Using learning analytics to measure self‐regulated learning: A systematic review of empirical studies in higher education by Saleh Alhazbi (16869960)

“…Recently, there has been a growing interest in utilizing learning analytics (LA) to capture students' self‐regulated learning (SRL) by extracting indicators from their online trace data.…”

Online Transient Stability Assessment Under Concept Drift: An ARF-Method-Assisted Federated Learning for Data Streams by Mohamed Massaoudi (16888710)

“…Despite the success of data-driven transient stability assessment (TSA), its practical implementation remains limited by challenges in processing high-speed real-time data streams and preserving data privacy. …”

Artificial intelligence in medical referrals triage based on Clinical Prioritization Criteria by Ahmad Abdel-Hafez (17289934)

KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

Processing airborne LiDAR point cloud for solar cadasters: A review by Inas H. Mahir (20568158)

“…<p dir="ltr">This paper reviews existing literature in the critical role of processing Lidar point cloud data for generating Digital Elevation Models (DEMs)— Digital Surface Models (DSMs) and Digital Terrain Models (DTMs)—to develop solar cadasters, which are essential for optimizing solar energy deployment in urban environments. …”

Novel Evasion Attacks Against Adversarial Training Defense for Smart Grid Federated Learning by Atef H. Bondok (19482352)

“…The current methods for identifying such attacks raise privacy concerns due to the need for access to consumers’ detailed consumption data to train detection mechanisms. To address privacy concerns, federated learning (FL) is proposed as a collaborative training approach across multiple consumers. …”

Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

Smart Grid Big Data Analytics: Survey of Technologies, Techniques, and Applications by Dabeeruddin Syed (16864260)

“…The paper also presents the challenges and opportunities brought by the advent of machine learning and big data from smart grids.</p><h2>Other Information</h2><p>Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2020.3041178" target="_blank">https://dx.doi.org/10.1109/access.2020.3041178</a></p>…”

Arabic natural language processing for Qur’anic research: a systematic review by Muhammad Huzaifa Bashir (19467919)

Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations by Yassine Himeur (14158821)

Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model by Dabeeruddin Syed (16864260)

“…In the model-building phase, the hybrid model is trained on the processed data. The hybrid deep learning (DL) model is based on the stacking of fully connected layers, and unidirectional Long Short Term Memory (LSTMs) on bi-directional LSTMs. …”

Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”

Data-driven enhancement of cubic phase stability in mixed-cation perovskites by Heesoo Park (1604989)

Explainable deep learning for rainfall prediction: A CNN-XGBoost hybrid approach in the northern region of Bangladesh by Md Safayet Islam (23073187)

“…These findings demonstrate the model’s efficacy across several data sources. To enhance the interpretability of the proposed CNN-XGB model, we deployed the SHAP (Shapley Additive exPlanations) explainer, providing insights into the model’s decision-making process. …”

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …”

The future of sleep health: a data-driven revolution in sleep science and medicine by Ignacio Perez-Pozuelo (14153007)

Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey by Faria Nawshin (21841598)

A collaborative filtering recommendation framework utilizing social networks by Aamir Fareed (17019087)

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)