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Among them, the car's steering stability is particularly important that we take a look at the car swerved caused by the traffic accident data.
ESP computer calculates the theoretical values ​​to maintain vehicle stability, and then compare the yaw angular acceleration sensor and the measured lateral acceleration sensor data, determine the vehicle unstable forms.
From the above analysis if the ABS reduces target slip rate, the braking force is reduced, the lateral force is increased, if you reduce the vehicle rear side two wheels ABS target slip rate, the lateral force Fy3, Fy4 increases, Fy3, Fy4 reduced, Fy3, Fy4 increasing lead to increasing MZr, but also makes the reduction of Fx4 and MZr, thus the method of increasing the lateral force Fy3, Fy4 is not obvious.
Analysis known, if we reduce upper and lower limits of ABS work area, Fx1, Fx3 reduced, Fy1, Fy3 increases, and Fy1, Fy3 has the role of offset the vehicle center of gravity torque, Fy1, Fy3 increasing has little effect on the reduction of MZf, reducing longitudinal braking force Fx1, Fx3 by reducing the target slip rate of ABS leads to the reduction of torque MZf, at the same time , Fy1, Fy3 increasing also improving the ability of vehicle lateral resistance interfere ensuring the vehicle's lateral stability; increased outside wheel slip ratio curve working range limits can ensure the braking performance.

Besides a further reduction of the on-resistance other characteristics like the temperature dependence of the on-resistance and the saturation behavior of the drain current are subject of redesign and technology refinements.
The reduction of the on-resistance was indirectly achieved by reducing the field crowding at the buried gate.
Potential for improving the device performance is mainly present in the control region since for a given breakdown voltage the data sets for the drift regions (epilayer thickness and doping) are restricted.
As already stated earlier we are able to design the controlling head region (see Fig. 1) nearly independent of the actual blocking voltage (for this parameter only the data of the drift region are of importance).
As already presented earlier there are additional possibilities for a further reduction of the field crowding at the edge of the buried p-implantation [3].

The two shells are replaced by finite element of fourth order reduction model.
The upper and lower shells are simplified to finite element of fourth order reduction model.
Upper and lower shells are simplified as finite element of fourth order reduction models.
Experiments are performed by the Labview-based data generation and collection system.
Data are collected by accelerometers in a 1s window that cover 10,000 sampling points in total.

Introduction As requirement of energy conservation, emissions reduction and sustainable development increases, China developed new energy actively.
Analytical hierarchy process is a multi-objective decision-making method combining qualitative and quantitative analysis and has the advantage of clear and distinct layer, low data accuracy and more accurate results.
Table 1 Evaluation index system of wind power industry comprehensive benefits Target Level Primary Index Secondary Index Third Level Index Comprehensive Benefits(A) Economic Benefit (A1) Profitability (B1) Cost Profit Margin(C1) Assets Profit Margins (C2) Solvency (B2) Liquidity Ratios (C3) Asset-liability Ratio (C4) Interest Coverage Ratio (C5) Development ability (B3) Sales Growth (C6) Profit Growth(C7) Social Benefit (A2) Social Economy (B4) GDP Growth (C8) Living Standard Improvement( C9) Social Environment(B5) Employment Promotion(C10) Energy Structure Adjustment(C11) Environmental Benefit (A3) Natural Resources (B6) Natural Resource Saving(C12) Pollution Reduction (C13) Natural Environment(B7) Fan Noise Effect (C14) Electromagnetic Radiation(C15) Effect on Birds (C16) Vegetation Destruction (C17) Weight Determination Based on AHP.
Comprehensive benefits of wind power industry are ordinary and because of its energy conservation and emission reduction effect, wind power has certain feasibility.
All the evaluation data are presented by experts based on grading standard.

The impedance data were then fitted with ZView software.
Le Bail refinement on its XRD data found that SDC crystallized in cubic phase with space group of .
Le Bail refinement of XRD data of carbonate-SDC composite shows that the composite contains of two phases, i.e SDC and Na2O, with the molar percentage of SDC is 19.25(1) % and molar percentage of Na2O as phase 2 is 80.75(7) %.
Meanwhile the impedance data of SDC at 600 °C is fitted well with two R-CPE networks (Figure 3(b)) related to grain boundary conductivity and electronic conductivity.
It indicates that the reduction of Ce4+ into Ce3+ occured at 600 °C and produced electrons migration inside SDC structure.

