Journal of Computational Science 

TL;DR: A novel convolutional neural network (CNN) based multi-grade brain tumor classification system that is experimentally evaluated on both augmented and original data and results show its convincing performance compared to existing methods.

TL;DR: A new hybrid model can be used to estimate the intrusion scope threshold degree based on the network transaction data’s optimal features that were made available for training and revealed that the hybrid approach had a significant effect on the minimisation of the computational and time complexity involved when determining the feature association impact scale.

TL;DR: The flexible structure of the model that is open to the inclusion of different disease structures and local intervention policies makes GLEaM suitable for the computational modeling and anticipation of the spatio-temporal patterns of global epidemic spreading.

TL;DR: Chaos is introduced into Bat algorithm so as to increase its global search mobility for robust global optimization and results show that some variants of chaotic BAs can clearly outperform the standard BA for these benchmarks.