Efficiency Optimization of PMSM-Type Elevator Machine: An Industrial Comparison by Mucahit Soyaslan, Osman Eldogan, Ahmet Fenercioglu, Yusuf Avsar, Nurdogan Ceylan, Muhammed Salih Sarıkaya

“…This study presents the design, modeling, and prototyping of an external rotor permanent magnet synchronous motor (ER-PMSM) specifically for elevator traction systems. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…Although MAE was slightly higher, the overall error control remained within an acceptable range, validating the model’s stability and effectiveness. The importance of the attention mechanism was further verified through ablation experiments, with the complete model’s R2 value improving by 87.04% and MSE decreasing by 87.18% compared to using TCN alone, confirming the effectiveness of the multi-module collaborative design. …”
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Artificial Intelligence in Hand Surgery: The Future is Upon Us by Bryan S. Crook, MD, Eoghan T. Hurley, MBBS, PhD, Marc J. Richard, MD, Suhail K. Mithani, MD, Tyler S. Pidgeon, MD

“…The resulting impact of these technologies, including machine learning algorithms and large language models, has yet to be fully realized, but has already begun improving patient care, offloading administrative burden, and disrupting clinical research. …”
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A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

“…Sparsity is a highly desired feature in deep neural networks (DNNs) since it ensures numerical efficiency, improves the interpretability (due to the smaller number of relevant features), and robustness. …”
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SLPOD: superclass learning on point cloud object detection by Xiaokang Yang, Kai Zhang, Yangyue Feng, Beibei Su, Yiming Cai, Kaibo Zhang, Zhiheng Zhang

“…To tackle this challenge, we introduce SLPOD, a Superclass-based point cloud object detection algorithm. Employing a siamese network structure, SLPOD conducts unsupervised clustering of samples within the same category to enhance the extraction of individual-specific features, thereby improving detection accuracy when confronted with complex datasets. …”
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A Prototype for Computing the Distance of Features of High-Pressure Die-Cast Aluminum Products by Luis Alberto Arroniz Alcántara, Óscar Hernández-Uribe, Leonor Adriana Cárdenas-Robledo, José Alejandro Fernández Ramírez

“…Automotive manufacturers are changing their product models faster due to the customization of users’ demands. …”
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Machine Learning Detection of Melting Layers From Radar Observations by Yan Xie, Fraser King, Claire Pettersen, Mark Flanner

“…Compared to a traditional detection method, the U‐Net model increases the Probability of Detection by 57% and improves the mean Dice‐Sørensen coefficient from 0.69 to 0.91. …”
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A Critical Review of the Prospect of Integrating Artificial Intelligence in Infectious Disease Diagnosis and Prognosis by Shuaibu Abdullahi Hudu, Ahmed Subeh Alshrari, Esra’a Jebreel Ibrahim Abu-Shoura, Amira Osman, Abdulgafar Olayiwola Jimoh

“…This paper reviews how AI-driven models improve diagnostic accuracy, predict patient outcomes, and contribute to effective disease management. …”
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Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage by Aniket Basu, Hooman Oroojeni, Georgios Samakovitis, Mohammad Majid Al-Rifaie

“…Algorithmic diversity has been explored, leading to several modifications and improvements in the implemented models. …”
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An efficient method for identifying surface damage in hydraulic concrete buildings by Libo Yang, Dawei Zhu, Xuemei Liu

“…Furthermore, the paucity of data diversity leads to a singular function of the model that cannot provide comprehensive decision support for improving maintenance measures. …”
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Control and management in a complex biotechnical system of a dairy farm by V. V. Kirsanov, R. A. Baisheva

“…The paper presents the scheme of transformation and expansion of machine functionality in a biotechnical system; mathematical modeling of the dependence of technological signals controlled by the functions of local biotechnological systems (LBTS); mathematical model of diagnostic signals about the corresponding parameters of technical blocks of LBTS. …”
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Numerical Optimization of Laser Powder Bed Fusion Process Parameters for High-Precision Manufacturing of Pure Molybdenum by İnayet Burcu Toprak, Nafel Dogdu, Metin Uymaz Salamci

