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There exists a need to propose novel techniques to improve both computational efficiency and spectrum reuse.
We propose novel techniques for assessing the strength of borders within a regional partitioning scheme, and for assessing the impact of inappropriate partitioning on model accuracy.
In this paper, we propose novel techniques to improve the performance of NN classifier and at the same time to reduce its computational burden.
In the following section, we propose novel techniques for quantifying the impact of a regional partition scheme on model accuracy, and for assessing the strength of borders in a given partitioning scheme.
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The authors in [29] proposed novel techniques for placement and power consolidation of VMs in the virtualized data centers.
The second section is related to the image filtering and restoration with three papers proposing novel techniques in this quite competitive field.
Finally, we address these challenges by proposing novel techniques to assess the strength of borders in a regional partitioning scheme and to quantify the impact of border strength on mobility model accuracy.
This paper proposes novel techniques that are based on the orthogonal lattice and are practical with any number of free-parameters.
To improve the solution efficiency for diagnosability, this paper proposes novel techniques to solve the problems of testing and optimizing for diagnosability.
This paper proposes novel techniques to deal with cognitive scalability issues in risk assessment studies, amongst which graphical extensions to traditional risk management approaches, such as chain diagrams, and the seamless integration of attack trees.
We propose novel MO naive Bayes learning techniques modeled by a Harmony Search meta-heuristic algorithm.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com