Deep Mining on the Formation Cycle Features for Concurrent SOH Estimation and RUL Prognostication in Lithium-Ion Batteries by Dongchen Yang, Weilin He, Xin He

“…By integrating diverse datasets with advanced algorithms and models, we perform correlation analyses of parameters such as capacity, voltage, temperature, pressure, and strain, enabling precise SOH estimation and RUL prediction. …”
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Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma by Yun Liang, Yun Liang, Min He, Wenqing Chen, Wenqing Chen, Lizhen Li, Lizhen Li, Yumeng Dong, Yumeng Dong, Gang Liang, Hui Huangfu, Zengyu Jiang, Zengyu Jiang, Sheng He, Sheng He, Sheng He

“…Radiomics features were extracted from CT images, and 7 machine learning algorithms were used to develop 7 radiomics models, which were combined with deep learning features extracted from the ResNet50 deep learning network to form deep learning radiomics (DLR) models. …”
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Research on the Virtual Coupling Technology for Urban Rail Transit Trains by YANG Weifeng, LEI Chengjian, HAN Chen, LI Qihe, XIE Xing

“…The paper additionally highlights the technical challenges faced in engineering applications, including the need for improved cooperative control algorithms, enhanced vehicle-to-vehicle communication mechanisms, and optimized safety braking models.…”
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Software and methodological support for additional professional courses: ideas, problems, monitoring by O. D. Prokhorenko, S. V. Morin, O. A. Kozyreva

“…By building prospects for theorizing and implementing ideas for improving the quality of modeling and using software and methodological support for further education courses, we can distinguish in the integrative representation of the direction and prospects of an individual’s achievements three types of solving professional and pedagogical problems theorized in the work (algorithmic, creative-stimulative and innovative-promising).…”
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Research on Hybrid Wind Speed Prediction System Based on Artificial Intelligence and Double Prediction Scheme by Ying Nie, He Bo, Weiqun Zhang, Haipeng Zhang

“…Regarding point prediction in the developed double prediction system, a novel nonlinear integration method based on a backpropagation network optimized using the multiobjective evolutionary algorithm based on decomposition was successfully implemented to derive the final prediction results, which enable further improvement of the accuracy of point prediction. …”
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Multiobjective Synchronous Control of Heavy-Duty Vehicles Based on Longitudinal and Lateral Coupling Dynamics by Yongjie Lu, Tongtong Wang, Hangxing Zhang

“…But the vertical and lateral dynamics equations and controls system of the vehicle are always independent of each other, and the multiobjective control is generally achieved through the coordination of control algorithms. In this paper, taking the dynamic load of the tire as a link, the vertical dynamic model and the lateral dynamic model of heavy-duty vehicle are coupled. …”
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CTAB modified SnO₂ PEDOT PSS heterojunction humidity sensor with enhanced sensitivity stability and machine learning evaluation by Poundoss Chellamuthu, Kirubaveni Savarimuthu, M Gulam Nabi Alsath, R. Krishnamoorthy, Yuvaraj T, Feras Alnaimat, Mohammad Shabaz

“…Furthermore, to validate real-time application feasibility, machine learning (ML) algorithms were implemented to model and predict sensor behavior. …”
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Ensemble Transformer–Based Detection of Fake and AI–Generated News by Md. Ishraquzzaman, Mohammed Ashraful Islam Chowdhury, Shahreen Rahman, Riasat Khan

“…The proposed ensemble model is optimized by applying model pruning (reducing parameters from 265M to 210M, improving training time by 25%) and dynamic quantization (reducing model size by 50%, maintaining 95.68% accuracy), enhancing scalability and efficiency while minimizing computational overhead. …”
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The Heart of Transformation: Exploring Artificial Intelligence in Cardiovascular Disease by Mohammed A. Chowdhury, Rodrigue Rizk, Conroy Chiu, Jing J. Zhang, Jamie L. Scholl, Taylor J. Bosch, Arun Singh, Lee A. Baugh, Jeffrey S. McGough, KC Santosh, William C.W. Chen

“…We analyze and discuss commonly used AI and ML models, algorithms, and methodologies, highlighting their roles in improving clinical outcomes while addressing current limitations and future clinical applications. …”
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Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results by Andy Victor Pakpahan, Fahmi Reza Ferdiansyah, Robby Gustian, Muhammad Nur Faiz, Sukma Aji

