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. …”

Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

“…Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”

A Comprehensive Review on Conventional and Machine Learning-Assisted Design of 5G Microstrip Patch Antenna by Nupur Chhaule (21224987)

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…</p><h3>Objective</h3><p dir="ltr">This review aims to explore the machine learning algorithms used for the detection and diagnosis of bipolar disorder and its subtypes.…”

Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain by Farshad Rahimi Ghashghaei (20880995)

TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…However, high dimensional data present a significant challenge for machine learning techniques. …”

Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques by Arifa Zahir (20748764)

“…Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. …”

Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) by Tay, Bilal M.

“…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …”
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Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”

DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems by Amal Hichri (21383672)

R-CONV++: uncovering privacy vulnerabilities through analytical gradient inversion attacks by Tamer Ahmed Eltaras (22565414)

“…<p dir="ltr">Federated learning has emerged as a prominent privacy-preserving technique for leveraging large-scale distributed datasets by sharing gradients instead of raw data. …”

Deep and transfer learning for building occupancy detection: A review and comparative analysis by Aya Nabil Sayed (17317006)

“…This article provides an in-depth survey of the strategies used to analyze sensor data and determine occupancy. The article’s primary emphasis is on reviewing deep learning (DL), and transfer learning (TL) approaches for occupancy detection. …”

Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic by Hassan Farhat (9000509)

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

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. …”

A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

“…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …”
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)