A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…In step 3, after filtering out non-grassland pixels, the performance of RF, SVM, and GTB classifiers was evaluated with combined S1 and S2 data to distinguish different grassland types. …”
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BESS-Set: A Dataset for Cybersecurity Monitoring in a Battery Energy Storage System by Giovanni Battista Gaggero, Alessandro Armellin, Giulio Ferro, Michela Robba, Paola Girdinio, Mario Marchese

“…In this context, there is a need to develop datasets of attacks on these systems to evaluate the risks and allow researchers to develop proper monitoring algorithms. …”
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Consumer Happiness in the Purchase of Electric Vehicles: a Fuzzy Logic Model by Fernando Lámbarry-Vilchis, Aboud Barsekh Onji, Leticia Refugio Chavarría López, Paola Judith Maldonado Colín

“…This research was conducted using a fuzzy Delphi method survey targeting a specific consumer group and two fuzzy inference systems: a multi-input single-output FIS model and an FIS Tree employing a hierarchical fuzzy inference structure, which leverages the survey's training data to optimize the models using different machine learning algorithms. The FIS tree model demonstrated superior efficacy in predicting the consumer satisfaction index, achieving an average forecast error of 0.65%. …”
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Forest cover restoration analysis using remote sensing and machine learning in central Malawi by Jabulani Nyengere, Precious Masuku, Sylvester Chikabvumbwa, Weston Mwase, Msaiwale Kathewera, Allena Laura Njala, Wilson Tchongwe, Isaac Tchuwa, Tiwonge I Mzumara, Chikondi Chisenga, Wilfred Kadewa, Emmanuel Chinkaka, Harineck Tholo

“…Utilizing a Support Vector Machine (SVM) classification algorithm applied to time-series Landsat and high-resolution imagery (2003–2023), we quantify land cover changes, while Normalized Difference Vegetation Index (NDVI) trends serve as indicators of ecological recovery. …”
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Do Calibrated Recommendations Affect Explanations? A Study on Post-Hoc Adjustments by Paul Dany Flores Atauchi, André Levi Zanon, Leonardo Chaves Dutra da Rocha, Marcelo Garcia Manzato

“…Our study investigates two key research gaps: (1) the impact of graph embeddings in model-agnostic knowledge graph explanations, exploring their under-researched potential compared to syntactic approaches to produce meaningful explanations; and (2) the effect of calibration on recommendation explanations, assessing whether calibrated recommendation reordering influences the outcomes of explanation algorithms. We evaluate the quality of explanations using a set of metrics, such as diversity, which measures how well different interests of the user are covered; popularity, which assesses how well explanations avoid favoring already popular items; and recency, which examines the inclusion of recently interacted items. …”
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Deep reinforcement learning for inverse inorganic materials design by Christopher Karpovich, Elton Pan, Elsa A. Olivetti

“…This work isolates and evaluates the effects of different RL methodologies to suggest promising, valid compounds of interest by exploring the chemical design space for materials discovery.…”
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Language task-based fMRI analysis using machine learning and deep learning by Elaine Kuan, Elaine Kuan, Elaine Kuan, Viktor Vegh, Viktor Vegh, Viktor Vegh, John Phamnguyen, John Phamnguyen, John Phamnguyen, Kieran O’Brien, Amanda Hammond, David Reutens, David Reutens, David Reutens, David Reutens

“…Their analysis necessitates the use of alternative methods such as machine learning (ML) and deep learning (DL) because task regressors may be difficult to define in these paradigms.MethodsUsing task-based language fMRI as a starting point, this study investigates the use of different categories of ML and DL algorithms to identify brain regions subserving language. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Three (3) classification algorithms including Random Forest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) were trained using the QoS dataset and then evaluated in order to determine the most effective model based on certain evaluation metrics – accuracy, precision, F1-Score and recall. …”
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Enhancing Security of Error Correction in Quantum Key Distribution Using Tree Parity Machine Update Rule Randomization by Bartłomiej Gdowski, Miralem Mehic, Marcin Niemiec

