Abdulaziz Alarifi

TL;DR: This work introduces a novel big data and machine learning technique for evaluating sentiment analysis processes to improve system efficiency, and results obtained are compared; CSO-LSTMNN outperforms PSO in terms of increasing accuracy and decreasing error rate.

TL;DR: A novel hybrid cryptosystem combining DNA (Deoxyribonucleic Acid) sequences, Arnold chaotic map, and Mandelbrot sets is suggested for secure streaming of compressed HEVC streams, which reveals astonishing robustness and security accomplishment in contrast to the literature cryptosSystems.

TL;DR: This research attempts to propose a reinforcement-based learning technique, adaptive Q-learning (AQL) to improve network performance with minimum energy–overhead tradeoff in a sensor network-aided CIoT and illustrates the effectiveness of the proposed learning technique by improving network lifetime with a high request–response rate and by minimizing delay, overhead, and request failures.

TL;DR: An effective and optimized fall detection system that uses an approach based on a killer heuristics optimized AlexNet convolution neural network to recognize a fall with maximum accuracy and minimum complexity is introduced.

TL;DR: In this article, a cancelable biometric recognition system (CBRS) based on the suggested optical PTFT (Phase Truncated Fourier Transform) asymmetric encryption algorithm is introduced.