Introduction In the last decades the need of improving both processes and components has matched with the need of weight reduction.
Above discussed plastic and anisotropic data were used for modelling the mechanical behaviour of the investigated Ti alloy: in particular, the Hill 1948 yield criterion was adopted using Lankford’s parameters evaluated at the same value of the longitudinal strain (2.5%).
According to user input data (punch’s diameter, D, initial location of the tool, Z0, sheet thickness, T) target surface was created using an offset of the desired surface.
Fig. 6 Contour plot for STMmin Fig. 7 Contour plot for dW As expected (according to the sine law) large values of the Draw Angle determined the reduction of the sheet thickness, thus producing dangerous thinning.
Fig. 8 Geometrical features of the car door shell Results in Fig. 9, presented in terms of deformed shape and thickness distribution map (STH), highlight that the adoption of large values of D/p could determine an effective reduction of the “step effect” on the part.

The decrease is more pronounced for x = 0.3 (67% reduction between 0 and 9x10⁻⁴ V/cm) compared to x = 0.6 (45% reduction between 0 and 9x10⁻⁴ V/cm).
As with the hole, the decline is more pronounced for x = 0.3, with a reduction of 20% compared to 17% for x = 0.6.
As with the hole, the decline is more pronounced for x = 0.3, with a reduction of 20% compared to 17% for x = 0.6.
Also, the negative nonlinear term decreases in amplitude with an increasing intensity of the electric fields leading to a reduction of the total optical constants.
Data availability All data generated or analysed during this study are included in this published article Author Contribution Statement Rihab Sellami: Investigation, Writing- Original draft preparation, Visualization, Adnen Melliti: Conceptualization, Methodology, Validation, Supervision, Afef Ben Mansour, Mohamed Souhail Kehili: Investigation, References [1] R.

MES system is researched in domestic[2], the intelligent real-time control management system is very rare, the intelligent real-time control system is a networked application management system with data collection, field control, wireless data transmission and data processing, the data analysis is obtained.
Overall design and key technology of system In the overall design of the system, the Internet of things technology is used for the network design, the manufacturing intelligent management system has the functions such as data collection, field control, wireless data transmission and data processing and analysis.
The real-time and reliability of data are ensured to achieve energy-saving emission reduction and improve the design efficiency of production management[3].
The technology has the advantages of low power consumption, data transmission to establish routing features automatically, solve the problem of traditional network of high cost, poor versatility, it can greatly reduces the system cost, and it can be very convenient to add the module reduction.
Conclusions Based on the Internet of things technology, the manufacturing intelligent management system is designed, and it is a real time processing and intelligent system with data collection, field control, wireless data transmission and data processing and analysis.

This paper using the way of Support Vector Data Description(SVDD) and considering the tightness between the Membrane Bio-Reactor(MBR) samples, applies the Fuzzy Weighted Twin Support Vector Regression(FTSVR) to the MBR simulation prediction research.
This method considers the different effects on the regression hyperplane of different MBR samples,and effectively eliminates the negative effects due to error even outliers in the process of MBR data measurement.
In order to improve the prediction accuracy,this paper adds fuzzy weights to the TSVR ,and then uses it to the prediction of MBR membrane fouling.The building process is as follows: (1)Make the fooling factorsdimension reduced by PCA as the input vector,as the response vector.Suppose that the training set is denoted by,letdenote input data set,denote output data set
Experimental Results of MBR Simulation Prediction Use TSVR and FTSVR to predict test data from MBR sewage treatment plant,and compare the prediction results.Experiment collected 80 groups of MBR membrane fouling data.Randomly selected 70 groups as training samples,the remained 10 groups as test samples.In the training process, all the quadratic programming problems are solved by the function of Quadprog in matlab function library.
So as to compare the prediction results exactly for MBR flux of the two algorithms,Table 1 gives the comparison of the relative error of the 10 groups of test data.

These vibration characteristics have been extracted, in most studies, using either model-based approaches or data-driven methods.
Data from both laboratory investigations and field measurements on cracked concrete structures have provided useful information.
This presence of non-linearity in RC structures has led researchers to consider extracting non-linear quantities from the vibration data and relating them to damage.
Vibration data were first collected before the application of loading and then at every 250 thousand cycles up to the first million cycles.
Another way of scrutinising changes in the vibration data is by performing direct comparisons between the FRFs at different damage levels.