Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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Towards Multimedia Fragmentation by Saad, Samir

“…Database fragmentation is a process for reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. …”
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An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
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An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic Algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
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Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

“…Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

“…<p dir="ltr">Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”

Real-Time Implementation of GPS Aided Low Cost Strapdown Inertial Navigation System by Sahawneh, Laith Rasmi

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An XML Document Comparison Framework by Tekli, Joe

“…As the Web continues to grow and evolve, more and more information is being placed in structurally rich documents, XML documents in particular, so as to improve the efficiency of similarity clustering, information retrieval and data management applications. Various algorithms for comparing hierarchically structured data, e.g., XML documents, have been proposed in the literature. …”
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A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics by Tekli, Joe

“…XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. …”
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Accelerating Blockchain Transaction Verification With Parallel Computing by Zhou, Huangjin

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Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…Cyberbullying involves the use of communication technology and data, including messages, photographs, and videos, to undertake aggressive negative actions to harm others. …”
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Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

“…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER⁺), HER2⁺, ER⁺HER2⁺, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …”

LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…Currently, it is difficult to classify cancers using microarray data. Nearly many data mining techniques have failed because of the small sample size, which has become more critical for organizations. …”

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”

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. …”

Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

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The Impact of AI on Decision-Making in Educational Management: Benefits, Risks, and Ethical Concerns by JA’AROUN, WAED YOUSEF

“…However, the adoption of AI also presents challenges, including potential biases in algorithms, privacy concerns, and the risk of an over-reliance on automated systems. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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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. Since the introduction of the Lee sigma filter in 1980, the various versions of the minimum mean square error (MMSE) filter were developed, focusing essentially on how to estimate the processed pixels. …”
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