A Multi-scale, Hierarchical Model to Map Riparian Zones

Abstract Bone has a complex hierarchical structure. We study trabecular bone as a multi-scale material. In particular, we distinguish the following scales: nanostructural (collagen fibrils and apatite crystals), microscale (single laminae and laminated structure), mesoscale (random network of struts), and macroscale. We first present experimental observations and an overview of existing theoretical models of bone. Then, we construct a hierarchical model to predict elastic properties of trabecular bone.

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A novel connectivity-based hierarchical model for multi-scale fracture system in carbonate reservoir simulation

Fuel ◽

10.1016/j.fuel.2019.03.048 ◽

2019 ◽

Vol 250 ◽

pp. 327-338

Author(s):

Ye Guo ◽

Yu Liang ◽

Junchao Li ◽

Bin Gong

Keyword(s):

Hierarchical Model ◽

Reservoir Simulation ◽

Carbonate Reservoir ◽

Fracture System ◽

Multi Scale

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Mechanical Principles of a Self-Similar Hierarchical Structure

MRS Proceedings ◽

10.1557/proc-1188-ll01-01 ◽

2009 ◽

Vol 1188 ◽

Cited By ~ 1

Author(s):

Huajian Gao

Keyword(s):

Aspect Ratio ◽

Hierarchical Structure ◽

Hierarchical Model ◽

Characteristic Length ◽

Hierarchical Structures ◽

Hierarchical Level ◽

Multi Scale ◽

Flaw Tolerance ◽

Email Address ◽

Self Similar

AbstractNatural materials such as bone, shell, tendon and the attachment system of gecko exhibit multi-scale hierarchical structures. Here we summarize some recent studies on an idealized self-similar hierarchical model of bone and bone-like materials, and discuss mechanical principles of self-similar hierarchy, in particular to show how the characteristic length, aspect ratio and density at each hierarchical level can be selected to achieve flaw tolerance and superior stiffness and toughness across scale. Tel.: (401) 863-2626; Email address:

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A Multi-Scale Cascaded Hierarchical Model for Image Labeling

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001416600053 ◽

2016 ◽

Vol 30 (09) ◽

pp. 1660005 ◽

Cited By ~ 2

Author(s):

Degui Xiao ◽

Qilei Chen ◽

Shanshan Li

Keyword(s):

Hierarchical Model ◽

Scale Space ◽

Image Pyramid ◽

Original Image ◽

Iterative Approximation ◽

Space Condition ◽

Image Labeling ◽

Optimization Constraints ◽

Multi Scale ◽

Visual Computing

Image labeling is an important and challenging task in the area of graphics and visual computing, where datasets with high quality labeling are critically needed. In this paper, based on the commonly accepted observation that the same semantic object in images with different resolutions may have different representations, we propose a novel multi-scale cascaded hierarchical model (MCHM) to enhance general image labeling methods. Our proposed approach first creates multi-resolution images from the original one to form an image pyramid and labels each image at different scale individually. Next, it constructs a cascaded hierarchical model and a feedback circle between image pyramid and labeling methods. The original image labeling result is used to adjust labeling parameters of those scaled images. Labeling results from the scaled images are then fed back to enhance the original image labeling results. These naturally form a global optimization problem under scale-space condition. We further propose a desirable iterative algorithm in order to run the model. The global convergence of the algorithm is proven through iterative approximation with latent optimization constraints. We have conducted extensive experiments with five widely used labeling methods on five popular image datasets. Experimental results indicate that MCHM improves labeling accuracy of the state-of-the-art image labeling approaches impressively.

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Multispectral target detection based on the space–spectrum structure constraint with the multi-scale hierarchical model

Signal Processing Image Communication ◽

10.1016/j.image.2018.06.014 ◽

2018 ◽

Vol 68 ◽

pp. 58-67 ◽

Cited By ~ 2

Author(s):

Zhuang Zhao ◽

Yuwei Zhang ◽

Lianfa Bai ◽

Yi Zhang ◽

Jing Han

Keyword(s):

Target Detection ◽

Hierarchical Model ◽

Multi Scale ◽

Structure Constraint ◽

Spectrum Structure ◽

Space Spectrum

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Influence of General and Crystallized Intelligence on Vocabulary Test Performance

European Journal of Psychological Assessment ◽

10.1027//1015-5759.18.1.78 ◽

2002 ◽

Vol 18 (1) ◽

pp. 78-84 ◽

Cited By ~ 10

Author(s):

Eva Ullstadius ◽

Jan-Eric Gustafsson ◽

Berit Carlstedt

Keyword(s):

Hierarchical Model ◽

Test Performance ◽

Verbal Ability ◽

Testing Procedure ◽

Intellectual Ability ◽

Analysis Of Covariance ◽

Categorical Variables ◽

Vocabulary Test ◽

Crystallized Intelligence ◽

General Ability

Summary: Vocabulary tests, part of most test batteries of general intellectual ability, measure both verbal and general ability. Newly developed techniques for confirmatory factor analysis of dichotomous variables make it possible to analyze the influence of different abilities on the performance on each item. In the testing procedure of the Computerized Swedish Enlistment test battery, eight different subtests of a new vocabulary test were given randomly to subsamples of a representative sample of 18-year-old male conscripts (N = 9001). Three central dimensions of a hierarchical model of intellectual abilities, general (G), verbal (Gc'), and spatial ability (Gv') were estimated under different assumptions of the nature of the data. In addition to an ordinary analysis of covariance matrices, assuming linearity of relations, the item variables were treated as categorical variables in the Mplus program. All eight subtests fit the hierarchical model, and the items were found to load about equally on G and Gc'. The results also indicate that if nonlinearity is not taken into account, the G loadings for the easy items are underestimated. These items, moreover, appear to be better measures of G than the difficult ones. The practical utility of the outcome for item selection and the theoretical implications for the question of the origin of verbal ability are discussed.

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Masked Translation Priming Effects With Highly Proficient Simultaneous Bilinguals

Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) ◽

10.1027/1618-3169/a000013 ◽

2010 ◽

Vol 57 (2) ◽

pp. 98-107 ◽

Cited By ~ 90

Author(s):

Jon Andoni Duñabeitia ◽

Manuel Perea ◽

Manuel Carreiras

Keyword(s):

Lexical Decision ◽

Hierarchical Model ◽

Priming Effect ◽

Masked Priming ◽

The Other ◽

Memory Organization ◽

Priming Effects ◽

Bilingual Memory ◽

Translation Priming ◽

Masked Translation Priming

One essential issue for models of bilingual memory organization is to what degree the representation from one of the languages is shared with the other language. In this study, we examine whether there is a symmetrical translation priming effect with highly proficient, simultaneous bilinguals. We conducted a masked priming lexical decision experiment with cognate and noncognate translation equivalents. Results showed a significant masked translation priming effect for both cognates and noncognates, with a greater priming effect for cognates. Furthermore, the magnitude of the translation priming was similar in the two directions. Thus, highly fluent bilinguals do develop symmetrical between-language links, as predicted by the Revised Hierarchical model and the BIA+ model. We examine the implications of these results for models of bilingual memory.

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