The pressure- and temperature-sensitive paint (PSP/TSP) technique, for steady-state and unsteady-state measurements, is becoming widespread. However, unsteady quantitative measurement is still difficult because non-uniform distribution of the probes over a test model may cause errors in the results. We focus on the dipping method that applies two luminophores into a binding material to improve ...

Abstract—New physical insights into the nonlinear Lorenz equations related to flow resistance is discussed in this work. The chaotic dynamics related to Lorenz equations has been studied in many papers, which is due to the sensitivity of Lorenz equations to initial conditions and parameter uncertainties. However, the physical implication arising from Lorenz equations about convectional motion a...

copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies. This article integrates fuzzy set theory in Data Envelopment Analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in convectional DEA is that inputs and outputs data are measured with prec...

Convectional Omni directional sensors that always have an omni angle of sensing range, directional sensors may have a limited angle of sensing range due to the technical constraints or cost considerations. A directional sensor network consists of a number of directional sensors, which can switch to several directions to extend their sensing ability to cover all the targets in a given area. Impr...

A gravitationally stable boundary between two polymer solutions in a ternary system can develop into an interphase of structured convectional flow. The transport over this interphase is by counter-current distribution and as a result high-molecular weight material moves by bulk-flow and much more rapidly than low-molecular weight material, which is transported essentially by ordinary diffusion.

Proteins are linear chain biomolecules composed of 20 different amino acids which form secondary structures such as helixes and loops [8]. Here, we use deep recurrent memory networks and deep convectional networks for predicting secondary structure annotations on sequences from the Uniprot database. We compare different network architectures and memory models, and discuss possible improvements....