Large language models for code completion: A systematic literature review حسب Rasha Ahmad Husein (19744756)

"…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …"

Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques حسب Kais Abdulmawjood (17947784)

Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging حسب Maricar, Mohammed Farook

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Decision-level fusion for single-view gait recognition with various carrying and clothing conditions حسب Al-Tayyan, Amer

"…The methods are evaluated on CASIA B Dataset using four different experimental setups, and on OU-ISIR Dataset B using two different setups. …"
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Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE حسب Mathew, Elezabeth

"…The novel LSTM time series algorithm proved to work best for demand forecasting. …"
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Exploring the System Dynamics of Covid-19 in Emergency Medical Services حسب Ali, Muhammad

"…The predictive analysis yielded a model of response times for emergency missions through machine learning, specifically using a random forest algorithm. …"
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Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation حسب Zakaria Shams Siam (22048001)

"…Efforts are underway to develop algorithms that can generate 7T MRI from 3T MRI to achieve better image quality without the need for 7T MRI machines. …"

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier حسب Syed Ali Jafar Zaidi (19563178)

"…Modern ML models are used for prediction, prioritization, and decision making. Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …"

Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review حسب Daksh Dave (17949239)

"…This review focuses on the diagnostic accuracy of AI-assisted mammography, synthesizing findings from studies across different clinical settings and algorithms. The motivation for this research lies in addressing the need for enhanced diagnostic tools in breast cancer screening, where early detection can significantly impact patient outcomes. …"

Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort حسب Mohamed Adil Shah Khoodoruth (14589828)

"…The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. …"

Cross-linguistic authorship attribution and gender profiling. Machine translation as a method for bridging the language gap حسب George Mikros (19197997)

Extremely boosted neural network for more accurate multi-stage Cyber attack prediction in cloud computing environment حسب Surjeet Dalal (4906894)

"…This paper demonstrated the results of executing various machine learning algorithms and proposed an enormously boosted neural network. …"

Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System حسب Fahmida Haque (16896489)

"…The model accuracy was validated with the results from different machine learning algorithms. The Accuracy, sensitivity, and specificity of the ANFIS model are 91.17±1.18%, 92±2.26%, 96.72±0.93%, respectively. …"

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…The performance of the deep learning models is measured using three well-known performance matrices viz. mean absolute error (MAE)-based construction error, the difference in the signal-to-noise ratio (ΔSNR), and percentage reduction in motion artifacts (<i>η</i>). …"

A multi-pretraining U-Net architecture for semantic segmentation حسب Cagla Copurkaya (22502042)

"…In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …"

Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks حسب Jafari, Reza

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Loop based scheduling for high level synthesis حسب Al-Sukhni, H.F.

"…This paper describes a new loop based scheduling algorithm. The algorithm aims at reducing the runtime processing complexity of path based scheduling techniques. …"
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An Ontology-based Semantic Web for Arabic Question Answering: The Case of E-Government Services حسب ALBARGHOTHI, ALI BAHA’EDDIN

"…After that, the Natural Language Processing (NLP) tasks are used to process the services’ profiles and extract the ontological keywords. …"
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Bridge Structural Health Monitoring Using Mobile Sensor Networks حسب Amin, Fouad

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Fixed set search applied to the multi-objective minimum weighted vertex cover problem حسب Raka Jovanovic (17947838)

"…To fully evaluate the learning mechanism of the FSS, it is compared to the underlying GRASP algorithm on a wide range of performance indicators related to convergence, distribution, spread and cardinality.…"