A Two-Stage Feature Selection Approach for Fruit Recognition Using Camera Images With Various Machine Learning Classifiers by Tri Tran Minh Huynh, Tuan Minh Le, Long Ton That, Ly Van Tran, Son Vu Truong Dao

“…Fruit and vegetable identification and classification system is always necessary and advantageous for the agriculture business, the food processing sector, as well as the convenience shops and hypermarkets where these products are sold. …”
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Enhancing drilling performance in 3D printed PLA implants application of PIV and ML models by K Shunmugesh, M Ganesh, R Bhavani, M. Adam Khan, M. Saravana Kumar, L. Rajeshkumar, Priyanka Mishra, Rajesh Jesudoss Hynes Navasingh, Angela Jennifa Sujana J, Jana Petru, Čep Robert

“…This work employs the Proximity Indexed Value (PIV) tool to predict the near-optimal value for improving hole quality and enhancing the drilling process. In addition, Artificial neural network (ANN), Support vector machine (SVM), and Random Forest (RF) models were employed to predict the optimized results by PIV method. …”
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Machine learning aided UV absorbance spectroscopy for microbial contamination in cell therapy products by Shruthi Pandi Chelvam, Alice Jie Ying Ng, Jiayi Huang, Elizabeth Lee, Maciej Baranski, Derrick Yong, Rohan B. H. Williams, Stacy L. Springs, Rajeev J. Ram

“…This method leverages a one-class support vector machine to analyse the absorbance spectra of cell cultures and predict if a sample is sterile or contaminated. …”
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Human spinal cord activation during filling and emptying of the bladder by Kofi A. Agyeman, Darrin J. Lee, Aidin Abedi, Sofia Sakellaridi, Evgeniy I. Kreydin, Jonathan Russin, Yu Tung Lo, Kevin Wu, Wooseong Choi, Sumant Iyer, V. Reggie Edgerton, Charles Y. Liu, Vassilios N. Christopoulos

“…Abstract The spinal cord is essential for processing sensory information and regulating autonomic functions, such as bladder control, which is critical for urinary continence and voiding. …”
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A 100-degree lithospheric magnetic field model constructed using MSS-1, Swarm-A, and CHAMP satellite data by JiaXuan Zhang, Yan Feng, Pan Zhang, YuXuan Lin, XinWu Li, Ya Huang

“…Subsequently, orbit-by-orbit processing was applied to both scalar and vector data, such as spherical harmonic high-pass filtering, singular spectrum analysis, and line leveling, to suppress noise and residual signals along the satellite tracks. …”
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An efficient retrieval method on Google Earth Engine and comparison with hybrid methods: a case study of leaf area index retrieval by Sijia Li, Zhiguang Tang, Kaisen Ma, Zhenyi Wang, Wenjuan Li

“…The performances of LUT and hybrid methods, including random forest (RF), gradient boosting regression tree (GBRT), classification and regression tree (CART), support vector regression (SVR), and Gaussian process regression (GPR), were evaluated on GEE by simulation experiments. …”
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Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms by Arunadevi M, Karthikeyan B, Anirudh Shrihari, Saravanan S, Sundararaju K, R Palanisamy, Mohamed Awad, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Hany S. Hussein, Mahmoud M. Hussein, Ahmed I. Omar

“…Different MLAs are modelled to explore the PEMFC performance and results proved that gradient boosting regression provides better predictions compared to other algorithms such as decision tree regressor, support vector machine regressor, and random forest regression.…”
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Predicting Predisposition to Tropical Diseases in Female Adults Using Risk Factors: An Explainable-Machine Learning Approach by Kingsley Friday Attai, Constance Amannah, Moses Ekpenyong, Said Baadel, Okure Obot, Daniel Asuquo, Ekerette Attai, Faith-Valentine Uzoka, Emem Dan, Christie Akwaowo, Faith-Michael Uzoka

“…Most studies have focused on vector control measures, such as insecticide-treated nets and time series analysis, often neglecting emerging yet critical risk factors vital for effectively preventing febrile diseases. …”
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On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

“…The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. …”
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Enhanced Performance by Time-Frequency-Phase Feature for EEG-Based BCI Systems by Baolei Xu, Yunfa Fu, Gang Shi, Xuxian Yin, Zhidong Wang, Hongyi Li, Changhao Jiang

