be conducted.
And as the computing rate, data volume and the information complexity required by each algorithm are different, the choosing of the mode can be flexible to meet the needs of cost avoidance and the efficiency [5].
And as the computing rate, data volume and the information complexity required by each algorithm are different, the choosing of the hardware and the embedded algorithms can be flexible to meet the needs of cost avoidance.
With the available and historical information stored in host processor, critical extractions of data are conducted.

One is reduction of the reflection of incident light with an anti-reflection coating, and the other is optical confinement of incident light with textured surface.
The system consists of sensors for measuring the electrical parameters and the atmospheric parameters, a data logger for data acquisition and a display unit to display the measured values instantly.
Data from the PV modules and the atmospheric data are collected through various sensors and electronics circuit.
All these data are in analog form and converted into digital format and displayed.
A reduction in magnitude of relative humidity implies low water vapour in the atmosphere resulting to high solar radiation intensity reaching the earth surface thereby increases the ambient temperature.

Hence, extracting the most useful features from the real world data not only helps to probe into the essential structure of the data, but also contributes to accomplish the task of fault diagnosis or performance assessment.
Wavelet packet transform (WPT) is an important process in feature extraction [1], where the goal is to project the input data onto a feature space which can reflect the important inherent structure of the original data.
Therefore, Feature extraction of signals is crucial to finding useful information from large volume of raw data, eventually achieving dimension reduction and making decision further.
Twenty groups of data sets are obtained from the experimental system.
Dey: Data & Knowledge Engineering, Vol. 63 (2007) No. 2, pp. 503-527

The results can be written as: (1) (2) Where is the AR model parameters at time interval; is the difference between the observed flow data and computed flow data predited by AR model at time interval.
All measured data will be divided into three ranges: confidence range, suspect range, rejected range respectively.
If rejected range is too large, the probability that the good observed data is falsely declared as outliers increases.
When the error is the same extreme, outliers occurred a long time interval, the adjusted risk reduction.
The robustness performance that resists the outliers in flow data sets is good.

Field data obtained at fire-damaged sites reflect the extent of material degradation and enable the identification of critical heat-affected zones and potential fire origin points.
A machine learning model trained on virtual laser scanning data enables high-accuracy classification of damage levels (severe, extreme, destruction) with an accuracy of 92.0 %–95.1 %.
The obtained material strength data reflect the extent of changes in the physical properties of concrete.
These data are collected at the fire site and allow for the identification of fire temperature zones or dominant directions of heat flow.
[18] Zahs, V., Anders, K., Kohns, J., Stark, A., Höfle, B., Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data.

With the interface users can edit, download recipe data, display critical process parameters, historical data and real-time data curves, etc., the human-machine interface can be communicate with upper host by serial communication [2].
Thus, energy saving, cost consuming and noise reduction can be easily reached by this device.
Through the man-machine interface the running state and alarm of dry mortar production line can be displayed, and a real-time data curve and data report for display and printing can be formed also [3, 4].
Conclusions Via PROFUBUS-DP network all electrical devices can be bidirectional interconnected as a whole and thus high speed data communication can be realized also.
Advanced friendly Human-Machine Interface, like IPC (Industrial Personal Computer) or touch screen, were selected as host computer interface, which can perfectly realize the important data and recipe editing, download, the key data in the PLC upload, important process parameters displaying, key parameter setting, process monitoring and so on.