How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

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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. …”

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

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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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Damage assessment & recovery from malicious transactions using data dependency for deffensive information warfare. (c2006) by Zeitunlian, Arda

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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. …”

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

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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. …”

Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem by Assaker, Guy

“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
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A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model by Md. Nazmul Islam Shuzan (16888827)

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An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

“…We use an ant colony optimization algorithm in the adaptation process. The approach is validated on stability of classes in object-oriented software systems and can easily be used for any other software quality characteristic. …”
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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. …”

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. …”

Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…The automatic segmentation algorithm is adopted to extract the region of interest, and subsequently morphological and texture features are computed. …”

Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions by Liu, Wenpeng

“…This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole.…”
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DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor by Maen Takruri (10873368)

A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…Particularly, we present a novel non-sequential multi-pretraining U-Net architecture and demonstrate that employing a number of persistent parallel models can boost the effectiveness of the segmentation procedures. The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”

VEGAWES: variational segmentation on whole exome sequencing for copy number detection by Samreen Anjum (19651882)

“…In this work, we developed VEGAWES for accurate and robust detection of copy number variations on WES data. VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data. …”

Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection by Serkan Kiranyaz (3762058)

Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)