A Novel Temperature Reconstruction Method for Acoustic Pyrometry Under Strong Temperature Gradients and Limited Measurement Points by Jingkao Tan, Lehang Chen, Na Li, Qulan Zhou, Zhongquan Gao, Jie Zhou

“…Acoustic pyrometry (AP) is a promising methodology for high-quality temperature field reconstruction, which is widely used in the monitoring of atmosphere, room, and furnace. However, most of the existing acoustic reconstruction algorithms are developed and utilized in relatively uniform temperature distributions. …”
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A Comprehensive Review of the Diagnostics for Pediatric Tuberculosis Based on Assay Time, Ease of Operation, and Performance by Soumya Basu, Subhra Chakraborty

“…Gaps in the existing diagnostic methods, algorithms, and operational costs were also reviewed. …”
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Remote Sensing Target Tracking Method Based on Super-Resolution Reconstruction and Hybrid Networks by Hongqing Wan, Sha Xu, Yali Yang, Yongfang Li

“…And obtaining high-resolution images by optimizing algorithms will save a lot of costs. Aiming at the problem of large tracking errors in remote sensing target tracking by current tracking algorithms, this paper proposes a target tracking method combined with a super-resolution hybrid network. …”
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A Rapid Design Method for Centrifugal Pump Impellers Based on Machine Learning by Y. Chen, W. Li, Y. Luo, L. Ji, S. Li, Y. Long

“…Variations in the cross-sectional area of the flow passage influence the internal flow state of the centrifugal pump, ultimately impacting its hydraulic efficiency. A genetic algorithm, guided by variations in the cross-sectional area of the flow passage, optimizes the blade profile, achieving an improved impeller flow path and completing the rapid design of the centrifuge. …”
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Deep Reinforcement Learning Based Transferable EMS for Hybrid Electric Trains by Yogesh Wankhede, Sheetal Rana, Faruk Kazi

“…To enhance the performance of the EMS, proposes to use of a deep reinforcement learning (DRL) algorithm specifically the deep deterministic policy gradient (DDPG) combined with transfer learning (TL) which can improve the system's efficiency when driving cycles are changed. …”
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Initialization Methods for FPGA-Based EMT Simulations by Xin Ma, Xiao-Ping Zhang

“…The performance of these four methods are also compared, and Method 4 can initialize instantly with the simplest code. To improve hardware adaptability, optimized strategies are developed for address sequence, interface, update modes and dataflow. …”
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Integration of Hash Encoding Technique with Machine Learning for Employee Turnover Prediction by Ahya Radiatul Kamila, Johanes Fernandes Andry, Francka Sakti Lee, Felliks F. Tampinongkol

“…It is part of the preprocessing stage, aiming to reduce memory usage, speed up data preprocessing, and improve model performance. After preprocessing is completed, the prediction model is trained using the Random Forest algorithm to predict employee turnover. …”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…DNN demonstrates strong capabilities in handling complex nonlinear relationships, and XGBoost further improves classification accuracy by optimizing decision tree models through gradient boosting. …”
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Comparative Assessment of Several Effective Machine Learning Classification Methods for Maternal Health Risk by Md Nurul Raihen, Sultana Akter

“…Maternal risk analysis can improve prenatal care, improve mother and baby health, and optimize healthcare resources by identifying misclassified observations using machine learning algorithms such as LDA, QDA, KNN, Decision Tree, Random Forest, Bagging, and Support Vector Machine, all of which have a significant impact on maternity health risk assessment. …”
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Cardiac Computed Tomography Measurements in Pulmonary Embolism Associated with Clinical Deterioration by Anthony J. Weekes, Angela M. Pikus, Parker L. Hambright, Kelly L. Goonan, Nathaniel O’Connell

“…Introduction: Most pulmonary embolism response teams (PERT) use a radiologist-determined right ventricle to left ventricle ratio (RV:LV) cut-off of 1.0 to risk-stratify pulmonary embolism (PE) patients. …”
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On Flood Detection Using Dual-Polarimetric SAR Observation by Su-Young Kim, Yeji Lee, Sang-Eun Park

“…This study aims to elucidate the optimal exploitation of polarimetric scattering information in dual-pol SAR data. …”
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Enhancing phase change thermal energy storage material properties prediction with digital technologies by Minghao Yu, Jing Liu, Cheng Chen, Mingyue Li

“…Hierarchical feature fusion modules combine low-level atomistic descriptors with high-level continuum features.ResultsBenchmark evaluations show improved performance in predicting elastic modulus, thermal conductivity, and phase transition temperature across five material classes. …”
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Real-Time Common Rust Maize Leaf Disease Severity Identification and Pesticide Dose Recommendation Using Deep Neural Network by Zemzem Mohammed Megersa, Abebe Belay Adege, Faizur Rashid

“…We applied image preprocessing techniques such as image equalization, noise removal, and enhancement to improve model performance. Additionally, during training, we utilized batch normalization, dropout, and early stopping to reduce overfitting, improve accuracy, and improve execution time. …”
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Approach to knowledge management and the development of a multi-agent knowledge representation and processing system by E. I. Zaytsev, E. V. Nurmatova

“…Methods for distribution of intelligent software agents on the MKRPS nodes are proposed along with algorithms for optimizing the logical structure of the distributed knowledge base (DKB) to improve the performance of the MKRPS in terms of volume, cost and time criteria.Conclusions. …”
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A Multi-Strategy Active Learning Framework for Enhanced Peripheral Blood Cell Image Detection by Yuheng Feng, Jiangtao He, Linjin Wang, Wuchen Yang, Sihan Deng, Lanlin Li, Xinwei Li

“…The framework reduces annotation costs and improves detection performance by combining uncertainty-based selection, diversity querying, and density-based querying to prioritize the most informative and diverse samples. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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Adaptive Feedforward Vibration Control of Helicopter Cabin Floor Driven by Piezoelectric Stack Actuators: Modeling, Simulation and Experiments by Laishou Song, Yingquan Wang, Xiaoyu Shen

“…Active control of structural response is the most practical and effective approach to mitigate helicopter vibration and enhance ride quality. …”
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Examination of Machining Parameters and Prediction of Cutting Velocity and Surface Roughness Using RSM and ANN Using WEDM of Altemp HX by I. V. Manoj, Hargovind Soni, S. Narendranath, P. M. Mashinini, Fuat Kara

“…The cutting velocity, surface roughness, recast layer, and microhardness variations were examined on the WEDMed surface. The genetic algorithm was used to optimize the cutting velocity and surface roughness, thereby improving the overall quality of the product. …”
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A comprehensive review of ball detection techniques in sports by Cristiano Moreira, Lino Ferreira, Paulo Jorge Coelho

“…This is a highly debated and researched topic, but most works focus on one sport. Effective generalization of a single method or algorithm to different sports is much harder to achieve. …”
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Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…It was determined that their integrated application provides an increase in the accuracy of reserve assessment by 15–20 % and a reduction in operating costs by 10–15 %. Key development trends are identified: integration of digital technologies, improvement of methods of collecting and processing geospatial data, introduction of machine learning algorithms for risk prediction. …”
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