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Product development process involves conceptual design selection, which is an activity engaging with numerous types of data including technical-customer specifications and current design developments.
The utilisation of this strategy in some projects can reduce cost and some applications which implemented CE were reported to achieve a 30–60% reduction in time-to-market, 15–50% reduction in life cycle costs and a 55–95% reduction in engineering change requests [4].

This study focuses on the analyses of surface mapping data of rock outcrops and subsurface data of rock cores from four boreholes.
The analysis focuses on drilling data, while surface data is needed as a guide in forming subsurface geological models.
Red rectangle indicates data at the tunnel elevation.
Red rectangle indicates data at the tunnel elevation.
Red rectangle indicates data at the tunnel elevation.

This result is also comparable to other data obtained in previously studied work which employed the same conventional treatment parameters.
Despite the benefits of the automotive oil listed above, these viscous liquids de-grade when exposed to severe build-up of temperature, thus leading to reduction in properties such as: viscosity, specific gravity, etc.
With increased time of usage, the lubricating oil loses its lubricating properties as a result of over-reduction of desired properties, and thus must be evacuated and a fresh one replaced [1].
This finding is however, contrary to that of Koh [2] where he traced reduction in treatment efficiency at low temperatures such as 15oC to either poor agitation at high viscosity or failure to attain equilibrium at that temperature.

A sample analysis result for the data of Fig. 3 is shown in Fig. 5a.
Possible ways to improve data quality Since the analysis of available data shows that the position and the vehicle speed (both related to each other) have the strongest effect on the selected measures, we propose to apply some procedures for data selection in order to eliminate data from outside of a specified range.
Rejection of the 25% of the initial and final track section and the reduction of data to the speed range 10 ¸ 40 km/h can be achieved acceptable results for more than the original number of symptoms (Fig. 9).
PCA used as a transformation of the original data varies a large amount of input data into a set of statistically independent components, with respect to their importance.
As before, this procedure reduces the variance of the data.

Data and Method Research Location.
Population data for the years 2013, 2018, and 2022 from BPS (Statistics Indonesia).
Data Processing.
The main components of the research can be divided into three sections: the image data extraction process, population data calculation, and the correlational modelling of the observed phenomena.
In the first section, image data extraction involves processing satellite imagery to derive land surface temperature (LST) data.

The analytical results of ultimate shear loads with different shear-span ratios show good agreement with experimental data.
(16) In Eq.15 and Eq.16, is the tangent modulus of stirrups and is the reduction matrix of which can be expressed as: . (17) In Eq.17, is the concrete stiffness matrix in the principal-stress coordinate system which can be deserved from the constitutive model, is the coordinate-transformation matrix of concrete with following expression:
Fig. 3 Subdivision of cross-section Fig. 4 Section Details of specimens Table 1 Comparison between Model Predictions and Experimental Results Specimen Testing data Results of proposed model [MPa] Vt [MN] Vu [MN] Vt/Vu G1M1 2.02 47.5 0.210 1.12 0.259773 0.808397 G1M2 1.51 47.5 0.322 0.61 0.34989 0.92029 G1M3 1.01 47.5 0.477 0.5 0.489756 0.973955 G2M1 2.47 47.4 0.190 1.57 0.2097 0.906056 G3M1 2.74 49.6 0.150 1.6 0.184853 0.811455 H1M1 2.75 55.0 0.218 1.6 0.234652 0.929037 H2M1 2.49 54.0 0.220 1.59 0.209649 1.049375 H3M1 2.00 55.0 0.230 1.1 0.269696 0.852812 H3M2 1.52 55.0 0.347 0.62 0.359596 0.964972 H3M3 1.00 55.0 0.526 0.5 0.509698 1.031983 H4M1 2.50 50.7 0.230 1.6 0.211752 1.086174 H4M2 1.00 50.7 0.479 0.5 0.469006 1.021309 I1M1 1.99 52.3 0.370 1.09 0.271565 1.362474 I1M2 1.49 52.3 0.375 0.59 0.369852 1.013919 I1M3 1.00 52.3 0.490 0.5 0.524821 0.933652 I2 2.26 43.8 0.270 1.36 0.224789 1.201127 I3M1 2.73 52.3 0.240 1.6 0.194874 1.231566 Average 1.005797 Coefficient
of variation 0.148486 Though the testing data of specimens under similar conditions has significant variation, the average ratio in column Vt/Vu shows good agreement between the testing shear loads and the predictions.

Data from experimental results indicated that oxygen concentrations went up along with the height above the bottom of landfill after deducting the oxygen transported by leachate collection pipes.
Take the 17th, 18th, 19th, 20th, 21st week’s data into consideration, oxygen concentration on X>0 m of Z1 (2.0%) was lower than X<0 m of Z1 (4.5%) because that there was no leachate collection pipe on X>0 m in S-A with cowl.
To evaluate the influence of cowl on oxygen concentration under different wind speeds, data from initial, 21st, 26th, 31st, 37th weeks were brought out to be analyzed.
Different microorganisms had different requirements for oxidation-reduction potential (OPR).
According to NERNST we can get equation as follow: E=0.0591• [pE0+1/n•lg (Ox/Red)] (1) n: gain or loss electronic numbers; Ox: oxidation state materials; Red: reduction state material Oxygen in the space of waste in semi-aerobic landfill is the main decisive substance on ORP value.

Therefore a special care must be given to the evaluation and a model of two Cu components (larger and smaller crystallites) was fitted to the data if an indication of some crystallite growth appears either in the XRD line profile shape or in two-dimensional diffraction patterns.
Filtered Cu Kα radiation, variable divergence and antiscatter slits enhancing the high-angle peaks important for the line profile analysis were used together with the PIXCel position-sensitive detector that allowed collection of high-quality low-noise data in reasonable time.
For further reduction of the broadening an increase of temperature is necessary.
Then with reduction of the fraction of broad-peak component (either due to strains or small crystallites), the ratio goes back to Lorentz function corresponding more or less to the instrumental function for this diffraction peak.
However, the model seems to describe the observed data well, the refinement was quite stable and the results looked very realistic.

It is hard to detect small cracks in beams using the direct data of mode shape change.
Reduction in stiffness is associated with decreases in the natural frequencies and modification of the mode shape of the structure.
Narkis [2] indicated that the data on the variation of the first two natural frequencies is sufficient for identification of the crack location of a cracked simply supported uniform beam.
Conclusion In the present work, it has been shown that it is hard to detect small cracks in beams by using the direct data of mode shape change.
Damage detection using a modified Laplacian operator on mode shape data.

The corrosion data and model outputs have been compared with data available from power plants operating on coal, straw or wood fuels.
As well as mass change data, dimensional metrology of the materials before and after exposure yield statistical data on metal loss from the materials.
Once cool, mass change data was recorded and the samples were recoated with synthetic deposit.
These data have been ordered and plotted as a function of the probability of that damage level being exceeded.
In addition to conventional mass change and micrographical data, quantitative data have been obtained on the performance of the materials using dimensional analysis.