“…This research seeks to improve sentiment analysis performance by implementing a stacking ensemble learning approach, which combines the predictive strengths of several base models. …”
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Experimental Study on Glass Deformation Calculation Using the Holographic Interferometry Double-Exposure Method by Yucheng Li, Yang Zhang, Deyu Jia, Song Gao, Muqun Zhang

“…This approach (1) eliminates object wave amplitude interference via dual-exposure superposition, establishing submicron linear mapping between fringe displacement and deformation amplitude; (2) introduces a fringe gradient-based direction detection algorithm resolving deformation vector ambiguity; and (3) implements an error-compensated fusion framework integrating theoretical modeling, MATLAB 2015b simulations, and experimental validation. …”
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The innovation path of VR technology integration into music classroom teaching in colleges and universities by Yupeng Han, Lin Han, Chun Zeng, Wei Zhao

“…To explore these possibilities, this study proposes an Intelligent Interactive Music Teaching (IIMT) model that combines VR technology with Deep Convolutional Generative Adversarial Networks and Deep Deterministic Policy Gradient algorithms. …”
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Early prediction of progression-free survival of patients with locally advanced nasopharyngeal carcinoma using multi-parametric MRI radiomics by Lian Jian, Cai Sheng, Huaping Liu, Handong Li, Pingsheng Hu, Zhaodong Ai, Xiaoping Yu, Huai Liu

“…Five machine learning algorithms with cross-validation were compared to develop the optimal single-layer and fusion radiomic models. …”
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Non‐local low‐rank constraint‐based self‐consistent PMRI reconstruction using eigenvector maps by Jizhong Duan, Ting Pan, Yu Liu, Junfeng Wang

“…Recently, the L1 norm and total variation were combined with the ESPIRiT model to improve the reconstruction quality of magnetic resonance (MR) images. …”
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Recent technical advancements and clinical applications of MR-guided radiotherapy in lung cancer treatment by Chi Ma, Xiao Wang, Ke Nie, Zhenyu Xiong, Keying Xu, Ning Yue, Yin Zhang

“…Additionally, MRgRT could potentially allow multileaf collimator (MLC) tracking to further improve the treatment efficiency. Recent technological innovations, including AI-powered auto-contouring algorithms, deep-learning (DL) based prediction models, and adaptive treatment strategies, further optimize MRgRT by improving workflow efficiency and reducing treatment time. …”
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ML-Based Materials Evaluation in 3D Printing by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Jakub Kopowski

“…Furthermore, by integrating real-time data from sensors during the printing process, ML can continuously monitor and adjust parameters, ensuring optimal material utilization and reducing waste. ML models can identify and correct defects in printed materials by recognizing patterns associated with defects, thus improving the reliability of 3D-printed objects. …”
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Transcriptome signature for multiple biotic and abiotic stress in barley (Hordeum vulgare L.) identifies using machine learning approach by Bahman Panahi

“…Machine learning models, specifically Random Forest and C4.5, were optimized and evaluated using a 10-fold cross-validation approach. …”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Photocatalysis prioritizes gaseous products (e.g., H2, CH4) with liquid fuel selectivity below 15% for most polymers. To address these challenges, three actionable pathways are proposed: (1) Pilot-scale optimization: Current studies predominantly use lab-scale feeds (<100 g), necessitating trials with industrial-grade plastics containing pigments and plasticizers. …”
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Prediction of induction motor faults using machine learning by Ademola Abdulkareem, Tochukwu Anyim, Olawale Popoola, John Abubakar, Agbetuyi Ayoade

“…To enhance model performance in future work, potential avenues include refining the ANN and RF models, exploring transfer learning or ensemble methods, and incorporating diverse datasets to improve generalization.…”
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Rapid Quality Assessment of Polygoni Multiflori Radix Based on Near-Infrared Spectroscopy by Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao

“…After optimizing the model using CARS, R2C increased by 0.15%, 0.41%, and 0.34%, RMSECV decreased by 0.53%, 0.32%, and 0.24%, R2P increased by 0.21%, 0.63%, and 0.35%, RMSEP decreased by 0.36%, 0.41%, and 0.31%, and RPD increased by 1.1, 0.9, and 0.6, significantly improving the predictive capacity of the model. …”
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