Retracted: Popular Song Composition Based on Deep Learning and Neural Network by Journal of Mathematics

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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…Machine learning methods open up great opportunities in predicting the rheological parameters of polymers. …”
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Machine learning-based equations for improved body composition estimation in Indian adults. by Nick Birk, Bharati Kulkarni, Santhi Bhogadi, Aastha Aggarwal, Gagandeep Kaur Walia, Vipin Gupta, Usha Rani, Hemant Mahajan, Sanjay Kinra, Poppy A C Mallinson

“…However, existing equations for body composition based on BIA measures may not generalize well to all populations. …”
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A statistical and machine learning approach for monthly precipitation forecasting in an Amazon city by Ewerton Cristhian Lima de Oliveira, Eduardo Costa de Carvalho, Edmir dos Santos Jesus, Rafael de Lima Rocha, Rafael de Lima Rocha, Helder Moreira Arruda, Ronnie Cley de Oliveira Alves, Ronnie Cley de Oliveira Alves, Renata Gonçalves Tedeschi

“…Additionally, we use meteorological data from a set of sensors installed at a meteorological station located in Belém to train multivariate statistical and machine learning (ML) models to predict precipitation. Besides the use of algorithms, another evaluation was conducted on Feature Composition based on statistical methods to investigate the impact of variables on the prediction.ResultsThe results obtained in our investigation indicate that the vector autoregressive moving average with exogenous regressors (VARMAX) model achieved the best performance in rainfall forecasting, with an average root mean square error (RMSE) of 9.1833 in time series cross-validation, outperforming the other models.DiscussionThe climate-driven patterns directly influenced the performance of the rainfall forecasting models evaluated in this study. …”
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Deep Learning in Music Generation: A Comprehensive Investigation of Models, Challenges and Future Directions by Kong Xiangchen

“…Transformer models, like MUSICGEN and STEMGEN, handle large amounts of data and dependencies efficiently, but they need a lot of computational resources. Reinforcement Learning models, such as MusicRL, combine human feedback to fine-tune AI-generated compositions based on the individual's preferences. …”
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Transcriptomic analysis and machine learning modeling identifies novel biomarkers and genetic characteristics of hypertrophic cardiomyopathy by Feng Zhang, Chunrui Li, Lulu Zhang

“…A predictive model for HCM was developed through systematic evaluation of 113 combinations of 12 machine-learning algorithms, employing 10-fold cross-validation on training datasets and external validation using an independent cohort (GSE180313).ResultsA total of 271 DEGs were identified, primarily enriched in multiple biological pathways. …”
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Inversion of Aerosol Chemical Composition in the Beijing–Tianjin–Hebei Region Using a Machine Learning Algorithm by Baojiang Li, Gang Cheng, Chunlin Shang, Ruirui Si, Zhenping Shao, Pu Zhang, Wenyu Zhang, Lingbin Kong

“…We then established models of aerosol chemical composition based on a machine learning algorithm. By comparing the inversion accuracies of single models—namely MLR (Multivariable Linear Regression) model, SVR (Support Vector Regression) model, RF (Random Forest) model, KNN (K-Nearest Neighbor) model, and LightGBM (Light Gradient Boosting Machine)—with that of the combined model (CM) after selecting the optimal model, we found that although the accuracy of the KNN model was the highest among the other single models, the accuracy of the CM model was higher. …”
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Multiscale computational framework linking alloy composition to microstructure evolution via machine learning and nanoscale analysis by Jaemin Wang, Hyeonseok Kwon, Sang-Ho Oh, Jae Heung Lee, Dae Won Yun, Hyungsoo Lee, Seong-Moon Seo, Young-Soo Yoo, Hi Won Jeong, Hyoung Seop Kim, Byeong-Joo Lee

“…Machine learning models trained on 750,000 CALPHAD-derived datapoints enabled rapid screening of two billion compositions based on thermodynamic criteria. …”
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Research on predicting the thermocompression deformation behavior of Mg–Li matrix composite using machine learning and traditional techniques by Dandan Li, Xiaoyu Hou, Yangfan Liu, Linhao Gu, Jinhui Wang, Jiaxuan Ma, Xiaoqiang Li, Zhi Jia, Qichi Le, Dexue Liu, Xincheng Yin