“…A series of simulations were conducted to evaluate the security implications under various configurations, including different values of K, N, and L parameters of neural networks. …”
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Explainable Model Prediction of Memristor by Sruthi Pallathuvalappil, Rahul Kottappuzhackal, Alex James

“…The accuracy, macro average, and weighted average of both algorithms at different operational frequencies are explored.…”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Results We introduce novel acquisition functions for experiment design in gene expression data, leveraging active learning in both Essential Graph and Graphical Model spaces. We evaluate scalable structure learning algorithms within an active learning framework to optimize intervention selection. …”
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Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…Despite significant advancements in this area, a comprehensive comparison of these algorithms across different deep learning architectures remains lacking. …”
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A Comparative Study of Breast Cancer Detection and Recurrence Prediction Using CatBoost Classifier by Rana Dhia’a Abdu-aljabar, Khansaa Dheya Aljafaar, Zinah Jaffar Mohammed Ameen, Hala A. Naman

“…Among all algorithms examined, CatBoost stood out, showcasing AUC values above 98 %, 90 %, and 83% on different datasets. …”
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An Experimental Study of GPR Near-Field Problem in Depth Ranging of Buried Objects by Rex Yui Kei Cham, Wallace Wai Lok Lai

“…Two different velocity algorithms, based on semi- and full-trilaterated ray paths, were applied to estimate the wave travelling velocity as a prerequisite of cover depth measurement. …”
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Comparison of Machine Learning and Statistical Approaches of Detecting Anomalies Using a Simulation Study by Klaudia Lenart

“…The effectiveness of each method was evaluated based on measures of classification model performance. …”
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Unveiling psychobiological correlates in primary Sjögren’s syndrome: a machine learning approach to determinants of disease burden by László V. Módis, László V. Módis, András Matuz, András Matuz, Zsófia Aradi, Ildikó Fanny Horváth, Antónia Szántó, Antal Bugán

“…This study aimed to evaluate the predictive weight of different factors in determining both objective and subjective disease burden using machine learning (ML) models.Methods117 pSS patients, whose biological (blood cell counts, complement activity, IgG, RF, SSA, SSB), psychological (personality traits, depression, anxiety, basic self-esteem assessed via self-reported questionnaires), and social (socioeconomic status and social support) measures were collected in a composite database. …”
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Multi-dimensional sleep health and dementia risk: a prospective study in the UK Biobank by Tianyi Huang, May A. Beydoun, Sina Kianersi, Susan Redline, Lenore J. Launer

“…Incident dementia was identified using validated algorithms through primary care, hospital admissions, or death records through 2022. …”
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Comprehensive analysis of total knee arthroplasty kinematics and functional recovery: Exploring full-body gait deviations in patients with knee osteoarthritis. by Xavier Gasparutto, Alice Bonnefoy-Mazure, Michael Attias, Katia Turcot, Stéphane Armand, Hermès H Miozzari

“…The knee was excluded from classification to focus on full-body kinematics. Differences between groups, with controls, as well as before and after surgery were evaluated for patients reported outcome measures, kinematic features, and spatio-temporal parameters. …”
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A Review of Recipe Recommendation Methods by Yao Wu, Ling Kang, Quan Guo, Lei Zhao

“…Secondly, it examines the sub-methods associated with each category of research methodologies while evaluating the technical advantages and limitations inherent in different approaches. …”
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Gut microbiome composition changes in obstructive sleep apnoea syndrome also in relation to excessive daytime sleepiness by Mariana Fernandes, Orazio Palmieri, Stefano Castellana, Matteo Spanetta, Tiziana Latiano, Clementina Lupo, Claudia De Masi, Christian Cardile, Carmen Calvello, Francesca Izzi, Fabio Placidi, Tommaso Mazza, Nicola Biagio Mercuri, Anna Latiano, Claudio Liguori

“…Composition, community diversity, differences in taxa abundance profiles and sample dysbiosis were evaluated through 16S metagenomics and multiple bioinformatics algorithms. …”
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