Enhancing cotton irrigation with distributional actor–critic reinforcement learning by Yi Chen, Meiwei Lin, Zhuo Yu, Weihong Sun, Weiguo Fu, Liang He

“…This method surpasses previous irrigation strategies managed by standard reinforcement learning techniques (e.g., DQN). Empirical results indicate that our approach significantly outperforms traditional agronomic decision-making, enhancing cotton yield by 13.6% and improving water use efficiency per kilogram of crop by 6.7%. …”
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An efficient plant disease detection using transfer learning approach by Bosubabu Sambana, Hillary Sunday Nnadi, Mohd Anas Wajid, Nwosu Ogochukwu Fidelia, Claudia Camacho-Zuñiga, Henry Dozie Ajuzie, Edeh Michael Onyema

“…The model's performance was evaluated using several metrics, including mean Average Precision (mAP), F1-score, Precision, and Recall, yielding values of 91.05, 89.40, 91.22, and 87.66, respectively. …”
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The experience of conscious reflection within a general theory of learning by Espen Hoff Dyngeland

“…Questions regarding what constitutes the process of learning and how best to facilitate it have been addressed from numerous perspectives, often yielding competing interpretations and approaches. …”
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E .mail Writing as a cross-cultural learning experience by Nacira Hocine

“…E .mail entries were analysed to yield insights into the cross- cultural communication process. …”
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Mobile learning for less-commonly taught languages: design and application by Tang Jinlan, Zhai Yuming, Li Lingxiao, Liu Peixin, Deng Hongxun

“…Learners reported increased interest, improvements in spoken communication and learner autonomy. The study will yield implications to future mobile language learning resources design and the pedagogy of integrating the application into teaching and learning of foreign languages.…”
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Analysis of Machine Learning Performance in Spatial Interpolation of Rainfall Data by Alexandre E. L. Nobrega, Itamir M. Barroca Filho

“…After testing different models for data spatialization and conducting a thorough statistical analysis, we conclude that machine learning models outperformed the Inverse Distance Weighting method, yielding greater variability in accumulated Annual Maximum Daily Precipitation values and improved overall results.…”
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Exploring Effects of Modified Machine Learning Pipelines of Astrochemical Inventories by Hannah Toru Shay, Haley N. Scolati, Gabi Wenzel, Kin Long Kelvin Lee, Aravindh N. Marimuthu, Brett A. McGuire

“…Finally, we provide suggestions for future machine learning of interstellar sources.…”
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Comparative Analysis of Machine Learning Algorithms on Family Wellness Classification by Retno Budiarti, Febri Hemarani, Mohammad Reza, Rindi Melati Mulyasari

“…The analysis results from the KNN, random forest, and naive Bayes methods each yield an F1-score of 65.46%, 68%, and 69.44%, respectively.…”
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Adaptive circuits for action and value information in rodent operant learning by Alain Rios, Kyohei Fujita, Yoshikazu Isomura, Nobuya Sato

“…Operant learning is a behavioral paradigm where animals learn to associate their actions with consequences, adapting their behavior accordingly. …”
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Investigating of Machine Learning Based Algorithms for Liver Cirrhosis Prediction by Young Choi, Eunsung Oh

“…This paper presents a study on utilizing machine learning algorithms for predicting liver cirrhosis with a focus on enhancing accuracy rates. …”
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Lessons learned from qualitative fieldwork in a multilingual setting by Shweta Jain Verma

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AI-Driven Phishing Detection: Enhancing Cybersecurity with Reinforcement Learning by Haidar Jabbar, Samir Al-Janabi

“…This study presents a Reinforcement Learning (RL)-based phishing detection framework, leveraging a Deep Q-Network (DQN) to enhance detection accuracy, reduce false positives, and improve classification performance. …”
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Machine Learning–Driven Adaptive Testing: An Application for the MMPI Assessment by Daiana Colledani, Egidio Robusto, Pasquale Anselmi

“…The findings indicate that a machine learning classifier based on a model tree (ML-MT) algorithm effectively handled the complex MMPI-2 scales, yielding accurate scores while noticeably reducing item administration. …”
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Transfer Learning Methods for Hate Speech Detection in Bahasa Indonesia by Fairuz Astari Devianty

“…To address this issue, we study whether the transfer learning method can yield improved results. This study performs extensive experiments to show that transfer learning methods are suitable for low-resource hate speech prediction. …”
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Contrastive learning method for leak detection in water distribution networks by Rongsheng Liu, Tarek Zayed, Rui Xiao

“…Experimental results indicate that flip-x and amplitude scaling are optimal combinations for contrastive learning. Besides, ablation and t-distributed stochastic neighbor embedding (t-SNE) results reveal that increasing the model depth does not always yield performance improvement, and five convolutional blocks are more suitable for the leak detection problem in this study. …”
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Lessons Learned from Three Agrivoltaic Installations in New Jersey by A.J. Both, Bill Bamka, Thierry Besancon, Dunbar Birnie, Clint Burgher, Daniel Gimenez, Serpil Guran, Michael Kornitas, Pete Nitzsche, David Robinson, W. Ross Rucker, Ethan Schoolman, David Specca, Kevin Sullivan, Daniel Ward, Mike Westendorf, Christian Wyenandt

“…This paper discusses the lessons we have learned along the way, including all the steps necessary to see an agrivoltaic project through to completion. …”
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Probabilistic and deep learning approaches for conductivity-driven nanocomposite classification by Wejden Gazehi, Rania Loukil, Mongi Besbes

“…The hybrid model combines the probabilistic reasoning capabilities of BNs with the deep learning strengths of RNNs, yielding a more robust and adaptable classification methodology. …”
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Integrating QSAR modelling with reinforcement learning for Syk inhibitor discovery by Maria Zavadskaya, Anastasia Orlova, Andrei Dmitrenko, Vladimir Vinogradov

“…Scientific contribution The study presents the first application of QSAR-guided reinforcement learning for Syk inhibitor discovery, yielding structurally novel candidates with predicted high potency. …”
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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

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Integrating Machine Learning and IoT for Effective Plant Disease Management by Bhoi Manjulata, Dubey Ahilya

“…Machine learning (ML) and Internet of Things (IoT) are bolting down the agriculture in the area of plant disease management, especially. …”
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