Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan by Ahmed Emara, Sameh A. Kantoush, Mohamed Saber, Tetsuya Sumi, Vahid Nourani, Emad Mabrouk

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An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…Regression scores equal to 1 indicate a good match between the actual data and the predictions. Conclusively, the proposed investigation provides insightful AI, ML and CFD-proposed analysis of blood-based nano-particles which can improve imaging techniques, provide tailored drug delivery, reduce hyperthermia, improve blood flow, and show potential for application in medicine.Highlights Artificial intelligence and machine learning-based CFD simulation of the blood-mediated tri-hybrid nano-fluid flow is presented.An improved finite difference scheme (the Keller-Box method), is utilized to numerically evaluate the problem.The LMA-ANN forecasts with an absolute error range of [Formula: see text] to [Formula: see text] relative to the actual data.Regression scores equal to 1 indicate a strong correlation between forecasts and actual data.…”
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Generalized and open selection approaches for the population mean: accounting for non-response and measurement error in single-phase sampling by Muhammad Sajjad, Muhammad Ismail, Atta-ur-Rahman, Amjad Rehman, Tariq Mahmood

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Segment-based Eulerian-Lagrangian transition method for flat nozzle spray atomization simulation by Mengqi Liu, David L.S. Hung

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Artificial neural networking for computational assessment of ternary hybrid nanofluid flow caused by a stretching sheet: implications of machine-learning approach by Imad Khan, M. Waleed Ahmed Khan

“…Researchers are mainly interested in using soft computing artificial intelligence (AI) methods due to their broad applications in analysis, modelling and simulations. …”
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An AIoT-Based Automated Farming Irrigation System for Farmers in Limpopo Province by Relebogile Langa, Michael Nthabiseng Moeti, Thabiso Maubane

“…In acquiring these, the ARIMA model was applied alongside DSRM for implementing the mobile application. The results obtained indicate that the use of AI and IoT (AIoT) in agriculture can improve operational efficiency with reduced human intervention as there is real-time data acquisition with real-time processing and predictions.…”
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Achieving supply chain sustainability: enhancing supply chain resilience, organizational performance, innovation and information sharing: empirical evidence from Chinese SMEs by Saqib Mehmood, Samera Nazir, Jianqiang Fan, Zarish Nazir

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Risk Management Guide for Information System Infrastructure in Digital Banking by Raden Budiraharjo, Silhi, Ali Jazzy, Na'il Ghani Prihartono

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CNN-based vane-type vortex generator modelling by Koldo Portal-Porras, Unai Fernandez-Gamiz, Ekaitz Zulueta, Roberto Garcia-Fernandez, Xabier Uralde-Guinea

“…This fact, added to the growth of the Artificial Intelligence, has led to an increasing number of studies using data-driven methods to solve fluid dynamic problems. …”
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High-speed aerated jet trajectory simulated by compounding method of Euler-Euler model and meshless SPH method by Junling He, Qingzhi Hou, Jijian Lian, Wenxiao Jia, Panhong Ren

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Distribution and sources of fallout ¹³⁷Cs and ^239+240Pu in equatorial and Southern Hemisphere reference soils by G. Dicen, G. Dicen, F. Guillevic, S. Gupta, P.-A. Chaboche, P.-A. Chaboche, P.-A. Chaboche, K. Meusburger, P. Sabatier, O. Evrard, C. Alewell

“…</p> <p>We compiled <span class="inline-formula">¹³⁷</span>Cs and <span class="inline-formula">^239+240</span>Pu data published from undisturbed (so-called “reference”) soils in the equatorial and Southern Hemisphere regions to build a database within the framework of the AVATAR (A reVised dATing framework for quantifying geomorphological processes during the Anthropocene) project. …”
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Performance Optimization in Three-Modality Biometric Verification using Heterogeneous CPU-GPU Computation by Bopatriciat Boluma Mangata, Pierre Tshibanda wa Tshibanda, Guy-Patient Mbiya Mpoyi, Jean Pepe Buanga Mapetu, Rostin Mabela Matendo Makengo, Eugène Mbuyi Mukendi

“…Execution times were significantly reduced, ranging from 0.03 ms to 0.67 ms for data sizes between 50 and 1000. Analysis of the performance gains, based on Amdahl's law, reveals that the proportion of tasks that can be parallelized remains higher in heterogeneous systems than in parallel and sequential systems, even though part of processing remains sequential for large data sizes. …”
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Interpretable Deep Learning Model for Grape Leaf Disease Classification Based on EfficientNet with Grad-CAM Visualization by Castaka Agus Sugianto, Dini Rohmayani, Jhoanne Fredricka, Mohamed Doheir

“…Future research can explore real-time field data collection, attention mechanisms, and self-supervised learning to further improve classification accuracy and model generalization for large-scale agricultural applications.…”
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Computationally Efficient Light Field Video Compression Using 5-D Approximate DCT by Braveenan Sritharan, Chamira U. S. Edussooriya, Chamith Wijenayake, R. J. Cintra, Arjuna Madanayake

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Arctic tern-optimized weighted feature regression system for predicting bridge scour depth by Jui-Sheng Chou, Asmare Molla

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Blast loading prediction in a typical urban environment based on Bayesian deep learning by Weiwen Peng, Meilin Pan, Chunjiang Leng, Shufei Wang, Wei Zhong

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Propulsion curve analysis and optimisation of biomimetic pectoral fin with three degree of freedom based on multi-layer perception by Zonggang Li, Bin Li, Guangqing Xia, Huifeng Kang

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Analysis of the influence of the daily regulation of power stations on navigable flow conditions at river confluences using the LSTM model by Hongcheng Xue, Shihao Cui, Qian Ma, Zhongyong Li, Pengyu Zhou, Yuanyuan Li, Lingyun Xie

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A Nonparametric K-sample Test for Variability Based on Gini’s Mean Difference by Sameera Hewage

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Indicators of Global Climate Change 2024: annual update of key indicators of the state of the climate system and human influence by P. M. Forster, C. Smith, C. Smith, T. Walsh, W. F. Lamb, W. F. Lamb, R. Lamboll, C. Cassou, C. Cassou, M. Hauser, Z. Hausfather, Z. Hausfather, J.-Y. Lee, J.-Y. Lee, M. D. Palmer, M. D. Palmer, K. von Schuckmann, A. B. A. Slangen, S. Szopa, B. Trewin, J. Yun, N. P. Gillett, S. Jenkins, H. D. Matthews, K. Raghavan, A. Ribes, J. Rogelj, J. Rogelj, J. Rogelj, D. Rosen, X. Zhang, M. Allen, M. Allen, L. Aleluia Reis, L. Aleluia Reis, R. M. Andrew, R. A. Betts, R. A. Betts, A. Borger, J. A. Broersma, S. N. Burgess, L. Cheng, P. Friedlingstein, P. Friedlingstein, C. M. Domingues, C. M. Domingues, M. Gambarini, M. Gambarini, T. Gasser, J. Gütschow, M. Ishii, C. Kadow, J. Kennedy, R. E. Killick, P. B. Krummel, A. Liné, A. Liné, A. Liné, D. P. Monselesan, C. Morice, J. Mühle, V. Naik, G. P. Peters, A. Pirani, J. Pongratz, J. Pongratz, J. C. Minx, J. C. Minx, M. Rigby, R. Rohde, A. Savita, A. Savita, S. I. Seneviratne, P. Thorne, C. Wells, L. M. Western, G. R. van der Werf, S. E. Wijffels, S. E. Wijffels, V. Masson-Delmotte, P. Zhai

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