Convergence and Quantum Advantage of Trotterized MERA for Strongly-Correlated Systems by Qiang Miao, Thomas Barthel

“…Furthermore, we show how the convergence can be substantially improved by building up the MERA layer by layer in the initialization stage and by scanning through the phase diagram during optimization. …”
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Predicting hospital outpatient volume using XGBoost: a machine learning approach by Lingling Zhou, Qin Zhu, Qian Chen, Ping Wang, Hao Huang

“…Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allocation of medical resources. This study aims to develop a predictive model for daily hospital outpatient volume using the XGBoost algorithm. …”
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Calibration of the Composition of Low-Alloy Steels by the Interval Partial Least Squares Using Low-Resolution Emission Spectra with Baseline Correction by M. V. Belkov, K. Y. Catsalap, M. A. Khodasevich, D. A. Korolko, A. V. Aseev

“…Further improvement of calibration accuracy was achieved by using the adaptive iteratively reweighted penalized least squares algorithm for spectrum baseline correction. …”
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Multi-Fidelity Machine Learning for Identifying Thermal Insulation Integrity of Liquefied Natural Gas Storage Tanks by Wei Lin, Meitao Zou, Mingrui Zhao, Jiaqi Chang, Xiongyao Xie

“…The results of the data experiments demonstrate that the multi-fidelity framework outperforms models trained solely on low- or high-fidelity data, achieving a coefficient of determination of 0.980 and a root mean square error of 0.078 m. Three machine learning algorithms—Multilayer Perceptron, Random Forest, and Extreme Gradient Boosting—were evaluated to determine the optimal implementation. …”
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Corrective soft bus-bar splitting for reliable operation of hybrid AC/DC grids by Basel Morsy, Matthew Deakin, Adolfo Anta, Jochen Cremer

“…As the original problem is NP-hard, this paper utilizes a column-and-constraint generation algorithm. Case studies on IEEE 5, 24, 39, and 67 hybrid AC/DC systems show superiority of the proposed method, manifested as significant improvement in operating costs, security, and converter redispatch needs, under different loading conditions.…”
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Predicting postoperative nausea and vomiting using machine learning: a model development and validation study by Maxim Glebov, Teddy Lazebnik, Maksim Katsin, Boris Orkin, Haim Berkenstadt, Svetlana Bunimovich-Mendrazitsky

“…Conclusions The machine learning-based models developed in this study enabled improved PONV prediction, thereby facilitating personalized care and improved patient outcomes.…”
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Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends by Chen Boshan

“…Second, the research focuses on key AI applications in quantitative investment, including multi-factor model optimization, high-frequency market risk management, multimodal data integration, and algorithmic trading enhancement. …”
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Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

“…Utilizing the high-quality data processed by this model, this study proposes and constructs a novel Grey Wolf Optimizer and Bidirectional Long Short-Term Memory (GWO-BiLSTM) temperature prediction framework, which combines a Grey Wolf Optimizer (GWO)-enhanced algorithm with a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Distributed Authentication of Power Grid Safety and Stability Control Terminals Based on DHT and Blockchain by Yening LAI, Ke FENG, Tongwei YU, Wang WANG, Guanjun TANG

“…The proposed scheme improves the communication safety between terminals of the power grid safety and stability control system without affecting the communication efficiency, thus ensuring the safe and stable operation of power grid.…”
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Intelligent resource allocation in internet of things using random forest and clustering techniques by Nahideh Derakhshanfard, Lida Hosseinzadeh, Fahimeh Rashid Jafari, Ali Ghaffari

“…Numerous current resource allocation methods, such as evolutionary algorithms and multi-agent reinforcement learning, are grossly inefficient at adapting well to IoT networks in light of dynamic and rapid changes due to the inherent computational complexity and high cost. …”
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Efficient Material Flow and Storage Space Determination in Automated Distribution Centers by Mohammed Alnahhal, Nikola Gjeldum, Mohammed Ruzayqat

“…Items with relatively large demand levels have scenario 3 as the optimal one. Results also showed that the model reduces both total costs and stacker crane utilization while improving system flexibility.…”
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Research status of gearboxes for high-power nuclear power circulation pumps by WEI Fude, WANG Huanhuan, YANG Shuncheng

“…Many scholars are committed to in-depth research on high-power nuclear power circulating pump gearboxes from the perspectives of dynamics, mechanical design, big data, optimization algorithms, etc., in response to the above-mentioned issues. …”
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Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome by Tarkan Karakan, Aycan Gundogdu, Hakan Alagözlü, Nergiz Ekmen, Seckin Ozgul, Varol Tunali, Mehmet Hora, Damla Beyazgul, O. Ufuk Nalbantoglu

“…The IBS-SSS evaluation for pre- and post-intervention exhibited significant improvement (p < .02 and p < .001 for the standard IBS diet and personalized nutrition groups, respectively). …”
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Monolayer graphene/platinum-modified 3D origami microfluidic paper-based biosensor for smartphone-assisted biomarkers detection by Arda Fridua Putra, Annisa Septyana Ningrum, Suyanto Suyanto, Vania Mitha Pratiwi, Muhammad Yusuf Hakim Widianto, Irkham Irkham, Wulan Tri Wahyuni, Isnaini Rahmawati, Fu-Ming Wang, Chi-Hsien Huang, Ruri Agung Wahyuono

“…Conclusion: The 3D origami structure facilitates efficient fluid handling and multiplex detection, while the nanocatalyst modification improves pore infiltration and sensitivity. This work demonstrates, for the first time, a cost-effective, portable, and high-performance biosensor for dual biomarker detection, offering substantial promise for point-of-care diagnostics in neurological and metabolic health monitoring.   …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…Proper thermal management ensures uniform heat distribution, which is essential for optimizing efficiency, safety, and reliability. However, obtaining comprehensive real-time temperature data for large-scale battery systems is challenging due to the high costs, complexity, and impracticality of deploying extensive sensor networks. …”
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Modelling and Optimisation of Hysteresis and Sensitivity of Multicomponent Flexible Sensing Materials by Kai Chen, Qiang Gao, Yijin Ouyang, Jianyong Lei, Shuge Li, Songxiying He, Guotian He

“…Furthermore, the sensing performance in this study shows a significant enhancement compared to prior research, with the hysteresis performance improved by 31% and sensitivity increased by 26%. This approach enhances the experimental efficiency and reduces costs. …”
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High-robustness integrated adversarial training method for fingerprint-based indoor localization systems by ZHANG Xuejun, LI Mei, CHEN Hui, WANG Guohua

“…In EDEAD, the data distillation technique was employed to improve the quality of the augmented data and the early stopping algorithm was used to save training costs. …”
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Research on Self-Diagnosis and Self-Healing Technologies for Intelligent Fiber Optic Sensing Networks by Ruiqi Zhang, Liang Fan, Dongzhu Lu

“…Unlike traditional self-diagnosis techniques that rely on an optical time domain reflectometer, the proposed self-diagnosis algorithm utilizes data structure analysis, significantly reducing dependence on costly equipment and improving self-diagnosis efficiency. …”
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TECHNOLOGICAL ADVANCES IN ELECTROPLATING: ARTIFICIAL INTELLIGENCE TO PREDICT ZINC COATING THICKNESS ON SAE 1008 LOW CARBON STEELS by Luciano M. L. de Oliveira, Fabiana L. da Silva, Paulo R. Janissek, Juliano C. Toniolo

“…This ultimately reduces costs and improves product quality.…”
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