Knowledge Graphs and Their Reciprocal Relationship with Large Language Models by Ramandeep Singh Dehal, Mehak Sharma, Enayat Rajabi

“…The reciprocal relationship between Large Language Models (LLMs) and Knowledge Graphs (KGs) highlights their synergistic potential in enhancing artificial intelligence (AI) applications. …”
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Mechanisms and optimization for simultaneous removal of Cd(II) and Sb(V) from aqueous solutions using birnessite and fulvic acid composite by Changsheng Jin, Jingjing Lu, Yin Gao, Baowei Hu, Yuxi Liu

“…In this study, the adsorption performance of a birnessite (BS) and fulvic acid (FA) composite (BS-FA) for the simultaneous removal of Cd(II) and Sb(V) was optimized using response surface methodology (RSM) in combination with machine learning (ML) techniques, including the genetic algorithm-back propagation neural network (GABP) and random forest (RF) models. …”
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AOPxSVM: A Support Vector Machine for Identifying Antioxidant Peptides Using a Block Substitution Matrix and Amino Acid Composition, Transformation, and Distribution Embeddings by Rujun Li, Haotian Wang, Qiunan Yu, Jing Cai, Liangzhen Jiang, Ximei Luo, Quan Zou, Zhibin Lv

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A study on data-driven and multi-scale modeling method for production system simulation “Model configuration and identification for flow shop production systems” by Satoshi NAGAHARA, Toshiya KAIHARA, Nobutada FUJII, Daisuke KOKURYO

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Thermal Error Prediction in High-Power Grinding Motorized Spindles for Computer Numerical Control Machining Based on Data-Driven Methods by Quanhui Wu, Yafeng Li, Zhengfu Lin, Baisong Pan, Dawei Gu, Hailin Luo

“…The subsequent problem of thermal error compensation can be effectively solved by a suitable thermal error model, which is crucial for improving the machining accuracy of the actual machining process. …”
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Daily-Scale Fire Risk Assessment for Eastern Mongolian Grasslands by Integrating Multi-Source Remote Sensing and Machine Learning by Risu Na, Byambakhuu Gantumur, Wala Du, Sainbuyan Bayarsaikhan, Yu Shan, Qier Mu, Yuhai Bao, Nyamaa Tegshjargal, Battsengel Vandansambuu

“…Model performance was enhanced using Bayesian hyperparameter optimization via Optuna. …”
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Adoption of Data-Driven Automation Techniques to Create Smart Key Performance Indicators for Business Optimization by Michael Sishi, Arnesh Telukdarie

“…The model then employs exploratory Factor Analysis (FA) techniques to identify correlations and patterns, prioritize KPIs, and automatically generate smart KPIs for business optimization. …”
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In-Season Potato Nitrogen Prediction Using Multispectral Drone Data and Machine Learning by Ehsan Chatraei Azizabadi, Mohamed El-Shetehy, Xiaodong Cheng, Ali Youssef, Nasem Badreldin

“…This study evaluated the performance of three machine learning (ML) models—Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Regression (GBR)—for predicting potato N status and examined the impact of feature selection techniques, including Partial Least Squares Regression (PLSR), Boruta, and Recursive Feature Elimination (RFE). …”
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Indonesian Banking Stock Portfolio Optimization Based on Ridge Regression Prediction by Moch Panji Agung Saputra, Deva Putra Setyawan, Alim Jaizul Wahid

“…Traditional asset allocation strategies such as equal weighting or based on historical performance have limitations in dynamic market conditions, while the application of machine learning, especially Ridge Regression, in stock return prediction and portfolio optimization in the Indonesian market has not been widely explored. …”
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Portable NIR Spectroscopy Combined with Machine Learning for Kiwi Ripeness Classification: An Approach to Precision Farming by Giuseppe Altieri, Sabina Laveglia, Mahdi Rashvand, Francesco Genovese, Attilio Matera, Alba Nicoletta Mininni, Maria Calabritto, Giovanni Carlo Di Renzo

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Comparison of Different Heuristics Integrated with Neural Networks: A Case Study for Earthquake Damage Estimation by Ayşe Berika Varol Malkoçoğlu, Zeynep Orman, Rüya Şamlı

“…In this study, various Machine Learning (ML) algorithms were compared on a public dataset of earthquakes, which had occurred worldwide and had a local magnitude Ml ≥ 3, and the algorithm with the highest performance was selected and optimized with various other algorithms. …”
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Machine Learning Strategies for Preoperative PJI Diagnosis: Integrative Analysis of Serum and Synovial Fluid Markers by Chen B, Yang Y, Zhou H, Li F, Shen Y, Cheng Q, Huang W, Qin L

“…The eXtreme Gradient Boosting model was the optimal model, achieving an area under the curve of 0.998 (95% CI 0.993– 1) in the test set, outperforming other models. …”
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Prediction of Vehicle Interior Wind Noise Based on Shape Features Using the WOA-Xception Model by Yan Ma, Hongwei Yi, Long Ma, Yuwei Deng, Jifeng Wang, Yudong Wu, Yuming Peng

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Application of interpretable machine learning algorithms to predict macroangiopathy risk in Chinese patients with type 2 diabetes mellitus by Ningjie Zhang, Yan Wang, Hui Zhang, Huilong Fang, Xinyi Li, Zhifen Li, Zhenghang Huan, Zugui Zhang, Yongjun Wang, Wei Li, Zheng Gong

“…This study aims to develop a machine learning model that can accurately predict diabetic macroangiopathy in Chinese patients. …”
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Research on predicting the thermocompression deformation behavior of Mg–Li matrix composite using machine learning and traditional techniques by Dandan Li, Xiaoyu Hou, Yangfan Liu, Linhao Gu, Jinhui Wang, Jiaxuan Ma, Xiaoqiang Li, Zhi Jia, Qichi Le, Dexue Liu, Xincheng Yin

“…Artificial intelligence and machine learning (ML) technologies have emerged as powerful tools for analyzing the thermal compression deformation behavior of metal matrix composites, offering significant potential to optimize their plastic deformation processing techniques. …”
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Dual-Domain Synergistic Optimization for Dynamic Reliability Enhancement of Towering Structures in Nonstationary Wind Fields by Leilei Wang, Siyu Wu, Jiaxing Pei, Xinjia Meng

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Ultra-Local Model-Based Adaptive Enhanced Model-Free Control for PMSM Speed Regulation by Chunlei Hua, Difen Shi, Xi Chen, Guangfa Gao

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Integrating Machine Learning Techniques for Enhanced Safety and Crime Analysis in Maryland by Zeinab Bandpey, Soroush Piri, Mehdi Shokouhian

“…Our research utilized an enhanced combination of machine learning models, including random forest, gradient boosting, XGBoost, extra trees, and advanced ensemble methods like stacking regressors. …”
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A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…The increased use of advanced metaheuristic optimization techniques and hybrid machine learning and deep learning models is observed for optimization and forecasting applications. …”
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Harnessing quantum power: Revolutionizing materials design through advanced quantum computation by Zikang Guo, Rui Li, Xianfeng He, Jiang Guo, Shenghong Ju

“…This review introduces a comprehensive methodology for materials design using cutting‐edge quantum computing, with a particular focus on quadratic unconstrained binary optimization (QUBO) and quantum machine learning (QML). …”
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