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

“…In this context, research activities aimed at an automated objective assessment of the quality of wine in terms of its chemical composition using machine learning methods seem to be relevant. …”
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Graph neural networks for mechanical property prediction of 2D fiber composites by Erdem Caliskan, Reza Abedi, Massimiliano Lupo Pasini

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MixtureMetrics: A comprehensive package to develop additive numerical features to describe complex materials for machine learning modeling by Rahil Ashtari Mahini, Gerardo Casanola-Martin, Simone A. Ludwig, Bakhtiyor Rasulev

“…Multi-component materials/compounds and polymeric/composite systems pose structural complexity that challenges the conventional methods of molecular representation in cheminformatics, which have limited applicability in such cases. …”
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The state-of-the-art review on biochar as green additives in cementitious composites: performance, applications, machine learning predictions, and environmental and economic implic... by Ping Ye, Binglin Guo, Huyong Qin, Cheng Wang, Yang Liu, Yuyang Chen, Pengfei Bian, Di Lu, Lei Wang, Weiping Zhao, Yonggan Yang, Li Hong, Peng Gao, Peiyong Ma, Binggen Zhan, Qijun Yu

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A deep learning sex-specific body composition ageing biomarker using dual-energy X-ray absorptiometry scan by Jie Lian, Pei Cai, Fan Huang, Jianpan Huang, Varut Vardhanabhuti

“…Methods A deep learning model was trained on a reference population from the UK Biobank to estimate body composition biological age (BCBA). …”
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Corrosion resistance prediction of high-entropy alloys: framework and knowledge graph-driven method integrating composition, processing, and crystal structure by Guangxuan Song, Dongmei Fu, Yongjie Lin, Lingwei Ma, Dawei Zhang

“…Abstract The prediction of corrosion resistance in High-entropy alloys (HEAs) faces challenges due to previous machine learning methods not fully capturing the interdependencies between composition, processing, and crystal structure. …”
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Student modelling in a web-based platform for learning games composing by V. Atanasov, I. Ivanova

“…Purpose: The main goal of this research is to introduce an approach of student modeling in a WEB based platform for learning games composing. Methods: As a theoretical background of the proposed model is used a didactical model of learning game, developed by the authors. …”
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Deep learning based segmentation of binder and fibers in gas diffusion layers by Andreas Grießer, Rolf Westerteiger, Erik Glatt, Hans Hagen, Andreas Wiegmann

“…To overcome this, we introduce a machine learning-based method that segments fibers and binder from the local morphology of a CCCP. …”
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Stock Price Pattern Prediction Based on Complex Network and Machine Learning by Hongduo Cao, Tiantian Lin, Ying Li, Hanyu Zhang

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Process simulations of fiber reinforced polymer composites towards AI ages by ZHOU Yubo, LI Min, WANG Shaokai, GU Yizhuo, TAO Fei, CHEN Xiangbao, ZHANG Zuoguang

“…Computer-based process simulation plays a significant role in improving the manufacturing quality of composite components and reducing the manufacturing cost. …”
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A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling by Pujie Han, Wentao Hu, Zhengjun Zhai, Min Huang

“…This paper proposes a model-based optimization method for ARINC 653 multicore partition scheduling. …”
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Damage Identification of Conduit Rack in Offshore Platform Structures Based on a Novel Composite Neural Network by Jiaqiang Yan, Yuanchao Qiu, Renhe Shao, Ziqiao Ling, Ruixiang Zhang

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Unlocking chickpea flour potential: AI-powered prediction for quality assessment and compositional characterisation by Ali Zia, Muhammad Husnain, Sally Buck, Jonathan Richetti, Elizabeth Hulm, Jean-Philippe Ral, Vivien Rolland, Xavier Sirault

“…The growing demand for sustainable, nutritious, and environmentally friendly food sources has placed chickpea flour as a vital component in the global shift to plant-based diets. However, the inherent variability in the composition of chickpea flour, influenced by genetic diversity, environmental conditions, and processing techniques, poses significant challenges to standardisation and quality control. …”
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A Signal-Based Data Fusion Approach in Non-DestructiveTesting of Composite Materials in the Aerospace Industry by Tom Avikasis Cohen, Anna Brook

“…Despite its sensitivity to stress-induced anomalies in composites, it requires a stable environment due to susceptibility to vibrations. …”
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A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

“…However, the existing CS ISAR imaging methods based on deep learning (DL) mainly focus on improving the performance of the reconstruction algorithm while ignoring the potential room for improvement given by the design of the measurement matrix. …”
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Triboinformatic analysis and prediction of B4C and granite powder filled Al 6082 composites using machine learning regression models by Amit Aherwar, Anamika Ahirwar, Vimal Kumar Pathak

“…To address these challenges, machine learning (ML) has emerged as a potent approach in predicting the mechanical and tribological behavior of advanced materials, including Al-based composites. …”
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A Hybrid LMD–ARIMA–Machine Learning Framework for Enhanced Forecasting of Financial Time Series: Evidence from the NASDAQ Composite Index by Jawaria Nasir, Hasnain Iftikhar, Muhammad Aamir, Hasnain Iftikhar, Paulo Canas Rodrigues, Mohd Ziaur Rehman

“…It incorporates LMD (Local Mean Decomposition), SD (Signal Decomposition), and sophisticated machine learning methods. The framework for the NASDAQ Composite Index begins by decomposing the original time series into stochastic and deterministic components using the LMD approach. …”
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BioCompNet: A Deep Learning Workflow Enabling Automated Body Composition Analysis toward Precision Management of Cardiometabolic Disorders by Jianyong Wei, Hongli Chen, Lijun Yao, Xuhong Hou, Rong Zhang, Liang Shi, Jianqing Sun, Cheng Hu, Xiaoer Wei, Weiping Jia

“…Growing evidence highlights the importance of body composition (BC), including bone, muscle, and adipose tissue (AT), as a critical biomarker for cardiometabolic risk stratification. …”
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Eco-anxiety and a Desire for Hope: A Composite Article on the Impacts of Climate Change in Environmental Education by Scott Jukes, Robyn Fox, David Hills, Peta J. White, Joseph Paul Ferguson, Amrita Kamath, Marianne Logan, Kathryn Riley, David Rousell, Sandra Wooltorton, Hilary Whitehouse

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Enhanced convolutional neural networks for defect detection in fiber-reinforced composites: a hyperparameter optimization approach by Pankaj Beldar, Rasika Chandramore, Sarika Jagtap, Dipali Bendale

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