Pinned Repositories
nmpa
Nonlinear Marine Predator Algorithm (NMPA) NMPA an influential attempt to identify and alleviate some of the issues with the recently proposed optimization technique called the Marine Predator Algorithm (MPA). With a visual investigation of its exploratory and exploitative behavior, it is observed that the transition of search from being global to local can be further improved. As an extremely cost-effective method, a set of nonlinear functions is used to change the search patterns of the MPA algorithm. The proposed algorithm is called Nonlinear Marin Predator Algorithm (NMPA) is tested on a set of benchmark functions. A comprehensive comparative study shows the superiority of the proposed method compared to the original MPA and even other recent meta-heuristics. The paper also considers solving a real-world case study around power allocation in non-orthogonal multiple access (NOMA) and visible light communications (VLC) for Beyond 5G (B5G) networks to showcase the applicability of the NMPA algorithm. NMPA algorithm shows its superiority in solving a wide range of benchmark functions as well as obtaining fair power allocation for multiple users in NOMA-VLC-B5G systems compared with the state-of-the-art algorithms. In case you can't access the paper, please email me on ali.sadiq@wlv.ac.uk or alisafa09@gmail.com and I will get back to you soon.
Nonlinear-based-Chaotic-Harris-Hawks-Optimization_Internet-of-Vehicles_Application
NCHHO uses chaotic and nonlinear control parameters to improve HHO’s optimization performance. The main goal of using the chaotic maps in the proposed method is to improve the exploratory behavior of HHO. In addition, this paper introduces a nonlinear control parameter to adjust HHO’s exploratory and exploitative behaviours. The proposed NCHHO algorithm shows an improved performance using a variety of chaotic maps that were implemented to identify the most effective one, and tested on several well-known benchmark functions. Also, this work considers solving an Internet of Vehicles (IoV) optimization problem that showcases the applicability of NCHHO in solving large-scale, real-world problems.
alisafaa12
Config files for my GitHub profile.
autocheri
AutoCHERI project website, for the UKRI funded project to put CHERI into an automotive setting via the Arm Morello dev platform
az-deep-realtime-score
AKS Deployment Tutorial
bias-in-AI-course
cheribsd
FreeBSD adapted for CHERI-RISC-V and Arm Morello.
cheriot-rtos
The RTOS components for the CHERIoT research platform
ColBERT
ColBERT: state-of-the-art neural search (SIGIR'20, TACL'21, NeurIPS'21, NAACL'22, CIKM'22)
demo
alisafaa12's Repositories
alisafaa12/FreeRTOS
'Classic' FreeRTOS distribution. Started as Git clone of FreeRTOS SourceForge SVN repo. Submodules the kernel.
alisafaa12/FreeRTOS-Demos-CHERI-RISC-V
alisafaa12/autocheri
AutoCHERI project website, for the UKRI funded project to put CHERI into an automotive setting via the Arm Morello dev platform
alisafaa12/MoBShield
MoBShield: A Novel XML Approach for Securing Mobile Banking
alisafaa12/FlexiCubes
alisafaa12/spdk
Storage Performance Development Kit
alisafaa12/cheribsd
FreeBSD adapted for CHERI-RISC-V and Arm Morello.
alisafaa12/cheriot-rtos
The RTOS components for the CHERIoT research platform
alisafaa12/intravisor
Virtualisation platform using CHERI for isolation and sharing
alisafaa12/mavsdk_drone_show
All in one Drone Show and Smart Swarm Solutin for PX4
alisafaa12/test
alisafaa12/bias-in-AI-course
alisafaa12/alisafaa12
Config files for my GitHub profile.
alisafaa12/ColBERT
ColBERT: state-of-the-art neural search (SIGIR'20, TACL'21, NeurIPS'21, NAACL'22, CIKM'22)
alisafaa12/demo2
alisafaa12/demo
alisafaa12/fuzzgoat
A vulnerable C program for testing fuzzers.
alisafaa12/nmpa
Nonlinear Marine Predator Algorithm (NMPA) NMPA an influential attempt to identify and alleviate some of the issues with the recently proposed optimization technique called the Marine Predator Algorithm (MPA). With a visual investigation of its exploratory and exploitative behavior, it is observed that the transition of search from being global to local can be further improved. As an extremely cost-effective method, a set of nonlinear functions is used to change the search patterns of the MPA algorithm. The proposed algorithm is called Nonlinear Marin Predator Algorithm (NMPA) is tested on a set of benchmark functions. A comprehensive comparative study shows the superiority of the proposed method compared to the original MPA and even other recent meta-heuristics. The paper also considers solving a real-world case study around power allocation in non-orthogonal multiple access (NOMA) and visible light communications (VLC) for Beyond 5G (B5G) networks to showcase the applicability of the NMPA algorithm. NMPA algorithm shows its superiority in solving a wide range of benchmark functions as well as obtaining fair power allocation for multiple users in NOMA-VLC-B5G systems compared with the state-of-the-art algorithms. In case you can't access the paper, please email me on ali.sadiq@wlv.ac.uk or alisafa09@gmail.com and I will get back to you soon.
alisafaa12/Non-Linear-L-vy-Brownian-Generalized-Normal-Distribution-Optimization-LBGNDO-
Trustworthy and Efficient Routing Algorithm for IoT-FinTech Applications Using Non-Linear Lévy Brownian Generalized Normal Distribution Optimization
alisafaa12/Nonlinear-based-Chaotic-Harris-Hawks-Optimization_Internet-of-Vehicles_Application
NCHHO uses chaotic and nonlinear control parameters to improve HHO’s optimization performance. The main goal of using the chaotic maps in the proposed method is to improve the exploratory behavior of HHO. In addition, this paper introduces a nonlinear control parameter to adjust HHO’s exploratory and exploitative behaviours. The proposed NCHHO algorithm shows an improved performance using a variety of chaotic maps that were implemented to identify the most effective one, and tested on several well-known benchmark functions. Also, this work considers solving an Internet of Vehicles (IoV) optimization problem that showcases the applicability of NCHHO in solving large-scale, real-world problems.
alisafaa12/az-deep-realtime-score
AKS Deployment Tutorial