Investigation of mechanical properties and microstructural characteristics of rice husk ash-based geopolymer mortar as patch repair by Pinta Astuti, Muhammad Sakti Isnaini, Devi Sasmita, Adhitya Yoga Purnama, Asiya Nurhasanah Habirun, Anisa Zulkarnain, Angga Jordi Nouvaldi, Fanny Monika

“…This study explored the use of rice husk ash and alkali activators (NaOH/Na2SiO3), with different activator percentages (40%, 45%, and 50%), to evaluate their mechanical properties and potential applications as patch repair materials. This research involved formulating an optimal mix design through trial and error in a laboratory setting, followed by curing at 70 °C and testing at room temperature. …”
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Bridging experiments and models, towards a new paradigm: DROP-PINN, a physics-informed neural network to predict droplet rupture in multiphase systems by Grégory Bana, Fabrice Lamadie, Sophie Charton, Didier Lucor, Nida Sheibat-Othman

“…However, ANN training requires a large and high-fidelity dataset, making it time-consuming and error-prone. Physics-Informed Neural Networks (PINNs) may address this challenge by embedding physical laws into the learning process, ensuring physically consistent PBE predictions. …”
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AI-driven diagnosis and health management of autonomous electric vehicle powertrains: An empirical data-driven approach by Hicham El hadraoui, Adila El maghraoui, Oussama Laayati, Erroumayssae Sabani, Mourad Zegrari, Ahmed Chebak

“…Among the models, the optimized neural network combined with CA-selected features achieved the most consistent diagnostic performance, supported by low root mean square error and balanced evaluation metrics. The novelty of this work lies in the empirical benchmarking of reduced feature sets across diverse classifier families and the end-to-end validation of diagnostic robustness using real vibration signals under controlled EV-relevant fault scenarios. …”
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Large-Scale Completion of Ionospheric TEC Maps Using Machine Learning Models With Constraints Conditions by Qingfeng Li, Hanxian Fang, Chao Xiao, Die Duan, Hongtao Huang, Ganming Ren

“…Results show that the CGVAE-label model excels in TEC completion, achieving a mean structural similarity of 93.80% and a root mean square error of 2.20 TECU. It outperforms the baseline CGVAE model, particularly in reconstructing peak ionospheric structures. …”
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Bayesian Model Averaging for Satellite Precipitation Data Fusion: From Accuracy Estimation to Runoff Simulation by Shaowei Ning, Yang Cheng, Yuliang Zhou, Jie Wang, Yuliang Zhang, Juliang Jin, Bhesh Raj Thapa

“…Evaluation metrics included the correlation coefficient (CC), root mean square error (RMSE), and Kling–Gupta efficiency (KGE). The Variable Infiltration Capacity (VIC) hydrological model was further applied to assess how these datasets affect runoff simulations. …”
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Adaptive control strategies for button motor actuated insect scale flapping wing MAV mechanisms by Spoorthi Singh, Meet Hitesh Jain, Kanishk Kaushal, Mohammad Zuber, Ernnie Illyani Basri, Kamarul Arifin Ahmad, Sharul Sham Dol, Vishnu G. Nair

“…Performance metrics such as rise time, settling time, overshoot, and integral absolute error (IAE) demonstrate the superior efficiency and disturbance rejection capabilities of SRFFC compared to FPID. …”
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Novel Mathematical Modeling Parameters of PEMFC Based on Newton–Raphson Iterative Method by Ahmed A. Zaki Diab, Ahmed Hamdy Ali, Hamdy M. Sultan, Mohamed A. Ismeil, Montaser Abdelsattar

“…The suggested model attained a relative error of under 0.5% and SSE values as low as <inline-formula> <tex-math notation="LaTeX">$2.9795\times 10^{-7}$ </tex-math></inline-formula> for five measurement locations in the SR-250W stack, hence affirming the estimation&#x2019;s excellent precision.…”
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Research on a New Method of Macro–Micro Platform Linkage Processing for Large-Format Laser Precision Machining by Longjie Xiong, Haifeng Ma, Zheng Sun, Xintian Wang, Yukui Cai, Qinghua Song, Zhanqiang Liu

“…The proposed method can generate a smooth trajectory of the servo platform with bounded acceleration by the finite impulse response (FIR) filter under the global blending error constrained by the galvanometer FOV. Moreover, the trajectory of the galvanometer is generated by vector subtraction, and the motion distribution of macro–micro structure is accurately realized. …”
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From Stationary to Nonstationary UAVs: Deep-Learning-Based Method for Vehicle Speed Estimation by Muhammad Waqas Ahmed, Muhammad Adnan, Muhammad Ahmed, Davy Janssens, Geert Wets, Afzal Ahmed, Wim Ectors

“…The results indicate that the proposed method can estimate vehicle speeds with an absolute error as low as 0.53 km/h. The study also discusses the associated problems and constraints with nonstationary drone footage as input and proposes strategies for minimizing noise and inaccuracies. …”
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Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospec... by Sheng Chen, Danling Zhang, Guisheng Ding, Mengqi Chen, Songsong Wu, Jianzhong Zou

