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To mitigate such sophisticated attacks, Kitts et al. [11] discussed how to design a data mining system to detect large-scale click fraud attacks.
For this purpose, we design a data processing scheme to optimize the number of RBFs and their parameters simultaneously.
As such, it is imperative to design a data hiding scheme that is compatible with the compression algorithm and at the same time, introduces as little perceptual distortion as possible.
To overcome such disadvantages, we design a data structure called Reference Primary Key table (RPK-table) which stores the relationship of primary key and foreign key between tables.
We design a data structure of circular two-dimensional array for storing both conductance coefficients related with presynaptic neurons and correcting conductance related with postsynaptic neurons.
In solving these problems, we design a data structure T that maintains in O logn) time per operation, a function f :R→R under the following query and update operations where [a,b) is a continuous interval in R:.
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The method is used to design a data-driven controller for an atomic-force microscope.
Our main contribution is to design a data-driven hybrid model of human mobility, in which social media traces are combined with the classical gravity model under a machine learning approach, by training and cross-validating with real datasets.
The purpose of this work was to design a data-driven model to improve the spatial accuracy of fMRI maps in the rat olfactory bulb.
We design a data-dependent metric in Rd and use it to define the k-nearest neighbors of a given point.
In addition, for feedback controller design, a data-based stabilizability condition is developed by using a geometrical relationship in data spaces.
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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