Electrical Engineering
Recent Submissions
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Machine learning-based prognostic model for 30-day mortality prediction in Sepsis-3
( BioMed Central Ltd , 2024 , Article)Background: Sepsis poses a critical threat to hospitalized patients, particularly those in the Intensive Care Unit (ICU). Rapid identification of Sepsis is crucial for improving survival rates. Machine learning techniques ... -
Automated grading of prenatal hydronephrosis severity from segmented kidney ultrasounds using deep learning
( Elsevier , 2024 , Article)Background and motivations: Antenatal or prenatal hydronephrosis (AHN) is a common kidney complication in unborn children. While AHN is generally benign and resolves over time, this condition can inflict serious kidney ... -
Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights
( BioMed Central Ltd , 2024 , Article)The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric ... -
Combating jamming attacks in multi-channel IoT networks using game theory
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2020 , Conference Paper)Jamming attacks are among the most widely used techniques to block and disturb legitimate communications. Several techniques are used in the literature to combat these attacks. However, most of them either require the ... -
IoT Anti-Jamming Strategy Using Game Theory and Neural Network
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2020 , Conference Paper)The internet of things (IoT) is one of the most exposed networks to attackers due to its widespread and its heterogeneity. In such networks, jamming attacks are widely used by malicious users to compromise the private and ... -
SRM power density improvement utilising rotor conducting screens and DC-link voltage boosting for EV applications
( John Wiley and Sons Inc , 2021 , Article)The power density enhancement of a four-phase switched reluctance motor using rotor conducting screens and DC-link voltage boosting for electric vehicle applications is studied. The effect of conducting screen thickness ... -
A Comprehensive Review of Lithium-Ion Batteries Modeling, and State of Health and Remaining Useful Lifetime Prediction
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)According to the United States environmental protection agency (EPA), every burned gallon of gasoline generates 8.87 Kg of CO2. The pollution created by vehicles' fuel consumption has been one of the primary sources of ... -
A New Torque Ripple Minimization Approach for Switched Reluctance Drives
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)This paper presents a new torque control function for torque ripple reduction in switched reluctance drives. The approach is based on the maximum utilization of available dc link voltage, extending the zero torque-ripple ... -
An Intelligent Two-Stage Energy Dispatch Management System for Hybrid Power Plants: Impact of Machine Learning Deployment
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)The utilization of renewable energy sources such as PV and wind power has become imperative due to the increase of carbon dioxide emissions, which leads to the increase in global temperature and the negative consequences ... -
Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)The intermittent non-dispatchable power produced by Renewable Energy Sources (RESs) in distribution networks caused additional challenges in load forecasting due to the introduced uncertainties. Therefore, high-quality ... -
Power Density Improvement Due To Rotor Flux Screens In An Srm With A Higher Number Of Rotor Poles Than Stator Poles
( Academy Publishing Center, Arab Academy for Science, Technology and Maritime Transport , 2023 , Article)This paper studies the performance of screened switched reluctance motors (SRMs) with a number of rotor poles higher than the number of stator poles. Flux (conducting) screens are electrically conducting, non-magnetic ... -
AI-Assisted RLF Avoidance for Smart EN-DC Activation
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)In the first phase of 5G network deployment, User Equipment (UE) will camp traditionally on LTE network. Later on, if the UE requests a 5G service, it will be made to camp simultaneously on LTE and 5G. This dual-camping ... -
Machine Learning Aided Holistic Handover Optimization for Emerging Networks
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)In the wake of network densification and multi-band operation in emerging cellular networks, mobility and handover management is becoming a major bottleneck. The problem is further aggravated by the fact that holistic ... -
Data Driven Optimization of Inter-Frequency Mobility Parameters for Emerging Multi-band Networks
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Densification and multi-band operation in 5G and beyond pose an unprecedented challenge for mobility management, particularly for inter-frequency handovers. The challenge is aggravated by the fact that the impact of key ... -
Deep Learning-based Framework for Multi-Fault Diagnosis in Self-Healing Cellular Networks
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)Fault diagnosis is turning out to be an intense challenge due to the increasing complexity of the emerging cellular networks. The root-cause analysis of coverage-related network anomalies is traditionally carried out by ... -
Enhanced MDT-based performance estimation for ai driven optimization in future cellular networks
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Minimization of drive test (MDT) allows coverage estimation at a base station by leveraging measurement reports gathered at the user equipment (UE) without the need for drive tests. Therefore, MDT is a key enabling feature ... -
A Data-Driven Self-Optimization Solution for Inter-Frequency Mobility Parameters in Emerging Networks
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Densification and multi-band operation means inter-frequency handovers can become a bottleneck for mobile user experience in emerging cellular networks. The challenge is aggravated by the fact that there does not exist a ... -
A Data-Driven Framework for Inter-Frequency Handover Failure Prediction and Mitigation
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)With 5G already deployed, challenges related to handover exacerbate due to the dense base station deployment operating on a motley of frequencies. In this paper, we present and evaluate a novel data-driven solution, to ... -
A Hybrid Deep Learning-Based (HYDRA) Framework for Multifault Diagnosis Using Sparse MDT Reports
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Diminishing viability of manual fault diagnosis in the increasingly complex emerging cellular network has motivated research towards artificial intelligence (AI)-based fault diagnosis using the minimization of drive test ... -
D-RAN: A DRL-Based Demand-Driven Elastic User-Centric RAN Optimization for 6G & Beyond
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)With highly heterogeneous application requirements, 6G and beyond cellular networks are expected to be demand-driven, elastic, user-centric, and capable of supporting multiple services. A redesign of the one-size-fits-all ...
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