Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... by BACHIR, HIBAH AHMAD

“…Findings referred these barriers to limited teacher training, technological accessibility, and data privacy concerns, as well as ethical biases in AI algorithms. …”
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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

“…Future research should focus on refining algorithms, ensuring real‐time adaptability, addressing ethical considerations, evaluating long‐term patient outcomes, fostering cooperative systems, and integrating relevant data and policies within the healthcare framework.…”

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

“…<p dir="ltr">Electroencephalogram (EEG) signals suffer substantially from motion artifacts when recorded in ambulatory settings utilizing wearable sensors. 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. …”

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. …”

Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges by Muhammad Mohsin Khan (22303366)

“…Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. …”

SemIndex: Semantic-Aware Inverted Index by Chbeir, Richard

“…We provide here a new approach, called SemIndex, that extends the standard inverted index by constructing a tight coupling inverted index graph that combines two main resources: a general purpose semantic network, and a standard inverted index on a collection of textual data. We also provide an extended query model and related processing algorithms with the help of SemIndex. …”
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Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review by Rehaan Hussain (22302742)

“…In current literature, there are a number of papers that address all these faults using different methods, and this paper compiles the information from the written works for ease of access. Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”

PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits by Hind Almerekhi (7434776)

“…Implications are that toxicity trigger detection algorithms can leverage generic approaches but must also tailor detections to specific communities.…”

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

“…<p dir="ltr">Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”

Automatic White Blood Cell Differential Classification by Al-Muhairy, Juma A. Bin Darwish

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Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR) by Elaine Beller (44602)

“…Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. …”

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

“…The class imbalance issue was handled through multiple data augmentation methods to overcome the biases. …”

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…Potentially disregarded age-related ECG variations may result from skewed age data in training sets. ECG patterns are affected by physiological differences between the sexes; a dataset that is inclined toward one sex may compromise the accuracy of the others. …”

Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…</p><h3>Methods</h3><p dir="ltr">We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. …”

The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation by Getahun, Fekade

“…We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. …”
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Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter by Yahia, Mohamed

“…The recent advancement in synthetic aperture radar (SAR) technology has enabled high-resolution imaging capability that calls for efficient speckle filtering algorithms to preprocess radar imagery. …”
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Localizing-ground Transmitters Using Airborne Antenna Array by Daffalla, Mirghani Moutaman

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