“…Support vector machines (SVMs) and extreme learning machines (ELMs) are compared for classification between clench speed and clench force motor imagery using the optimized feature. …”
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Medium and short-term load forecasting based on NPMA-LSSVM algorithm in the case of unbalance and minority sample data by YANG Qiuyu, KUANG Shusen, ZHENG Xiaogang, YE Guoqi, ZHANG Zhongxin

“…Finally, the least square support vector machine (LSSVM) load forecasting model is established, and the improved mayfly algorithm with nonlinear inertia factor and polynomial variation is used to optimize the model parameters to achieve accurate load forecasts. …”
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Detection of Psychomotor Retardation in Youth Depression: A Machine Learning Approach to Kinematic Analysis of Handwriting by Vladimir Džepina, Nikola Ivančević, Sunčica Rosić, Blažo Nikolić, Dejan Stevanović, Jasna Jančić, Milica M. Janković

“…The feature selection process revealed that velocity-related features were most effective in distinguishing patients with depression from controls, expectedly reflecting a slowdown in psychomotor functioning among the patients. …”
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Rapid Nondestructive Detection of Welsh Onion, Onion, and Chinese Chives Seeds Based on Hyperspectral Imaging Technology by Sisi Zhao, Danqi Zhao, Jiangping Song, Huixia Jia, Xiaohui Zhang, Wenlong Yang, Haiping Wang

“…Four classification models, Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbor (KNN), were used to classify seeds quickly and accurately. …”
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N-dimensional Lomb Scargle Periodogram analysis of traveling ionospheric disturbances using ionosonde data by Joe Hughes, Ian Collett, Anastasia Newheart, Ryan Kelly, Walter Junk Wilson, Ken Obenberger, Russell Landry, Jonah Colman, Joe Malins

“…The ND LSP resolves the full 3-dimensional wave vector as well as the period for many discrete TIDs. …”
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Research on Reservoir Identification of Gas Hydrates with Well Logging Data Based on Machine Learning in Marine Areas: A Case Study from IODP Expedition 311 by Xudong Hu, Wangfeng Leng, Kun Xiao, Guo Song, Yiming Wei, Changchun Zou

“…This article selects six ML methods, including Gaussian process classification (GPC), support vector machine (SVM), multilayer perceptron (MLP), random forest (RF), extreme gradient boosting (XGBoost), and logistic regression (LR). …”
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A comparative study of the microbiomes of the ticks Rhipicephalus microplus and Hyalomma anatolicum by Abbasi Adeel Mumtaz, Nasir Shiza, Bajwa Amna Arshad, Akbar Haroon, Ali Muhammad Muddassir, Rashid Muhammad Imran

“…Hyalomma anatolicum and Rhipicephalus microplus are tick species that are important vectors of numerous pathogens affecting both humans and livestock. …”
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Copy-Move Forgery Detection Technique Using Graph Convolutional Networks Feature Extraction by Varun Shinde, Vineet Dhanawat, Ahmad Almogren, Anjanava Biswas, Muhammad Bilal, Rizwan Ali Naqvi, Ateeq Ur Rehman

“…In proposed methodology, we utilized Support Vector machine (SVM) for classification and the binary cross-entropy loss, and the Adam optimizer for improving accuracy. …”
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A comparative performance analysis of machine learning models for compressive strength prediction in fly ash-based geopolymers concrete using reference data by Muhammad Kashif Anwar, Muhammad Ahmed Qurashi, Xingyi Zhu, Syyed Adnan Raheel Shah, Muhammad Usman Siddiq

“…This study will have made attempt to address the complexities involves in the concrete mix designs process with the aim of achieving the desired 28-day compressive strength for FAGP. …”
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Research on Rapid and Non-Destructive Detection of Coffee Powder Adulteration Based on Portable Near-Infrared Spectroscopy Technology by Fujie Zhang, Xiaoning Yu, Lixia Li, Wanxia Song, Defeng Dong, Xiaoxian Yue, Shenao Chen, Qingyu Zeng

“…Spectral data from adulterated coffee samples in the 900–1700 nm range were collected and processed using five preprocessing methods. For qualitative detection, the Support Vector Machine (SVM) algorithm was applied. …”
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A Comparative Study of Machine Learning Models for Accurate E-Waste Prediction by Mohammed Algafri, Mohammed Sayad, Mohammad A.M. Abdel-Aal, Ahmed M. Attia

“…This study evaluates six Machine Learning (ML) models, Linear Regression, Regression Tree, Support Vector Regression, Ensemble Regression, Gaussian Process Regression (GPR), and Artificial Neural Networks, for e-waste forecasting. …”
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