On the Pair Uninorm-Implication in the Morphological Gradient

2015 ◽  
pp. 183-197 ◽  
Author(s):  
Manuel González-Hidalgo ◽  
Sebastià Massanet ◽  
Arnau Mir ◽  
Daniel Ruiz-Aguilera
Keyword(s):  
Morphological Gradient

Chemical and morphological gradient scaffolds to mimic hierarchically complex tissues: From theoretical modeling to their fabrication

2016 ◽  
Vol 113 (10) ◽  
pp. 2286-2297 ◽  
Author(s):  
Alessandra Marrella ◽  
Maurizio Aiello ◽  
Rodolfo Quarto ◽  
Silvia Scaglione
Keyword(s):  
Theoretical Modeling ◽  
Morphological Gradient ◽  
Gradient Scaffolds

An abundance- and morphology-based similarity index

Paleobiology ◽  
2021 ◽  
pp. 1-18
Author(s):  
Daniel G. Dick ◽  
Marc Laflamme
Keyword(s):  
River Flow ◽  
Similarity Index ◽  
Ecological Gradients ◽  
Jaccard Similarity ◽  
Real World Data ◽  
Large Component ◽  
Morphological Gradient ◽  
Random Samples ◽  
Similarity Indices ◽  
General Method

Abstract Classic similarity indices measure community resemblance in terms of incidence (the number of shared species) and abundance (the extent to which the shared species are an equivalently large component of the ecosystem). Here we describe a general method for increasing the amount of information contained in the output of these indices and describe a new “soft” ecological similarity measure (here called “soft Chao-Jaccard similarity”). The new measure quantifies community resemblance in terms of shared species, while accounting for intraspecific variation in abundance and morphology between samples. We demonstrate how our proposed measure can reconstruct short ecological gradients using random samples of taxa, recognizing patterns that are completely missed by classic measures of similarity. To demonstrate the utility of our new index, we reconstruct a morphological gradient driven by river flow velocity using random samples drawn from simulated and real-world data. Results suggest that the new index can be used to recognize complex short ecological gradients in settings where only information about specimens is available. We include open-source R code for calculating the proposed index.

scholarly journals Remote Sensing Image Fusion via Boundary Measured Dual-Channel PCNN in Multi-Scale Morphological Gradient Domain

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 42540-42549 ◽  
Author(s):  
Wei Tan ◽  
Pei Xiang ◽  
Jiajia Zhang ◽  
Huixin Zhou ◽  
Hanlin Qin
Keyword(s):  
Remote Sensing ◽  
Image Fusion ◽  
Remote Sensing Image ◽  
Multi Scale ◽  
Dual Channel ◽  
Morphological Gradient ◽  
Remote Sensing Image Fusion ◽  
Gradient Domain
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