Penaeus vannamei aquaculture water quality prediction based on the improved back propagation neural network by DING Jinting, ZANG Zelin, HUANG Min

“…The comparison between the original measured and predicted values of the BP-neural network showed that the relative errors, with a few exceptions, were lower than 2.5%.In conclusion, the BP-neural network model can well reveal the complicated non-linear relationship between the input and output water quality variables in intensive P. vannamei tanks, and the improved BP-neural network (FABPM) method based on fuzzy method has the characteristics of fast convergence, high accuracy and good stability. …”
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A comprehensive IoT cloud-based wind station ready for real-time measurements and artificial intelligence integration by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…Using this method, all station data are processed every 3 seconds and stored ready for Artificial Intelligence usage with an approximate latency of 150–300 milliseconds, representing up to an 85% reduction in processing delay compared to similar solutions with over 1-second latencies. …”
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Patient-specific fluid–structure simulations of anomalous aortic origin of right coronary arteriesCentral MessagePerspective by Michael X. Jiang, MD, MEng, Muhammad O. Khan, PhD, Joanna Ghobrial, MD, Ian S. Rogers, MD, Gosta B. Pettersson, MD, PhD, Eugene H. Blackstone, MD, Alison L. Marsden, PhD

“…Conclusions: Patient-specific FSI modeling of AAORCA is a promising, noninvasive method to assess the iFR reduction caused by intramural geometries and inform surgical intervention. …”
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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…Results demonstrate three key findings: (1) By introducing prototype learning, a meta-learning approach, to guide model updates, we achieved precise assessments with small training samples, attaining an MAE of 1.02, representing 58.5–76.1% error reduction compared to conventional machine learning algorithms. …”
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Revolutionizing Clear-Sky Humidity Profile Retrieval with Multi-Angle-Aware Networks for Ground-Based Microwave Radiometers by Yinshan Yang, Zhanqing Li, Jianping Guo, Yuying Wang, Hao Wu, Yi Shang, Ye Wang, Langfeng Zhu, Xing Yan

“…Based on the 7-year (2018–2024) in situ measurements from Beijing, Nanjing, and Shanghai, validation results reveal that AngleNet achieves substantial improvements, with an average R2 of 0.71 and a root mean square error (RMSE) of 10.39%, surpassing conventional models such as LGBM (light gradient boosting machine) and RF (random forest) by over 10% in both metrics, and demonstrating a remarkable 41% increase in R2 and a 10% reduction in RMSE compared to the previous BRNN method (batch normalization and robust neural network). …”
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Seismic site characterization and development of SPT(N) to shear wave velocity correlation of Noida city by Pankaj Kundu, Devagya Raman, Anindya Pain, Josodhir Das, Ravi Sundaram, Sorabh Gupta

“…However, the Standard penetration test (SPT–N), a method widely used by civil engineers, can be leveraged to estimate $$V_{S}$$ in such areas by developing correlations between $$V_{S}$$ and SPT–N values. …”
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A Hybrid RBF-PSO Framework for Real-Time Temperature Field Prediction and Hydration Heat Parameter Inversion in Mass Concrete Structures by Shi Zheng, Lifen Lin, Wufeng Mao, Yanhong Wang, Jinsong Liu, Yili Yuan

“…The hybrid F₃, incorporating Dynamic Time Warping (DTW) for elastic time alignment and feature penalties for engineering-critical metrics, achieved superior performance with a 74% reduction in the prediction error (mean MAE = 1.0 °C) and <2% parameter identification errors, resolving the phase mismatches inherent in F₂ and avoiding F₁’s prohibitive computational costs (498 FEM calls). …”
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The possibilities of the non-contrast MRI perfusion in the quantitative assessment of changes in cerebral blood flow by V. V. Popov, Yu. A. Stankevich, O. B. Bogomyakova, A. A. Tulupov

“…Conclusions. The ASL method allows for the quantitative assessment of the dynamics of cerebral perfusion in the early recovery period, with a significant (p &lt; 0.001) reduction in tissue blood flow in the ischemic focus relative to the analyzed regions of interest and the control group. …”
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Modeling drug retention as memory effects in obese patients using fractional and augmented models by Amani R. Ynineb, Erhan Yumuk, Dana Copot, Bora Ayvaz, Bouchra Khoumeri, Ghada Ben Othman, Marcian D. Mihai, Isabela R. Birs, Cristina I. Muresan, Clara M. Ionescu

