Deep learning-based modeling of land use/land cover changes impact on land surface temperature in Greater Amman Municipality, Jordan (1980–2030) by Khaled F. Alkaraki (22051967)

“…A set of maps for land cover, LST, Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and topography was integrated into the Cellular Automata-Artificial Neural Network (CA-ANN) and the Long-Short-Term Model (LSTM) models to predict the LULC and LST for 2030. …”

Experimental validation of numerical model for thermomechanical performance of material extrusion additive manufacturing process: Effect of infill design & density by Ans Al Rashid (14777050)

“…The numerical model predictions were validated via experiments performed under similar conditions. …”

3D GEOSTATISTICAL MODELING OF FACIES AND PETROPHYSICAL PROPERTIES OF THE UPPER KHARTAM OUTCROP OF KHUFF FORMATION, CENTRAL SAUDI ARABIA by Makkawi, Mohammad

“…Oolitic grainstones can contain significant hydrocarbon reserves. The heterogeneity in carbonate reservoir ascribes to the depositional and digenetic processes. …”
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Family resources, resilience beliefs, and parental adaptation: A moderated mediation analysis by Anis Ben Brik (19239442)

“…The present study aims to address this gap by exploring a moderated mediation model that predicts parental stress resulting from the accumulation of pandemic‐related stressors. …”

Strengthening of High Strength Reinforced Concrete Slabs with CFRP Laminates by Mahmoud, Hasan Saleh

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GAN-Based Data Augmentation for Fault Diagnosis and Prognosis of Rolling Bearings: A Literature Review by Md. Sulyman Islam Sifat (22928983)

“…The review further reveals that CNN models have been widely used, achieving accuracy rates exceeding 95% in fault diagnosis and prognosis. …”

Mitigating undercooling and overheating risk in existing desert schools under current and future climate using validated building simulation model by Mutasim Baba, Fuad

“…In Palestine and neighboring regions, buildings are constructed without insulation and mechanical heating and cooling systems, leading to significant thermal discomfort for occupants. To address this issue, the paper in troduces a robust methodology that utilizes a validated building simulation model (BSM) created based on hourly indoor air temperature to assess indoor thermal comfort during winter and summer seasons under both current and future climates. …”
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The impact of nozzle diameter and printing speed on geopolymer-based 3D-Printed concrete structures: Numerical modeling and experimental validation by Shoukat Alim Khan (14778226)

“…Nevertheless, the overall performance of the numerical model remains reliable in predicting the influence of printing parameters on buildability.…”

New model for estimating geometric tortuosity of variably saturated porous media using 3D synchrotron microcomputed tomography imaging by Zaher A. Jarrar (14779072)

“…Geometric tortuosity was directly determined from the 3D images using the centroids of the connected paths in the flow direction of the media, and multivariate nonlinear regression analysis was adopted to develop a simple practical model to predict tortuosity of variably saturated natural unconsolidated porous media. …”

Evaluating the impact of the COVID-19 pandemic on the geospatial distribution of buildings' carbon footprints associated with electricity consumption by Esmat, Zaidan

“…Additionally, the study evaluates the influence of the pandemic on the accuracy of CF model predictions by employing three distinct machine-learning models. …”
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Experimental Verification of Low-Pressure Kinetics Model for Direct Synthesis of Dimethyl Carbonate Over CeO₂ Catalyst by G. Ibrahim (7601063)

“…The investigation suggests that DMC formation in the direct synthetic route is a surface reaction of CO₂ and methanol on the catalyst. The kinetic model predictions closely aligned with experimental data, demonstrating a 17% mean absolute percentage error and indicating a high level of predictability. …”

Refractive Index of Engine‐Emitted Black Carbon and the Influence of Organic Coatings on Optical Properties by Dawei Hu (2186113)

“…In addition, organics were condensed onto BC to test optical models for coated particles. For BC particles coated with non‐absorbing organics, the extinction is predicted accurately by all models. …”

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat (22457821)

“…By 2090, a 44.56 % (range: 33–57.9 %) across the models, increase in suitable habitat is predicted, accompanied by a 27.66 % (range: 22.4–31.7 %) loss of current habitats. …”

Cloud-based deep learning-assisted system for diagnosis of sports injuries by Xiaoe Wu (17541951)

“…Using the metrics accuracy, precision, recall, and F1-score, the performance of the proposed model is assessed and compared with current models.…”

Navigating the Stock Market: The Role of State-of-the-Art Deep Learning Techniques by Anika Kanwal (18905377)

“…Additionally, our experiments demonstrated a 42–91% reduction in RMSE compared to standard CNN and GRU-based approaches, reflecting significantly improved prediction precision.</p><p dir="ltr">Implications</p><p dir="ltr">The results indicate that the hybrid Bidirectional GRU and CNN model is effective for precise stock price prediction, offering enhanced reliability for investment decision-making. …”

The impact of socio-economic factors on waste generation in the UAE by Daoud, Omar Walid Omar

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Secondary School Students’ Interest in STEM Careers in Qatar by Abdel Latif Sellami (16937031)

Critical Success Factors for Implementing Artificial Intelligence (AI) Projects in Dubai Government United Arab Emirates (UAE) Health Sector: Applying the Extended Technology Accep... by ALHASHMI, SHAIKHA ALI MOHSIN ALATTAR

“…Health care sector is one of the significant sectors they are focusing on and the planned (AI) projects of it is aiming to minimize chronic and early prediction of dangerous diseases affecting human beings. …”
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DiaNet v2 deep learning based method for diabetes diagnosis using retinal images by Hamada R. H. Al-Absi (16726299)

“…The aim of this study is to enhance diabetes diagnosis accuracy by developing an improved predictive model using retinal images from the Qatari population, addressing the limitations of current diagnostic methods. …”

Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…This research motivated by the unprecedented increase in diabetes and specifically Type 2 Diabetes Miletus (T2DM), proposes two significant contributions. The first is a comprehensive ML framework for the construction of diagnostic binary classification high accuracy models to predict T2DM in the United Arab Emirates based on STEPS style National Health Survey. …”
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