Ensemble Machine Learning for the Prediction and Understanding of the Refractive Index in Chalcogenide Glasses by Miruna-Ioana Belciu, Alin Velea

“…This study employs various machine learning models to reliably predict the refractive index at 20 °C using a small dataset of 541 samples extracted from the SciGlass database. …”
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Alloys innovation through machine learning: a statistical literature review by Alireza Valizadeh, Ryoji Sahara, Maaouia Souissi

“…In terms of methodology, while 68% of the examined papers rely on a single machine learning model, the remainder employ a range of 2 to 12 models, with Neural Network being the most prevalent choice. …”
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Comparative Study on Rail Damage Recognition Methods Based on Machine Vision by Wanlin Gao, Riqin Geng, Hao Wu

“…To further enhance performance, this study integrated the Multi-Head Self-Attention (MHSA) module into YOLO, creating MHSA-YOLOv8. The optimized model achieved a significant improvement in <i>mAP</i> by 10% (to 0.89), increased <i>mAR</i> by 20%, and reduced training time by 50% (to 0.14 h). …”
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Dynamic Surgical Prioritization: A Machine Learning and XAI-Based Strategy by Fabián Silva-Aravena, Jenny Morales, Manoj Jayabalan, Muhammad Ehsan Rana, Jimmy H. Gutiérrez-Bahamondes

“…Specifically, we employ the Light Gradient Boosting Machine (LightGBM) for predictive modeling, stochastic simulations to account for dynamic variables and competitive interactions, and SHapley Additive Explanations (SHAPs) to interpret model outputs at both the global and patient-specific levels. …”
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Design and Experiment of Pineapple Eye Removal Device Based on Machine Vision by Manfeng Gong, Shuai Wang, Xingzao Ma, Hua Li, Chenglong Tu, Ziyi Guo

“…The performance of various YOLOv5 models was compared in terms of accuracy, recall rate, mean detection error, and detection time. …”
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Design and Performance Testing of Seed Potato Cutting Machine with Posture Adjustment by Yingsi Wu, Xiangming La, Xuan Zhao, Fei Liu, Jianguo Yan

“…The cross-shaped cutter performed best at 14 r/min, 44 conical rollers, and a 0° cutting angle, with a qualified rate of 87.1% and a blind eye rate of 3.80%. All optimal configurations met agronomic requirements, demonstrating the efficacy of the designed machine and cutters.…”
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Optimising water use in copper flotation with the design of experiments and machine learning by Rachid El-Bacha, Abderrahim Salhi, Hafid Abderrafia, Souad Rabi

“…Through the design of experiments with the integration of machine learning, especially for the choice of the model, the optimal proportion was determined, which made it possible to achieve a metal recovery of more than 80% using a 50/50 mix of fresh and recycled water. …”
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Signal Detection in Intelligent Reflecting Surface-Assisted NOMA Network Using LSTM Model: A ML Approach by Haleema Sadia, Hafsa Iqbal, Syed Fawad Hussain, Nasir Saeed

“…The proposed scheme exploits a four layer deep learning (DL) model by employing a long short-term memory (LSTM) core structure. …”
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Enhancing Aerosol Vertical Distribution Retrieval With Combined LSTM and Transformer Model From OCO-2 O2 A-Band Observations by YuXuan Wang, RuFang Ti, ZhenHai Liu, Xiao Liu, HaiXiao Yu, YiChen Wei, YiZhe Fan, YuYao Wang, HongLian Huang, XiaoBing Sun

“…Through systematic optimization, the model provides a robust solution for accurately characterizing aerosol layers, making it a valuable tool for advancing atmospheric aerosol research.…”
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Prediction of adolescent subjective well-being: A machine learning approach by Lin He, Fei Xu, Yifeng Xu, Naixin Zhang, Chuanxin Liu, Zhixuan Chen, Lin An, Decheng Ren, Fan Yuan, Ruixue Yuan, Lei Ji, Yan Bi, Zhenming Guo, Gaini Ma, Fengping Yang, Liping Zhu, Gabirel Robert, Bo Bai, Tao Yu, Guang He

