Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models by AL SHAMSI, ARWA AHMED

“…The study of thoughts, feelings, judgments, values, attitudes, and emotions regarding goods, services, organizations, persons, tasks, occasions, titles, and their attributes is known as sentiment analysis and it involves a polarity classification task for recognizing positive, negative, or neutral text to quantify what individuals believe using textual qualitative data. The rise of social media platforms provided an excellent source for sentiment analysis data. …”
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THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar by M. Walid Qoronfleh (14153088)

“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. …”

Copy number variations in the genome of the Qatari population by Khalid A. Fakhro (3158862)

“…Genotyping intensities and genome sequencing data from 97 Qataris were analyzed with four different algorithms and integrated to discover 16,660 high confidence CNV regions (CNVRs) in the total population, affecting ~28 Mb in the median Qatari genome. …”

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

“…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …”

Reconstruction and simulation of neocortical microcircuitry by Khazen, Georges

“…The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. …”
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Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review by Daksh Dave (17949239)

“…This review focuses on the diagnostic accuracy of AI-assisted mammography, synthesizing findings from studies across different clinical settings and algorithms. …”

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

“…Additionally, the GRU-CNN hybrid model attained a notable accuracy of 90%. These findings establish the robustness and effectiveness of hybrid architectures in enhancing emotion recognition accuracy in Arabic speech data, presenting a novel approach for Arabic dialect sentiment analysis.…”
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Study of the Impact of Land Use and Land Cover (LULC) Changes on local climate in Six Mega Global Cities in the 21st Century by Sabobeh, Lara Ali

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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…Based on publicly available datasets, several machine learning models are comprehensively analysed across different fingerprints and toolkits to find the best suitable models. Several dataset analysis models are utilised to study the data diversity. …”

Effective dispatch strategies assortment according to the effect of the operation for an islanded hybrid microgrid by Sk.A. Shezan (21323048)

“…Following the simulation data, load-following is the best dispatch mechanism for stand-alone microgrid architecture since it has the lowest LCOE and NPC.…”

LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications by Aldamani, Raghad

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Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) by AL SHOUBAKI, HAMZA YOUNIS

“…We discuss what would be the impact of our research findings on Arabic literature in particularly Arabic poetry. …”
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Nonlinear Friction Identification of A Linear Voice Coil DC Motor by Takrouri, Mohannad Hashem

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Iterative Methods for the Solution of a Steady State Biofilter Model by Salih, Mubarak Sahal

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A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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Developing a UAE-Based Disputes Prediction Model using Machine Learning by Abu Laila, Ibrahim Wasef Subhi

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Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study by Muhammad Atif Butt (10849980)

“…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …”

Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis by Jithin Kalathikudiyil Sreedharan (18268894)

“…It uses various models and algorithms to detect patterns and specific findings to diagnose a disease with utmost accuracy. …”