Exploring machine learning algorithms to predict short birth intervals and identify its determinants among reproductive-age women in East Africa by Tirualem Zeleke Yehuala, Bezawit Melak Fente, Sisay Maru Wubante

“…Hence, this study aimed to predict short birth intervals and identify their determinants using supervised machine learning models. Method This study employs machine learning algorithms to predict short birth intervals among reproductive-age women in East Africa, using a dataset from Demographic and Health Surveys. …”
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Deep learning driven methodology for the prediction of mushroom moisture content using a novel LED-based portable hyperspectral imaging system by Kai Yang, Ming Zhao, Dimitrios Argyropoulos

“…This study proposes a deep-learning driven methodology for the analysis of mushroom moisture content (MC) datasets acquired using a novel portable hyperspectral imaging (HSI) system. …”
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Predicting Emergency Severity Index (ESI) level, hospital admission, and admitting ward in an emergency department using data-driven machine learning by Steve Agius, Vincent Cassar, Caroline Magri, Wasiq Khan, Dhiya Al-Jumeily Obe, Godwin Caruana, Luke Topham

“…Conclusions This research demonstrates the efficacy of machine learning models in predicting key ED outcomes, highlighting their potential to transform emergency care through data-driven insights.…”
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A New Heterogeneous Hybrid Massive MIMO Receiver With an Intrinsic Ability of Removing Phase Ambiguity of DOA Estimation via Machine Learning by Feng Shu, Baihua Shi, Yiwen Chen, Jiatong Bai, Yifan Li, Tingting Liu, Zhu Han, Xiaohu You

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Designing context-specific physical activity interventions for English primary schools: key learning from a four-month rapid ethnography by Robert Walker, Danielle House, Simona Kent-Saisch, Alice Porter, Ruth Salway, Lydia Emm-Collison, Michael Beets, David Revalds Lubans, Frank de Vocht, Russell Jago

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Determining the Teachers' Attitude towards "Mistake" and "Making Mistakes" in the Learning Process and Improving the Culture facing it (case study: elementary school students) by Mazhar Babaee, Hedyeh Azagh

“…Some teachers have positive and constructive ideas about making mistakes and they see it as an opportunity to learn and as a stepping stone to progress and achieve success. …”
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Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli, Mohammad AL-Rawi

“…The second step is to develop a novel manipulation equation that integrates different variants of quasi-dynamic oppositional learning search schemes, guided by a novel intelligently devised adaptive switch mechanism. …”
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Metacognition & learning process: Using think-aloud protocol (TAP) to understand students and their teacher’s reflection processes during a problem-solving situation by O. Bouiri, S. Lotfi, M. Talbi

“…The authors consider hat their research is a first step towards a new approach of evaluation of the teaching-learning act that includes both the teacher and the learners simultaneously.Practical significance. …”
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Social media food marketing landscape of children living in Republic of Srpska, Bosnia and Herzegovina: Piloting the WHO CLICK framework, results and lessons learned by Jelena Niškanović, Dragana Stojisavljević, Magdalena Muc, Mimi Tatlow-Golden, Dijana Manigoda

“…Our learnings contributed to updates of the WHO Protocols and the EU- framework guidance. …”
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Pore size classification and prediction based on distribution of reservoir fluid volumes utilizing well logs and deep learning algorithm in a complex lithology by Hassan Bagheri, Reza Mohebian, Ali Moradzadeh, Behnia Azizzadeh Mehmandost Olya

“…To prognosticate NMR outputs (CBW, BVI, FFV) for these wells, a two-step deep learning (DL) algorithm is implemented. …”
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Geogenic perspectives on potassium dynamics and plant uptake: insights from natural and submerged conditions across different soil types with machine learning predictions by Saibal Ghosh, Gourav Mondal, Shreya Chakraborty, Sonali Banerjee, Sumit Kumar, Riddhi Basu, Pradip Bhattacharyya

“…Submerged conditions enhanced potassium availability, with red soil showing the highest levels of water-soluble K (WsK), exchangeable K (ExK), and non-exchangeable K (NEK), particularly Step-K and constant rate K (CR-K) forms. Rice potassium content was highest in grains, followed by shoots and roots, with red soil containing the most available potassium. …”
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Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

“…The Air Quality Index (AQI) is a crucial metric for assessing the severity of air pollution, making accurate AQI forecasting essential for air quality management. A hybrid deep learning model is developed for AQI prediction, incorporating two-stage decomposition and hyperparameter optimization. …”
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Analysis of graphene coatings on various metallic/oxide crystal/composite material substrates using machine learning for enhanced solar thermal energy conversion by Khaled Aliqab, Dhruvik Agravat, Shobhit K. Patel, Ammar Armghan, Naim Ben Ali, Meshari Alsharari

“…Thus, the data collection time is greatly reduced using ML compared to running simulations which have a step size of about 8 h per change. Where the machine learning efficacy is 98% for the thickness optimization of Fe, CuO, and MAPBI3 with 25% test data. …”
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Comparison of Empirical and Reinforcement Learning (RL)-Based Control Based on Proximal Policy Optimization (PPO) for Walking Assistance: Does AI Always Win? by Nadine Drewing, Arjang Ahmadi, Xiaofeng Xiong, Maziar Ahmad Sharbafi

“…Amidst prevailing assertions that AI could surpass human capabilities in customizing every facet of support for human needs, our study serves as an initial step towards such claims within the context of human walking assistance. …”
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A new method for early diagnosis and treatment of meniscus injury of knee joint in student physical fitness tests based on deep learning method by Yan Fang, Lu Liu, Qingyu Yang, Shuang Hao, Zhihai Luo

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A Survey of Traversability Estimation for Mobile Robots by Christos Sevastopoulos, Stasinos Konstantopoulos

“…In this survey we highlight the merits and limitations of all the major steps in the evolution of traversability estimation techniques, covering both non-trainable and machine-learning methods, leading up to the recent proliferation of deep learning literature. …”
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MQTTEEB-D: A Real-World IoT Cybersecurity Dataset for AI-Powered Threat Detection in MQTT NetworksMendeley Data by Abderrahmane Aqachtoul, Khaoula Karam, Abderrahmane Elamrani, Mehdi Najib, Najat Rafalia, Mohamed Bakhouya

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Procedural performance is linked to motor skills and language ability: Findings from a knot-tying task in children with and without developmental coordination disorder by Yu-Ting Tseng, Hsinjen Julie Hsu

“…Previous studies have demonstrated poor procedural learning of motor sequences in children with developmental coordination disorder (DCD). …”
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Perfect Labelling: A Review and Outlook of Label Optimization Techniques in Dynamic Earth Observation by Sarah Hauser, Lena Augner, Andreas Schmitt

“…Advances in Artificial Intelligence (AI) and Machine Learning (ML) have significantly enhanced the practice of Earth Observation (EO), enabling complex analyses such as land cover change detection, vegetation monitoring, and disaster response. …”
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Dataset of Sentinel-1 SAR and Sentinel-2 RGB-NDVI imageryMendeley Data by Ahmed Alejandro Cardona-Mesa, Rubén Darío Vásquez-Salazar, Luis Gómez, Carlos M. Travieso-González, Andrés F. Garavito-González, Esteban Vásquez-Cano, Jean Pierre Díaz-Paz

“…Additionally, the structure of the dataset and the preprocessing steps applied make it readily usable for various research purposes. …”
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