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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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 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. …”

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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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. …”

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

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. …”

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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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. …”

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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DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor by Maen Takruri (10873368)

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

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

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

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

Using Data Mining in CRM to Understand the Insurance Market by Qadadeh, Wafa

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Big Data Energy Management, Analytics and Visualization for Residential Areas by Gupta, Ragini

“…Utilizing the same common communication infrastructure, it also allows the utilities on different consumption levels (community, state, country) to monitor and visualize the energy consumption in their respective grid segments on daily, monthly, and yearly basis. A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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