A direct divider method for self-affine fractal profiles and surfaces

1997 ◽  
Vol 24 (16) ◽  
pp. 2099-2102 ◽  
Author(s):  
Angelo De Santis
Keyword(s):  
Divider Method

Fractal geometry of ammonoid sutures

Paleobiology ◽  
1995 ◽  
Vol 21 (3) ◽  
pp. 329-342 ◽  
Author(s):  
Timothy M. Lutz ◽  
George E. Boyajian
Keyword(s):  
Fractal Dimension ◽  
Fractal Geometry ◽  
Two Dimensional ◽  
Evolutionary Time ◽  
Linear Features ◽  
Divider Method ◽  
Richardson Method ◽  
Components Analysis ◽  
Box Method ◽  
Range Of Variation

Interior chamber walls of ammonites range from smoothly undulating surfaces in some taxa to complex surfaces, corrugated on many scales, in others. The ammonite suture, which is the expression of the intersection of these walls on the exterior of the shell, has been used to assess anatomical complexity. We used the fractal dimension to measure sutural complexity and to investigate complexity over evolutionary time and showed that the range of variation in sutural complexity increased through time. In this paper we extend our analyses and consider two new parameters that measure the range of scales over which fractal geometry is a satisfactory metric of a suture. We use a principal components analysis of these parameters and the fractal dimension to establish a two-dimensional morphospace in which the shapes of sutures can be plotted and in which variations and evolution of suture morphology can be investigated. Our results show that morphospace coordinates of ammonitic sutures correspond to visually perceptible differences in suture shape. However, three main classes of sutures (goniatitic, ceratitic, and ammonitic) are not unambiguously discriminated in this morphospace. Interestingly, ammonitic sutures occupy a smaller morphospace than other suture types (roughly one-half of the morphospace of goniatitic and ceratitic sutures combined), and the space they occupied did not change dimensions from the Jurassic to the late Cretaceous.We also compare two methods commonly used to measure the fractal dimension of linear features: the Box method and the Richardson (or divider) method. Both methods yield comparable results for ammonitic sutures but the Richardson method yields more precise results for less complex sutures.

scholarly journals Updates on the Mobile Divider and Its Use in Calabria Region to Monitor and Control Aethina tumida Infestation

2021 ◽  
Vol 11 (22) ◽  
pp. 10637
Author(s):  
Camilla Di Ruggiero ◽  
Ziad Mezher ◽  
Franco Mutinelli ◽  
Alessandra De Carolis ◽  
Naomi Pocci ◽  
...  
Keyword(s):  
Preliminary Data ◽  
Short Communication ◽  
Southern Italy ◽  
Aethina Tumida ◽  
Official Method ◽  
Small Hive Beetle ◽  
Inspection Method ◽  
Calabria Region ◽  
Divider Method ◽  
And Control

The small hive beetle (SHB), Aethina tumida was first detected in the Calabria and Sicily region (Southern Italy) in 2014. In this regard, a more effective and faster inspection method than the Official one (Ministry of Health) was tested to detect the beetle in the hive. In collaboration with Calabria beekeepers’ association, a “mobile divider”-based method was tested, in order to facilitate the detection of A. tumida and save time during hive inspection. In this short communication, we provide an update on the mobile divider technique and its related inspection procedure, which was first proposed and used in Calabria (Southern Italy) from 2014 to 2016. We report preliminary data concerning the number of detected SHBs and the time spent for their detection, based on the inspection of two apiaries in Calabria region, using both methods (official method and mobile divider method). The preliminary data presented here show that, on average, the mobile divider method seems to be able to recover a slightly higher number of beetles (0.9 adults) per inspected hive, in a shorter time (25 s).

