Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks حسب Daou, Leonardo

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Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv... حسب Atif Iqbal (5504636)

"…The investigation that involves analysis and comparison is done for obtaining reduced total harmonic distortion (THD) by using different level-shifted multicarrier SPWM schemes along with proposed GA-based SHE. …"

A reduced model for phase-change problems with radiation using simplified PN approximations حسب Belhamadia, Youssef

"…A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …"
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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation حسب Iman M. Hosseini Naveh (16891482)

"…The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). …"

A New Approach for Recognizing Saudi Arabian License Plates using Neural Networks حسب Deriche, Mohamed

"…Finally, a Multilayer Feedforward Neural Network (MFNN) with a backpropagation (BP) algorithm is used for character recognition. We discuss new features from the characters for training the NN. …"
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EEG Signal Processing for Medical Diagnosis, Healthcare, and Monitoring: A Comprehensive Review حسب Nisreen Said Amer (17984077)

"…<p dir="ltr">EEG is a common and safe test that uses small electrodes to record electrical signals from the brain. …"

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV حسب Zulkifli, Muhammad

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

Using artificial bee colony to optimize software quality estimation models. (c2015) حسب Abou Assi, Tatiana Antoine

"…In order to measure such software quality characteristics, we must wait until the software is implemented, tested and put to use for a certain amount of time. …"
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization حسب Muhammad Salman Khan (7202543)

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features حسب Muhammad Arif (769250)

"…The proposed StackDPPred method improves the overall accuracy by 13.41% and 7.62% compared to existing DPs predictors iDPF-PseRAAC and iDEF-PseRAAC, respectively on validation test. Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …"

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts حسب ALSHAMSI, SUROUR

"…As a function of the proposed objective, ensembling algorithms applicable to network security have been investigated and evaluated, and a methodology for detecting infected PAGE 2 hosts using ensembling has been developed, based on experiments designed and tested with real datasets. …"
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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network حسب KHAN, FIROZ

"…The feature selection uses Grey Wolf Optimisation and Binary Search algorithms for choosing the best features out of the dataset. …"
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) حسب Fares Almomani (12585685)

"…Experimental data was used to develop the appropriate architecture for the AAN using iterative steps of training and testing. …"

Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique حسب Iqbal Hassan (22155274)

"…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). The primary objective of this study is to estimate the CL index through an innovative approach that employs a hybrid, cluster-based, unsupervised learning technique seamlessly integrated with a 1D Convolutional Neural Network (CNN) architecture tailored for automated feature extraction, rather than conventional supervised algorithms, which facilitated in the acquisition of latent complex patterns without the need for manual categorization. …"

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

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

On the exact recovery of the FFT of noisy signals using a non-subtractively dither-quantized input channel حسب Cheded, L.

"…This paper proposes a new theory that resolves this conflict for any quantization resolution used. This theory, tested with a 1-bit quantization scheme and under very noisy environments is very well supported by our simulation results. …"
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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network حسب Monzure-Khoda Kazi (17191207)

"…Advanced machine learning algorithms are used in this study to figure out the complicated relationship between the crashworthiness parameters of the hexagonal composite ring specimens under lateral compressive, energy absorption, and failure modes. …"

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images حسب Rehan Raza (17019105)

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features حسب Mariam Bahameish (19255789)

"…This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …"