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Integrating renewable energy resources such as PV and WTG into traditional electricity grids enables the reduction of carbon emissions, diminishes reliance on fossil fuels, and enhances energy supply reliability [5].
The data obtained under real-world conditions is supplemented with assumed data from the article.
The data is illustrated in a single-line radial distribution diagram of PLN from the Meulaboh substation (refer to Figure 1).
A three-phase disturbance is applied to the Lamno Bus in the simulation, and the data collected from the simulation includes frequency and voltage profiles on the load bus side as well as the system bus side.
These transient conditions result in a reduction in system reliability.

The major advantages of LBW joints are reduction of weight, fuel sparing and a higher cargo load.
All data were read out by computer with a measurement frequency of 50 Hz.
In general, the strain has to be measured at least in six different directions for each data point to determine the six independent components of the stress tensor σ.
Along each scan line 19 data points were taken at the mid-thickness of the base sheet.
As it can be seen in Fig. 5, the largest distance of the data points to the clip surface was about 5 cm.

Von Mises equivalent stress-strain curves were obtained from the filtered torque-twist data using the classical Fields and Backofen equations [12].
Thus, optimal grain refinement (in terms of size reduction, homogeneity and grain shape) was achieved at relatively large strains (~5) carried out at an intermediate temperature within the cold-warm working range.
The EBSD maps and corresponding data of the as-deformed states are shown in Fig. 3.
The "best" refinement (in terms of grain size reduction, distribution and shape) was achieved at an intermediate temperature of 150 °C at relatively large strains (~5) in the Fe-60 alloy.
A390 (2005) 159 - 165 4 A correlated plot depicts the misorientation data between neighbouring points, whereas an uncorrelated plot displays misorientation data between randomly chosen points within the map. 5 A crystallite is defined here as being enclosed by a mixture of LAB and HAB.

However, osmotic dehydration adapts to all the different drying methods and production proportions, since besides being a technological alternative to the reduction of post harvest losses, it considerably reduces the energy consumption [4].
With the assumptions of mass transfer process controlled by internal diffusion and negligible external resistance, spherical geometry, shrinkage based on the average distance, a simplification of the second Fick's law solution, as shown in Eq. (2) [5,6] was applied to adjust the experimental data
The values of the effective diffusivity were calculated from the experimental data considering the average radius in the periods of intermittency.
At the fourth day it was not possible to adjust the model to experimental data due the lack of enough points.
Based on the data obtained, it was possible to observe that the Fickian diffusion model showed a good fit for the studied conditions.

The specimens were performed to a height reduction of 60% and immediately quenched to water to retrain the microstructure at elevated temperature.
The flow stress-strain curves were obtained from the load-displacement data automatically.
Analysis of Stress-Strain Data (b) (a) Fig.2.
At every fixed temperature and strain, the data is fitted to three degree polynomial using least square method.
The value of can be represented by the function of, the form is as follows[9]: (4) The strain rate sensitivity m is written as (5) The parameter is given in terms of the strain rates sensitivity as: (6) For the identification of metallurgical instability during plastic flow, the following condition is used ≤0 (7) ≤0 (8) The processing map obtained at strain of 0.1, 0.3, 0.5, and 0.7, which obtained on the basis of the flow data at different temperatures and strain rates, are shown in Fig(5) The contour numbers indicate the efficiency of power dissipation in percent and the variation tendency of efficiency on the temperature-strain rate field is marked by the triangle as shown in Fig(5).

This ultimately allows for faster speeds, higher reduction ratios, and lower billet temperatures, (b) Usually the ductility of the material increases when high pressures are applied, (c) An even flow of material, (d) Large billets and large cross-sections can be extruded, (e) No billet residue is left on the container walls.
Data for hot extrusion with actual values of quality parameters at each stage Hot finished pipe size to be manufactured in TP321 Stabilized austenitic stainless steel Ø 42.16 mm x thickness 4.50 mm x length 10,000 mm Billet size 136mm {peeled, burnished, 100 % ultrasonic tested bar} Drilled hole diameter 39 mm Outside diameter and inside diameter surface roughness of billet < 3.2 Ra Billet length – 460 mm Hot extrusion or forging ratio – {area of billet / area of extruded pipe} Area of billet – 13337 mm2 Area of extruded pipe – 533 mm2 Hot extrusion or forging ratio – 25 Hot extrusion time ~ 4 seconds Hot Extrusion temperature – 1180°C to 1220°C Hot extrusion yield ~ @ 82% Figure 2 Schematic diagram of a hot extrusion layout showing the different tooling along with the billet and hot extruded pipe Hot extrusion process for seamless pipe.
Data for hot piercing with actual values of quality parameters at each stage.
Above table has been prepared based on the actual production data which is available for hot extrusion and hot rotary piercing for stainless steel pipes.
Above table has been prepared based on the actual production data which is available for hot extrusion and hot rotary piercing for stainless steel pipes.

As reliable experimental data for intrinsic point defects in germanium are still lacking to a large extent, molecular dynamics calculations and comparison with results obtained for silicon can yield useful information.
The observed pit density reduction was accompanied by an increase of size of the remaining pits.
The vacancy solubility and diffusivity data of Mayburg [5] and of Giese et al [4] are used, respectively.
Despite the lack of reliable data on intrinsic parameter properties, the predictions of the simulation are in good agreement with the observed size distribution of COP's on germanium wafers [29].
Despite the vast amount of data and analyses available a number of open questions still remain.

XRD data collection was performed by a Bruker D8 advance diffractometer with Cu Kα X-ray source.
The data collections were performed at 1 eV/s energy step.
The fluorescence data were collected by 13-element Ge array semiconductor detectors.
XAFS data analysis was performed using IFEFFIT[8].
The passive reduction factors () of these standards were used for fitting the coordination numbers of the samples.

The nodes of ZigBee include full functional device (FFD) and reduction functional device (RFD).
Here, the local experiment is done with the data obtained from the two sensors located at mine working face.
By ZigBee communication network two sets of data were acquired from PC.
Weight training samples were acquired through the pro-processing of the two sets data, i.e., we should first make the data standardized by the formula, in whichstands for the average value of in each part and is the standard deviation of.
Here, the Support Vector Machines (SVM) method aims to the data set （） This data set can be nicely separated by a hyperplane , in whichstands for weight vector and is the offset of optimal surface The hyperplane should be normalized as follows： .

Results indicate that reductions in hydraulic conductivity values ranged from 1 x 10-9 to 6.79 x 10-11 m/s (i.e. two orders of magnitude) as the percentage of bentonite increased from 0 to 10%.
In this study, data on the influence of bentonite addition on the hydraulic conductivity of compacted lateritic soil was developed.
Influence of compaction water content on hydraulic conductivity of soil – bentonite mixtures Relationships between dry unit weight, hydraulic conductivity and compaction water content for the various soil mixtures are demonstrated by data shown in Figures 4 – 8.
In a manner similar to clay soils, increase in compaction water content led to reduction in hydraulic conductivity values [18-20].