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Some erroneous inputs were generated by contact forces that exceeded the input threshold during the experiment.
Fuzzing is a popular technique to find flaws in programs using invalid or erroneous inputs but not without its drawbacks.
To prevent erroneous inputs resulting from finger linkage, the force threshold needs to be set individually for each person, depending on how much finger-linkage movement they experience.
The IT2 fuzzy logic allows for an improved handling of uncertain assumptions about the distributions of noisy and erroneous inputs which are essential for correct design of the fuzzy voting scheme.
Although the perspective is quite different, in the end, the goal is to observe how the application deals with erroneous inputs, and this kind of concept also applies to other domains (e.g., fuzzing or even penetration testing).
The ability to gracefully handle erroneous inputs is a well-known problem in the robustness testing domain, where tests using invalid inputs applied on external interfaces of many different systems have been used with great success [10 12].
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In the future, we must devise a character-input algorithm that eliminates such erroneous input.
In the future, we will devise a better character input algorithm that eliminates erroneous input caused by finger linkage.
The goal of robustness testing is to characterize the behavior of a system in presence of erroneous input conditions.
Robustness testing consists in stimulating a system with erroneous input conditions with the goal of triggering internal errors.
Secondly, binding of erroneous input and desired output contributes to better convergence in terms of reduced prediction error when using the NN for unseen data.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com