Automated long-term monitoring of stereotypical movement in polar bears under human care using machine learning by Matthias Zuerl, Philip Stoll, Ingrid Brehm, Jonas Sueskind, René Raab, Jan Petermann, Dario Zanca, Ralph Simon, Lorenzo von Fersen, Bjoern Eskofier

“…Finally, we classified the trajectory patterns as SB or normal behaviour using a lightweight random forest approach with an accuracy of 94.9 %. …”
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Non-Invasive Fatigue Detection and Human–Machine Interaction Using LSTM and Multimodal AI: A Case Study by Muon Ha, Yulia Shichkina, Xuan-Hien Nguyen

“…The system analyzes eye blink patterns and facial expression changes captured through a webcam, achieving an accuracy of 92.35% on the UTA-RLDD dataset. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…Seasonal wind speed analysis revealed distinct patterns, with winter emerging as the most efficient season for wind, featuring a median wind speed of 7.96 m/s. …”
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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

“…Consequently, the new pattern, PSLG, was selected for predicting MRI behavior.…”
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A Comparative Analysis of Support Vector Machine and K-Nearest Neighbors Models for Network Attack Traffic Detection by Han Zhuoxi

“…This research centers on the use of advanced machine learning methods, particularly Support Vector Machines (SVM) and K-Nearest Neighbors (KNN), to improve the detection of network attack traffic. …”
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Comprehensive Framework for Leak Detection in Water Distribution Systems: A Vibration Signal Processing and Machine LEARNING Approach by Hayder Wthaij, Ajeel Al Ghasheem

“…These features enable capturing the specific vibration patterns of diverse leaks, ‎allowing for accurate identification. …”
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Creating a diagnostic assessment model for autism spectrum disorder by differentiating lexicogrammatical choices through machine learning. by Sumi Kato, Kazuaki Hanawa, Manabu Saito, Kazuhiko Nakamura

“…This approach suggests the possibility of using natural language processing to detect distinctive linguistic patterns in AS, aiming to enhance diagnostic accuracy for differentiating AS from non-AS in adolescents and adults.…”
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Support Vector and Linear Regression Machine Learning Model on Amperometric Signals to Predict Glucose Concentration and Hematocrit Volume by Kirti Sharma, Pawan K. Tiwari, Sanjay Kumar Sinha

“…The emergence of advanced machine learning tools and techniques, subsequent to a substantial evolution in data mining strategies, has bestowed the capacity to glean insights and discern concealed patterns from vast datasets, thus enabling extensive analytical pursuits. …”
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A Machine Learning Model for Procurement of Secondary Reserve Capacity in Power Systems with Significant vRES Penetrations by João Passagem dos Santos, Hugo Algarvio

“…Benchmark and test data are from the year 2024. Different machine learning architectures have been tested, but a Fully Connected Neural Network (FCNN) has the best results. …”
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Integrating Machine Learning and Digital Twins for Enhanced Smart Building Operation and Energy Management: A Systematic Review by Bruno Palley, João Poças Martins, Hermano Bernardo, Rosaldo Rossetti

“…Artificial Intelligence has recently expanded across various applications. Machine Learning, a subset of Artificial Intelligence, is a powerful technique for identifying patterns in data to support decision making and managing the increasing volume of information. …”
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Reservoir Inflow Prediction under GCM Scenario Downscaled by Wavelet Transform and Support Vector Machine Hybrid Models by Gusfan Halik, Nadjadji Anwar, Budi Santosa, Edijatno

“…Climate change has significant impacts on changing precipitation patterns causing the variation of the reservoir inflow. …”
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An optical brain-machine interface reveals a causal role of posterior parietal cortex in goal-directed navigation by Ethan Sorrell, Daniel E. Wilson, Michael E. Rule, Helen Yang, Fulvio Forni, Christopher D. Harvey, Timothy O’Leary

“…We develop a calcium-imaging-based brain-machine interface (BMI) to study the role of posterior parietal cortex (PPC) in controlling navigation in virtual reality. …”
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MediaWatchers4Climate: Assessing the Accuracy of Climate Change Narratives in Greek Media Through Machine Learning by Thomai Baltzi, Stella Nikitaki, Fani Galatsopoulou, Ioanna Kostarella, Andreas Veglis, Vasilis Vasilopoulos, Dimitris Papaevagelou, Antonis Skamnakis

“…This study introduces MediaWatchers4Climate, a methodological framework that leverages machine learning to evaluate the accuracy and rhetorical framing of climate change narratives in Greek online media. …”
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ReactorNet based on machine learning framework to identify control rod position for real time monitoring in PWRs by Ahmed Omar, Mohamed K. Elhadad, Moamen G. El-Samrah, Tarek F. Nagla, Tamer Mekkawy

“…Abstract This paper presents a novel approach, ReactorNet, a machine learning framework leveraging thermal neutron flux imaging to enable real-time monitoring of pressurized water reactors (PWRs). …”
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CryptoDNA: A Machine Learning Paradigm for DDoS Detection in Healthcare IoT, Inspired by Cryptojacking prevention Models by Zag ElSayed, Nelly Elsayed, Ahmed Abdelgawad

“…This study introduces CryptoDNA, an innovative machine learning detection framework influenced by cryptojacking detection methods, designed to identify and alleviate DDoS attacks in healthcare IoT settings. …”
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Multi-HM: A Chinese Multimodal Dataset and Fusion Framework for Emotion Recognition in Human–Machine Dialogue Systems by Yao Fu, Qiong Liu, Qing Song, Pengzhou Zhang, Gongdong Liao

“…To address these gaps, we present Multi-HM, the first multimodal emotion recognition dataset explicitly designed for human–machine consultation systems. It contains 2000 professionally annotated dialogues across 10 major HCI domains. …”
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A comparative analysis of classical machine learning models with quantum-inspired models for predicting world surface temperature by Trilok Nath Pandey, Vishvajeet Ravalekar, Sidharth D. Nair, Sunil Kumar Pradhan

“…The study compares the performance of classical machine learning algorithms to quantum algorithms, which use the concepts of superposition and entanglement to handle subtle temporal patterns in time-series data. …”
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Enhanced Fault Diagnosis in Milling Machines Using CWT Image Augmentation and Ant Colony Optimized AlexNet by Niamat Ullah, Muhammad Umar, Jae-Young Kim, Jong-Myon Kim

“…A method is proposed for fault classification in milling machines using advanced image processing and machine learning. …”
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Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning by Swetha Valavarasu, Yasaswini Sangu, Tanmaya Mahapatra

“…In this study, we applied various machine learning techniques to predict bacterial antibiotic resistance using the Pfizer ATLAS Antibiotics dataset. …”
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Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East by Younes Khosravi, Taha B.M.J. Ouarda, Saeid Homayouni

“…Abstract Climate change in the Middle East has intensified with rising temperatures, shifting rainfall patterns, and more frequent extreme events. This study introduces the Stacking-EML framework, which merges five machine learning models three meta-learners to predict maximum temperature, minimum temperature, and precipitation using CMIP6 data under SSP1-2.6, SSP2-4.5, and SSP5-8.5. …”
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