Intelligent scaling for 6G IoE services for resource provisioning by Abdullah Alharbi (4173502)

“…IScaler is considered to be made for MEC in Deep Reinforcement Learning (DRL). The paper has considered several requirements for making service placement decisions. …”

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari (22467148)

Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation by Rawan AlSaad (14159019)

“…However, in practice, a patient’s visits are irregularly spaced over a relatively long period of time, and disease progression patterns exhibit non-stationarity. …”

Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data by Alaa Awad Abdellatif (17151163)

“…<p dir="ltr">Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. …”

Effect of sulfonated poly (ether ether ketone) on the sensitivity of polyvinylidene fluoride-based resistive humidity sensors by Shoaib Mallick (14578565)

“…As the concentration of SPEEK increases in the blend film, the hydrophilicity of the composite film also increases, which enhances the sensitivity of the sensing film. …”

Towards electric digital twin grid: Technology and framework review by Md. Mhamud Hussen Sifat (17337913)

“…Electric Digital Twin grid can perform online analysis of the grid in real-time and integrates all the past and present data and express the current grid status to the producers and consumers and also predicts the future grid status. …”

Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities by Md Golam Morshed (19420537)

“…One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. …”

Evaluating machine learning technologies for food computing from a data set perspective by Nauman Ullah Gilal (17302714)

“…Food computing benefits from technologies based on modern machine learning techniques, including deep learning, deep convolutional neural networks, and transfer learning. …”

A systematic review and meta-analysis on the impact of early vs. delayed pharmacological thromboprophylaxis in patients with traumatic brain injury by Muhammad Hamza Shuja (19748620)

“…Early PTP was categorized based on the timing of administration: 1) within 24 h, 2) within 48 h, and 3) within 72 h of hospital admission. …”

A New Flow-Based Approach for Enhancing Botnet Detection Efficiency Using Convolutional Neural Networks and Long Short-Term Memory by Mehdi Asadi (12566741)

“…<p dir="ltr">Despite the growing research and development of botnet detection tools, an ever-increasing spread of botnets and their victims is being witnessed. …”

Food fraud detection using explainable artificial intelligence by Okan Buyuktepe (17991493)

“…<div><p>Recently, the global food supply chain has become increasingly complex, and its scalability has grown. …”

Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting by Abdelkader Baggag (16864140)

“…., its generation, propagation and mitigation, in order to increase operational efficiency and improve livability within smart cities. …”

TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images by Tawsifur Rahman (14150523)

“…However, it is difficult to identify TB from CXR images in the early stage, which leads to time-consuming and expensive treatments. Moreover, due to the increase of drug-resistant tuberculosis, the disease becomes more challenging in recent years. …”

Artificial intelligence in respiratory care by Manjush Karthika (18384907)

Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…Based on the performance metrics, such as confusion matrix, training time, prediction time, accuracy, and Area Under the Receiver Operating Characteristic curve (AUC-ROC), it was established that SDN-ML-IoT, when applied to RF, outperforms other ML algorithms, as well as similar approaches related to our work. …”

Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review by Alaa Abd-alrazaq (17058018)

Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review by Hazrat Ali (421019)

“…It provides key insights into how vision transformers complemented the performance of AI and deep learning methods for lung cancer. Furthermore, the review also identifies the datasets that contributed to advancing the field.…”

Applying Graph Neural Networks to the Decision Version of Graph Combinatorial Optimization Problems by Raka Jovanovic (17947838)

Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection by Ahmad Yaser Alhaddad (7017434)

Blockchain-Based Local Energy Market Enabling P2P Trading: An Australian Collated Case Study on Energy Users, Retailers and Utilities by Liaqat Ali (641438)

“…Moreover, the margins of both energy retailers and distribution utilities are kept unchanged or increased to some extent by the proposed trading model to incorporate them in the LEM framework effectively. …”