Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes حسب Muhammad Mohsin Khan (22150360)

"…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …"

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. …"

Next-generation energy systems for sustainable smart cities: Roles of transfer learning حسب Yassine Himeur (14158821)

"…These algorithms might not perform as expected, take much time in training, or do not have enough input data to generalize well. …"

Stability and Numerical Solutions of Second Wave Mathematical Modeling on COVID-19 and Omicron Outbreak Strategy of Pandemic: Analytical and Error Analysis of Approximate Series So... حسب Ashwin Muniyappan (19570051)

"…The algorithm guidelines are used for international arrivals, with Omicron variant cases updated by the Union Health Ministry in January 2022. …"

An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan حسب Ghulam Abbas (764241)

"…In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor method (NEPFM) via a direct search algorithm, i.e., simplex search algorithm (SSA). We designate the resulting algorithm as NEPFM-SSA as it took NEPFM’s Weibull distribution parameters as an initial guess and retuned them with the help of the simplex search algorithm to get updated Weibull distribution parameters, which ensure better fitting characteristics. …"

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

"…Magnetic resonance imaging data were most commonly used for classifying bipolar patients compared to other groups (11, 34%), whereas microarray expression data sets and genomic data were the least commonly used. …"

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

"…Occupancy data might be collected using a variety of devices. …"

An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication حسب Syed Muhammad Amrr (16855557)

"…Of late, within the ambit of control of systems over networks, event-triggered control has proved to be instrumental in ensuring acceptable closed-loop performance while respecting bandwidth constraints of the underlying network. Aligned with these design objectives, a robust event-triggered attitude control algorithm is proposed to regulate the orientation of a flexible spacecraft subjected to parametric uncertainties, external disturbances, and vibrations due to flexible appendages. …"

A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation حسب Reem Tluli (22282702)

"…<p dir="ltr">In the realm of Emergency Medical Services (EMS), the integration of Machine Learning (ML) techniques has emerged as a catalyst for revolutionizing ambulance operations. ML algorithms could play a pivotal role in dynamically allocating resources, devising efficient routes, and predicting demand patterns. …"

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas حسب Marwan Dhuheir (19170898)

"…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …"

An Optimal Energy Dispatch Management System for Hybrid Power Plants: PV-Grid-Battery-Diesel Generator-Pumped Hydro Storage حسب Fatma Ahmed (11084787)

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …"

Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation حسب Zakaria Shams Siam (22048001)

Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks حسب Haris M. Khalid (17017743)

"…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …"

Brain Source Localization in the Presence of Leadfield Perturbations حسب Momin, Rabiya Nakhat

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Edge intelligence for network intrusion prevention in IoT ecosystem حسب Mansura, Habiba

"…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. …"
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Edge intelligence for network intrusion prevention in IoT ecosystem حسب Mansura Habiba (17808302)

"…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. …"

PERF solutions for distributed query optimization. (c1999) حسب Fany, Roula

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Adaptive controlled superconducting magnetic energy storage devices for performance enhancement of wind energy systems حسب Rania A., Turky

"…This research paper introduces the Generalized Continuous Mixed P-Norm Sub-Band Adaptive Filtering (GCMPNSAF) algorithm, designed for efficient online control of Superconducting Magnetic Energy Storage Devices (SMESDs) in Wind Energy Systems (WESs). …"
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Scan Test Cost and Power Reduction Through Systematic Scan Reconfiguration حسب Al-Yamani, A.

"…Using SAS, this paper also presents systematic scan reconfiguration, a test data compression algorithm that is applied to achieve 10times to 40 times compression ratios without requiring any information from the automatic-test-pattern-generation tool about the unspecified bits. …"
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