Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods by Anton S. Chepurnenko, Tatiana N. Kondratieva, Ebrahim Al-Wali

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A Promising MM–Fe–Al–Ga–B Permanent Material with Substantially Boosted Magnetic Performance by Wang Chen, Shaoqing Ren, Jiaying Jin, Liang Zhou, Bo Xin, Mingjing Zhao, Mengfan Bu, Xu Li, Chen Wu, Mi Yan

“…Herein, a facile two‐step strategy is proposed that Al‐doping towards high maximum energy product (BH)max with the subsequential grain boundary diffusion processing (GBDP) toward high coercivity Hcj, i.e., a representative 0.7 wt% Al doping and Nd/Pr‐based GBDP yields the record‐high Hcj = 10.14 kOe and (BH)max = 28.02 MGOe for the MM–Fe–Al–Ga–B sintered magnets. …”
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Part B: Innovative Data Augmentation Approach to Boost Machine Learning for Hydrodynamic Purposes—Computational Efficiency by Hamed Majidiyan, Hossein Enshaei, Damon Howe, Eric Gubesch

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Hydroxytyrosol-Infused Extra Virgin Olive Oil: A Key to Minimizing Oxidation, Boosting Antioxidant Potential, and Enhancing Physicochemical Stability During Frying by Taha Mehany, José M. González-Sáiz, Consuelo Pizarro

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A leaner, meaner lifeline: How supply chain efficiency boosts the performance of humanitarian aid in Kenya by Erastus Kiswili Nyile

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Consolidation analysis of soft ground with air-boosted vacuum preloading considering attenuation of vacuum and boost pressure by Weiliang Gao, Lu Han, Yanming Zhao, Jinxin Sun, Lulu Liu

“…Abstract Air-boosted vacuum preloading (AVP), an innovative soil improvement methodology extensively employed in subgrade enhancement projects, demonstrates exceptional efficacy in accelerating soil consolidation processes and improving load-bearing characteristics of soft foundation. …”
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Experimental investigation and laser control in Ti10Mo6Cu powder bed fusion: optimizing process parameters with machine learning by Ouf A. Shams, Hanan B. Matar Al-Baity, Luttfi A. Al-Haddad

“…A Gradient Boosting Decision Tree (GBDT) model was developed to predict track characteristics which include width, height, and depth, based on experimental data. …”
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SHARAD Illuminates Deeper Martian Subsurface Structures with a Boost from Very Large Rolls of the MRO Spacecraft by Nathaniel E. Putzig, Gareth A. Morgan, Matthew R. Perry, Bruce A. Campbell, Jennifer L. Whitten, Fabrizio Bernardini, Alessandro DiCarlofelice, Piero Tognolatti, Pierfrancesco Lombardo

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Data-Driven Loan Default Prediction: A Machine Learning Approach for Enhancing Business Process Management by Xinyu Zhang, Tianhui Zhang, Lingmin Hou, Xianchen Liu, Zhen Guo, Yuanhao Tian, Yang Liu

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Boosting the Optical Activity of Titanium Oxide Through Conversion from Nanoplates to Nanotubes and Nanoparticle-Supported Nanolayers by Adil Alshoaibi

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Ultrafast Q-boosting in semiconductor metasurfaces by Yang Ziwei, Liu Mingkai, Smirnova Daria, Komar Andrei, Shcherbakov Maxim, Pertsch Thomas, Neshev Dragomir

“…However, the all-optical processes often induce optical absorption that fundamentally limits the possible dynamic increase of their quality factor (Q-boosting). …”
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Importance Sampling and Feature Fusion Paradigm-Boosted Multi-Modal Convolutional Neural Networks: Deployment in Composite Curing Process Monitored by Electro-Mechanical Impedance by Xin Zhao, Zeyuan Gao, Meng Li, Zhibin Han, Jianjian Zhu

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Solution Process–Based Facile Flame–Boosted Low‐Valence Transition Metal Doping on Pristine Oxide for Highly Enhanced Photoelectrochemical Solar Water Oxidation Reaction by Seung Hun Roh, Eujin Kwak, Won Tae Hong, Chengkai Xia, Sungsoon Kim, Heeyeop Chae, Xu Yu, Wooseok Yang, Jongwook Park, Jung Kyu Kim

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Reveling the Interrelationship of Digital Transformation and Business Intelligence Techniques to Boost Human Capital Development by Alawneh Osama Mousa, Tawalbeh Jawad, AlOqaily Ahmed Nader

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AdaBoost algorithm based on target perturbation by Shufen ZHANG, Yanling DONG, Jingcheng XU, Haoshi WANG

“…Aiming at the problem that the multi-round iteration process in the AdaBoost algorithm will amplify the noise added to achieve differential privacy protection, which leads to slow model convergence and greatly reduced data availability, an AdaBoost algorithm based on target perturbation—DPAda was proposed.Target perturbation was used to add noise to sample weights, accurately calculated their sensitivity, and a dynamic privacy budget was given.In order to solve the problem of excessive noise superposition, three noise injection algorithms based on swing sequence, random response and improved random response were proposed.The experimental results show that compared with DPAda_Random and DPAda_Swing, DPAda_Improved achieves the privacy protection of data, has higher classification accuracy, as well as better than other differential privacy AdaBoost algorithm, and can also solve the problem of excessive noise caused by continuous noise addition.…”
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Self-assessment in machines boosts human Trust by Dana Warmsley, Krishna Choudhary , Jocelyn Rego , Emma Viani , Praveen K. Pilly 

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Supervised Machine Learning Thyroid Carcinoma Diagnosis Using Wide-Field SHG Microscopy by Yaraslau Padrez, Radu Hristu, Igor Timoshchenko, Lucian G. Eftimie, Danielis Rutkauskas, Lena Golubewa

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Heat Re-process approach and thermally integrated renewable energy system for power, compressed hydrogen, and freshwater production; ANN boosted optimization and techno-enviro-economic analysis by Zhaoyang Zuo, Junhua Wang, Mohammed A. Alghassab, Nashwan Adnan Othman, Ahmad Almadhor, Fahad M. Alhomayani, Hind Albalawi, Samah G. Babiker, Barno Abdullaeva, Aboulbaba Eladeb

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APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

“…This paper will use the Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and hybrid Adaptive Boosting-SVM (AdaBoost-SVM) model. …”
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Prediksi Kualitas Udara Menggunakan Metode CatBoost by Mohamad Arif Abdul Syukur Syukur, Suhartono Suhartono, Totok Chamidy

“…The data is processed through pre-processing and divided into four models with different comparisons of training and testing data. …”
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