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The presented study aims at such reduction of costs involved in geotechnical testing.
This process has significantly improved with the advent of GIS, which provides new applications in presenting data.
The BIM and GIS data has been mapped using IFC and CityGML.
Moreover, the proposed geological data model uses a boundary and voxel geometric representation for the geological data.
A boundary and voxel-based 3D geological data management system leveraging BIM and GIS.

However, Gao et al. [7] pointed out that only a limited number of reports present data on the wear behavior of SPD-processed materials and that many of these results appear to be conflicting [8].
Table 1 summarizes the Vickers hardness data of HPT-processed disks at r = 2.5 mm with different numbers of turns.
Thus, the reduction in wear is considered to be due to hardening by the HPT process.
Fig. 7 shows the calculated K data plotted against the reciprocal of Vickers disk hardness at r = 2.5 mm.
A linear correlation can be observed between K and the inverse of disk hardness, which agrees with the Archard wear equation, and the data are plotted on the same line for both Fe and S45C.

Based on Arduino data acquisition results, thinner IPMC (t1) has more than 5 times respond speed than thicker IPMC (t2).
Simultaneous data logging analysis and real time control experiment can be done without great hassle with Arduino microcontroller.
Real time control data logging can be provided by MATLAB/Simulink through ArduinoIO programming which already uploaded previously into Arduino memory.
Besides, instead of MATLAB/Simulink, open source and light softwares such as Processing and PLX-DAQ can be used for data logging which ultimately allow Arduino to achieve near to its maximum 10 KHz sampling rate.
Based on Arduino data acquisition, thinner IPMC (t1) have more than 5 times respond speed than thicker IPMC (t2).

However, until recently, there has been no data reported in literature on the temperature dependence of dark specific electrical conductivity sd(T), on the carrier activation energy and the conductivity nature for the LN crystals annealed under hydrogen [8].
This figure also illustrates a similar dependence for a LN sample which has not undergone reduction treatment.
With the temperature being increased, a minor linear increase in and has been observed, which fully agrees with the known data reported in the literature [10].
Thus, based on the impedance investigation using optimum approximation of experimental data by the crystal equivalent circuit, it is possible to determine the temperature dependence Rs and Rb.
Circles are data for simulating specific conductivity of the surface layers ss (K=3); squares are data for simulating specific conductivity of the crystal volume (K = 7500).

Data were shown in Table 1.
After the de-emulsifier addition, all pH data of the 6 parallel experiments showed the tendency of increase.
Through the data of median size in the wastewater, the FeS colloid particle concentration was figured indirectly.
Table 2 Dissociated water phase phenomenon and turbidity data under different de-emulsifier Separated water layer Phenomenon Turbidity（NTU） FeS colloid particle conc.
And the zeta potential data (as shown in Table 5) was monitored at different FeS concentration.

Experimental I-V data from Schottky Barrier Diodes (SBDs), combined with TCAD simulation, demonstrated that approximately 40 % of boron atoms were activated in the SiC lattice (at a depth of 30-40 nm) without the need for high temperature ion implant activation.
TCAD simulation of Schottky barrier diodes (SBDs) with different percentage of boron activation with correlation to experimentally obtained I-V data.
The SCR of treated samples extracted, exhibited a one order of magnitude reduction from 10-4 Ω∙cm2 (untreated) to 5.6×10-5 Ω∙cm2 (treated) as shown in Fig. 6 (a-b).
This novel single step plasma treatment allows for the reduction of SCR at the source region in p-SiC.
Hannan et al., “The Effect of Nitrogen Plasma Treatment Process on Ohmic Contact Formation to N-Type 4H-SiC,” Diffusion and defect data, solid state data.

In this way, the motional data structure can be displayed clearly.
So the data projected into the subspace will change accordingly.
Nonlinear Manifold Learning for Data Stream.
Proceedings of SIAM Data Mining, p.33-44
A Robust Generalization of ISOMAP for New Data.

The methodology employed was qualitative, with data obtained through systematic, documentary, and field research.
Methodology General data and definitions.
These data are provided in Table 1.
The model validation was performed based on the experimental data available in [18].
Rocha, E.D. dos Santos, Thermal performance simulations of Earth-Air Heat Exchangers for different soils of a coastal city using in-situ data, Sustain.

The Ni-Mn-Ga alloys extruded at high temperature with a relatively large reduction rate were the subject of the studies.
The round ingots of 20 mm diameter were homogenized at 1100oC for 2 hours and extruded into rods of 10 mm diameter with the reduction rate of 75 %.
Fig. 4: Morphology of martensite (a) and diffraction pattern of five-layered structure in alloy 3 (b) Fig. 2: Elongated grains in the extruded rod Fig. 3: Microstructure of the martensitic elongated grains in the rod Fig. 5: EBSD pole figures of the columnar grains of the alloy 3 specimen The pole figures of the extruded rod from the alloy 3 taken from the longitudinal cross section (Fig. 6) contain the scattered data of the grains oriented about the <001> direction.
Computer processing of the scattered data allows to contour the pole figures and thus reveals the preferred orientation.
Fig. 6: EBSD pole figures with scattered data of the axial texture in the extruded rod of alloy 3 specimen The used relation is as follows: )/1/(])/(1[ 2 0 acac   (3) for the five-layered martensite 0=0.12.

Results indicate that the presence of δ leads to a slight increase in peak stress and a proportionately greater post-peak reduction in flow stress, as compared to solutiontreated material.
Fig. 3 shows optimised global fits of Eq. 1 to the experimental data using both peak stress, σp (Fig. 3a) and nominal steady-state stress, σss (Fig 3b).
The data is somewhat scattered, but the analysis confirms a lower steady-state stress, and a slightly higher peak stress, for the material containing δ phase.
Solid lines represent optimised fits of Eq. 1 to the flow data for solution-treated material (circles).
Dashed lines represent similar fits to the data for the as-received material containing δ precipitates (crosses).