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The model was derived by implementing the second law of thermodynamics that quantifies sentimental relationships within a dynamic gene identification framework, called systems mapping.
The model is derived by implementing the linearized free-surface boundary condition and bipolar coordinate transformation, resulting in a truncated system of linear ordinary differential equations, which is numerically solved to determine the fluid velocity potentials followed by the hydrodynamic forces and moment.
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The governing differential equations and related boundary conditions are derived by implementing Hamilton's principle on the basis of hyperbolic shear deformation beam and modified couple stress theories and they are analytically solved.
The formulation is derived by implementing an analytical solution of one-dimensional steady flow into a limit equilibrium-based effective stress analysis.
The governing equations and related boundary conditions are derived by implementing Hamilton's principle.
The equations of equilibrium and corresponding boundary conditions are derived by implementing minimum total potential energy principle.
We assume that each user is transmitting only one type of traffic (i.e., the video chosen for the simulation) which arrives at the edge router and we derive our results by implementing the policing mechanisms for the whole duration of the trace.
Thanks to functional mapping, a general framework constructed to map QTL for quantitative traits that undergo developmental changes [19], [20], we are now able to derive an analytical model for mapping TPCs by implementing the biological principle of the thermal sensitivity.
Background of the image was subtracted by superimposing a "mask" derived by applying grayscale erosion and gaussian Blur filters, followed by implementing the Kittler and Illingworth Minimum Error thresholding [ 13], implemented in the Auto Threshold (v1.10) ImageJ plugin [ 14].
The reference VAD sequence was derived by running the implemented envelope-based VAD algorithm on the speech material used for target speech, mixed with a very low-level noise signal (speech-weighted noise at −35 dB SNR) to ensure correct speech/noise classification, as shown in Figure 2.
CHY derived and implemented the algorithms and drafted the manuscript.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com