Enhancing river and lake wastewater reuse recommendation in industrial and agricultural using AquaMeld techniques by J. Priskilla Angel Rani, C. Yesubai Rubavathi

“…This study uses AquaMeld and Multi-Layer Perceptron with Recurrent Neural Network (MLP-RNN) algorithms to create a complete recommendation system. …”
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Structural and social determinants of health: The multi-ethnic study of atherosclerosis. by Lilah M Besser, Sarah N Forrester, Milla Arabadjian, Michael P Bancks, Margaret Culkin, Kathleen M Hayden, Elaine T Le, Isabelle Pierre-Louis, Jana A Hirsch

“…Forty-seven (11%) of the papers combined MESA with other cohorts for cross-cohort comparisons and replication/validation (e.g., validating algorithms).<h4>Conclusions</h4>Overall, MESA has made significant contributions to the field and the published literature, with 20% of its published papers focused on SSDOH. …”
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Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks by Ahmad Almadhor, Shtwai Alsubai, Imen Bouazzi, Vincent Karovic, Monika Davidekova, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…It is common for these systems to be constructed using conventional machine learning algorithms. So many common signs of attacks are ignored. …”
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Image-based maturity detection for selective cauliflower harvesting in field condition by Ajay Kushwah, P.K. Sharma, H.L. Kushwaha, Brij Bihari Sharma, Naseeb Singh, Ramineni Harsha Nag, Manojit Chowdhury, Nrusingh Charan Pradhan, Gopal Carpenter, Silpa Mandal, Ali Salem

“…To achieve optimal segmentation performance with the developed algorithms, threshold values were optimized using the response surface methodology technique. …”
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Evaluating multitemporal vegetation indices from Zhuhai-1 hyperspectral images for detecting a rapidly spreading invasive species - Spartina alterniflora by Yuanhui Zhu, Soe W. Myint, Jingjing Cao, Kai Liu, Mei Zeng, Chenxi Diao

“…Monitoring the spatiotemporal changes of Spartina alterniflora (SA) is essential in effectively managing coastal ecology since it is one of the most harmful invasive weeds worldwide. …”
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Tax obligation fulfillment by A. V. Krasyukov

“…This mechanism is a set of algorithms for the behavior of subjects of tax liability, defined by law, using specific legal means. …”
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GBM-Reservoir: Brain tumor (Glioblastoma Multiforme) MRI dataset collection with ground truth segmentation masksfigshare by Naida Solak, André Ferreira, Gijs Luijten, Behrus Puladi, Victor Alves, Jan Egger

“…This dataset can be utilized for various tasks, such as developing fully automated segmentation algorithms for new, unseen brain tumor cases, particularly through deep learning-based approaches, since ground truth is provided for each sample.…”
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Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning by Lin Song, Xingwei Wu, Mengjia Xu, Ling Xue, Xun Yu, Zongqi Cheng, Chenrong Huang, Liyan Miao

“…Meanwhile, correlation analysis and recursive feature elimination were used for feature screening before machine learning model development. Then fifteen algorithms were used to establish models, and an ensemble model was established through soft voting based on the top five performance algorithms. …”
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Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability by Danish Raza, Hong Shu, Muhsan Ehsan, Hong Fan, Kamal Abdelrahman, Hasnat Aslam, Abdul Quddoos, Rana Waqar Aslam, Majid Nazeer, Mohammed S. Fnais, Azeem Sardar

“…First, by incorporating more than three decades of satellite data (1990–2022) and different Landsat missions with machine learning algorithms, high-confidence classes were defined for different land features, including cropland. …”
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Design and refinement of a clinical trial staffing model within the evolving landscape of oncology clinical trials by Ellen Siglinsky, Hannah Phan, Silviya Meletath, Amber Neal, David E. Gerber, Asal Rahimi, Erin L. Williams

“…Methods: To address individual protocol acuity, the model's algorithms include metrics to account for visit frequency, and the quantity, and types of research-related procedures. …”
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Nurse management of minor problems in primary care emergencies: a non-randomized controlled trial by Jordi Estarlich-Corominas, Neus Soler-Abril, Anna Casanellas-Chuecos, Sara Becerra-Corzo, Andrea Sofia Bianco, Pere Torán-Monserrat, Rosa García-Sierra

“…Nurse resolution capacity, after applying algorithms, offered quality care, with fewer prescriptions and good patient satisfaction without increasing the total number of consultations due to the same problem. …”
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Research trends and prospects in global riverine carbon fluxes: A bibliometric analysis by Wei Fang, Mohd Remy Rozainy Mohd Arif Zainol, Xianbao Zha, Pingping Luo

“…Research on RCFs has sharply increased since 2009, with an average annual publication number of 115. …”
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Trading off Iodine and Radiation Dose in Coronary Computed Tomography by Guillaume Fahrni, Thomas Saliba, Damien Racine, Marianna Gulizia, Georgios Tzimas, Chiara Pozzessere, David C. Rotzinger

“…Coronary CT angiography (CCTA) has seen steady progress since its inception, becoming a key player in the non-invasive assessment of coronary artery disease (CAD). …”
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Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks? by Jowaria Khan, Rana Elfakharany, Hiba Saleem, Mahira Pathan, Emaan Shahzad, Salam Dhou, Fadi Aloul

“…Several machine learning algorithms are considered, namely Decision Tree (DT), K-Nearest Neighbors (KNN), Naïve Bayes (NB), Support Vector Machine (SVM), Light Gradient-Boosting Machine (LGBM), Extreme Gradient Boosting (XGB) and Random Forest (RF). …”
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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

“…By establishing a multi-level classification framework that included traditional statistical models (such as ARIMA), ML models (such as SVM), deep learning (DL) models (such as CNN, LSTM), ensemble learning methods (such as AdaBoost), and hybrid models (such as the fusion architecture of intelligent optimization algorithms and neural networks), it revealed that the hybrid modelling strategy effectively improved the prediction accuracy of the model through feature combination optimization and model cascade integration. …”
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Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…These models were trained based on different datasets, and their hyper-parameters were optimized using algorithms such as grid search, Bayesian optimization, and K-fold cross-validation. …”

Deep sea spy: An online citizen science annotation platform for science and ocean literacy by Marjolaine Matabos, Pierre Cottais, Riwan Leroux, Yannick Cenatiempo, Charlotte Gasne-Destaville, Nicolas Roullet, Jozée Sarrazin, Julie Tourolle, Catherine Borremans

“…Although deep learning offers an alternative to human processing, training algorithms requires large annotated reference datasets. …”
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Prediction of microbe-drug associations using a CNN-Bernoulli random forest model by Zihao Song, Qingnuo Li, Jincheng Zhao, Qinggang Bu, Zekang Bian, Jia Qu

“…The dual use of the Bernoulli distribution in BRF ensures algorithmic consistency and contributes to superior performance. …”
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A New Approach to Characterize Superplastic Materials from Free-Forming Test and Inverse Analysis by Gillo Giuliano, Wilma Polini

“…It allows for a reduction in the number of constants needed to determine the material constitutive equation, thus requiring low simulation time compared to models that adopt the multiple-objective optimization based on genetic algorithms (GAs). It is more suitable to be used in the industrial field. …”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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