Ata Ullah

TL;DR: A fog-assisted congestion avoidance scheme for IoV named energy efficient message dissemination (E2MD).

TL;DR: This work uses three classifiers: random forest, K -nearest neighbors and linear support vector machine to predict the occurrence of NTL in a real dataset of an electric supply company containing approximately 80,000 monthly consumption records and computes 14 performance evaluation metrics across these classifiers to provide insights into deciding which classifier can be more useful under given scenarios for NTL detection.

TL;DR: This research presents a Secure Authentication and Prescription Safety (SAPS) protocol to ensure secure communication between the patient, doctor/nurse, and the trusted server and relies upon the efficient elliptic curve cryptosystem which can generate a symmetric secure key.

TL;DR: A bandwidth aware routing scheme (BARS) that can avoid congestion by monitoring residual bandwidth capacity in network paths and available space in queues to cache the information and prove the dominance of the BARS over preliminaries in terms of packet delivery ratio, throughput and end-to-end delay.

TL;DR: The concept of hybrid human-artificial intelligence (H-AI) into a semi-autonomous driving system is introduced and a theoretical architecture based on it is proposed, which provides a new perspective for the future development of autonomous driving.