“…During the awakening phase, both the augmented and fractional-order models reduce BIS prediction error compared to the classical model. The augmented model lowers RMSE by 22.5% (from 10.38 to 8.04), while the fractional model achieves a 21.4% reduction (to 8.16) (based on one obese patient case). …”
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Path Planning and Motion Control of Robot Dog Through Rough Terrain Based on Vision Navigation by Tianxiang Chen, Yipeng Huangfu, Sutthiphong Srigrarom, Boo Cheong Khoo

“…The experimental results show that the RGB-D system exhibits superior velocity stability and trajectory accuracy to the SLAM system, with a 20% reduction in the cumulative velocity error and a 10% improvement in path tracking precision. …”
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Harnessing solar drying for starter cultures: A novel approach to backslopping fermentation by Marcel Houngbédji, Donan Bangbadé, D. Sylvain Dabadé, Schadrac D. Agossevi, B. Pélagie Agbobatinkpo, S. Wilfrid Padonou, Joseph Dossou, Paulin Azokpota, D. Joseph Hounhouigan

“…Solar drying is a cost-effective and sustainable method for the preservation of food and food ingredient, particularly in West Africa. …”
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Mechanical Anastomotic Coupling Device versus Hand-sewn Venous Anastomosis in Head and Neck Reconstruction—An Analysis of 1694 Venous Anastomoses by Rajan Arora, Kripa Shanker Mishra, Hemant T. Bhoye, Ajay Kumar Dewan, Ravi K. Singh, Ravikiran Naalla

“…The venous anastomosis is a critical step in free-tissue transfer. The margin of error is less and the outcome depends on the surgeon’s skill and technique. …”
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Evidence Based Gait Analysis Interpretation Tools (EB-GAIT) treatment recommendation and outcome prediction models to support decision-making based on clinical gait analysis data. by Michael H Schwartz, Andrew G Georgiadis

“…The EB-GAIT approach addresses the limitations of the conventional CGA interpretation method, offering a more structured and data-driven decision-making process. …”
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EU-GAN: A root inpainting network for improving 2D soil-cultivated root phenotyping by Shangyuan Xie, Jiawei Shi, Wen Li, Tao Luo, Weikun Li, Lingfeng Duan, Peng Song, Xiyan Yang, Baoqi Li, Wanneng Yang

“…The trait error reduction rates (TERRs) for the root area, root length, convex hull area, and root depth are 76.07 %, 68.63 %, 48.64 %, and 88.28 %, respectively, enabling a substantial improvement in the accuracy of root phenotyping. …”
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The Potential of a Laser-Aspiration Solution for Refractive Lens Exchange by D. E. Arakelyan, S. Yu. Kopaev, I. A. Il’inskaya, V. V. Pominova

“…This review presents the current knowledge about the methods of lens surgery for the correction of refractive errors in patients with presbyopia and other refractive errors. …”
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Multi-Level Feature Fusion Attention Generative Adversarial Network for Retinal Optical Coherence Tomography Image Denoising by Yiming Qian, Yichao Meng

“…Evaluations on three public OCT datasets compared traditional methods and deep learning models using PSNR, SSIM, CNR, and ENL metrics. …”
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AI-driven demand forecasting for enhanced energy management in renewable microgrids: A hybrid LSTM-CNN approach by Bashiru olalekan ariyo, mutalub adesina lambe, olalekan ogunbiyi, musa abdulwaheed, bilkisu jimada ojuolape, monsurat omolara balogun

“…Results: The hybrid LSTM-CNN model demonstrated superior performance, achieving an R2 value of 0.87, a Mean Absolute Error (MAE) of 1.45 MWh, and a Root Mean Squared Error (RMSE) of 2.12 MWh. …”
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Optimized deep neural network architectures for energy consumption and PV production forecasting by Eghbal Hosseini, Barzan Saeedpour, Mohsen Banaei, Razgar Ebrahimy

“…The results demonstrate that ODNN outperforms the average performance of other methods, achieving a 27% improvement in forecasting accuracy and a 22% reduction in error across various metrics. …”
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Bridge Scorekeeping Automation: An iOS Application to Improve Tournament Scoring Accuracy and Efficiency by Aqilla Shahbani Mahazoya, Trianggoro Wiradinata

“…Results demonstrated a reduction in scoring errors by 8–36% and increased efficiency compared to conventional methods. …”
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An adaptive processing model for large superalloy pipeline components by LUO Ziyan, QIN Xiansheng, WANG Zhanxi, LIU Weiwei, LI Shulu

“…Domestic and foreign scholars have conducted fruitful theoretical and experimental study of adaptive machining theory, curved surface path planning algorithms and model reconstruction methods. At present, the theoretical analysis methods for deformation analysis and error compensation in the adaptive machining of high-temperature alloys are not clear; The precise physical model reconstruction technology is not yet mature and engineering applications are not yet popularized. …”
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