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

“…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …”

A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies by Farideh Abdollahi (22303153)

“…This study aims to bridge this gap by comprehensively reviewing ML concepts, approach, and algorithms in the <u>membrane separation</u> sector. …”

A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…We identify promising directions: hybrid model-free and model-based DRL, offline-to-online learning, transfer and meta-learning for rapid adaptation, integration with federated learning and blockchain for privacy and trust, and progress in interpretability, uncertainty quantification, and formal safety guarantees. …”

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

“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”

Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Boosting the visibility of services in microservice architecture by Ahmet Vedat Tokmak (17773479)

“…Experimental results demonstrated that the CatBoost algorithm achieved the highest level of accuracy (90.42%) in predicting microservice quality.…”

Correlation Clustering with Overlaps by Fakhereldine, Amin

“…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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Artificial intelligence in respiratory care by Manjush Karthika (18384907)

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. …”

Software defect prediction. (c2019) by Moussa, Rebecca

“…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). We compare our approach to 9 well known machine learning techniques and results show the advantages of our model over the other techniques. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV by Zulkifli, Muhammad

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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

“…However, AI tools, for instance, Machine Learning (ML) and Deep Learning (DL), offer precise and well-timed solutions for disease detection, classification, and eradication. …”

DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs by Bahareh Jafari (22501715)

“…By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …”

Cooperative Caching Policy in Fog Computing for Connected Vehicles by Ghazleh, Ali

“…Furthermore, the results showed the proposed model's effectiveness compared to traditional algorithms.…”
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Single-channel speech denoising by masking the colored spectrograms by Sania Gul (18272227)

“…<p>Speech denoising (SD) covers the algorithms that remove the background noise from the target speech and thus improve its quality and intelligibility. …”

Plant disease detection using drones in precision agriculture by Ruben Chin (17725986)

“…The machine learning algorithm applied most is convolutional neural network (CNN). …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Creating and detecting fake reviews of online products by Joni Salminen (7434770)

A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System by Ekinci, Serdar

“…We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism. …”
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Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE by Mathew, Elezabeth

“…Various descriptive, diagnostic, predictive, and prescriptive analysis is done on the e-procurement data. The deep learning model developed can perform thousands of routine and, repetitive tasks within a fairly short period compared to what it would take for a human being without any compromise on the quality of work. …”
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