Other
CONTENTS OF THIS FILE
* Data Analysis
* Experimental Design
# Data Analysis
This folder consists of data obtained from the experiments and the materials we use for analysis. Here we provide the following documents:
01-The folder "Class diagrams"
This folder contains class diagrams realized by participants in three experiments.
02-Code.R
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Ground Penetrating Radar (GPR) has a wide range of applications such as detection of buried mines, pipes and wires. GPR has been used as a near-surface remote sensing technique, and its working principle is based on electromagnetic (EM) wave theory. Here proposed data set is meant for data driven surrogate modelling based Buried Object Characterization. The considered problem of estimating geophysical parameters of a buried object is 2D. The training and testing scenarios include B-scan images (2D data), which contain 16 pairs of A-scan (concatenated forms of A-scans).
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The supplementary material S2 includes experimental data of uniaxial tension tests of polylactic acid material (PLA) and thermoplastic polyurethane elastomer (TPU).
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Design files for proposed prototype
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Figures of Data
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Accurately obtaining the position of active transmitters within an indoor wireless network has promising applications in future wireless networks. However, due to the complex propagation phenomena experienced by signals indoors, classical model-based localization techniques present poor accuracy, and machine learning (ML) based positioning has a promising potential to deliver high accuracy localization services indoors.
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Astrictive-type grippers, which generate gripping forces from adhesive forces at the contact surface such as suction cup, are popular end-effectors as picking solutions because of their simplicity and small working space. However, the adhesive force of the astrictive gripper decreases with increasing complexity of the object surface; thus, its application has been restricted to simple picking of objects with a flat surface. Here, we present an all-round honeycomb astrictive gripper that has an orthotropic surface tension for grasping highly irregular shaped objects with an uneven surface.
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This appendix discribes how the elements of a Mason-circuit-based dynamic model is formed.
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the zip file ''matlabcodeforallfigures'' contains the Matlab code for all figures and one table.
Within which, the data for Figure 5, Figure 7 as well as Figure 9 are generated by the C ++ script in the zip file ''CsciptforFigure57and9'' and its correlated data collected in the zip file ''collecteddataforFigure57and9''.
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This is the result file of the simulation
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