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This is evidenced by the data on X-ray diffractometry of sintered and cooled ferrites (Fig. 3).
From these data, the effective magnetic anisotropy constant, Keff, were calculated in the temperature range 125-450 K.
The content of ferrous iron ions in the samples was estimated using the XRD analysis data and the crystal lattice parameter for the samples cooled at different rates.
Taking into account the large approximations in the calculations (the lattice parameter of pure magnetite is taken, possible lattice distortions are not taken into account, etc.), the agreement of the calculation with the data on the oxygen nonstoichiometry of quenched samples can be considered satisfactory.
This is evidenced by the data in Fig. 5, which shows the distributions of the activation energy of electrical conductivity over the depth of the sintered samples.

In addition, the lagging quality of operating personnel and management are led to a lack of historical data.
Consider of randomicity and continuity of hydro-meteorological sequence, it takes the moving average for original data to weaken the influence of outliers[4,5].
(23) After an accumulative generation again, formatting the sequence: (24) Also, estimated parameters,: (25) Obtained estimates of,represented ,: (26) The original data sequence model sets up[8]: (27) Instance analysis Selecting monthly output of a small hydropower station from 2009 to 2011 as historical data predicts monthly data of 2012.
The original data is shown in Tab.1.
In addition, it is easy to collect data about hydrology and meteorological.

By using of which along with the theory of rough set in rule reduction of expert system, the development of CAPP system framework is basis of .net platform, utilizing Visual Studio 2003 to design the system interface and associated structured query language (SQL) allow distributed data processing and data access, which is supported by SQL Server 2000.

Introduction In pursuit of remarkable structural weight reduction in aircraft industries, the primary structural materials of aircrafts are inclined to nonmetallic materials such as composite materials, honeycomb and PMMA, etc [1-3].
(a) (b) Fig 2 Fatigue testing machine Instron-8803 and clamping state of specimens According to ASTM D3479-2002 [7], by using staircase fatigue tests, the conditioned fatigue limit was obtained with five pairs of effective test data.
Experimental results Fig.3 shows the staircase diagrams of all specimens with four stress levels, follow from which five pairs of test data are available.
For specimens without scratches, the S-N curve obtained by the contained fatigue limit and logarithm fatigue median life at each stress level, among which the latter is calculated from the five experimental data of the fatigue life, is illustrated in Fig.4.
In addition, with the increase of the scratch depth from 0.0mm to 0.4mm, an initial gentle decrease turns into a rapid reduction of the fatigue life, in which the turning point is about 0.2mm.

(6) Using the DTA curve data, according to equation (6) the reaction progression n can be obtained.
The mensuration condition that rise temperature velocity was 10℃·min-1 and reduction reaction gas is N2 gas.
Fig.2TG-DTA-DTG curvers of nano-Ni(OH)2 power The DTA-TG-DTG curves data and equation (2) allow the calculation for apparent activation energy E and pre-exponential factor A of nano-Ni(OH)2 power.
Fig.3 Plot of LnK~1/T of nano-Ni(OH)2 power The Figure 3 shown that relation of lnK and 1/T was linear and indicated that the reduction reaction was Arrhenius type.
-E/R E(J·mol-1) LnA A n Ni(OH)2 -8805.724 73.210 28.485 2.349×1012 1.2767 Based on all above data, the kinetics equation of nano-Ni(OH)2 power was: Conclusions The conclusions were as followed: (1) In process of nano-Ni(OH)2 powders decomposition, the apparent activation energy of nano-Ni(OH)2 is 73.210kJ·mol-1, the frequency gene is 2.349×1012

Milling is carried out until no further particle size reduction is observed.
The nanocomposites are cured according to the technical data sheet for 75 min at 160 °C and for 120 min at 180°C.
In fact, the additional shrinkage reduction can be explained by the formation of an interphase between filler and epoxy resin [6].
The comparison of the experimental results with the theoretical calculations reveals a higher reduction of the CTE than expected.
The presented results show the reduction of chemical and thermal shrinkage due to the integration of nanoparticles.

These nanosalt fluids performed an excellent trend of surface tension and IFT reduction in comparison with distilled water too.
Results and Discussion SEM and XRD data of ZnO nanoparticles Fig. 1 shows typical SEM images of various ZnO nanostructure morphologies.
Table 2 shows the measured surface and interfacial tension data of the basic nanofluids.
Observed reduction of IFT is the result of the presence of nanoparticles at the interfacial layers.
The results of our experiments reveal that ZnO nanofluids have significant impact on reduction of surface tension and IFT.

The equilibrium data from adsorption studies fitted well the of Langmuir and Freundlich isotherm models.
As expected, there was reduction in weight due to the lost of volatile matters during rapid heating of carbonization process [6].
The equilibrium data obtained was analyzed using Langmuir and Freundlich isotherms.
From the values of correlation coefficient (R2) shown in Figure 4, both isotherm models gave good fit for the equilibrium data of Ni2+ adsorption on RHAC.
The equilibrium data fitted well with Langmuir and Freundlich isotherm models for the adsorption of Ni2+ on RHAC.

The workflow of the SHM system includes data acquisition from the sensors; data processing which involves the elimination of corrupted, redundant, and unreliable data followed by feature extraction from remaining useful data; data storage which requires the development of an appropriate algorithm for long-term, reliable and interpretable data; data diagnostic and statistical model development which comprises further interpretation of processed data and algorithm development to evaluate the structural condition [4].
This means we will have live data of the Bridge in the cloud.
Data storage in this framework will be done using cloud computing so the data can be remotely accessed and retrieved anytime.
The data will be logged on the cloud along with a timestamp so that later on we can perform data analytics with respect to time.
SHM Data Analytics and Decision-Making Using AI This layer involves noise reduction, feature extraction, development of statistical models to identify changes and trends in the response of the structure.

The paper presents the experimental data on the cement effect typeon the effects of heat generation during the 3D-printable cement materials’setting and hardening.
The combination of a highly active aluminosilicate modifier with high-strength cement causes a technologically unacceptable reduction in the setting time and open time of mixtures.
The use of a highly active aluminosilicate modifier (metakaolin) in combination with this type of cement causes a significant increase in the mixture temperature and a technologically unacceptable reduction in setting time due to the active interaction of related phasesС3A and metakaolin.
The combination of a highly active aluminosilicate modifier (metakaolin) with high-strength Portland cement CEM I 52.5 R causes a technologically unacceptable reduction in setting time and, as a consequence, in open-time mixtures.