Inverse Design of Plasmonic Nanostructures Using Machine Learning for Optimized Prediction of Physical Parameters by Luana S. P. Maia, Darlan A. Barroso, Aêdo B. Silveira, Waleska F. Oliveira, André Galembeck, Carlos Alexandre R. Fernandes, Dayse G. C. Bandeira, Benoit Cluzel, Auzuir R. Alexandria, Glendo F. Guimarães

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UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods by Minghu Zhao, Dashuai Wang, Qing Yan, Zhuolin Li, Xiaoguang Liu

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Enhancing Security in Industrial IoT Networks: Machine Learning Solutions for Feature Selection and Reduction by Ahmad Houkan, Ashwin Kumar Sahoo, Sarada Prasad Gochhayat, Prabodh Kumar Sahoo, Haipeng Liu, Syed Ghufran Khalid, Prince Jain

“…Six machine learning algorithms—Decision Trees, k-nearest neighbors, Gaussian Support Vector Machine, Neural Network, Support Vector Machines kernel, and Logistic Regression Kernel—were evaluated for both binary and multi-class classification using feature sets of 4, 12, 23, 50, and 79 features. …”
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Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data by Haniyeh Rafiepoor, Alireza Ghorbankhanloo, Kazem Zendehdel, Zahra Zangeneh Madar, Sepideh Hajivalizadeh, Zeinab Hasani, Ali Sarmadi, Behzad Amanpour‐Gharaei, Mohammad Amin Barati, Mozafar Saadat, Seyed‐Ali Sadegh‐Zadeh, Saeid Amanpour

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Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer’s disease biomarkers by Christoffer Ivarsson Orrelid, Oscar Rosberg, Sophia Weiner, Fredrik D. Johansson, Johan Gobom, Henrik Zetterberg, Newton Mwai, Lena Stempfle

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Influence of Cryogenic Treatment of Cutting Tools on the Machinability Characteristics of Materials: A Comprehensive Review by Shahnaza Akhter, M. Jebran Khan, M.F. Wani, Mohammad Arif Parray, Shuhaib Mushtaq

“…The cryogenic engineering is a vast and important field of engineering. …”
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Machine Learning Approach to Aerodynamic Analysis of NACA0005 Airfoil: ANN and CFD Integration by Taiba Kouser, Dilek Funda Kurtulus, Srikanth Goli, Abdulrahman Aliyu, Imil Hamda Imran, Luai M. Alhems, Azhar M. Memon

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Comparative study on machinability and surface integrity of γ-TiAl alloy in laser assisted milling by Yada Chi, Zexuan Dong, Minchao Cui, Chenwei Shan, Yifeng Xiong, Dinghua Zhang, Ming Luo

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EEMLCR: Energy-Efficient Machine Learning-Based Clustering and Routing for Wireless Sensor Networks by Muhammad Akram, Sibghat Ullah Bazai, Muhammad Imran Ghafoor, Saira Akram, Qazi Mudassar Ilyas, Abid Mehmood, Sajid Iqbal, Muhammad Asim Rafique

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Google Earth Engine-based Mangrove Mapping and Change Detections for Sustainable Development in Tien Yen District, Quang Ninh Province, Vietnam by M. H. Nguyen, N. T. Nguyen, G. Y. I. Ryadi, M. V. Nguyen, T. L. Duong, C.-H. Lin, T. B. Nguyen

“…Four supervised classification algorithms, including Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes classifier, and Classification and Regression Trees (CART) have been implemented on GEE platform to select the best algorithm to produce spatial-temporal mangrove maps, then change detection of mangroves is performed. …”
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Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

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Comparative Study of Dual- and Single-Rotor Radial-Flux Fractional-Slot PM Machines by Zhitong Ran, Zi-Qiang Zhu

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Machine learning modeling for the risk of acute kidney injury in inpatients receiving amikacin and etimicin by Pei Zhang, Qiong Chen, Jiahui Lao, Juan Shi, Jia Cao, Xiao Li, Xin Huang

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Integration of Probability Maps into Machine Learning Models for Enhanced Crack Segmentation in Concrete Bridges by Volodymyr Tyvoniuk, Roman Trach, Yuliia Trach

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Comparative Analysis of Inner and Outer Rotor Surface PM Machines Based on Optimization Dataset by Dong Myeong Choi, Seun Guy Min

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Robust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets by Inam Abousaber, Haitham F. Abdallah, Hany El-Ghaish

“…However, class imbalances, where non-diabetic cases dominate, can significantly affect machine learning model performance, leading to biased predictions and reduced generalization.MethodsA novel predictive framework employing cutting-edge machine learning algorithms and advanced imbalance handling techniques was developed. …”
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A comprehensive review of AI and machine learning techniques in antenna design optimization and measurement by Pradnya A. Gajbhiye, Satya P. Singh, Madan Kumar Sharma

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Interpreting machine learning models based on SHAP values in predicting suspended sediment concentration by Houda Lamane, Latifa Mouhir, Rachid Moussadek, Bouamar Baghdad, Ozgur Kisi, Ali El Bilali

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A machine learning model for hub-height short-term wind speed prediction by Zongwei Zhang, Lianlei Lin, Sheng Gao, Junkai Wang, Hanqing Zhao, Hangyi Yu

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Comparative Analysis of Machine Learning Models for Predicting Contaminant Concentration Distributions in Hospital Wards by Chonggang Zhou, Yunfei Ding

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