Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

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An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications by Abu Zitar, Raed

“…Initially, the optimization model and convergence characteristics of JAYA algorithm are carefully analyzed. …”
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Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”

Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”

An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

“…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. Therefore, this process can be seen as an optimization process. The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …”
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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

“…The important feature subset is identified using the modified Binary Grey Wolf Optimization Particle Swarm Optimization (BGWOPSO) algorithm. …”

Deep and transfer learning for building occupancy detection: A review and comparative analysis by Aya Nabil Sayed (17317006)

“…This work investigates occupancy detection methods to develop an efficient system for processing sensor data while providing accurate occupancy information. …”

A method for data path synthesis using neural networks by Harmanani, H.

“…The method is based on the modified Hopfield neural network model of computation and the McCulloch-Pitts binary neuron model. …”
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Towards Multimedia Fragmentation by Saad, Samir

“…Database fragmentation is a process for reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. …”
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From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”