Comparison between the American code ASCE7-16 and the Australian code AS1170.4 against the seismic design effects by AL-OBAIDI, ALI

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Deep learning-based beat-to-beat arterial blood pressure estimation using distant radar signals by Farhana Ahmed Chowdhury (22564808)

“…While traditional cuff-based approaches are non-invasive, they have limitations in providing continuous blood pressure monitoring. …”

The Prevalence and Genetic Spectrum of Familial Hypercholesterolemia in Qatar Based on Whole Genome Sequencing of 14,000 Subjects by Ilhame Diboun (3522413)

“…This pioneering study provides a reliable estimate of FH prevalence in Qatar based on a significantly large population-based cohort, whilst uncovering the spectrum of genetic variants associated with FH.…”

Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection by Mamun Or Rashid (21976373)

“…Our approach significantly outperformed state-of-the-art methods in terms of classification accuracy. …”

Provision of bystander CPR for out-of-hospital cardiac arrest in the Middle East: a retrospective gender-based analysis by Emad Awad (17541264)

Modelling, analysis, and implementation of a switched‐inductor based DC/DC converter with reduced switch current stress by Shima Sadaf (16875999)

MACGAN: An All-in-One Image Restoration Under Adverse Conditions Using Multidomain Attention-Based Conditional GAN by Maria Siddiqua (17949149)

“…<p dir="ltr">Various vision-based tasks suffer from inaccurate navigation and poor performance due to inevitable problems, such as adverse weather conditions like haze, fog, rain, snow, and clouds affecting ground and aerial navigation, as well as underwater images being degraded with blue-green tones and mud affecting marine navigation. …”

Deep Learning-Based Classification of Chest Diseases Using X-rays, CT Scans, and Cough Sound Images by Hassaan Malik (10486121)

“…Thus, the proposed DCDD_Net model can provide significant assistance to radiologists and medical experts. …”

A Diffusion-Based Probabilistic Ultra-Short-Term Solar Power Prediction Using the Sky Image Sequences by Razieh Rastgoo (22457767)

“…<p dir="ltr">The inherently unpredictable nature of solar power generation, primarily due to rapidly changing cloud cover, poses a significant challenge to the operation of solar-integrated energy systems. …”

Analysis of mode choice affects from the introduction of Doha Metro using machine learning and statistical analysis by Ammar Abulibdeh (15785928)

“…Revealed preference (RP) and stated preference (SP) survey questionnaires were designed to collect the necessary data. …”

Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles by Zainab Akhtar (15192184)

“…Subsequently, a sliding mode controller is designed based on the observed states to track the reference trajectories. …”

Safety and efficacy of chimeric antigen receptor T-cell therapy for acute myeloid leukemia: A subgroup based meta-analysis by Mahmoud M. Morsy (18560491)

“…<h3>Introduction</h3><p dir="ltr">Acute myeloid leukemia (AML) is a significant hematological malignancy in the United States, with a high mortality rate and limited treatment options. …”

A Multi-Feature Based Approach Incorporating Variable Thresholds for Detecting Price Spikes in the National Electricity Market of Australia by Dao H. Vu (19570225)

“…In this paper, a multi-feature based approach with the incorporation of variable thresholds is developed to detect electricity price spikes in the national electricity market of Australia. …”

Exploration and analysis of On-Surface and In-Air handwriting attributes to improve dysgraphia disorder diagnosis in children based on machine learning methods by Jayakanth, Kunhoth

“…Evaluation in a publicly available dataset indicates that the AdaBoost classifier achieved a classification accuracy of 80.8%, which is 1.3% more than the state-of-the-art method. Moreover, a deep analysis of different characteristics (kinematic, dynamic, temporal, spatial, etc.) of online handwriting is conducted to examine their significance in distinguishing normal and abnormal handwritten data. …”
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Exploration and analysis of On-Surface and In-Air handwriting attributes to improve dysgraphia disorder diagnosis in children based on machine learning methods by Jayakanth Kunhoth (14158908)

“…Evaluation in a publicly available dataset indicates that the AdaBoost classifier achieved a classification accuracy of 80.8%, which is 1.3% more than the state-of-the-art method. Moreover, a deep analysis of different characteristics (kinematic, dynamic, temporal, spatial, etc.) of online handwriting is conducted to examine their significance in distinguishing normal and abnormal handwritten data. …”

A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by Krishnamoorthy Natarajan (22047464)

Ultra high gain step up DC/DC converter based on switched inductor and improved voltage lift technique for high‐voltage applications by Shahrukh Khan (13791895)

Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

“…<p dir="ltr">This paper proposes a pattern recognition model to develop clusters of homogenous activities for blue-collar workers in the State of Qatar. The activity-based data from the travel diary of 1051 blue-collar workers collected by the Ministry of Transportation and Communication (MoTC) in Qatar was used for analysis. …”

A Novel Hybrid Physical-Layer Authentication Scheme for Multiuser Wireless Communication Systems by Elmehdi Illi (19368673)

“…In this article, an enhanced hybrid channel/device-based physical-layer authentication (PLA) scheme is proposed. …”

Parametric investigation and optimisation of mechanical properties of thick tri-material based composite of PLA-PETG-ABS 3D-printed using fused filament fabrication by Imran Khan (109715)

“…An analysis of variance (ANOVA) was also performed to check the significance of FFF process parameters. The results concluded that the selected FFF process parameters were significant in the interaction state of both tensile properties. …”