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Undoubtedly, addition of surfactant up to 20mL into 50 mL 0.5M HCl acid shows a reduction in copper degradation which might have caused steel corrosion reaction to endothermic.
As corrosion is induced, the metal (oxidation) releases electrons and they are produced by elements (reduction) in the corroding solutions.
Table 2: Electrochemical data of surfactant extracted from Zea mays on copper at various temperature Concentration of inhibitor (ml) Weight loss (g) JCORR (A/cm2) -ECORR (V) Inhibition efficiency (IE) (%) Corrosion rate (mm/year) Polarization resistance (Ω) Surface Coverage (ϴ) 298 Control 0.0032 0.00112 0.3984 0.000 13.054 11.399 0.0000 5 0.0020 0.00053 0.2527 52.82 6.1590 8.1229 0.5282 10 0.0052 0.00026 0.6802 76.76 3.0334 187.67 0.7676 15 0.0053 0.00018 0.6901 83.92 2.0986 217.51 0.8392 20 0.0009 0.00014 0.2463 86.99 1.6984 14.427 0.8699 313 Control 0.0019 0.00148 0.4925 0.000 17.232 44.738 0.0000 5 0.0018 0.00105 0.2668 28.93 12.246 3.4843 0.2893 10 0.0015 0.00060 0.3944 59.61 6.9593 69.532 0.5961 15 0.0019 0.00052 0.2300 64.43 6.1288 4.4810 0.6443 20 0.0014 0.00040 0.7483 72.70 4.7051 95.885 0.7270 323 Control 0.0011 0.00190 0.3069 0.000 22.142 3.6816 0.0000 5 0.0039 0.00170 0.7361 10.80 19.750 33.049 0.1080 10 0.0011 0.00104 0.6251 45.49 12.069 56.336 0.4549 15 0.0036 0.00084
The morphological studies also affirmed the reduction in pitting evolution trend from other active element.

When entering the tower, air conditions are recorded using a relative humidity sensor dht 11 (3); the recorded data is the dry bulb temperature and relative humidity taken as tower entry air data.
The recorded data is the dry bulb temperature and relative humidity taken as the air data exiting the tower and discharged into the neighborhood.
Water temperature drops at the fifth level as the cooling tower exits water temperature data.
Temperature, water flow rate, humidity, and air temperature at inlet and outlet conditions at all relevant locations were recorded using an Arduino Mega board (7) together with a data acquisition system, PLX-DAQ, and then the data were recorded using a personal computer (8) [33].
The data of wet bulb temperature, enthalpy, and absolute humidity of inlet and outlet air can be obtained from the table.

When performing recognition tasks it is important to identify temporal correlations within the input data.
However, CNNs have a limitation to capture dependencies within input data.
Deep learning methods can be used to extract discriminating features from data.
An LSTM layer learns long-term dependencies between time steps of sequence data.
The training data set is 3500 data points from 12 subjects and the test set is 700 data points from 12 subjects.

Statistics is a mathematical approach to interpreting calculation of data.
The statistical interrelation of data is calculated in the Minitab and Excel programs.
The statistical model is the most-used model for analysing tested data.
The null hypothesis for normality will be H0: the data are normally distributed.
It helps to detect the variations of input data from amount of observation.

The main benefits of usage of autopilot for control of ship can be elimination of a man from the dangers of the undersea environment and reduction in cost of exploration of deep seas.
He uses navigation data, sonar and video images and is supported by a navigation computer that integrates all available data.
The precise control autopilot adjustments are modified by a position and velocity data.
To make it less complicated, experimental data suggest that D can be viewed as a perturbation of the hull drag force dvr in surge.

In view of the inherent contradiction between mass data and real-time browsing in Highway 3D Visualization System, this paper proposes an edge folding algorithm for weighted average elevation base on vertex degrees, which will improve the model simplification effective.
Therefore, how to deal with the terrain data real-time 3d simulation system is the road to solve the problem and this directly determines the performance of the system, the feasibility and stability.
LOD method not only reduces the geometric distortion in graphics hardware, lighting calculation and rasterization of time, but also reduces the bandwidth bottlenecks when transmitting data from memory to graphics card.
The main aim of "Video-based Automatic Incident Detection of highway network monitoring system" is that using the existing highway surveillance cameras to provide video image and video data, and using image recognition technology to automatic identifying traffic abnormity, moving station detection, vehicle tracking, and automatic traffic incident detection.
Fig. 1. 3d visualization of TIN terrain (with 721,735 vertexes, 1,442,577 triangles) Continuous and reversible of LOD terrain model The magnitude of the terrain data scatterplot determines that the terrain model must contain abundant triangles.

Mainly local databases, historical or statistical data are referred to.
Strategical control may include investment planning, maintenance plan, outsourcing, and demonstration of sustainability and reduction of impact on the Environment, increase of capacity and functional output of equipment.
Punctuality of input data plays important role.
Among main barriers preventing wider or bigger LCC application belong: · Unavailability of reliable and adequate input data, either cost or time ones
· Bad data quality from suppliers and insufficient complex data on technical parameters in operation phase

All of them are aimed at working process optimization based on navigation data, regardless of the purpose of the system in general.
Thus, for transportation management systems navigation data are used to determine vehicle arrival time taking into account distances and road graph.
Navigation data about vehicle location not only serve as an additional selection factor but also as a supplement to other factors.
All criteria are accompanied by navigation data on vehicle locations.
The problem of optimization of the process of transmission of navigation data from moving objects to global network, Bulletin of the Tomsk Polytechnic University. 7, 2004.

From the slope of linear fitting in Fig. 3 (data for strains 2 and 4 are from [10]) for strain 5.5, the activation energy at the end of recovery (Q0) can be estimated as 131 kJ/mol, which is also very close to the activation energy found in [5] for strains 2 and 4.
These activation energies are slightly different from those published in [10] for the same aluminum as less data points for 140°C and 160°C and more data points for 220°C have been included in the present analysis.
Data points for annealing at 220°C for 408 hours and longer are not included in the current calculation.
Data for strains 2 and 4 are from [10].
Data points at 220°C are not included in the linear fitting.

The diffraction data were refined according to the Rietveld method using the Fullprof program.
Results (Pr0.55Ca0.45)MnO3 NPD data reveals that a structural transition takes place during cooling, between 200 K and 250 K.
Figure 1 shows a selected 2θ portion of three NPD data collected in this T range where some of the diffraction peaks split during cooling.
As a result three different atomic sites are available for the Mn ions and hence charge ordering can take place, as confirmed by the bond valence sum (BVS) calculations carried out with the refined structural data.
Figure 3: Rietveld refinement plot of the low angle NPD data collected at 5 K for the sample (Pr0.55Ca0.45)MnO3 that evidences the AFM lines.