“…The calibration curve of the nomogram demonstrated good consistency between actual observations and nomogram predictions, with an absolute error of 0.066. The model’s discriminative ability was evaluated by the area under the curve, which was 0.887 (95% CI: 0.818–0.955). …”
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Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

“…Evaluations are conducted on two large datasets from the Genomics of Drug Sensitivity in Cancer (GDSC) repository, and the proposed NNCAE-GEO-Conv-LSTM-based approach has achieved 96.99% and 97.79% accuracies, respectively, with reduced processing time and error rate for the DRP problem.…”
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An AI-Enabled Framework for <i>Cacopsylla chinensis</i> Monitoring and Population Dynamics Prediction by Ruijun Jing, Deyan Peng, Jingtong Xu, Zhengjie Zhao, Xinyi Yang, Yihai Yu, Liu Yang, Ruiyan Ma, Zhiguo Zhao

“…Furthermore, the population dynamics model yields a mean absolute error of 1.94% for the test dataset. These performance indicators fully meet the requirements of practical agricultural applications.…”
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Research on Missing Data Estimation Method for UPFC Submodules Based on Bayesian Multiple Imputation and Support Vector Machines by Xiaoming Yu, Jun Wang, Ke Zhang, Zhijun Chen, Ming Tong, Sibo Sun, Jiapeng Shen, Li Zhang, Chuyang Wang

“…Future research will explore dynamic weight optimization and extend the framework to multi-source heterogeneous data applications.…”
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The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model by Jiaxin Wang, Ying Yang, Xian Yang, Yulong Lu, Yang Liu, Da Hu, Yongjia Hu

“…When validated against 20 datasets from a representative karst region, the proposed model achieved exceptional performance, with a mean absolute error (MAE) of 0.0544 and a coefficient of determination (R2) of 0.9914, significantly surpassing the prediction accuracy of conventional ELM and SSA-ELM models. …”
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Dynamic Light Path and Bidirectional Reflectance Effects on Solar Noise in UAV-Borne Photon-Counting LiDAR by Kuifeng Luan, Jinhui Zheng, Wei Kong, Weidong Zhu, Lizhe Zhang, Peiyao Zhang, Lin Liu

“…BNR-B achieves 28.6% higher noise calculation accuracy than Lambertian models, with a relative phase error < 2% against empirical data. As the first BRDF-derived solar noise correction framework for coastal LiDAR, it addresses critical limitations of isotropic assumptions by resolving directional noise modulation. …”
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Sub-ppb H₂S Sensing with Screen-Printed Porous ZnO/SnO₂ Nanocomposite by Mehdi Akbari-Saatlu, Masoumeh Heidari, Claes Mattsson, Renyun Zhang, Göran Thungström

“…The relative concentration error was carefully calculated based on analytical sensitivity, confirming the sensor’s precision in measuring gas concentrations. …”
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Establishment of probabilistic model for Salmonella Enteritidis growth and inactivation under acid and osmotic pressure by Yujiao Shi, Hong Liu, Baozhang Luo, Yangtai Liu, Siyuan Yue, Qing Liu, Qingli Dong

“…And the established primary and secondary models could describe the growth of S. enteritis well by estimating four mathematics evaluation indexes, including determination coefficient (R2), root mean square error (RMSE), accuracy factor (Af) and bias factor (Bf). …”
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Predictive Performance of Anti-Lock Braking System with PID Controller Optimized by Gravitational Search Algorithm for a Quarter Car Model: Simulation Modeling and Control by Mohd Sabirin Rahmat, Fauzi Ahmad, Vimal Rau Aparow, Rizauddin Ramli, Sallehuddin Mohamed Haris, Mohd Anas Mohd Sabri, Mohd Anas Mohd Sabri, Meor Iqram Meor Ahmad, Mohd Muhyidin Mustafa

“…The PID parameters are tuned manually using a trial-and-error approach to provide a baseline for comparison. …”
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Reliability and Validity of the Articulation Motion Assessment System Using a Rotary Encoder by Hiroki Ito, Hideaki Yamaguchi, Mari Inoue, Hikaru Nagano, Ken Kitai, Kiichiro Morita, Takayuki Kodama

“…The average root mean squared error (RMSE) was significantly lower in AMAS (10.90 ± 2.93° for sagittal plane angles; 13.44 ± 1.09° for frontal plane angles) than in the inertial sensor-based three-dimensional (3D) motion analysis. …”
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Structural flexural strengthening through material bonded to the concrete substrate by Victor Hugo Dalosto de Oliveira, Rodolfo Alves Carvalho, Rodolfo Rabelo Neves, Luana Ferreira Borges, Paulo Chaves de Rezende Martins, Marcos Honorato de Oliveira, João Paulo de Almeida Siqueira, Rafael de Almeida Sobral, Sidney Luan Teixeira de Nazaré, Carlos Henrique de Moura Cunhac

“…As result, it was verified that the proposed procedure provides values similar to the trial-and-error method used in the FRP strengthening design. …”
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