Deep Federated Learning Based Convergence Analysis in Relaying-Aided MEC-IoT Networks by Jun Liu, Tao Cui, Lin Zhang, Yuwei Zhang, Jing Wang, Chao Li, Kai Chen, Huang Huang, Xuan Zhou, Wei Zhou, Sun Li, Suili Feng, Dongqing Xie, Yun Li, Haige Xiang, Kaimeno Dube, Abbarbas Muazu, Nakilavai Rono, Wen Zhou, Fusheng Zhu, Liming Chen, Dan Deng, Zhao Wang, Yajuan Tang

“…The work in this paper can provide some theoretical foundation for deep federated learning and computing networks.…”
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Pioneering precision in lumbar spine MRI segmentation with advanced deep learning and data enhancement by Istiak Ahmed, Md. Tanzim Hossain, Md. Zahirul Islam Nahid, Kazi Shahriar Sanjid, Md. Shakib Shahariar Junayed, M. Monir Uddin, Mohammad Monirujjaman Khan

“…This study presents an advanced approach to lumbar spine segmentation using deep learning techniques, focusing on addressing key challenges such as class imbalance and data preprocessing. …”
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Multi-modal expert system for automated durian ripeness classification using deep learning by Santi Sukkasem, Watchareewan Jitsakul, Phayung Meesad

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A machine learning–assisted analysis of essential oil constituents targeting Salmonella Typhimurium by Maria Lagerholm, Mirjana Pešić, Miloš Jovanović, Marija Kuzmanović, Viktor Nedović

“…In contrast, non-aromatic bicyclic structures present in monoterpenoids like alpha-pinene, beta-pinene and delta-3-carene were associated with a lack of efficacy against Salmonella. …”
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Research trends in the application of machine learning in sustainability practices based on a bibliometric analysis by Alejandro Valencia-Arias, Manuel Humberto Vásquez Coronado, Milagros Layesvka Clavo Medina, Maricarmen Jeneth Morales Garcia, Ana Rosa Requejo Arias, Josias Idelso Saavedra Tirado

“…The prevailing focus in this field has shifted towards the treatment of waste, the application of deep learning techniques, and the pursuit of sustainable development goals. …”
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An ECoG-Based Binary Classification of BCI Using Optimized Extreme Learning Machine by Xinman Zhang, Qi Xiong, Yixuan Dai, Xuebin Xu, Guokun Song

“…In order to improve the accuracy of brain signal processing and accelerate speed meanwhile, we present an optimal and intelligent method for large dataset classification application in this paper. …”
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Solutions for Lithium Battery Materials Data Issues in Machine Learning: Overview and Future Outlook by Pengcheng Xue, Rui Qiu, Chuchuan Peng, Zehang Peng, Kui Ding, Rui Long, Liang Ma, Qifeng Zheng

“…Abstract The application of machine learning (ML) techniques in the lithium battery field is relatively new and holds great potential for discovering new materials, optimizing electrochemical processes, and predicting battery life. …”
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Personalized decision making for coronary artery disease treatment using offline reinforcement learning by Peyman Ghasemi, Matthew Greenberg, Danielle A. Southern, Bing Li, James A. White, Joon Lee

“…We applied off-policy reinforcement learning (RL) to a composite data model from 41,328 unique patients with angiography-confirmed obstructive CAD. …”
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Learning causal networks using inducible transcription factors and transcriptome‐wide time series by Sean R Hackett, Edward A Baltz, Marc Coram, Bernd J Wranik, Griffin Kim, Adam Baker, Minjie Fan, David G Hendrickson, Marc Berndl, R Scott McIsaac

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Project-Based Learning in Social Innovation—Developing a Sense of Belonging in Online Contexts by Mats Danielson, Ivar Björkman

“…The study contributes to ongoing research on student belonging by identifying specific practices that may support SoB in digitally supported, team-oriented learning environments.…”
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A meta-learning approach to improving transferability for freeway traffic crash risk prediction by Chenlei Liao, Xiqun (Michael) Chen

“…However, only limited research has been conducted on transferability improvement and applications of existing models in large-scale freeway networks. This study presents a Model-Agnostic-Meta-Learning (MAML) based framework to improve transferability and robustness, which is applicable to any crash risk prediction model trained with gradient descent. …”
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Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…Hydrogen is increasingly recognized as a key contributor to a low-carbon energy future, and machine learning (ML) is emerging as a valuable tool to optimize hydrogen production processes. …”
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The Impact of Mnemonic Strategies and Inquiry-Based Learning on Memory Retention and Creativity in Biology Education by Nurul Azizah, Aditya Marianti, Wiwi Isnaeni, Endah Peniati

“…This study implies that the use of an inquiry learning model with mnemonic strategies can be an alternative learning strategy to improve the formation of LTM and students' creative thinking ability at the secondary school level. …”
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Robust analysis of photovoltaic plants: A framework based on prediction uncertainties by machine learning by Seyyed Shahabaddin Hosseini Dehshiri, Bahar Firoozabadi

“…In this context, the present study offers a novel framework for comprehensively assessing the photovoltaic project development. …”
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Password strength verification based on machine learning algorithms and LSTM recurrent neural networks by V. V. Belikov, I. A. Prokuronov

“…The proposed supervised machine learning algorithms comprise support vector machines, random forest, boosting, and long short-term memory (LSTM) recurrent neural network types. …”
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A Novel Technique for Facial Recognition Based on the GSO-CNN Deep Learning Algorithm by Rana H. Al-Abboodi, Ayad A. Al-Ani

“…However, conventional methods can no longer satisfy the demand at present due to their low recognition accuracy and restrictions on many occasions. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…To address these challenges, we propose a novel multi-aircraft autonomous decision-making approach based on graphs and multi-agent reinforcement learning (MADRL) under zero-order optimization, implemented through the GraphZero-PPO algorithm. …”
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Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data by Manuel Ciba, Marc Petzold, Caroline L. Alves, Francisco A. Rodrigues, Yasuhiko Jimbo, Christiane Thielemann

“…Abstract Biosensors, such as microelectrode arrays that record in vitro neuronal activity, provide powerful platforms for studying neuroactive substances. This study presents a machine learning workflow to analyze drug-induced changes in neuronal biosensor data using complex network measures from graph theory. …”
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Improved Patch-Mix Transformer and Contrastive Learning Method for Sound Classification in Noisy Environments by Xu Chen, Mei Wang, Ruixiang Kan, Hongbing Qiu

“…In urban environments, noise significantly impacts daily life and presents challenges for Environmental Sound Classification (ESC). …”
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CNN-ViT: A multi-feature learning based approach for driver drowsiness detection by Madduri Venkateswarlu, Venkata Rami Reddy Chirra

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