A Critical Comparison of Machine Learning Classifiers to Predict Match Outcomes in the NFL by Beal Ryan, Norman Timothy J., Ramchurn Sarvapali D.

“…In this paper, we critically evaluate the performance of nine machine learning classification techniques when applied to the match outcome prediction problem presented by American Football. …”
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A first-principles mathematical model integrates the disparate timescales of human learning by Mingzhen Lu, Tyler Marghetis, Vicky Chuqiao Yang

“…Here, in response to calls for more formal theory in the psychological sciences, we present a parsimonious mathematical model that unifies the nested timescales of learning. …”
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Caring, learning, improving quality and doing research: Different faces of the same process by G.J.O. Marincowitz, G.S. Fehrsen

“…Learning to understand the different processes becomes easier, as they have a lot in common. …”
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Fostering the Quality of Teaching and Learning by Developing the “Neglected Half ” of University Teachers’ Competencies by Barica Marentič Požarnik, Andreja Lavrič

“…For too long, the quality of teaching and learning in universities has been undervalued in comparison to research. …”
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Some Single-Machine Scheduling Problems with Learning Effects and Two Competing Agents by Hongjie Li, Zeyuan Li, Yunqiang Yin

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Investigating EFL Undergraduates’ Vocabulary Learning Strategies (VLSs) at a University in Syria by Maisaa Moustafa Daaboulis, Vahid Nimehchisalem, Mustafa Mahdi Jubier

“…Therefore, the present study aims to investigate the use of Vocabulary Learning Strategies (VLSs) among 100 randomly selected EFL Syrian first-year undergraduates in a university in Syria. …”
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Development of Machine Learning Atomistic Potential for Molecular Simulation of Hematite–Water Interfaces by Mozhdeh Shiranirad, Niall J. English

“…A novel approach for constructing a machine-learned potential energy surface (MLP) from unlabeled training data is presented. …”
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Occupant-Centric Load Optimization in Smart Green Townhouses Using Machine Learning by Seyed Morteza Moghimi, Thomas Aaron Gulliver, Ilamparithi Thirumarai Chelvan, Hossen Teimoorinia

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A new benchmark for machine learning applied to powder X-ray diffraction by Sergio Rincón, Gabriel González, Mario A. Macías, Pablo Arbeláez

“…Abstract Although crystal parameter prediction from powder X-ray diffraction has recently attracted the interest of the machine learning community, most existing datasets for this task are private and lack structural diversity. …”
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Machine Learning Analysis of Arterial Oscillograms for Depression Level Diagnosis in Cardiovascular Health by Vladislav Kaverinsky, Dmytro Vakulenko, Liudmyla Vakulenko, Kyrylo Malakhov

“…The presented study explores the clustering of arterial oscillogram (AO) data among a sample of patients, focusing on ultra-low-frequency (ULF) indicators and their relationship with depression levels. …”
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Predicting Coronary Heart Disease Using Data Mining and Machine Learning Solutions by VIJAI M. MOORTHY, BHUPAL N. DHARAMSOTH, VIJAYALAKSHMI MUTHUKARUPPAN, ARUL ELANGO, KALAIARASI GANESAN

“…Abstract This research focuses on predicting cardiovascular disease using machine learning classification strategies. The study presents a unique approach by integrating multiple machine learning techniques, leveraging the strengths of Random Forest and Gradient Boosting. …”
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Nanosatellite Autonomous Navigation via Extreme Learning Machine Using Magnetometer Measurements by Gilberto Goracci, Fabio Curti, Mark Anthony de Guzman

“…This work presents an algorithm to perform autonomous navigation in spacecraft using onboard magnetometer data during GPS outages. …”
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PRACTICAL TRAINING OF OFFICERS OF THE STATE FIRE SERVICE THROUGH GAME-BASED LEARNING by V. V. Bulgakov, A. A. Lazarev, E. P. Konovalenko, T. A. Mochalova

“…However, in a technologically developed society, there is a contradiction between the increased requirements to young officers’ competencies and the impossibility to achieve a proper complex of graduates’ characteristics by providing education through only standard traditional techniques, which continue to be prevalent in higher education and ensure optimisation of professional activity in general.The aim of the present publication was to present the developed methodology of game-based learning for training of cadets of educational organisations of higher education of the EMERCOM of Russia. …”
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A comprehensive review of large language models: issues and solutions in learning environments by Tariq Shahzad, Tehseen Mazhar, Muhammad Usman Tariq, Wasim Ahmad, Khmaies Ouahada, Habib Hamam

“…Furthermore, the study presents practical case studies and solutions to barriers, such as data privacy and bias, offering insights into their role in enhancing the teaching–learning process. …”
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The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review by Wilhelm Grzesiak, Daniel Zaborski, Marcin Pluciński, Magdalena Jędrzejczak-Silicka, Renata Pilarczyk, Piotr Sablik

“…The aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020–2024). …”
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Improving immunotherapy for the treatment of hepatocellular carcinoma: learning from patients and preclinical models by Romain Desert, Fabio Gianonne, Antonio Saviano, Yujin Hoshida, Mathias Heikenwälder, Pierre Nahon, Thomas F. Baumert

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Federated learning for crop yield prediction: A comprehensive review of techniques and applications by Vani Hiremani, Raghavendra M. Devadas, Preethi, R. Sapna, T. Sowmya, Praveen Gujjar, N. Shobha Rani, K.R. Bhavya

“…The demand for food all over the world requires the implementation of advanced technologies to improve agricultural productivity. Federated Learning (FL) as a decentralized approach to machine learning facilitates collaborative model training on different data sources while maintaining privacy—making it highly applicable technology for sensitive agricultural data. …”
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Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

“…Despite these advances, a key problem lies in defining the configuration criteria of the adaptive algorithm. This study presents an adaptive variant of PSO that relies on fitness landscape analysis, particularly via ruggedness factor estimation. …”
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Evaluation of the relationship between spatial learning and image maintenance through isovist analysis by Sinem Kırkan, Mina Hazal Taşcı, Orkan Zeynel Güzelci

“…This study presents a method, 3D parametric isovist volumes, to examine the relationship between ‘spatial visibility’ and ‘image maintenance’. …”

Robot-assisted knee arthroplasty: Analyzing the learning curve and initial institutional experience by Leandro Ejnisman, Eliane Antonioli, Luciana Cintra, Pamela Gabriela de Oliveira Souza, Lauro Augusto Veloso Costa, Mario Lenza

“…Robot-assisted total knee arthroplasty (rTKA) involves a learning curve for orthopedic surgeons. The aim of the present study was to assess the surgical times of rTKA procedures performed by initial stage and proficiency stage surgeons in comparison with times of conventional total knee arthroplasty (cTKA). …”
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