Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”

A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

CNN and HEVC Video Coding Features for Static Video Summarization by Issa, Obada

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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”

Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators by Al-Hamouz, Z.M.

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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”

On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

Subjects: “…Nature-inspired optimization algorithms…”

Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices by Khawam, Yahya Bader

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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

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Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

“…The authors report on the design of a digital feedback control system to provide null steering by controlling the array element positions automatically. The array comprises a signal processor, digital control algorithm (PID), stepper motors, shaft encoders, actuators and multiplexers. …”
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Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

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Automatic Video Summarization Using HEVC and CNN Features by Issa, Obada

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Adaptive bias simulated evolution algorithm for placement by Youssef, H.

“…A new solution is evolved from current solution by relocating some of the solution elements. Elements with lower goodnesses have higher probabilities of getting selected for perturbation. …”
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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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A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

“…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …”
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