Fractal dimension of irregular digitalized curves by divider method

2007 ◽  
Vol 189 (1) ◽  
pp. 68-71 ◽  
Author(s):  
R. Uthayakumar ◽  
P. Paramanathan
Keyword(s):  
Fractal Dimension ◽  
Divider Method

Estimating fractal dimension with the divider method in geomorphology

Geomorphology ◽  
1992 ◽  
Vol 5 (1-2) ◽  
pp. 131-141 ◽  
Author(s):  
Robert Andrle
Keyword(s):  
Fractal Dimension ◽  
Divider Method

Precision Capacitor Divider Method for Measuring High Voltages

1959 ◽  
Vol 30 (11) ◽  
pp. 1022-1024 ◽  
Author(s):  
H. V. Larson ◽  
I. T. Myers
Keyword(s):  
Divider Method ◽  
Capacitor Divider

Application End of Line Resistor (EOLR) and Voltage Divider for Passive Infrared Motion Sensor

2019 ◽  
Vol 5 (1) ◽  
pp. 50-56
Author(s):  
Bibit Hartono
Keyword(s):  
Voltage Divider ◽  
Control Panel ◽  
Motion Sensor ◽  
Security Systems ◽  
Analog Input ◽  
Monitor Function ◽  
Divider Method ◽  
In Series ◽  
Arduino Microcontroller ◽  
Passive Infrared

End of Line Resistor (EOLR) is a resistor that has a certain value to protect the circuit at the end of a loop or zone. The End of Line Resistors is used in security systems to enable the control panel to monitor wiring of open and closed. In this research using an Arduino microcontroller and Passive Infrared (PIR) Motion Sensor that connected with the systematic circuit to supervisory a loop or zone. Systematic circuit use combination of the resistor as the end of line resistor and voltage divider method. Analog input on Arduino uses to detect different states of sensors. The 1K resistor in series with the sensor line provides some protection for the input pin against the unexpected current flow. The 4K7 pull-up resistor, when combined with the resistance provided by the sensor, acts as a voltage divider, exposing the analog input to a different voltage depending on the state of the sensor. The result of measurement viewed by serial monitor function on the personal computer. PIR Sensor connected with an analog pin on microcontroller running well and there is no significant voltage value changing.

THE CORRELATION BETWEEN THE FRACTAL DIMENSION OF FRACTURED SURFACES AND MECHANICAL PROPERTIES OF 6061/Al2O3/10-20%p

Fractals ◽  
1994 ◽  
Vol 02 (02) ◽  
pp. 249-252 ◽  
Author(s):  
FAUSTIN DOSSOU ◽  
RAYNALD GAUVIN
Keyword(s):  
Mechanical Properties ◽  
Composite Material ◽  
Fractal Dimension ◽  
Tensile Test ◽  
Volume Fraction ◽  
Particle Volume Fraction ◽  
Unreinforced Alloy ◽  
Particle Volume ◽  
Divider Method ◽  
6061 Aluminium Alloy

The mechanical properties of a 6061 aluminium alloy and of a composite material 6061/ Al 2 O 3/10-20% p have been mesured after heat treatments using a tensile test. Fracture surfaces profiles were used to mesure fractal dimension using the step divider method. The fractal dimension of the fractured surfaces of the composite material 6061/ Al 2 O 3/10-20% p depend on the aging and on the particle volume fraction but is independent of aging time for the unreinforced alloy.

A fractal‐based algorithm for detecting first arrivals on seismic traces

Geophysics ◽  
1996 ◽  
Vol 61 (4) ◽  
pp. 1095-1102 ◽  
Author(s):  
Fabio Boschetti ◽  
Mike D. Dentith ◽  
Ron D. List
Keyword(s):  
Fractal Dimension ◽  
Real Data ◽  
Signal Amplitude ◽  
The Other ◽  
Data Sets ◽  
Detectable Change ◽  
Fractal Method ◽  
Divider Method ◽  
Automatic Picking ◽  
First Arrival

A new algorithm is proposed for the automatic picking of seismic first arrivals that detects the presence of a signal by analyzing the variation in fractal dimension along the trace. The “divider‐method” is found to be the most suitable method for calculating the fractal dimension. A change in dimension is found to occur close to the transition from noise to signal plus noise, that is the first arrival. The nature of this change varies from trace to trace, but a detectable change is always found to occur. The algorithm has been tested on real data sets with varying S/N ratios and the results compared to those obtained using previously published algorithms. With an appropriate tuning of its parameters, the fractal‐based algorithm proved more accurate than all these other algorithms, especially in the presence of significant noise. The fractal method proved able to tolerate noise up to 80% of the average signal amplitude. However, the fractal‐based algorithm is considerably slower than the other methods and hence is intended for use only on data sets with low S/N ratios.

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