Fractal Approach of Structuring by Fragmentation

2000 ◽  
pp. 539-557
Author(s):  
Cristian Suteanu ◽  
Dorel Zugravescu ◽  
Florin Munteanu
Keyword(s):  
Fractal Approach

Heterogeneity of Cerebral Blood Flow: a Fractal Approach

2000 ◽  
Vol 39 (02) ◽  
pp. 37-42 ◽  
Author(s):  
P. Hartikainen ◽  
J. T. Kuikka
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Fractal Dimension ◽  
Frontal Lobe ◽  
Fractal Analysis ◽  
Relative Dispersion ◽  
Emission Computed Tomography ◽  
Brain Blood Flow ◽  
Healthy Controls ◽  
Fractal Approach

Summary Aim: We demonstrate the heterogeneity of regional cerebral blood flow using a fractal approach and singlephoton emission computed tomography (SPECT). Method: Tc-99m-labelled ethylcysteine dimer was injected intravenously in 10 healthy controls and in 10 patients with dementia of frontal lobe type. The head was imaged with a gamma camera and transaxial, sagittal and coronal slices were reconstructed. Two hundred fifty-six symmetrical regions of interest (ROIs) were drawn onto each hemisphere of functioning brain matter. Fractal analysis was used to examine the spatial heterogeneity of blood flow as a function of the number of ROIs. Results: Relative dispersion (= coefficient of variation of the regional flows) was fractal-like in healthy subjects and could be characterized by a fractal dimension of 1.17 ± 0.05 (mean ± SD) for the left hemisphere and 1.15 ± 0.04 for the right hemisphere, respectively. The fractal dimension of 1.0 reflects completely homogeneous blood flow and 1.5 indicates a random blood flow distribution. Patients with dementia of frontal lobe type had a significantly lower fractal dimension of 1.04 ± 0.03 than in healthy controls. Conclusion: Within the limits of spatial resolution of SPECT, the heterogeneity of brain blood flow is well characterized by a fractal dimension. Fractal analysis may help brain scientists to assess age-, sex- and laterality-related anatomic and physiological changes of brain blood flow and possibly to improve precision of diagnostic information available for patient care.

The Fractal Approach to Secondary Mechanisms in SEC

2007 ◽  
Vol 30 (9-10) ◽  
pp. 1227-1249
Author(s):  
R. García‐Lopera ◽  
Juan E. Figueruelo ◽  
Iolanda Porcar ◽  
Agustín Campos ◽  
Concepción Abad
Keyword(s):  
Fractal Approach

A Fractal Approach to the Modelling and Simulation of Heterogeneous and Anisotropic Reservoirs

2019 ◽  
Author(s):  
Paul W. J. Glover ◽  
Piroska Lorinczi ◽  
Saud Al-Zainaldin ◽  
Hassan Al-Ramadhan ◽  
Saddam Sinan ◽  
...  
Keyword(s):  
Modelling And Simulation ◽  
Fractal Approach ◽  
Anisotropic Reservoirs

A fractal approach to the relationship between ore grade and tonnage

1986 ◽  
Vol 81 (6) ◽  
pp. 1528-1532 ◽  
Author(s):  
Donald L. Turcotte
Keyword(s):  
Fractal Approach ◽  
The Relationship ◽  
Ore Grade

scholarly journals Spatial and Temporal Spread of the COVID-19 Pandemic Using Self Organizing Neural Networks and a Fuzzy Fractal Approach

2021 ◽  
Vol 13 (15) ◽  
pp. 8295
Author(s):  
Patricia Melin ◽  
Oscar Castillo
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Temporal Trends ◽  
Main Idea ◽  
Temporal Analysis ◽  
Virus Propagation ◽  
Self Organizing Maps ◽  
Fractal Approach ◽  
The Times ◽  
Self Organizing

In this article, the evolution in both space and time of the COVID-19 pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries considered in this study. Self-organizing neural networks possess the capability to cluster countries in the space domain based on their similar characteristics, with respect to their COVID-19 cases. This form enables the finding of countries that have a similar behavior, and thus can benefit from utilizing the same methods in fighting the virus propagation. In order to validate the approach, publicly available datasets of COVID-19 cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of the time series of the countries considered in this study. Then, a hybrid combination, using fuzzy rules, of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient coronavirus disease 2019 (COVID-19) forecasting of the countries. Relevant conclusions have emerged from this study that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. Many of the existing works concerned with COVID-19 look at the problem mostly from a temporal viewpoint, which is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant for improving the forecasting ability. The main idea of this article is combining neural networks with a self-organizing nature for clustering countries with a high similarity and the fuzzy fractal approach for being able to forecast the times series. Simulation results of COVID-19 data from countries around the world show the ability of the proposed approach to first spatially cluster the countries and then to accurately predict in time the COVID-19 data for different countries with a fuzzy fractal approach.

A fractal approach of the sound absorption behaviour of materials. Theoretical and experimental aspects

2018 ◽  
Vol 103 ◽  
pp. 128-137 ◽  
Author(s):  
Carmen Bujoreanu ◽  
Ştefan Irimiciuc ◽  
Marcelin Benchea ◽  
Florin Nedeff ◽  
Maricel Agop
Keyword(s):  
Sound Absorption ◽  
Fractal Approach

The fractal approach for the evaluation of microdefects in silicon

1995 ◽  
Vol 34 (2-3) ◽  
pp. 164-167 ◽  
Author(s):  
A.P. Fedtchouk ◽  
R.A. Rudenko ◽  
L.D. Shevchenko
Keyword(s):  
Fractal Approach
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