Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”

Collaborative Caching for D2D Content Sharing in 5G by Abdelsalam, Ansam Elfadil Kamel

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Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…These AI algorithms are effective non-invasive biomarkers for cardiovascular illnesses because they can identify subtle patterns and signals in the ECG that may not be readily apparent to human interpreters. …”

RFID localization using single reader antenna. (c2014) by Msheik, Hamze

“…Unlike conventional Power Map Matching schemes which create the map from actual measurements; the proposed Power Map is automatically generated based on a model. In this work we will justify the proposed Localization scheme analytically and provide numerical and experimental data to substantiate our methodology.…”
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Humanizing AI in medical training: ethical framework for responsible design by Mohammed Tahri Sqalli (18420840)

“…The transparency pillar highlights the crucial role of maintaining the explainabilty of AI algorithms, while the fairness and justice pillar emphasizes on addressing biases in healthcare data and designing models that prioritize equitable medical training outcomes. …”

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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Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks by Mohammed Almehdhar (22046597)

“…Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. …”

LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …”

Video Streaming over D2D Networks by Ahmed, Ibtihal Mohamed Taha

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A decentralized load balancing approach for parallel search-tree optimization by Abu-Khzam, F.N.

“…An area that could largely benefit from such processing capabilities is naturally that of exact algorithms for NP-hard problems. …”
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Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis by Jithin Kalathikudiyil Sreedharan (18268894)

“…<h3>Introduction</h3><p dir="ltr">Artificial intelligence has come to be the highlight in almost all fields of science. It uses various models and algorithms to detect patterns and specific findings to diagnose a disease with utmost accuracy. …”

Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring by Sakib Mahmud (15302404)

“…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”

Resilience analytics: coverage and robustness in multi-modal transportation networks by Abdelkader Baggag (14153040)

“…<p>A multi-modal transportation system of a city can be modeled as a multiplex network with different layers corresponding to different transportation modes. …”

Could Petrol Stations Play a Key Role in Transportation Electrification? A GIS-Based Coverage Maximization of Fast EV Chargers in Urban Environment by Safak Bayram (16925975)

“…More specifically, the location problem is modelled as a maximum coverage location problem (MCLP) and solved using a geographic information system (GIS) based platform. …”

An Anchor-Based Localization in Underwater Wireless Sensor Networks for Industrial Oil Pipeline Monitoring by Nitin Goyal (7876730)

“…Anchor-based localization techniques are segregated into range-free and range-based processes. Range-based schemes depend on various techniques like angle of arrival (AoA), time of arrival (ToA), time difference of arrival (TDoA), and received signal strength indicator (RSSI). …”

Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review by SHEHADEH, KHADIJA

“…New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …”
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ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks by Muhammad Asif Khan (7367468)

“…In this paper, we propose data-driven machine learning (ML) schemes to efficiently solve these problems in wireless LAN (WLAN) networks. …”

Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling by Majed Hadid (17148364)

“…<div><p>Outpatient Chemotherapy Appointment (OCA) planning and scheduling is a process of distributing appointments to available days and times to be handled by various resources through a multi-stage process. …”

CEAP by Abdel Wahab, Omar

“…To reduce the overhead of the proposed detection model and make it feasible for the resource-constrained nodes, we reduce the size of the training dataset by (1) restricting the data collection, storage, and analysis to concern only a set of specialized nodes (i.e., Multi-Point Relays) that are responsible for forwarding packets on behalf of their clusters; and (2) migrating only few tuples (i.e., support vectors) from one detection iteration to another. …”
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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits by Hind Almerekhi (7434776)

“…Before finding toxicity triggers, we built and evaluated various machine learning models to detect toxicity from Reddit comments. Subsequently, we used our best-performing model, a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model that achieved an area under the receiver operating characteristic curve (AUC) score of 0.983 to detect toxicity. …”