Joint Beamforming Design and Power Minimization for Friendly Jamming Relaying Hybrid RF/VLC Systems حسب Jaber Al-Khori (16855470)

An Adaptive Sliding Mode Control for a Dual Active Bridge Converter With Extended Phase Shift Modulation حسب Farzaneh Bagheri (17947811)

"…The conventional single-phase shift (SPS) modulation-based DAB converter is known to be inefficient. Hence, an optimization algorithm based on the Lagrange multiplier method (LMM) is proposed to minimize both backflow power and inductor current stress simultaneously. …"

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas حسب Marwan Dhuheir (19170898)

"…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …"

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... حسب Tarik Elhadd (5480393)

"…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…"

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches حسب Natasha Akram (20749538)

"…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …"

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI حسب Oishi Jyoti (21593819)

"…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …"

Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks حسب Abbas, Nadine

"…We also propose efficient sub-optimal hierarchical tree-based algorithms that operate in real time with dynamic and fast solutions for ultra dense networks. …"
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Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review حسب Chakraborty, Sanjoy

"…Differential evolution (DE) is one of the highly acknowledged population-based optimization algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems. …"
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Scatter search technique for exam timetabling حسب Mansour, Nashat

"…We evaluate our suggested technique on real-world university data and compare our results with the registrar’s manual timetable in addition to the timetables of other heuristic optimization algorithms. The experimental results show that our adapted scatter search technique generates better timetables than those produced by the registrar, manually, and by other meta-heuristics.…"
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Effective solutions for the capacitated vehicle routing problem and for the split delivery vehicle routing problem with time windows. (c2013) حسب Hilal, Nathalie

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A new bi-objective model of the urban public transportation hub network design under uncertainty حسب Firoozeh Kaveh (14150877)

"…For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. …"

Multi-UAV-Enabled Mobile Edge Computing IoT Systems: Joint Association and Resource Allocation Framework حسب Abu Farha, Yazan Mahmoud

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Boosting the Training of Neural Networks Through Hybrid Metaheuristics حسب Abou Doush, Iyad

"…In this paper, six versions of memetic algorithms (MAs) are proposed to replace gradient descent learning mechanism of MLP where adaptive β�-hill climbing (Aβ�HC) as a local search algorithm is hybridized with six population-based metaheuristics which are hybrid flower pollination algorithm, hybrid salp swarm algorithm, hybrid crow search algorithm, hybrid grey wolf optimization (HGWO), hybrid particle swarm optimization, and hybrid JAYA algorithm. …"
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A METHODOLOGY FOR NETWORK TOPOLOGY DESIGN USING FUZZY EVALUATIONS حسب Khan, Salman A.

"…In this paper, we present a methodology to address design issues. This methodology is based on two algorithms, namely, fuzzy simulated evolution algorithm and the augmenting path algorithm. …"
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A linear programming approach for the weighted graph matchingproblem حسب Almohamad, H.A.

"…A linear program is obtained by formulating the graph matching problem in L1 norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a simplex-based algorithm. …"
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GENETIC SCHEDULING OF TASK GRAPHS حسب Benten, M. S.

"…The problem of assigning tasks to processing elements as a combinatorital optimization is formulated, and a heuristic based on a genetic algorithm is presented. …"
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A LINEAR-PROGRAMMING APPROACH FOR THE WEIGHTED GRAPH MATCHING PROBLEM حسب Al-Mohamad, HA

"…A linear program is obtained by formulating the graph matching problem in L1 norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a Simplex-based algorithm. …"
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Final exams scheduling for univeristies. (c2001) حسب Timany, Mazen Nuhad

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Digital Image Watermarking Using Balanced Multiwavelets حسب Ghouti, L.

"…The optimal bounds for the embedding capacity are derived using a statistical model for balanced multiwavelet coefficients of the host image. …"
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Power system output feedback stabilizer design via geneticalgorithms حسب Abdel-Magid, Y.L.

"…A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …"
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