“…The findings highlight that optimized parameter selection significantly improves the structural integrity of Mo-based components while minimizing manufacturing defects, thus offering valuable guidance for advancing industrial-scale additive manufacturing of refractory metals.…”
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Research on Laser Radar Inspection Station Planning of Vehicle Body-In-White (BIW) with Complex Constraints by Lijuan Li, Siyi Wang, Jichao Ma, Xiaobing Gao

“…Firstly, a parametric geometric modeling approach is developed to define measurement spaces for individual features, accompanied by an innovative maximal complete subgraph mining algorithm to intelligently identify shared feasible measurement regions among multiple features. …”
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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

“…The C4.5 algorithm demonstrated superior accuracy in predicting stress-responsive signatures. …”
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Application of Artificial Intelligence in Support of NAFLD Diagnosis by Jakub Płudowski, Jan Mulawka

“…Those models have achieved diagnostic accuracy higher than 95%, and the system is designed for continuous improvement by aggregating more data and automatically retraining models. …”
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Machine Learning-Based Environment-Aware GNSS Integrity Monitoring for Urban Air Mobility by Oguz Kagan Isik, Ivan Petrunin, Antonios Tsourdos

“…This study introduces a novel machine learning-based GNSS integrity monitoring framework that incorporates environment recognition to create environment-specific error models. Using a comprehensive Hardware-in-the-Loop (HIL) simulation setup, extensive data were generated for suburban, urban, and urban canyon environments to train and validate the models. …”
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Hardware Implementation of Next Generation Reservoir Computing with RRAM‐Based Hybrid Digital‐Analog System by Danian Dong, Woyu Zhang, Yuanlu Xie, Jinshan Yue, Kuan Ren, Hongjian Huang, Xu Zheng, Wen Xuan Sun, Jin Ru Lai, Shaoyang Fan, Hongzhou Wang, Zhaoan Yu, Zhihong Yao, Xiaoxin Xu, Dashan Shang, Ming Liu

“…Reservoir computing (RC) possesses a simple architecture and high energy efficiency for time‐series data analysis through machine learning algorithms. To date, RC has evolved into several innovative variants. …”
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Prediction of outcomes following intravenous thrombolysis in patients with acute ischemic stroke using serum UCH-L1, S100β, and NSE: a multicenter prospective cohort study employin... by Ming-Ya Luo, Yang Qu, Peng Zhang, Reziya Abuduxukuer, Li-Juan Wang, Li-Chong Yang, Zhi-Guo Li, Xiao-Dong Liu, Ce Han, Dan Li, Wei-Jia Wang, Dian-Ping Lv, Ming Liu, Jian Gao, Jing Xu, Yongfei Jiang, Hai-Nan Chen, Fu-Jin Li, Li-Ming Sun, Qi-Dong Sun, Yingbin Qi, Si-Yin Sun, Yu Zhang, Zhen-Ni Guo, Yi Yang

“…Least Absolute Shrinkage and Selection Operator regression was used for feature selection, and six ML algorithms were tested. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F 1-score, calibration curve, and decision curve analysis. …”
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Nondestructive estimation of leaf chlorophyll content in banana based on unmanned aerial vehicle hyperspectral images using image feature combination methods by Weiping Kong, Weiping Kong, Lingling Ma, Huichun Ye, Huichun Ye, Jingjing Wang, Chaojia Nie, Binbin Chen, Xianfeng Zhou, Wenjiang Huang, Zikun Fan

“…We proposed two methods of image feature combination for banana LCC inversion, which are a two-pair feature combination and a multivariable feature combination based on four machine learning algorithms (MLRAs).ResultsThe results indicated that compared to conventionally used VIs alone, the banana LCC estimations with both proposed VI and TF combination methods were all significantly improved. …”
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High-accuracy combustible gas cloud imaging system using YOLO-plume classification network by Jiani Zhou, Yang Liu, Yong Zhang, Haotian Hu, Zenan Leng, Feng Sun, Chen Chen

“…Experimental results show that the proposed model achieves an F1-score of 88.97% and an IoU of 89.74%, improving upon the baseline by 7.37% and 7.59%, respectively, with a detection accuracy reaching 99.78%.…”
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