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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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. …”

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.…”

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

“…A model's performance is impacted when diverse demographics are inadequately represented. …”

Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

“…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”

A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

“…LR DoS attacks are difficult to detect as their attack signature is similar to benign network traffic. The existing AI-based detection algorithms in the literature are signature-based, and their efficacy in detecting unknown LR DoS attacks was not explored. …”

Accelerating Blockchain Transaction Verification With Parallel Computing by Zhou, Huangjin

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Identification of phantom movements with an ensemble learning approach by Akhan Akbulut (17380285)

“…Our study demonstrated that the ensemble learning-based models resulted in higher accuracy in the detection of phantom movements. …”

Efficient XML Structural Similarity Detection using Sub-tree Commonalities by Tekli, Joe

“…Various algorithms for comparing hierarchically structured data, e.g. …”
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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. …”

Systematic reviews in sentiment analysis: a tertiary study by Alexander Ligthart (14150871)

“…Different features, algorithms, and datasets used in sentiment analysis models are mapped. …”

Comparative Study on Arabic Text Classification: Challenges and Opportunities by Abualigah, Laith

“…This paper presents a comparative study based on a list of chosen published papers that focus on improving Arabic text classifications, to highlight the given models and the used classifiers besides discussing the faced challenges in these types of researches, then this paper proposes the expected research opportunities in the field of text classification research. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. …”
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Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks by Mohammed Almehdhar (22046597)

“…Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. …”

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. …”

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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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

“…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …”
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Radar Pulse Interleaving For Multi-Target Tracking by Elshafei, M.

“…In this paper, we present new tight 0-1 integer programming models for the radar pulse interleaving problem and develop effective solution methods based on Lagrangian relaxation techniques.…”
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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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