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The method has a number of advantages: It makes use of well-known techniques, is straightforward to implement, does not require species absence data, produces georeferenced digital maps for visual analysis and geographical identification, and can be adapted to any scale of analysis or data resolution.
MaxSim is straightforward to implement, does not require any parameter tuning, has been well studied [34, 35], and is intuitively simple.
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Importantly, the proposed coordination mechanism is straightforward to implement and does not require any additional infrastructure.
This technique is simple to implement and does not require any special column connections.
This controller is simple to implement and does not require any special hardware.
This method is efficient and easy to implement, and does not require a structured mesh around the crack front.
Both algorithms are based on a new evaluation function that is easy to implement and does not require user-tuned parameters.
It should be noted that our proposed scheme is easy to implement and does not require exact knowledge of the node positions.
It permits some camera motion, is simple to implement, fast, does not require statistical models of background nor foreground, works well in the presence of rich and cluttered backgrounds, and the results show that there is no visible blurring or motion artifacts.
However our method has two main advantages over the use of SVMs or other complex machine learning algorithms: first, it is simple to implement and does not require much computational power; and second, the RCGs, and in particular the functionally characterized ones, can be further mined to obtain insight on other biological problems.
LTTA is fairly straightforward to implement as it does not require global synchronization or blocking communication.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com