“…We applied feature selection to achieve the balance between optimal prediction and result interpretation.Results The top 20 happiness risks and protective factors were finally brought into the predicting model. …”
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Quantum Computing in Community Detection for Anti-Fraud Applications by Yanbo (Justin) Wang, Xuan Yang, Chao Ju, Yue Zhang, Jun Zhang, Qi Xu, Yiduo Wang, Xinkai Gao, Xiaofeng Cao, Yin Ma, Jie Wu

“…Using a Coherent Ising Machine (CIM) to solve the QUBO model, we successfully divide 308 nodes into four communities. …”
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A Short-Term Load Interval Forecasting Method Based on EEMD-SE and PSO-KELM by Lin ZHANG, Jichun LIU

“…Finally, the particle swarm optimization (PSO) is used to optimize the weight of output layer of kernel extreme learning machine (KELM), and a prediction model is established to reconstruct the interval of each subseries. …”
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Estimated ultimate recovery prediction of shale gas wells based on stacked integrated learning algorithm by Min Pang, Zheyuan Zhang, Zhaoming Zhou, Wendi Zhou, Qiong Li

“…Furthermore, the model is optimized using the Tree-structured Parzen Estimator (TPE) algorithm. …”
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Evaluation of the Performance of Unsupervised Learning Algorithms for Intrusion Detection in Unbalanced Data Environments by Gutierrez-Portela Fernando, Almenares Mendoza Florina, Calderon-Benavides Liliana

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Electricity demand forecasting methodologies and applications: a review by Prosper O. Ugbehe, Ogheneruona E. Diemuodeke, Daniel O. Aikhuele

“…The forecasting methodologies are categorized into statistical, Machine Learning/Artificial Intelligence (ML/AI), and hybrid models. …”
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M&M: an RNA-seq based pan-cancer classifier for paediatric tumoursResearch in context by Fleur S.A. Wallis, John L. Baker-Hernandez, Marc van Tuil, Claudia van Hamersveld, Marco J. Koudijs, Eugène T.P. Verwiel, Alex Janse, Laura S. Hiemcke-Jiwa, Ronald R. de Krijger, Mariëtte E.G. Kranendonk, Marijn A. Vermeulen, Pieter Wesseling, Uta E. Flucke, Valérie de Haas, Maaike Luesink, Eelco W. Hoving, Josef H. Vormoor, Max M. van Noesel, Jayne Y. Hehir-Kwa, Bastiaan B.J. Tops, Patrick Kemmeren, Lennart A. Kester

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Integrating Artificial Neural Network-PROSAIL With Sentinel-2 to Monitor Crop Traits Dynamics and Nitrogen Status by Jose Luis Pancorbo, Miguel Quemada, Maria Dolores Raya-Sereno, Beniamino Gioli, Pieter S. A. Beck, Carlos Camino

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Implementation and Evaluation of Machine Learning Algorithms in Ball Bearing Fault Detection by Stepanić Pavle, Dučić Nedeljko, Vidaković Jelena, Baralić Jelena, Popović Marko

“…By optimizing the hyperparameters, models with a maximum classification success of 100 % were achieved.…”
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Identifying ovarian cancer with machine learning DNA methylation pattern analysis by Jesus Gonzalez Bosquet, Vincent M. Wagner, Douglas Russo, Henry D. Reyes, Andreea M. Newtson, David P. Bender, Michael J. Goodheart

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Machine-Learning Methods Estimating Flights’ Hidden Parameters for the Prediction of KPIs by George Vouros, Ioannis Ioannidis, Georgios Santipantakis, Theodore Tranos, Konstantinos Blekas, Marc Melgosa, Xavier Prats

“…This research proposes a data-driven methodology for the estimation of flights’ hidden parameters combining mechanistic and advanced Artificial Intelligence/Machine Learning (AI/ML) models. Aiming at microsimulation models, our goal is to study the effect of these estimations on the prediction of flights’ KPIs. …”
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