Optimizing Time-Constrained Multi-Objective Process Parameters for Thin-Walled Maraging Steels Manufactured by Laser Powder Bed Fusion (LPBF) by Yeo-Ul Song, Byeong Uk Song, Joon Phil Choi, Min-Kyo Jung, Taeho Ha, Pil-Ho Lee

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Prediction of 5-year postoperative survival and analysis of key prognostic factors in stage III colorectal cancer patients using novel machine learning algorithms by Wei Zhang, Yan Li, Jinghan Jia, Yuhang Yang, Yuyuan Hu, Yanhong Wang, Jinxi Wang

“…These factors were incorporated into machine learning models, including logistic regression, decision tree, LightGBM, and others. …”
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An interpretable machine learning method for fault diagnosis of oil-immersed transformers based on edge inference by Dong Hu, Yong Yang, Hao Dai, Chao Tang, Jufang Xie

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Optimizing Dual-Microstructure Parameters in Ball-End Milling Tools: Synergistic Effects and Parameter Combination Analysis by Qinghua Li, Qingyu Guan, Yi Ji, Wenyang Xu, Tiantian Xu

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Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra, Bhanja Kishor Swain, Manohar Mishra

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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

“…Multiple algorithms were trained and evaluated, with the Decision Tree classifier emerging as the optimal model, achieving remarkable performance metrics: 99.8% accuracy, precision, recall, and F1-score, a 99.6% Matthews Correlation Coefficient (MCC), and the highest Area Under the Curve (AUC) score for multi-class classification. …”
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Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…First, experimental data from continuous dark fermentation are modeled using support vector machine (SVM) algorithm for response prediction and then, optimization algorithms are employed to identify the key parameters that enhance H2 production. …”
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Performance of deep learning models in predicting the nugent score to diagnose bacterial vaginosis by Naoki Watanabe, Tomohisa Watari, Kenji Akamatsu, Isao Miyatsuka, Yoshihito Otsuka

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Exploring small-scale optimization coupling learning approaches for enterprises’ financial health forecasts by Lin Zhu, Zhihua Zhang, M. James C. Crabbe

“…Most data-driven financial health forecasts are based on the direct use of small-scale machine learning. In this study, we proposed the idea of optimization coupling learning to improve these machine learning models in financial health forecasting. …”
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Optimizing the morphology transition on MOVPE-grown (100) β-Ga2O3 film between step-flow growth and step-bunching: A machine learning-assisted approach by Ta-Shun Chou, Saud Bin Anooz, Natasha Dropka, Han-Hsu Chen, Zbigniew Galazka, Martin Albrecht, Andreas Fiedler, Andreas Popp

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Models, systems, networks in economics, engineering, nature and society by A.D. Stolyarov, V.V. Gordeev, V.I. Abramov

Artificial Intelligence-driven optimization of V2G and charging point selection en-route: A systematic literature review by Christoph Sommer, M.J. Hossain

“…Further investigation is warranted into the impact of high PV generation shares on charging behavoir and the optimization of charging strategies within the Australian context. …”
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FraudX AI: An Interpretable Machine Learning Framework for Credit Card Fraud Detection on Imbalanced Datasets by Nazerke Baisholan, J. Eric Dietz, Sergiy Gnatyuk, Mussa Turdalyuly, Eric T. Matson, Karlygash Baisholanova

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ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models by Song-Quan Ong, Nathan Pinoy, Min Hui Lim, Kim Bjerge, Francisco Javier Peris-Felipo, Rob Lind, Jordan P. Cuff, Samantha M. Cook, Toke Thomas Høye

“…However, imaging large numbers of specimens is time consuming, and it is difficult to achieve the high image quality required for machine learning models. Conventional imaging methods for identifying and digitizing arthropods, such as insects and spiders, use a stereomicroscope or macro lenses with a camera. …”
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Clinical decision support for pharmacologic management of treatment-resistant depression with augmented large language models by Roy H. Perlis, Pilar F. Verhaak, Joseph Goldberg, Cristina Cusin, Michael Ostacher, Gin S. Malhi, Carlos A. Zarate, Richard C. Shelton, Dan V. Iosifescu, Mauricio Tohen, Manish Kumar Jha, Martha Sajatovic, Michael Berk

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Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic–Ischemic Encephalopathy Injury by Leah Twomey, Sergi Gomez, Emanuel Popovici, Andriy Temko

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Hyperspectral imaging for precision nitrogen management: A comparative exploration of two methodological approaches to estimate optimal nitrogen rate in processing tomato by Vito Aurelio Cerasola, Francesco Orsini, Giuseppina Pennisi, Gaia Moretti, Stefano Bona, Francesco Mirone, Jochem Verrelst, Katja Berger, Giorgio Gianquinto

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K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain by Vivek Kumar, Diego Reforgiato Recupero, Rim Helaoui, Daniele Riboni

“…The use of superior algorithms and complex architectures in language models have successfully imparted human-like abilities to machines for specific tasks. …”
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Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis by Yuxing Liu, Jintao Chen, Daifeng Yang, Chenming Liu, Chunhui Tang, Shanshan Cai, Yingxuan Huang

“…Utilizing transcriptomic and gene expression data from TCGA and GEO databases, 72 immune-related lncRNAs were identified through weighted gene co-expression network analysis (WGCNA) and ImmuLncRNA algorithms. The model was further optimized using 101 combinations of 10 machine learning approaches, ultimately constructing an immune-related lncRNA signature(IRLS) scoring system comprising nine key lncRNAs. …”
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Fatigue failure analysis of washing machine top frame under cyclic loading – an investigative study in mitigating market complaint by Sohail Hasnain, Muhammad Mansoor Uz Zaman Siddiqui, Adeel Tabassum, Syed Haider Raza Naqvi, Asad A. Naqvi

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