Preventing Overturning of Mobile Cranes Using an Electrical Resistivity Measurement System by Hongseok Jang, Yeonho Lee, Hongseok Lee, Youngtaek Cha, Sungjoon Choi, Jongkyu Park

“…While numerous studies have addressed the causes and prevention of mechanical accidents, there has been a lack of research focusing on the prevention of environmental accidents. …”
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Machine learning enhanced formation pressure prediction using integrated well logging and mud logging by Jiwen Liang, Ming Luo, Wentuo Li, Bo Sun, Chuanliang Yan, Zhongying Han, Yuanfang Cheng

“…Based on machine learning algorithms and a large amount of known data, a machine learning formation pressure model with integrated well logging and mud logging data (IWM) was established. …”
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Optimization of Flavor Quality of Lactic Acid Bacteria Fermented Pomegranate Juice Based on Machine Learning by Wenhui ZOU, Fei PAN, Junjie YI, Linyan ZHOU

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Hybrid method for automatic initialization and segmentation of ventricular on large-scale cardiovascular magnetic resonance images by Ning Pan, Zhi Li, Cailu Xu, Junfeng Gao, Huaifei Hu

“…Thus, we proposed a full automatic and robust algorithm for large-scale cardiac MRI segmentation by combining the advantages of deep learning localization and 3D-ASM restriction. …”
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Failure mechanism-driven multi-adversarial domain transfer learning for rolling bearing fault diagnosis by Zhihui Zhang, Zhidan Zhong, Zhe Li, Wentao Mao, Yunhao Cui

“…To address these challenges, this paper proposes a Failure Mechanism-Driven Multi-Adversarial Domain Transfer Learning algorithm. The core of this method is the deep integration of physical prior knowledge with data-driven models. …”
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Beyond buzzwords: NLP reveals common threads in sustainable and circular construction discourse by Shakarim Aubakirov, Alexandr Pak, Iskander Akhmetov, Aidana Tleuken, Huseyin Atakan Varol, Assel Akzhalova, Ferhat Karaca

“…By clarifying the distinctions and overlaps between the terms “circular construction” and “sustainable construction”, our research offers enhanced understanding for policymakers, industry practitioners, and academics aiming to integrate sustainable and circular principles effectively within the construction sector.…”
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Combining Camera–LiDAR Fusion and Motion Planning Using Bird’s-Eye View Representation for End-to-End Autonomous Driving by Ze Yu, Jun Li, Yuzhen Wei, Yuandong Lyu, Xiaojun Tan

“…End-to-end autonomous driving has become a key research focus in autonomous vehicles. However, existing methods struggle with effectively fusing heterogeneous sensor inputs and converting dense perceptual features into sparse motion representations. …”
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari, M. Murugappan, Javeed Shaikh-Mohammed, Muhammad E. H. Chowdhury

“…The rapid development of intelligent technologies has led researchers to strive to improve facial emotion recognition techniques. …”
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Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

“…The clinical community has a lot of diabetes diagnostic data. Machine learning algorithms may simplify finding hidden patterns, retrieving data from databases, and predicting outcomes. …”
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Optimal allocation of renewable energy resources in a smart grid under neutrosophic credibility-based uncertainty by Muhammad Zafar Abbas, Rukhshanda Anjum, Muhammad Umar Mirza, Abdulrahman A. Almehizia, Amir Hussain

“…Modern research in renewable energy systems faces many challenges in dealing with uncertain data and inconsistent expert evaluations, particularly in the context of smart grid systems. …”
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Exploring the synchronization of cortical networks via entrainment to intrinsic frequencies by Sandeep Kumar Agnihotri, Jiang Cai, Zhen Wang

“…Both tACS and tDCS were simulated to assess their effect on network synchronization. An algorithm was employed to extract the network's intrinsic frequency and align stimulation frequencies accordingly. …”
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Regression models for predicting the effect of trash rack on flow properties at power intakes by Shuguang Li, Sultan Noman Qasem, Hojat Karami, Ely Salwana, Alireza Rezaei, Danyal Shahmirzadi, Shahab S. Band

“…Vortex flow characteristics in a reservoir and horizontal water intake have been predicted by using regression models in this numerical research. In this paper, three standalone machine learning models – Random Forest (RF), K-nearest neighbours (KNN), Gradient Boosting (GB) – and a proposed hybrid model based on Lévy Jaya Algorithm (LJA) and GB (LJA-GB) are employed to estimate the effect of trash racks on flow properties at power intakes. …”
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Advancing Water Quality Management: An Integrated Approach Using Ensemble Machine Learning and Real-Time Interactive Visualization by Jigna K. Pandya, Suresh S. Khandelwal, Rupesh Kumar Tipu, Kartik S. Pandya

“…This integration reflects the heightened prominence of deep learning methods and aligns the study’s methodology with cutting-edge research trends. Cross-validation results further confirmed the model’s robustness, with a mean accuracy of 96.9% and a low standard deviation. …”
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Optimization of dual-layer flow field in a water electrolyzer using a data-driven surrogate model by Lizhen Wu, Zhefei Pan, Shu Yuan, Xiaoyu Huo, Qiang Zheng, Xiaohui Yan, Liang An

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Associations between exposure to multiple environmental chemicals and metabolic syndrome: A mixture analysis by Ruiqiang Li, Xiaoyi Lin, Tingyu Lu, Jiao Wang, Ying Wang, Lin Xu

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Global Assessment of Mesoscale Eddies with TOEddies: Comparison Between Multiple Datasets and Colocation with In Situ Measurements by Artemis Ioannou, Lionel Guez, Rémi Laxenaire, Sabrina Speich

“…This atlas aims to be a valuable resource for the oceanographic community, providing an open dataset that can support diverse applications in ocean dynamics, climate research, and marine resource management.…”
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ASTER GDEM Correction Based on Stacked Ensemble Learning and ICEsat-2/ATL08: A Case Study from the Qilian Mountains by Qi Wei, Yanli Zhang, Yalong Ma, Ruirui Yang, Kairui Lei

“…This study can provide high-precision DEM scientific data for quantitative remote sensing, flood prediction, and other research.…”
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Phenotyping of risk factors and prediction of inhospital mortality in patients with coronary artery disease after coronary artery bypass grafting based on explainable artificial in... by B. I. Geltser, K. I. Shakhgeldyan, V. Yu. Rublev, I. G. Domzhalov, M. M. Tsivanyuk, O. I. Shekunova

“…The developed data processing and analysis algorithm ensured high quality of preoperative risk factors identification and IHM prediction after CABG. …”
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An Adaptive Weight Physics-Informed Neural Network for Vortex-Induced Vibration Problems by Ping Zhu, Zhonglin Liu, Ziqing Xu, Junxue Lv

“…Vortex-induced vibration (VIV) is a common fluid–structure interaction phenomenon in practical engineering with significant research value. Traditional methods to solve VIV issues include experimental studies and numerical simulations. …”
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Automated Alerts Systems for Pediatric Sepsis Patients: A Systematic Review by Mahmasoni Masdar, Ariani Arista Putri Pertiwi, Tiara Royani, Nana Caterina Sandi, Muhammad Ulin Nuha, Fransiska Regina Cealy, Alessandra Hernanda Soselisa, Suprihatiningsih Suprihatiningsih, Desi Dwi Siwi Atika Dewi

“…Limitations include language restrictions and the inability to assess each tool's effectiveness or identify the optimal sepsis detection algorithm, underscoring the need for further research, including a meta-analysis.…”
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