Jose Antonio Marmolejo Saucedo

TL;DR: The proposed approach allows profiting data transfer capability by data packet and using this information for routing and preventing overcrowd in network nodes and finally, distributing the load over it and revealed that at least 10% of undue delays through network can be prevented while permittivity does not reduce, thanks to the approach.

TL;DR: The proposed scheme efficiently provides security to IoT devices by delegating most of the resource consuming cryptographic processing to a local entity that coordinates with other peer entities to provide a distributed key as well as an authentication mechanism to network devices.

TL;DR: This study proposes a three‐stage methodology where data envelopment analysis (DEA) is augmented with unsupervised and supervised machine learning (ML) to generate a trained model for getting the unique rankings and predicted efficiency scores of layouts.

TL;DR: In the current market with a fiercer competition, shorter product life cycles, changes in technologies, and increasingly interconnected economies; supply chain management is boosted by means of mind-boggling technological innovations like Digital Twins and Agent-Based Model as discussed by the authors.

TL;DR: In this article, a mathematical model is proposed; it takes into account the product’s weight derived from a case study, as the only location for each product in a warehouse with a general layout.