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. …”

Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT) by AlHamaydeh, Mohammad

“…The powerful genetic algorithm optimization technique is augmented with an innovative “domain-trimming” modification. …”
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Second-order conic programming for data envelopment analysis models by Mourad, Nahia

“…Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures by Leduc, Guillaume

“…We develop a semi-analytical method to determine the price of European options on these energy futures, involving the derivation of the characteristic function for the energy futures' dynamics. …”
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A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks by Saad, Walid

“…In this work, we propose a utility-based joint uplink/downlink scheduling algorithm suitable for wireless services involving pairwise communication among mobile users. …”
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Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller by Sk. A., Shezan

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Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks by Haris M. Khalid (17017743)

“…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …”

Minimizing using BBO and DFO methods by El Zeghondy, Jean

“…In [1], Nour and Zeidan proposed a numerical algorithm to solve optimal control problems involving sweeping processes. …”
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On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

“…For the first optimization scenario, distribution-free analysis showed that at intermediate function evaluation budgets, detectable differences emerge among algorithms, whereas in the second scenario, these differences diminish at higher evaluation budgets (with no significant pairwise contrasts), indicating convergence. …”

R-CONV++: uncovering privacy vulnerabilities through analytical gradient inversion attacks by Tamer Ahmed Eltaras (22565414)

“…The first algorithm presents a novel data leakage method that efficiently exploits convolutional layer gradients, demonstrating that even with non-fully invertible activation functions, such as ReLU, training samples can be analytically reconstructed directly from gradients without the need to reconstruct intermediate layer outputs. …”

Cohen syndrome and early-onset epileptic encephalopathy in male triplets: two disease-causing mutations in VPS13B and NAPB by Alice AbdelAleem (17753799)

“…Homozygosity mapping of ES data of this consanguineous family revealed multiple chromosomal regions of homozygosity stretches with the residing of VPS13B (chr8: 100830758G > A) and NAPB (Chr20: 23,375,774 A > C) variants within the largest homozygous blocks further supporting the disease-genes causal role. Interestingly, the functions of the two proteins; VPS13B, a transmembrane protein involved in intracellular protein transport, and SNAP-beta involved in neurotransmitters release at the neuronal synaptic complexes, have been associated with Golgi-mediated vesicular trafficking. …”

SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data by Tekli, Joe

“…This paper describes SemIndex+, a semantic-aware indexing and querying framework that allows semantic search, result selection, and result ranking of structured (relational DB-style), unstructured (IR-style), and partly structured (NoSQL) data. Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …”
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Estimating Bridge Deterioration Age Using Artificial Neural Networks by AL HUSSEIN, ASEEL

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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. …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ObjectiveThis study utilized various classical machine learning techniques, such as support vector machines, k-nearest neighbors, and random forests, in conjunction with a modified deep learning approach called DeepRaman. These algorithms were employed to distinguish and categorize bacterial endotoxins, following appropriate spectral pre-processing, which involved novel filtering techniques and advanced feature extraction methods. …”
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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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Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning by Moussa, Mostafa Mohamed

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Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials by Ghouti, Lahouari

“…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

“…First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. …”

Deploying model obfuscation: towards the privacy of decision-making models on shared platforms by Sadhukhan, Payel

“…Privacy and security of data and models are fundamental necessities that must be satisfied for this protocol's proper functioning. To this end, we propose a conceptual and algorithmic framework of a model obfuscation scheme. …”
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