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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.

(3) Data analysis Sleep EEG data used in this paper were from the PhysioBank the MIT-BIH Polysomnographic Database.
Records in the Database is a multi-parameter sleep data, including EEG, ECG, EOG, EMG etc.
The data sampling frequency is of 250Hz.
It was randomly extracted 5 wake stage signals and 5 NREM I stage signals from subjects slp41 with data length 2000.
The analyzed data were 500 sampling points.

Automotive operation data sharing has become a feature of the automotive network.
Data is sent in one direction of the ring.
All the data between the nodes in the network is transmitted through the central node
Any node can send data to other nodes at any time.
Gateway is used to accomplish the data exchange between them.

The output of CAM module – CL data – is imported into new software application as the basis of NC program.
Many CNC machines can be programmed on the shop floor, with the operator entering data at the control panel.
The data verification was realized on the part displayed in the Fig.5b.
The background where were data loaded and processed is displayed in the Fig.6.
The ground tasks for near future in focus of authors are: · Research for general format of process plan data

The multi-layer perceptron (MLP) of the neural network structure was trained to reveal the underlying pattern within the data sample.
The sample data was obtained from a sensitivity analysis drive from FEA.
A sensitivity analysis has been conducted to generate the sample data.
Sample data available was split in half for training and validation.
(Left) Meta-model ANN of the torque ripple output response ( black dots are the sampling data calculated during sensitivity analysis).

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.

Shapiro-Wilk Test was used to check the distribution of data.
At T3, T7, T14, all ligatures as well as the supernatant showed significant reduction of bacterial growth except NL-w at T3, as shown in Fig. 4B, C, and D, respectively.
At T28 [Fig. 4E], NL, 5ZL, 10 ZL and its supernatant showed significant growth reduction, whereas the supernatant water, NL-w, 5ZL-w did not show significant reduction.
These results indicated the reduction of bacterial growth of supernatant groups might be due to the bacterial toxicity of PU material.
In addition, the small release of Zn2+ in water could be the reasons for insignificant difference of bacterial reduction among supernatant groups.

Data generated were analyzed using SPSS software, version 22 for Windows. 3.
It is well known that reduction in fiber diameter tends to enhance the mechanical strength of the fibers [25].
There is a wide spectrum of bacterial strains that lactoferrin show an important inhibition which bacterial reduction depends on generally concentration.
In this study, it was very clear that increasing concentrations of lactoferrin showed a better reduction in bacterial growth in all strains (Fig.3).
Low reduction in growth of Flavobacterium psychrophilum by L including FG nanofibers can be explained by the antimicrobial/antibiotic resistant structure of the organism.

While the loss of the original variable are minimized in river analysis variables, which contains information on the collected data to do a comprehensive analysis [10].First with spss20.0 pairs each index data for factor analysis, variables are classified to reduce the dimensionality of the data space to get a comprehensive evaluation.
Now data are measured on 21 samples of Tang River in 17-dimensional index and analyzed for two times.
(Original variables are essentially independent of dimensionality reduction may fail, it is difficult to use too many independent variables, few relevant comprehensive summary data after dimensionality reduction is better.) [15] Factor extraction and naming firstly.
Take data on typical sites to do factor analysis at the second time.
Data in Figure 2, Figure 3 about various factors impacting on Tang River study reach are organized in percentage, which are showed in Table 4.

Sensor data were wireless transmitted from the sensor board (I-SkyEx Chemical Detector) to a signal receiver installed in a desktop PC, running the data analysis software for the chemical detection.
Operational Open Protocol The sensor must provide an open protocol data format.
Operational Open Protocol The sensor must provide its data in an open data format.
In reality, a safety perimeter could be drawn from the acquired radiation data.
However, the main goal was to set this perimeter-based on radiation data collected in flight mode.