Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study by Maik JM Beuken, Melanie Kleynen, Susy Braun, Kees Van Berkel, Carla van der Kallen, Annemarie Koster, Hans Bosma, Tos TJM Berendschot, Alfons JHM Houben, Nicole Dukers-Muijrers, Joop P van den Bergh, Abraham A Kroon, Iris M Kanera

“…For cluster 3 (n=1149), the most significant continuous variable was overall higher cognitive functioning (mean 0.2349, SD 0.5702 vs mean –0.3088, SD 0.7212; P<.001), and educational level was the most significant categorical variable (P<.001). …”
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Grid-Connected Solar PV System with Maximum Power Point Tracking and Battery Energy Storage Integrated with Sophisticated Three-Level NPC Inverter by D. Ravi Kishore, T. Vijay Muni, B. Srinivas Raja, Mukesh Pushkarna, B. Srikanth Goud, Kareem M. AboRas, Sadam Alphonse

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Reliability analysis of landing gear operation based on improved support vector machine-based decomposed-coordinated by ZHANG Lei, CHEN Junyu, FENG Jun, FENG Yunwen, LIU Lei

“…The improved support vector machine aims to optimize the performance of the limit state function in each sub-mathematical model by applying multi-stage adaptive point position control of hyperparameters. …”
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Multi-objective Optimization of Staggered Tube Banks in Cross-flow Using Machine Learning and Genetic Algorithm by A. Tamanaei, F. Kowsary, S. Sahamifar, F. Samadi

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Integrated Machine Learning and Region Growing Algorithms for Enhanced Concrete Crack Detection: A Novel Approach by Wenxuan Yao, Hui Li, Yanlin Li

“…The region growth algorithm is used to expand the threshold from the seed points of the image to obtain the crack recognition results. …”
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Revealing Spatiotemporal Urban Activity Patterns: A Machine Learning Study Using Google Popular Times by Mikel Barrena-Herrán, Itziar Modrego-Monforte, Olatz Grijalba

“…This study presents a methodology for analyzing the spatiotemporal use of cities and identifying occupancy patterns taking into consideration urban form and function. The analysis relies on data obtained from Google Popular Times (GPT), transforming the relative occupancy of a large number of points of interest (POI) classified into five categories, for estimating the number of people aggregated within urban nodes during a typical day. …”
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Assessing the accuracy of a machine learning prediction for 2 different shoulder prostheses: an external validation study by Gianluca Caprili, MD, Andrea G. Calamita, MD, Michele Novi, MD, Domenico A. Campanacci, MD, PhD, Simone Nicoletti, MD

“…Background: The integration of machine learning in orthopedic surgery, including shoulder procedures, has garnered increasing interest. …”
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A systematic review on machine learning-aided design of engineered biochar for soil and water contaminant removal by Yunpeng Ge, Kaiyang Ying, Guo Yu, Muhammad Ubaid Ali, Abubakr M. Idris, Abubakr M. Idris, Asfandyar Shahab, Habib Ullah, Habib Ullah

“…For adsorption, surface area and pore volume are distinctly important; in redox reactions for heavy metal removal, functional groups like C-O and C=O play vital roles. …”
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Machine learning-enabled multiscale modeling platform for damage sensing digital twin in piezoelectric composite structures by Somnath Ghosh, Saikat Dan, Preetam Tarafder

“…The DT framework consists of a two-step computational process integrating multiscale-multiphysics modeling with machine learning (ML) tools to detect damage progression in the piezoelectric composite structure using electrical signal measurements at a few surface points. …”
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Machine learning-based radiomics prognostic model for patients with proximal esophageal cancer after definitive chemoradiotherapy by Linrui Li, Zhihui Qin, Juan Bo, Jiaru Hu, Yu Zhang, Liting Qian, Jiangning Dong

“…Radiomics models were established by five machine learning approaches. The optimal radiomics model was selected using receiver operating curve analysis. …”
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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…By predicting vector functions from vector input features, we effectively reduced prediction errors. …”
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Machine Learning-Based VO₂ Estimation Using a Wearable Multiwavelength Photoplethysmography Device by Chin-To Hsiao, Carl Tong, Gerard L. Coté

“…This study presents a novel wrist-worn multiwavelength photoplethysmography (PPG) device and machine learning algorithm designed to estimate VO₂ continuously. …”
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Colorimetric Biosensors: Advancements in Nanomaterials and Cutting-Edge Detection Strategies by Yubeen Lee, Izzati Haizan, Sang Baek Sim, Jin-Ha Choi

“…In order to enhance the color change reactions in colorimetric techniques, functional nanomaterials are often integrated due to their desirable intrinsic properties. …”
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Modeling functional connectivity with learning and memory in a mouse model of Alzheimer's disease by Lindsay Fadel, Elizabeth Hipskind, Steen E. Pedersen, Jonathan Romero, Caitlyn Ortiz, Caitlyn Ortiz, Eric Shin, Md Abul Hassan Samee, Robia G. Pautler, Robia G. Pautler, Robia G. Pautler

“…IntroductionFunctional connectivity (FC) is a metric of how different brain regions interact with each other. …”
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Design and Development of a Bespoke Rotary Friction Welding Machine in Exploration of Joining Dissimilar Materials for Nuclear Applications by Michail Dellepiane, Laurie Da Silva, Athanasios Toumpis

“…However, access to expensive and complex industrial-grade friction welding machines is not always possible. This study explores the design process and functionality of a laboratory-scale friction welding setup following the fundamentals of large-scale machinery. …”
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Clinical Characterization of Patients with Syncope of Unclear Cause Using Unsupervised Machine-Learning Tools: A Pilot Study by María-José Muñoz-Martínez, Manuel Casal-Guisande, María Torres-Durán, Bernardo Sopeña, Alberto Fernández-Villar

“…The number of clusters was determined through cost function analysis and silhouette index, and visual validation was performed using UMAP. …”
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Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…This research aims to compare the key machine learning approaches, Namely Support Vector Machines (SVM), Random Forest (RF) and Decision Trees (DT), in their ability to classify Intrusion Detection Systems (IDS) via routing networks over distributed computing systems. …”
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Application of microscopic smartphone attachment for remote preoperative lab testing by Kefan Song, Kefan Song, Alexander T. Adams, Alexander T. Adams

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Variational Quantum Circuit-Based Quantum Machine Learning Approach for Predicting Corrosion Inhibition Efficiency of Expired Pharmaceuticals by Muhamad Akrom, Muhammad Reesa Rosyid, Lubna Mawaddah, Akbar Priyo Santosa

“…This study examines the potential of quantum machine learning (QML) to predict the corrosion inhibition capacity of expired pharmaceutical compounds. …”
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Documenting the Production Process of Faba bean (Vicia faba L.) in Gorgan, Ali Abadkatol and Aqqola Regions by Mohammad Reza Mansouri Vajari, Ebrahim Zeinali, Afshin Soltani, Benjamin Torabi, Alireza Nehbandani

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