An improved kernelization algorithm for r-Set Packing by Abu-Khzam, Faisal N.

“…Such parameterized reductions are known as kernelization algorithms, and a reduced instance is called a problem kernel. …”
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Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

“…Given the protein's sequence of Amino Acids (AAs), our algorithm produces a 3D structure that aims to minimise the energy function associated with the structure. …”
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LINE SEARCH TECHNIQUES FOR THE LOGARITHMIC BARRIER FUNCTION IN QUADRATIC-PROGRAMMING by Bendaya, M.

“…In this paper, we propose a line-search procedure for the logarithmic barrier function in the context of an interior point algorithm for convex quadratic programming. …”
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Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

“…To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using game theory and bootstrapping mechanism. Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”

AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics by Naila Rabbani (291722)

“…In this review, I describe the utility of AGEomics biomarkers and provide evidence why these are close to the phenotype of a condition or disease compared to other metabolites and metabolomic approaches and how to train and test algorithms for clinical diagnostic and screening applications with high accuracy, sensitivity and specificity using machine learning approaches.…”

Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…<h3>Background</h3><p dir="ltr">Existing BRCA2-specific variant pathogenicity prediction algorithms focus on the prediction of the functional impact of a subtype of variants alone. …”

Economic Production Lot-Sizing For An Unreliable Machine Under Imperfect Age-Based Maintenance Policy by El-Ferik, S

“…Numerical results are provided to illustrate both the use of the algorithm in the study of the optimal cost function and the latter's sensitivity to different changes in cost factors. …”
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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by Krishnamoorthy Natarajan (22047464)

“…<p dir="ltr">A disease is a distinct abnormal state that significantly affects the functioning of all or part of an individual and is not caused by external harm. …”

Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…In the first, the spring stiffness, the position of the second attachment point of the string and a preliminary damping constant are calculated using a genetic algorithm approach where the objective function is the maximum displacement on the beam. …”
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Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques by Kais Abdulmawjood (17947784)

“…In the first stage, the WPT is used to split the PV voltage and string currents into specific sub-band frequencies, and then EMD is used to decompose the selected frequency bands into a number of intrinsic mode functions (IMFs) and a residual. …”

Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter by Syed Rahman (569240)

Exploring New Parameters to Advance Surface Roughness Prediction in Grinding Processes for the Enhancement of Automated Machining by Mohammadjafar Hadad (21142499)

“…To evaluate a robust algorithm, a method is devised that involves different networks utilizing various activation functions and neuron sizes to distinguish and select the best architecture for this study. …”

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

“…The proposed DRL controllers are benchmarked against model-based controllers, i.e., linear quadratic regulator with the sequential quadratic programming (LSQP) and sliding mode control with SQP (SSQP). A tailored multi-term reward function is structured to penalize excessive yaw rate error, sideslip angle, tire slip deviations beyond peak grip regions, and power losses based on a realistic electric machine efficiency map. …”

Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

“…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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Optimal design of power-system stabilizers using particle swarm optimization by Abido, M.A.

“…In this paper, a novel evolutionary algorithm-based approach to optimal design of multimachine power-system stabilizers (PSSs) is proposed. …”
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

“…<p dir="ltr">CubeSats have been gaining significant interest as a cost-effective solution that can be built with low power requirements for different mission types. …”

Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System by Abualigah, Laith

“…Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…Unlike standard machine learning approaches such as PCA, LDA, SVM, RF, GBM etc, DeepRaman functions independently, requiring no human interaction, and can be used to much smaller datasets than traditional CNNs. …”
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…<p>This work aims to provide an effective hybrid beam forming method with Dual-Deep-Network to overcome overhead for mm-wave massive MIMO systems. In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. …”