Estimation of minimum miscible pressure in carbon dioxide gas injection using machine learning methods by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Fatemeh Mohammadinia, Amirjavad Borhani

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Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning by Shogo Nakamura, Nobuaki Yasuo, Masakazu Sekijima

“…Because of recent advances in deep learning, molecular generative models have been developed. …”
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Sorghum yield prediction based on remote sensing and machine learning in conflict affected South Sudan by John Karongo, Joseph Ivivi Mwaniki, John Ndiritu, Victor Mokaya

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Teacher-student relationships as a pathway to sustainable learning: Psychological insights on motivation and self-efficacy by Jurong Liu, Juan Gao, Muhammad Hassan Arshad

“…The findings bear implications for educators and policymakers aiming to create more inclusive, supportive, and sustainability-driven learning environments.…”
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Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction by Waqar A. Sulaiman, Charithea Stylianides, Andria Nikolaou, Andria Nikolaou, Zinonas Antoniou, Ioannis Constantinou, Lakis Palazis, Anna Vavlitou, Theodoros Kyprianou, Theodoros Kyprianou, Efthyvoulos Kyriacou, Antonis Kakas, Antonis Kakas, Marios S. Pattichis, Andreas S. Panayides, Constantinos S. Pattichis, Constantinos S. Pattichis

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Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach by Pei Yang, Zeao Zhang, Jianan Wei, Lisha Jiang, Liqian Yu, Huawei Cai, Lin Li, Quan Guo, Zhen Zhao

Subjects: “…Deep learning…”
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Using machine learning models to plan HIV services: Emerging opportunities in design, implementation and evaluation by T Dzinamarira, E Mbunge, I Chingombe, D F Cuadros, E Moyo, I Chitungo, G Murewanhema, B Muchemwa, G Rwibasira, O Mugurungi, G Musuka, H Herrera

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Electrogastrogram-based detection of cybersickness with the application of wavelet transformation and machine learning: A case study by Ilija V. Tanasković, Nenad B. Popović, Jaka J. Sodnik, Sašo J. Tomažič, Nadica S. Miljković

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Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data by Tian Xia, Lanju Zhou, Khalil Ahmad

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Machine learning based sucker rod pump fault diagnosis using motor power curve by Othman H. Ahmed, Samuel I. Tecle, Anatoliy A. Zyuzev, Vladimir P. Metelkov

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Advancing education through e-learning innovation: the case of the Crocodile Chemistry program in higher education by Nawal Alqallaf, Zahra Almahmeed, Ahmad Alsaber, Bedour Alboloushi, Anwaar Alkandari, Fatimah Alhashem

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Family adoption program (FAP) as a learning tool—perceptions of students and faculty of community medicine by Rajyalakshmi Chepuru, Kuppli Sai Sushma, Sarada Vadlamani, Rongala V. Manasa, Bodhi Srividya Vennam

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Physics-aware machine learning for glacier ice thickness estimation: a case study for Svalbard by V. Steidl, J. L. Bamber, J. L. Bamber, X. X. Zhu, X. X. Zhu

“…In this study, we use deep learning paired with physical knowledge to generate ice thickness estimates for all glaciers of Spitsbergen, Barentsøya, and Edgeøya in Svalbard. …”
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Mathematics learning for school readiness of kindergarteners in the western rural area of china – taking county s as an example by Min Li, Xiaoping Yang

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Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm by Rafiqul Islam, Md. Arif Hossain

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Machine Learning-Based Mobile Device Resale Price Estimator: A Predictive Analytics Approach by Umm-e-Laila Mehdi, Khalid Mahboob, Samar Raza Talpur, Khaliq Ahmed, Mohammad Khurram

Subjects: “…Machine Learning…”
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Estimation of PM10 and PM2.5 Using Backscatter Coefficient of Ceilometer and Machine Learning by Bu-Yo Kim, Joo Wan Cha, Yong Hee Lee

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A Collection of Machine Learning Models for Improved Airport Operations Amidst Adverse Weather Conditions by Ramon Dalmau, Jonathan Attia

Subjects: “…Machine Learning…”
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Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning by Zhaoxiang Cai, Sofia Apolinário, Ana R. Baião, Clare Pacini, Miguel D. Sousa, Susana Vinga, Roger R. Reddel, Phillip J. Robinson, Mathew J. Garnett, Qing Zhong, Emanuel Gonçalves

“…Addressing this, our study introduces an unsupervised deep learning model, MOSA (Multi-Omic Synthetic Augmentation), specifically designed to integrate and augment the Cancer Dependency Map (DepMap). …”
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Creating a Successful Early Learning Environment for Children Who Have Autistic Spectrum Disorders by Heidi Liss Radunovich, Jessica L. Kochert

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