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Fractals are patterns that feature geometric elements at ever smaller scales to produce both self-similar and irregular shapes and surfaces. Fractal shapes are often self-similar (segments look like each other and like the whole object) and independent of scale (they look similar, no matter how close you zoom in).
Fractals found in naturally occurring phenomena such as lightning and snowflakes, take fractal forms because they provide structural efficiency. Plants like ferns and capillary patterns in skin have evolved fractal forms because they effectively exploit all the available space to maximize their functions.
Fractal properties are defined by the underlying mathematics however, not by perceived shapes, and fractals can define much less formal geometries including shorelines and irregular shaped fractal antennas
Robust communications links are achieved with fractal-shaped antennas by not only using repeating and self-similar shapes, but also with irregular shapes that may not be immediately recognised as fractal.
Fractal antenna technology is geometry-based, not material based. Therefore, fractal antennas are manufactured from standard materials and substrates, using standard processes. OEMs, ODMs and CEMs are able to take advantage of maximum flexibility and cost-effectiveness, from design through to final assembly, with no need to change processes or deal with special materials to produce Fractus fractal antennas.
ScienceDaily (Jan. 31, 2002) — Predicting the size, location, and timing of natural hazards is virtually impossible, but now, earth scientists are able to forecast hurricanes, floods, earthquakes, volcanic eruptions, wildfires, and landslides using fractals. A fractal is a mathematical formula of a pattern that repeats over a wide range of size and time scales. These patterns are hidden within more complex systems. A good example of a fractal is the branching system of a river. Small tributaries join to form larger and larger "branches" in the system, but each small piece of the system closely resembles the branching pattern as a whole.
"By understanding the fractal order and scale imbedded in patterns of chaos, researchers found a deeper level of understanding that can be used to predict natural hazards," says Christopher Barton, a research geologist at the United States Geological Survey, "They can measure past events like a hurricane and then apply fractal mathematics to predict future hurricane events."
In the past, earth scientists have relied on statistical methods to forecast natural hazard events, but when Barton used fractals, he found that these patterns contain a level of information that has never been seen using statistical methods. Barton discovered that by comparing the fractal formulas of the size and frequency of a hurricane’s wind speed to the historic record of information about past hurricane landfall location and timing that he was able to predict the approximate wind speed of the hurricane when it made landfall at a given coastal location along the United States Atlantic and Gulf of Mexico coasts.
Forecasts of hazardous natural phenomena based on the application of fractals are now available to government agencies responsible for planning and responding to natural disasters such the Federal Emergency Management Association and other emergency personnel to be able to better forecast the size, location, and timing of future events. "Based on the fractal patterns seen over the past 100 years," says Barton, "We can better forecast the probability of a future event."
Thanks to Dr. Mandelbrot, earth scientists like Dr. Barton have a powerful, new tool to predict future chaotic events of nature
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