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The most typical application for non-volatile memories has traditionally been program codes for microcontrollers, parameters for DSP's, boot for systems with other type of mass storage media, data and parameters for security codes, trimming of analog functions, end-user programmable data, system self-diagnostic, etc [7].
As a consequence of their different cost/performance trade-offs, EPROM have been mostly used for code storage while EEPROM have been used to store parameters and user's data.
In this approach, the process simplicity is balanced with a heavily stressed CMOS and the data-storage long endurance concern translated into MOSFET reliability.
The integration of the data-storage occurs between the front-end and the back-end of the CMOS process.
Hence the development efforts are mainly focus on the optimization of the data-storage structure with respect to the reset current.

As can be seen from the data in this table, in both samples, approximately half of the specific surface area corresponds to micropores and half to mesopores.
It is evident that these are reduction processes which result in the formation of particles with sufficiently high magnetisation values.
According to the X-ray phase analysis, during the synthesis, the FeO, Fe3O4, and Fe phases were formed as a consequence of the reduction of iron oxides by carbon monoxide.
The reduction of iron oxides follows the scheme [24, 25]: Fe2O3 → Fe3O4 → FeO → Fe (1) by the following reactions: 3Fe2O3 + CO = 2Fe3O4 + CO2, Fe3O4 + CO = 3FeO + CO2, (2) FeO + CO = Fe + CO2.
The increase in magnetisation compared to the FeO precursor is due to reduction processes occurring during synthesis, as described by reactions (1) and (2), which lead to the formation of Fe-based particles with higher magnetisation values.

To achieve carbon concentration reduction, it is necessary to reduce carbon monoxide (CO) contamination from the CZ furnace graphite components and to remove the carbon impurities originating from the starting material.
Therefore, carbon contamination reduction during the CZ growth process is important in order to grow CZ silicon with a carbon concentration lower than that of FZ silicon.
Summary of results from data fit to measured carbon concentrations using Eq. 9.
From the carbon concentration reduction rate measured after the increase in the Ar flow rate, the CO evaporation rate from the silicon melt was calculated to be 2.9 × 10-5 μg/cm2∙s (8.2 × 10-3 μg/s).

These factors can contribute to a reduction in product strength.
This reduction in hardness in the welded samples is attributed to variations in the temperature of the heat treatment solution.
During the solution heat treatment process, large particle deposits form and spread over rare distances, facilitating dislocation movement and leading to a notable reduction in material strength.
The test data indicate that the highest hardness index is observed in the ST 475 °C sample, specifically measuring 80 HRE in the weld metal area.

Solute Mn atom of Cu-Mn with high atomic size misfit and may suppress the dynamic recovery which transforms cell walls to grain boundaries, and allow accumulation of higher dislocations and reduction of cell size to smaller scales.
Dislocation density was calculated from data acquired from X-ray diffraction (XRD, Smart Lab).
High atomic size misfit by Mn solute atoms may suppress the dynamic recovery that transforms cell walls to grain boundaries, and allow accumulation of dislocations to higher density and reduction cell size. 3.
The effect of increasing SFE and low atomic size misfit by Ni solute atoms may offset grain size reduction.

Employing the designed parameters, the slabs were hot rolled to 5 mm x 1135 mm x 4600 mm plates, which were subsequently hardened and tempered to obtain hardness levels >460 BHN, YS >1300 MPa, UTS >1500 MPa, elongation >8% and reduction in area >25% in the material.
With the help of the aquired data, critical transformation temperatures such as AC3, AC1, transformation start (Ms) and transformation finish (Mf) were determined in each case for further use in deciding process parameters to be employed during rolling as well in the heat treatment processes. 2.4 Calculated Critical Transformation Temperatures.
Hardening Tempering Temp (°C) Time (mins) Hardness (BHN) Temp (°C) Time (mins) Hardness (BHN) YS (MPa) UTS (MPa) El (%) RA (%) A 930 25 441-468 240 90 469-488 1500 1671 8.5 30 B 910 25 452-478 240 90 472-483 1338 1507 8.3 25 C 880 25 438-474 240 90 467-482 1310 1479 8.3 22 D 895 25 441-468 240 90 472-476 1366 1521 9.4 27 E 910 25 - 240 60 462-480 1297 1459 7.1 28 F 910 25 - 230 90 466-480 1449 1609 8.5 25 It is observed from Table-5 that after tempering, hardness varied in the range of 462-488 BHN, YS 1297-1500 MPa, UTS 1479-1671 MPa, elongation 7.1- 9.4% and reduction in area 22-30%.
Oil quenching from a temperature range of 910-930°C and tempering within 230-240°C for 90 minutes helped in achieving an average hardness of 470 BHN, yield strength >1300 MPa, tensile strength >1500 MPa, elongation >8.0% and reduction in area >25% in the steel. 5.

The experimental data have been very well approximated by this model and thus it is proposed for the use in the following study.
The experimental data are rather limited because the testing of failure in compression requires extremely stiff machines which are not available at many laboratories.
The lack of experimental data leads to use of simple models of the descending branch of the stress-strain diagram.
This reduction is linearly proportional to the strain normal to the crack.
Data delocalization and verification.

Section 2 briefly describes the previous CAD system, data used and experimental setup in this paper.
Data used To test the approach we used a real-world problem.
(5) Use bootstrap method to sample from the data set and build base classifiers with NN, then choose base classifiers which meet the accuracy requirement to vote for the final decision.
In addition, in forward stepwise feature selection procedure, we may also use a validation set for evaluating the performance of each combination of features for computation time reduction and reduction of overfitting.
Motoda, Feature Selection for Knowledge Discovery and Data Mining, Kluwer Academic Publishers, 1998, p.62-68.

The equilibrium sorption data are well demonstrated by Langmuir model.
Various methods for the removal of heavy metal ions from wastewater were developed, including chemical precipitation, membrane technology, electrolytic reduction, ion exchange and adsorption [2].
The equilibrium adsorption isotherm is one of the most useful data to understand the mechanism of the adsorption.
The Langmuir isotherm model proved an excellent fit to the isotherm data, giving R2 values of 0.9990 , which indicates that a monolayer adsorption process plays an important role in the whole process.
The Langmuir model gives an excellent fit of adsorption isotherm equilibrium data, which suggests that the most Cu2+ and Pb2+ adsorbed are monolayer arranged on the surface of distillers' grains.

Such data belong to mechanical properties essential for an assessment of residual life of components and structures containing cracks of length more than several millimetres.
Such data are important for an assessment of residual life of components and structures containing cracks of length more than several millimetres.
The measurement sensitivity in the region of short cracks up to 1 mm is not unfortunately increased by the reduction of specimen width.
Data of cut depth (i.e. crack length) and corresponding potentials were gradually recorded – Fig. 2.
The measurement provides an important knowledge and data for assessment of crack arrest conditions or fatigue life extension with existing short crack.