Time series forecasting of bed occupancy in mental health facilities in India using machine learning by G. Avinash, Hariom Pachori, Avinash Sharma, SukhDev Mishra

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XAI-Enhanced Machine Learning for Obesity Risk Classification: A Stacking Approach With LIME Explanations by Mohammad Azad, Md Faraz Kabir Khan, Sameh Abd El-Ghany

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MLAS: Machine Learning-Based Approach for Predicting Abiotic Stress-Responsive Genes in Chinese Cabbage by Xiong You, Yiting Shu, Xingcheng Ni, Hengmin Lv, Jian Luo, Jianping Tao, Guanghui Bai, Shusu Feng

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Comparison of Machine Learning Algorithms on Classification of Covid-19 Cough Sounds Using MFCC Extraction by Mohammad Reza Faisal, Muhammad Thoriq Hidayat, Dwi Kartini, Fatma Indriani, Irwan Budiman, Triando Hamonangan Saragih

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Combining machine-learned and empirical force fields with the parareal algorithm: application to the diffusion of atomistic defects by Gorynina, Olga, Legoll, Frédéric, Lelièvre, Tony, Perez, Danny

“…In this work, the parareal algorithm uses a family of machine-learning spectral neighbor analysis potentials (SNAP) as fine, reference, potentials and embedded-atom method potentials (EAM) as coarse potentials. …”
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Advanced Machine Learning Ensembles for Improved Precipitation Forecasting: The Modified Stacking Ensemble Strategy in China by Tiantian Tang, Yifan Wu, Yujie Li, Lexi Xu, Xinyi Shi, Haitao Zhao, Guan Gui

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From Integer Programming to Machine Learning: A Technical Review on Solving University Timetabling Problems by Xin Gu, Muralee Krish, Shaleeza Sohail, Sweta Thakur, Fariza Sabrina, Zongwen Fan

“…We explored the uses of machine learning algorithms and the hybrid solutions of combining the integer programming and machine learning algorithms in higher education timetabling solutions. …”
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Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study by Stanford Martinez, Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Kal Clark, Adel Alaeddini, Nicholas Czarnek, Aarushi Aggarwal, Sahra Emamzadeh, Jeffrey R Mock, Edward J Golob

“…The encoded features of the eye-fixation data are used by machine learning classifiers to discriminate between faculty and trainee radiologists. …”
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Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data by Qingwen Xue, Ke Wang, Jian John Lu, Yujie Liu

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Evaluating Urban Sewage Sludge Distribution on Agricultural Land Using Interpolation and Machine Learning Techniques by Andrea Lazzari, Simone Giovinazzo, Giovanni Cabassi, Massimo Brambilla, Carlo Bisaglia, Elio Romano

“…Various interpolation methods and machine learning models were employed to analyze the spatial distribution patterns of the sludge. …”
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Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy by Bo Zhang, Rongji Liao

“…The application of machine learning touches all activities of human behavior such as computer network and routing packets in LAN. …”
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Research on 3D printing concrete mechanical properties prediction model based on machine learning by Yonghong Zhang, Suping Cui, Bohao Yang, Xinxin Wang, Tao Liu

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Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study by Maik JM Beuken, Melanie Kleynen, Susy Braun, Kees Van Berkel, Carla van der Kallen, Annemarie Koster, Hans Bosma, Tos TJM Berendschot, Alfons JHM Houben, Nicole Dukers-Muijrers, Joop P van den Bergh, Abraham A Kroon, Iris M Kanera

“…Particularly personalized interventions have been shown to be effective for long-term behavior change. Machine learning can be used to uncover insights without predefined hypotheses, revealing complex relationships and distinct population clusters. …”
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Cross-Brand Machine Learning of Coffee’s Temporal Liking from Temporal Dominance of Sensations Curves by Hiroharu Natsume, Shogo Okamoto

“…In this study, we used reservoir computing, a machine learning technique well-suited for time-series data, to predict temporal changes in liking based on the temporal evolution of dominant sensations. …”
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Prediction of digestible energy requirement in growing finishing stage of pigs using machine learning models by Nibas Chandra Deb, Jayanta Kumar Basak, Sijan Karki, Elanchezhian Arulmozhi, Dae Yeong Kang, Niraj Tamrakar, Eun Wan Seo, Junghoo Kook, Myeong Yong Kang, Hyeon Tae Kim

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Machine Learning-Based Relative Performance Analysis of Monocrystalline and Polycrystalline Grid-Tied PV Systems by Asfand Yar, Muhammad Yousaf Arshad, Faran Asghar, Waseem Amjad, Furqan Asghar, Muhammad Imtiaz Hussain, Gwi Hyun Lee, Faisal Mahmood

“…In this research study, the design and performance evaluation of grid-tied photovoltaic systems has been carried out through experimentation, HelioScope simulation, and black-box machine learning methods for data-driven artificial intelligence system performance assessment and validation. …”
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Advancements in Machine Learning and Deep Learning Techniques for Crop Yield Prediction: A Comprehensive Review by V. Ramesh and P. Kumaresan

Subjects: “…crop yield prediction, machine learning, deep learning, artificial neural networks, optimization algorithms…”
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Depression Detection in Social Media: A Comprehensive Review of Machine Learning and Deep Learning Techniques by Waleed Bin Tahir, Shah Khalid, Sulaiman Almutairi, Mohammed Abohashrh, Sufyan Ali Memon, Jawad Khan

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Harnessing Machine Learning for Diabetes Prediction: Optimizing Classifiers to Tackle Canada's Growing Health Challenge by Mark Gerald Anastacio, Alam Md Twariqul

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The Comparison of Classical Statistical and Machine Learning Methods in Prediction of Thrombosis in Patients with Acute Myeloid Leukemia by Ilija Doknić, Mirjana Mitrović, Zoran Bukumirić, Marijana Virijević, Nikola Pantić, Nikica Sabljić, Darko Antić, Živko Bojović

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