Digitally twin driven ship cooling pump fault monitoring system and application case by Shaojuan Su, Zhe Miao, Yong Zhao, Nanzhe Song

“…Using the random forest algorithm for data training and testing, the results showed that the root mean square error for the training set was 0.0037873, and for the test set, it was 0.008929, indicating high accuracy in predicting the status of cooling pumps. …”
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Finite Element Modeling of the behavior of Hybrid-Fiber Reinforced Concrete under Triaxial Compression by Ali Naserifar

“…However, the behavior of fiber reinforced concrete has been studied frequently but a numerical model that can predict the behavior of fiber reinforced concrete well is under research. …”
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Fault Diagnosis Research on Bearingof Motor Based on LMD And Support Vector Machine by YIN Zhao-jie, XU Tong-le, ZHENG Dian-kun

“…Finally，the energy feature vector is used as the training sample and test sample of SVM，and the fault information of motor bearing is trained and predicted. Experimental results show that the proposed method can effectively diagnose the fault of motor bearing.…”
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Fracture toughness of rough and frictional cracks emanating from a re-entrant corner by Andrea Carpinteri, Andrea Spagnoli, Michele Terzano, Sabrina Vantadori

“…In mixed-mode conditions, the competing contribution of the different stress intensity factors predicts fracture initiation load as well as crack propagation direction. …”
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Urban Triatomines in Central México: Linking Ecological Niche Models with New <i>Triatoma barberi</i> (Reduviidae:Triatominae) Records by Salvador Zamora-Ledesma, Norma Hernández-Camacho, Jesús Luna-Cozar, Robert W. Jones, María Elena Villagrán-Herrera, Brenda Camacho-Macías

“…This study employs ecological niche modeling (ENM) to predict the potential distribution of <i>T. barberi</i> in the region, using occurrence records and environmental variables. …”
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Stellar Streams Reveal the Mass Loss of Globular Clusters by Yingtian Chen, Hui Li, Oleg Y. Gnedin

“…By fitting power-law relations between the mass-loss rate and key GC properties, we identify positive correlations with GC mass and orbital frequency, consistent with the predictions from N -body simulations.…”
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Robust Smooth Sliding-Mode-Based Controller with Fixed-Time Convergence for Missiles considering Aerodynamic Uncertainty by Yuhang Yun, Jie Guo, Shengjing Tang

“…A cascade control structure is employed with the derived control algorithm, and therein, the control input signal is obtained. …”
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Design of an Intelligent Energy Management Prototype for an Electric Lighting Network on a Raspberry Pi Board by Jouahri Mohammed Amine, Moukhtari Manal, Oulhaj Nabil, Khimouj Mounir, Tajer Abdelouahed, Boulghasoul Zakaria

“…These data are transmitted to the Raspberry Pi via the MQTT protocol, where a neural network model, trained beforehand, predicts the optimal operating cycle of the street lamps to adjust their brightness in real time. …”
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Computationally Effective Modeling of Cold Rolling: Application to Al Alloys by János György Bátorfi, Jurij J. Sidor

“…The distortion of meshes predicted by both FEM and FLM follow the same evolutionary pattern.…”
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Automatic location of surface-monitored microseismicity with deep learning by Zhaolong Gan, Xiao Tian, Xiong Zhang, Mengxue Dai

“…In this study, we propose an approach to locate microseismic events using a deep learning algorithm with surface data. A fully convolutional network is designed to predict source locations. …”
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Machine tool FEM model correction assisted by dynamic evolution sequence by Weihao Lin, Peng Zhong, Xindi Wei, Li Zhu, Xuanlong Wu

“…Moreover, replacing the random sequence with a dynamic evolution sequence enhances the search space coverage of the heterogeneous comprehensive learning particle swarm optimization (HCLPSO) algorithm. The results of numerical examples demonstrate that the finite element model, corrected using the proposed method, accurately predicts the true displacement responses of the machine tool. …”
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On Evaluation and Comparison of Blast Loading Methods Used In Numerical Simulations by Vahdet Uçar, Atıl Erdik

“…Mesh resolution study of ALE formulation is conducted todetermine the influence of element mesh size on predicting blast loadingeffects that is converted through fluid structure interaction algorithm fromEulerian to Lagrangian type of elements. …”
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Thermoelectric Modeling and Online SOC Estimation of Li-Ion Battery for Plug-In Hybrid Electric Vehicles by Aishwarya Panday, Hari Om Bansal, Pramod Srinivasan

“…Therefore, an accurate battery model is required to predict the I-V characteristic and dynamic behavior of a battery. …”
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Modeling emotional abuse based on emotional maturity and self-differentiation with the mediating role of marital intimacy by mehran sharifi, qumarth karimi, omid moradi, shokooh navabinejad

“…The findings showed that emotional maturity, self-differentiation and marital intimacy can directly predict emotional abuse (P< 0.001). Also, the indirect effect of emotional maturity (P= 0.001) and self-differentiation (P< 0.001) with the mediation of marital intimacy on emotional abuse was significant. …”
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Novel insights of disulfidptosis-mediated immune microenvironment regulation in atherosclerosis based on bioinformatics analyses by Huanyi Zhao, Zheng Jin, Junlong Li, Junfeng Fang, Wei Wu, J. F. Fang

“…Furthermore, a nomogram including hub genes was established that accurately predicted the occurrence of AS. The consensus clustering algorithm was used to separate patients with early atherosclerotic plaques and patients with advanced atherosclerotic plaques into two disulfidptosis subtypes. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…These outputs are fused into a combined feature vector, which is then used by a meta-classifier for final predictions. This approach effectively captures both structured features and non-linear patterns, making it suitable for datasets with complex dependencies. …”
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Development and Analysis of Patient-Based Complete Conducting Airways Models. by Rafel Bordas, Christophe Lefevre, Bart Veeckmans, Joe Pitt-Francis, Catalin Fetita, Christopher E Brightling, David Kay, Salman Siddiqui, Kelly S Burrowes

“…A number of global clinical lung function measures are compared to resistance predictions in the models to assess their suitability for use in a patient-specific setting. …”
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A deep learning software tool for automated sleep staging in rats via single channel EEG by Andrew Smith, Snezana Milosavljevic, Courtney J. Wright, Charlie A. Grant, Ana Pocivavsek, Homayoun Valafar

“…The algorithm was able to predict key parameters of sleep architecture, including total bout duration, average bout duration, and number of bouts, with significant accuracy. …”
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Block Markov superposition transmission of LDPC codes by Qianfan Wang, Kongjing Guo, Xiao Ma

“…To analyze the error-floor performance of BMST-LDPC codes, we employ the genie-aided (GA) lower bound, which can efficiently predict the error-correcting performance in error-floor region. …”
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Exothermic thermosolutal convection in a nanofluid-filled square cavity with a rotating Z-Fin: ISPH and AI integration by Kuiyu Cheng, Abdelraheem M. Aly, Nghia Nguyen Ho, Sang-Wook Lee, Andaç Batur Çolak, Weaam Alhejaili

“…The ANN model, employing the Levenberg–Marquardt algorithm, achieved a coefficient of determination $ R = 0.99994 $ and a mean squared error $ \text{MSE} = 4.21\times {10}^{-6} $, demonstrating its reliability in predicting thermal performance. …”
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