“…In this study, the Al3La/LAZ532 composite based on in-situ self-reaction technology was successfully prepared by adding La2O3 particles. …”
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Machine learning assisted design of low-carbon aluminosilicate cementitious composites with diverse raw materials and target mechanical strength by Jinyang Jiang, Yi Liu, Junlin Lin, Tao Yang, Fengjuan Wang

“…This study proposes a machine learning assisted design framework for the aluminosilicate cementitious composites based on the data extracted from hundreds of relevant literatures in recent five years. …”
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Machine Learning-Driven Prediction of Glass-Forming Ability in Fe-Based Bulk Metallic Glasses Using Thermophysical Features and Data Augmentation by Renato Dario Bashualdo Bobadilla, Marcello Baricco, Mauro Palumbo

“…In this study, we developed machine learning (ML) models to predict the critical casting diameter (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>D</mi><mrow><mi>m</mi><mi>a</mi><mi>x</mi></mrow></msub></semantics></math></inline-formula>) of Fe-based BMGs, enabling rapid assessment of glass-forming ability (GFA) using composition-based and calculated thermophysical features. …”
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COMPARATIVE ANALYSIS OF CLASSIFICATION MODELS FOR DETERMINING THE QUALITY OF WINE BY ITS CHEMICAL COMPOSITION by Vladimir S. Repkin, Artemy V. Li, Grigory Yu. Semenov, Nikita I. Sermavkin, Alexander S. Kovalenko, Nikolai S. Egoshin

“…The purpose of the research is to create a system for automated assessment of wine quality by its chemical composition based on a classification model that provides better compliance with the reference data set. …”
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Improving the Universal Performance of Land Cover Semantic Segmentation Through Training Data Refinement and Multi-Dataset Fusion via Redundant Models by Jae Young Chang, Kwan-Young Oh, Kwang-Jae Lee

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The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department by Evan S. Bradley, Celina Stansky, Abigail L. Zeamer, Ziyuan Huang, Lindsey Cincotta, Abigail Lopes, Linda Potter, Theresa Fontes, Doyle V. Ward, Vanni Bucci, Beth A. McCormick, John P. Haran

“…Positive UA samples showed significantly lower alpha diversity (2.29 versus 0.086, p < 0.01) and distinct community composition based on beta-diversity (PERMANOVA on Bray-Curtis distance p < 0.01). …”
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Accelerating materials property prediction via a hybrid Transformer Graph framework that leverages four body interactions by Mohammad Madani, Valentina Lacivita, Yongwoo Shin, Anna Tarakanova

“…We propose a framework utilizing a Graph Neural Network with composition-based and crystal structure-based architectures, combined with a transfer learning scheme. …”
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Automatic Integrated Scoring Model for English Composition Oriented to Part-Of-Speech Tagging by Fei Chen

“…Therefore, this paper proposes an automatic scoring model for English composition based on article part-of-speech tagging. First, use the convolutional neural network to extract the word information from the character level and use this part of the information in the coarse-grained learning layer. …”
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Linking Animal Feed Formulation to Milk Quantity, Quality, and Animal Health Through Data-Driven Decision-Making by Oreofeoluwa A. Akintan, Kifle G. Gebremedhin, Daniel Dooyum Uyeh

“…Leveraging advanced analytical techniques, such as machine learning and optimization algorithms, have created highly accurate feed formulations tailored to specific livestock needs. …”
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The impact of artificial intelligence on accounting practices: an academic perspective by Talal Fawzi Alruwaili, Mahfoudh Hussein Mgammal

“…Using structured surveys and composite-based structural equation modeling (SEM) with the ADANCO approach, the research evaluates accounting academics’ knowledge, attitudes, and practices (KAP) regarding-AI. …”
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Romani Music Collections, the Ruptured Archive, and Epistemic Justice in the United States by Ian MacMillen

“… Creating collections and archives of genres such as csardas, parallel to holdings of Romantic compositions based on those styles, affords a means for contemporary Romani performance to provoke institutional recognition of Roma’s historical influence on art music. …”
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