Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”

K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation by Ashhadul Islam (16869981)

“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”

Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”

Public Administration Studies: The Digital Trajectory by " (19517680)

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Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

“…We show how our algorithm supports the definition of a budget for alignment computation and also augment it with strategies for meta-heuristic optimization and pruning of the search space. …”
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KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”

A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights by Malekloo, Arman

“…A detailed analysis of the ML pipelines is provided, and the in-demand methods and algorithms are summarized in augmentative tables and figures. …”
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Privacy-Preserving Framework for Blockchain-Based Stock Exchange Platform by Hamed Al-Shaibani (19497412)

“…Furthermore, to assess the overhead of the proposed privacy algorithms on the trading execution time, we conduct several experiments considering different anonymity levels <i>k</i> . …”

Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations by Mueen Uddin (4903510)

“…<p dir="ltr">Cyber threats are increasingly frequent in today’s world, posing challenges for organizations and individuals to protect their data from cybercriminals. On the other hand, Generative Artificial Intelligence (GAI) technology offers an efficient way to automatically address these issues with the help of AI models and algorithms. …”

Can AI Help in Screening Viral and COVID-19 Pneumonia? by Muhammad E. H. Chowdhury (14150526)

Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

“…After selecting the most appropriate lattice map (32 × 32) in 750,000 iterations using SOMs, the data points below the dark blue region are mapped onto the data frame to get the videos. …”

Exploring Digital Competitiveness through Bayesian Belief Networks by Qazi, Abroon

“…Three states were assigned to variables—low, medium, and high performance—and the tree augmented naive Bayes (TAN) algorithm was applied to model interdependencies. …”
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A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”

Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care by Regina Padmanabhan (14231606)

“…Other highlights are (1) a novel set of easily available features for the prediction of the aforementioned clinical complications and (2) the use of data augmentation methods and model-scoring-based hyperparameter tuning to address the problem of class disproportionality, a common challenge in medical datasets and often the reason behind poor event prediction rate of various predictive models reported so far. …”

Deepfakes Signatures Detection in the Handcrafted Features Space by Hamadene, Assia

“…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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