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

“…Our analysis reveals that LLMs significantly enhance code completion performance across several programming languages and contexts, and their capability to predict relevant code snippets based on context and partial input boosts developer productivity substantially.…”

Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

“…Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. …”
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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems by Amal Hichri (21383672)

“…This is addressed such that the genetic algorithm (GA) technique is used for selecting the best features and the artificial neural network (ANN) classifier is applied for fault diagnosis. …”

Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain by Jun Zhu (84054)

“…The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. …”

Deep learning-based user experience evaluation in distance learning by Rahim Sadigov (17714301)

“…More than 160,000 tweets, addressing conditions related to the major change in the education system, were gathered from Twitter social network and deep learning-based sentiment analysis models and topic models based on latent dirichlet allocation (LDA) algorithm were developed and analyzed. …”

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

“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…However, with the huge increase in data size, sophisticated models have to be created which require big data platforms. …”

Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”

Detecting sleep outside the clinic using wearable heart rate devices by Ignacio Perez-Pozuelo (14153007)

“…We developed and tested a heart rate-based algorithm that captures inter- and intra-individual sleep differences in free-living conditions and does not require human input. …”

Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

“…Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”

Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

Subjects:

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. Our proposed framework consists of two essential steps: establishing a correlation between IL viscosity and CO₂ solubility by merging two deep learning models (DNN-GC and ANN-GC) and utilizing this correlation to identify the optimal IL structure with maximal CO₂ absorption capacity. …”

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends by Abdellatif M. Sadeq (16931841)

“…<p dir="ltr">Studying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. Based on previous 3D numerical analyses, this study aims to develop data-driven machine learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, gas-to-liquids (GTL), and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. …”

Real-Time Performance Evaluation of a Genetic Algorithm Based Fuzzy Logic Controller for IPM Motor Drives by Nasir Uddin, M.

“…This work presents a novel speed control scheme using a genetic-based fuzzy logic controller (GFLC) for an interior permanent-magnet synchronous motor (IPMSM) drive. …”
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Stacking-based ensemble learning for remaining useful life estimation by Begum Ay Ture (17773170)

Fault-Tolerant Network Topologies for Datacenters by Attia, Heba Mahmoud Helal

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Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Identification of errors-in-variables model with observation outliers based on Minimum-Covariance-Determinant by ALMutawa, J.

“…The proposed algorithm has been applied to a heat exchanger data.…”
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On the periodic hierarchical Chinese postman problem by Muhammed Emre Keskin (19457413)

Fuzzy Logic Based Patients' Monitoring System by Al-Dmour, Jumana

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