A Workload Characterization Methodology Using Supervised and Unsupervised Deep Learning by Bing Hu, Karl Kempf, Nicholas Mason

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Effect of water entry temperature and aging parameters on precipitation and mechanical properties of 7075 aluminum alloy by NIU Changhai, SUN Qian, ZHENG Jia, PANG Qiu

“…After training， the prediction accuracy of the BP neural network model is 94.9977%. Experimental verification of the optimal process parameters predicted by the model shows that its prediction similarity is 96.9%. …”
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Landslide Susceptibility Evaluation Based on the Combination of Environmental Similarity and BP Neural Networks by Ruiting Wang, Wenfei Xi, Guangcai Huang, Zhiquan Yang, Kunwu Yang, Yongzai Zhuang, Ruihan Cao, Dingjie Zhou, Yijie Ma

“…The BP neural network model was subsequently applied for susceptibility assessment, with comparative validation against support vector machine (SVM) and random forest (RF) models. …”
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Exploring ferroptosis-associated immune characteristics in Kawasaki disease through bioinformatics by Wei Li, Yan Duan, Lingyun Zhang, Jialin Zou, Bin Liu, Jun Jiang, Dong Liu, Haiyan Liu, Gang Li

“…We used data from the Gene Expression Omnibus (GEO) database to identify ferroptosis-related genes, and variable selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) analysis. We employed seven machine learning methods to determine the optimal predictive model, revealing that the Support Vector Machine (SVM) model exhibited optimal performance in external validation. …”
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Integrating AutoGluon for Real-Time Monitoring and Classification of Dental Equipment Performance by Muxiu Yang, Fengzhou Li, Wenfeng Qiu

“…The intent is to enable predictive maintenance through data processing automation, model selection and performance classification. Using sensor data, such as temperature readings, vibration readings, and pressure readings from different dental tools, we trained machine learning models using AutoGluon. …”
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Advanced Estimation of Winter Wheat Leaf’s Relative Chlorophyll Content Across Growth Stages Using Satellite-Derived Texture Indices in a Region with Various Sowing Dates by Jingyun Chen, Quan Yin, Jianjun Wang, Weilong Li, Zhi Ding, Pei Sun Loh, Guisheng Zhou, Zhongyang Huo

“…Moreover, this optimal model also exhibited a notable level of transferability at another location with different sowing times, wheat varieties, and soil types from the modeling area. …”
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Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes by Guoqing Li, Hongyi Chen, Jiacheng Shen, Yimin Ding, Jingqiong Chen, Yongbin Zhang, Mingrui Tang, Nan Xu, Yuxuan Fang

“…Diagnostic performance evaluated via receiver operating characteristic (ROC) curves using pROC for area under the curve (AUC). Optimal LASSO model with 4 circRNAs determined, with AUC > 0.6 for key genes. …”
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Privacy-preserving federated learning for collaborative medical data mining in multi-institutional settings by Rahul Haripriya, Nilay Khare, Manish Pandey

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Forecasting the Shredder Output Volume Flow Towards Dynamic Control in Waste Management by Tatjana Lasch, Jason Imhof, Lisa Kandlbauer, Renato Sarc, Karim Khodier

“…Therefore, influencing factors on machines and the entire plant must be known. Furthermore, optimization potentials can be developed with the help of digital approaches, such as dynamic control of machine and plant operation, to be able to control the heterogeneous material streams to enable optimized treatment and preserve valuable materials. …”
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Automated chick gender determination using optical coherence tomography and deep learning by Jadsada Saetiew, Papawit Nongkhunsan, Jiraporn Saenjae, Rapeephat Yodsungnoen, Amonrat Molee, Sirichok Jungthawan, Ittipon Fongkaew, Panomsak Meemon

“…Our model achieved 79 % accuracy, outperforming conventional architectures such as Inception (63 %) and VGG-16 (74 %), highlighting the importance of a tailored, domain-specific model. …”
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Artificial intelligence-based prediction of second stage duration in labor: a multicenter retrospective cohort analysisResearch in context by Xiaoqing Huang, Xiaodan Di, Suiwen Lin, Minrong Yao, Suijin Zheng, Shuyi Liu, Wayan Lau, Zhixin Ye, Zilian Wang, Bin Liu

“…We aimed to develop a personalized machine learning (ML) model to predict the possible second-stage duration. …”
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Combination of Conditioning Factors for Generation of Landslide Susceptibility Maps by Extreme Gradient Boosting in Cuenca, Ecuador by Esteban Bravo-López, Tomás Fernández, Chester Sellers, Jorge Delgado-García

“…Additionally, a hyperparameter tuning process of XGBoost has been employed in order to optimize the predictive and computational performance of each model. …”
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Innovative Design Method for Lingnan Region Veranda Architectural Heritage (Qi-Lou) Facades Based on Computer Vision by Qiang Tang, Liang Zheng, Yile Chen, Junming Chen, Shuai Yang

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Large-scale groundwater pollution risk assessment research based on artificial intelligence technology: A case study of Shenyang City in Northeast China by Lingjun Meng, Yuru Yan, Haihua Jing, Muhammad Yousuf Jat Baloch, Shouying Du, Shanghai Du

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Enhancing credit card fraud detection: the impact of oversampling rates and ensemble methods with diverse feature selection by Mohamed Akouhar, Abdallah Abarda, Mohamed El Fatini, Mohamed Ouhssini

“…The results show that the application of SMOTE significantly improves the performance of the machine learning models, with an optimal oversampling rate of 20% identified. …”
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Temporal generalization in evergreen leaf type classification using tailored Sentinel-2 composites by Peter Hofinger, Jan Dempewolf, Simon Ecke, Hans-Joachim Klemmt

“…Eight machine learning models were tuned and trained on 16,162 tree crowns across 48 areas in Bavarian strict forest reserves (2019 to 2023) and validated with ForestGEO Traunstein Forest Dynamics Plot ground truth data (2018). …”
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Bioinformatic insights into five Chinese population substructures inferred from the East Asian-specific AISNP panel by Jing Chen, Yuguo Huang, Jie Zhong, Mengge Wang, Guanglin He, Jiangwei Yan

“…The accuracy of the random forest model was confirmed through a confusion matrix based on machine learning. …”
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Research on bolt loosening recognition based on sound signal and GA-SVM–RFE by Li-Ye Hou, De-Bing Zhuo

“…SVM-RFE was used for sensitive feature selection, and genetic algorithm was combined to optimize SVM parameters, ultimately obtaining the optimal recognition model. …”
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Numerical simulation study of tunneling process using TBM disc cutter under extremely hard rock condition by Huawei WANG, Zhengyang KANG, Yingcai WANG, Sijin LIU, Peng LIU

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Eco-friendly synthesis coupled with predictive analytics: Developing hierarchical lignin-derived ordered mesoporous carbon for advanced supercapacitors by Xiaolan Zhao, Xiaoqi Wang, Pei Gao, Peng Zhao, Jingjing Wang, Yingna Li, Zhibin Han, Boxiong Shen

“…The ANN model suggested an ideal hierarchical structure and optimized oxygen level, achieved through the adjustment of Zn2+ additive concentration, carbonization temperature, and subsequent KHCO3 activation to maximize capacitance. …”
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