A Comprehensive Review of Wind Power Prediction Based on Machine Learning: Models, Applications, and Challenges by Zongxu Liu, Hui Guo, Yingshuai Zhang, Zongliang Zuo

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On-site quantitative detection of fentanyl in heroin by machine learning-enabled SERS on super absorbing metasurfaces by Yingkun Zhu, Haomin Song, Ruiying Liu, Yunyun Mu, Murali Gedda, Abdullah N. Alodhay, Lei Ying, Qiaoqiang Gan

“…Our study introduces a novel approach for on-site quantitative detection of fentanyl in heroin, employing machine learning-enabled surface-enhanced Raman spectroscopy (SERS) on superabsorbing metasurfaces. …”
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Predicting turbidity dynamics in small reservoirs in central Kenya using remote sensing and machine learning by Stefanie Steinbach, Anna Bartels, Andreas Rienow, Bartholomew Thiong’o Kuria, Sander Jaap Zwart, Andrew Nelson

“…Here we modelled turbidity in 34 small reservoirs in central Kenya with Sentinel-2 data from 2017 to 2023 and predicted turbidity outcomes using primary and secondary Earth observation data, and machine learning. We found distinct monthly turbidity patterns. …”
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A machine learning interpretation of the correlation between poverty and air pollution in the contiguous United States by Sajeev Magesh, Kevin Geng

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Machine Learning Model-Based Applications for Food Management in Alzheimer’s Using Regression Analysis Approach by Sajadul Hassan Kumhar, Prabhakara Rao Kapula, Harveen Kaur, Radeep R. Krishna, Mudasir M Kirmani, Vijay Anant Athavale, Mohd Wazih Ahmad

“…Scientists are trying to find a solution using some machine learning (ML) techniques. The ML algorithms used for this purpose are neural networks, support vector machines, regression and many more. …”
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Data Augmentation and Machine Learning algorithms for multi-class imbalanced morphometrics data of stingless bees by Daisy Salifu, Lorna Chepkemoi, Eric Ali Ibrahim, Kiatoko Nkoba, Henri E.Z. Tonnang

“…These techniques are applied in combination with machine learning (ML) algorithms; specifically Random Forest (RF), and Support Vector Machine (SVM), to assess the models’ predictive performance to infer stingless bee samples identities. …”
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Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters by C. Braxton Owens, Nithin Mathew, Tyce W. Olaveson, Jacob P. Tavenner, Edward M. Kober, Garritt J. Tucker, Gus L. W. Hart, Eric R. Homer

“…Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. …”
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A Machine Learning System for Routing Decision-Making in Urban Vehicular Ad Hoc Networks by Wei Kuang Lai, Mei-Tso Lin, Yu-Hsuan Yang

“…In MARS, road information is maintained in roadside units with the help of machine learning. We use machine learning to predict the moves of vehicles and then choose some suitable routing paths with better transmission capacity to transmit packets. …”
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Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques by Luis Mariano Esteban, Ángel Borque-Fernando, Maria Etelvina Escorihuela, Javier Esteban-Escaño, Jose María Abascal, Pol Servian, Juan Morote

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Explainable machine learning models for identifying mild cognitive impairment in older patients with chronic pain by Xiaoang Zhang, Yuping Liao, Daying Zhang, Weichen Liu, Zhijian Wang, Yaxin Jin, Shushu Chen, Jianmei Wei

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Portable optical spectroscopy and machine learning techniques for quantification of the biochemical content of raw food materials by Cosimo Ricci, Agata Gadaleta, Annamaria Gerardino, Angelo Didonna, Giuseppe Ferrara, Francesca Romana Bertani

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Smart Predictor for Spontaneous Combustion in Cotton Storages Using Wireless Sensor Network and Machine Learning by Umar Farooq Shafi, Waheed Anwar, Imran Sarwar Bajwa, Hina Sattar, Iqra Yaqoob, Aqsa Mahmood, Shabana Ramzan

“…In current research, we propose an efficient wireless sensor network (WSN) and machine learning- (ML-) based storage area monitoring system for early prediction of spontaneous combustion in the cotton storage area. …”
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A Machine Learning Approach for the Autonomous Identification of Hardness in Extraterrestrial Rocks from Digital Images by Shuyun Liu, Haifeng Zhao, Zihao Yuan, Liping Xiao, Chengcheng Shen, Xue Wan, Xuhai Tang, Lu Zhang

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Implications of Spatiotemporal Data Aggregation on Short-Term Traffic Prediction Using Machine Learning Algorithms by Rivindu Weerasekera, Mohan Sridharan, Prakash Ranjitkar

“…Experimental results indicate that data aggregation does not necessarily achieve good performance for multivariate spatiotemporal machine learning models. The models learned using high-resolution 30-second input data outperformed the corresponding baseline ARIMA models by 8%. …”
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Investigation of the Role of Machine Learning and Deep Learning in Improving Clinical Decision Making for Musculoskeletal Rehabilitation by Madhu Yadav, Pushpendra Kumar Verma, Sumaiya Ansari

Subjects: “…machine learning…”
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The impact of precompetition state on athletic performance among track and field athletes using machine learning by Yuting Zhang, Pengyu Fu, Qi Yu, Qingmei Niu, Dongfeng Nie, Xiangya Dou, Xiaoqin Zhang

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Interpretable machine learning and radiomics in hip MRI diagnostics: comparing ONFH and OA predictions to experts by Tariq Alkhatatbeh, Ahmad Alkhatatbeh, Qin Guo, Jiechen Chen, Jidong Song, Xingru Qin, Wang Wei

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Fault Prediction and Recovery Using Machine Learning Techniques and the HTM Algorithm in Vehicular Network Environment by Salah Zidi, Bechir Alaya, Tarek Moulahi, Amal Al-Shargabi, Salim El Khediri

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Machine Learning-Driven Resilient Modulus Prediction for Flexible Pavements Across Mountainous and Other Regions by Rauf Ayesha, Asif Usama, Javed Muhammad Faisal

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Enhanced Forecasting and Assessment of Urban Air Quality by an Automated Machine Learning System: The AI‐Air by Jiayu Yang, Huabing Ke, Sunling Gong, Yaqiang Wang, Lei Zhang, Chunhong Zhou, Jingyue Mo, Yan You

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