Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…This investigation provides valuable perspectives on amalgamating machine learning methodologies for predicting chemical solubility, presenting a scalable strategy for forthcoming applications in analogous domains.…”
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An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product by Siyuan Chen, Liangyun Liu, Lichun Sui, Xinjie Liu, Yan Ma

“…However, current SIF products are limited for applications toward vegetation photosynthesis monitoring because of low spatial resolution or spatial discontinuity. …”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…The proposed methodology showcases the effectiveness of combining hybrid deep learning with metaheuristic optimization in solar radiation forecasting, offering a robust and adaptable framework for renewable energy applications.…”
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Enhanced Mobile Multiple-Input Multiple-Output Underwater Acoustic Communications by Kexin Zhao, Jun Ling, Jian Li

“…GoSLIM-V is user parameter free and is easy to use in practical applications. This paper also considers turbo equalization for retrieving the transmitted signal. …”
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Probabilistic Dressing of a Storm Surge Prediction in the Adriatic Sea by R. Mel, P. Lionello

“…Here, a sophisticated error distribution form is developed, which includes the superposition of the uncertainty caused by inaccuracies of the ensemble prediction system, which depends on surge level and lead time, and the uncertainty of the meteorological forcing, which is described using a combination of cross-basin pressure gradients. …”
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Small radius inclusive jet production at the LHC through NNLO+NNLL by Terry Generet, Kyle Lee, Ian Moult, Rene Poncelet, Xiaoyuan Zhang

“…We compare with CMS data for small-R jet production, and find that our results greatly improve the accuracy of the predictions at small-R, and stabilize the perturbative convergence and error estimates at larger R. Our approach is applicable to a wide class of jet substructure observables exhibiting similar factorization theorems, opening the door to an NNLO jet substructure program at the LHC.…”
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Design and Simulation of a Four-Legged Mobile Robot for Autonomous Navigation on a Spacecraft Hull by Motaz Hassan, Kayla Dremann, Ashton Orosa, Emily Metzger, Nathan Doty, Julia Patek, Siamak Farhad, Ajay Mahajan

“…These results highlight the robot’s iterative improvement in trajectory tracking and its potential for future use in autonomous on-orbit servicing and spacecraft inspection applications.…”
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Efficient AI-Driven Query Optimization in Large-Scale Databases: A Reinforcement Learning and Graph-Based Approach by Najla Sassi, Wassim Jaziri

“…As data-centric applications become increasingly complex, understanding effective query optimization in large-scale relational databases is crucial for managing this complexity. …”
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Automated Classification Model for Elementary Mathematics Diagnostic Assessment Data Based on TF-IDF and XGBoost by Seonghyun Park, Seungmin Oh, Woncheol Park

“…This study highlights the automation and scalability of educational data analysis, suggesting potential applications across various subjects and grade levels.…”
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Optimizing balanced accuracy in medical data threshold models by Benjamin F. Dribus, Jamie Hill, Neil Goldsmith, Daniel Martingano

“…While our viewpoint and featured applications involve medical datasets, our methods apply to general threshold-defined classification problems. …”
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A Comprehensive Ensemble Model for Marine Atmospheric Boundary-Layer Prediction in Meteorologically Sparse and Complex Regions: A Case Study in the South China Sea by Yehui Chen, Tao Luo, Gang Sun, Wenyue Zhu, Qing Liu, Ying Liu, Xiaomei Jin, Ningquan Weng

“…Overall, the SOEM provides a precise approach for estimating convective boundary-layer height, supporting marine meteorology, onshore wind power, and coastal protection applications.…”
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Optimizing wind energy conversion system efficiency using advanced modified super-twisting direct power control: Real-time implementation on dSPACE 1104 board by Mourad Yessef, Habib Benbouhenni, Ahmed Lagrioui, Youness El Mourabit, Nicu Bizon, Ilhami Colak, Badre Bossoufi, Ayman Alhejji

“…Furthermore, the steady-state error, overshoot, and reactive power ripples were reduced by 60 %, 81.25 %, and 66.66 %, respectively, compared to the classical direct power control strategy.…”
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Numerical analysis of heat and mass transfer in eyring-powell fluid employing python with convective boundary conditions by Chenxu Duan, Muflih Alhazmi, Zahoor Shah, Hamza iqbal, Maryam Jawaid, Mhassen E.E. Dalam, Mohammed M.A. Almazah

“…Industrial applications show rising interest in non-Newtonian fluids because they enable superior heat and mass transfer qualities that promote system performance enhancement. …”
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Comparison of Two System Identification Approaches for a Four-Wheel Differential Robot Based on Velocity Command Execution by Diego Guffanti, Moisés Filiberto Mora Murillo, Marco Alejandro Hinojosa, Santiago Bustamante Sanchez, Javier Oswaldo Obregón Gutiérrez, Nelson Gutiérrez, Miguel Sánchez

“…Similarly, the maximum position error averaged 0.522 m for MBM and 0.710 m for SM, confirming that MBM is more accurate and consistent in position tracking. …”
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A secure and efficient user selection scheme in vehicular crowdsensing by Min Zhang, Qing Ye, Zhimin Yuan, Kaihuan Deng

“…The SEUS-VCS scheme has advantages in reducing loss function (Loss), Mean Square Error (MSE), and Mean Absolute Error (MAE), and the predicted results match the true data very well. …”
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Symmetrized Neural Network Operators in Fractional Calculus: Caputo Derivatives, Asymptotic Analysis, and the Voronovskaya–Santos–Sales Theorem by Rômulo Damasclin Chaves dos Santos, Jorge Henrique de Oliveira Sales, Gislan Silveira Santos

“…The theoretical framework is thoroughly validated through applications in signal processing and fractional fluid dynamics, including the formulation of nonlocal viscous models and fractional Navier–Stokes equations with memory effects. …”
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Impact of TAK-003 on epidemiologic, economic and quality-of-life burden of dengue: comparison of the results from a dynamic transmission model and a static model with a dynamic com... by Elizaveta Kharitonova, Dr Jing Shen, Anna Tytula, Justyna Zawieja, Yaneth Gil Rojas, Samuel Aballea, Riona Hanley

“…The goodness of fit was assessed by visual assessment and two formal goodness-of-fit metrics (mean absolute error and root mean squared error). Results: The combination of 2-month-cycle and 2-month-lag was found to provide the closest fit with the dynamic model for all timeframes between 1–30 years, on outcomes of predicted cases averted, costs savings and disability-adjusted-life-years (DALYs) averted. …”
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Forecasting Average Daily and Peak Electrical Load Based on Average Monthly Electricity Consumption Data by Saidjon Tavarov, Aleksandr Sidorov, Natalia Glotova

“…The decrease in mean absolute error due to clustering was 0.52 MW (57%). The use of meteorological conditions allowed the forecast error to be reduced by 0.22 MW (27%). …”
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A Voice-Based Personal Assistant for Mental Health in Kreol Morisien by B. Gobin-Rahimbux, N. Gooda Sahib, N. Peerthy, A. Taylor

“…Voice-based smart personal assistants (VSPAs) are applications that recognize speech-based input and perform a task. …”
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A study on monthly sales forecasting of new energy vehicles in urban areas using the WOA-BiGRU model. by Xiangtu Li

“…To accurately predict the sales of new energy vehicles (NEVs) in Chinese cities and explore the applicability of optimization algorithms for GRU models in forecasting urban NEV sales., this paper conducts a spatiotemporal analysis of urban NEV sales data. …”
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