An Improved Artificial Neural Network Model for Effective Diabetes Prediction by Muhammad Mazhar Bukhari, Bader Fahad Alkhamees, Saddam Hussain, Abdu Gumaei, Adel Assiri, Syed Sajid Ullah

“…The revolution of artificial neural networks (ANNs) in the medical discipline emerged for data-driven applications, particularly in the healthcare domain. …”
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Robust Multi-Performances Control for Four-Link Manipulator Arm by Kuang-Hui Chi, Yung-Feng Hsiao, Chung-Cheng Chen

“…The globally robust control of a four-link manipulator arm (FLMA) is an important subject for a wide range of industrial applications such as COVID-19 prevention robotics, lower limb rehabilitation robotics and underwater robotics. …”
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Generative adversarial network–enabled microstructural mapping from surface profiles for laser powder bed fusion by Jingwen Gao, Chenyang Zhu, Shubo Gao, Weiming Ji, Ming Xue, Kun Zhou

“…However, conventional quality control of LPBF-fabricated parts, including microstructure characterisation, often relies on trial-and-error experiments. These methods can be time-consuming, resource-intensive, and potentially destructive to specimens. …”
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Analysis of the Utilization of Machine Learning to Map Flood Susceptibility by Ali Pourzangbar, Peter Oberle, Andreas Kron, Mário J. Franca

“…Recognizing the challenge that some stages of ML modeling inherently rely on experience or trial‐and‐error approaches, this work aims at establishing a clear roadmap for the deployment of ML‐based FSM frameworks. …”
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Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics by Mohamed Salem, Witesyavwirwa Vianney Kambale, Ali Deeb, Sergii Tkachov, Anjeza Karaj, Joachim Pichler, Manuel Ludwig Lexer, Kyandoghere Kyamakya

“…Inference latency was measured at 5–10ms per schematic on standard GPU hardware, confirming its applicability to interactive industrial Electronic Design Automation (EDA) workflows. …”
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Impact of Parameters and Tree Stand Features on Accuracy of Watershed-Based Individual Tree Crown Detection Method Using ALS Data in Coniferous Forests from North-Eastern Poland by Marcin Kozniewski, Łukasz Kolendo, Szymon Chmur, Marek Ksepko

“…The precision of tree crown detection algorithms plays a critical role in providing reliable data for these applications, where even slight inaccuracies can lead to significant deviations in tree population estimates and ecological indicators. …”
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A Comprehensive Analysis of Dropout Assisted Regularized Deep Learning Architectures for Dynamic Electricity Price Forecasting by Pooja Joshi, Stale Stordal, Gudbrand Lien, Deepti Mishra, Erik Haugom

“…Many existing EPF approaches show limited performance due to significant nonlinearity, high volatility, and continuous evolutions of exogenous variables. For such applications, data-driven approaches such as deep learning (DL) have shown promising forecasting capabilities in recent years. …”
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Real-Time Sensor Fault Tolerant Control of DC-DC Converters in DC Microgrids Using a Switching Unknown Input Observer by Mohammed Said Ouahabi, Abdelhafid Benyounes, Said Barkat, Syphax Ihammouchen, Toufik Rekioua, Abdelaziz Rabehi, El-Sayed M. El-Kenawy, Amal H. Alharbi

“…Their growing adoption in critical applications raises the need for operational safety and reliability, particularly under fault conditions. …”
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Performance evaluation of limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm for image reconstruction in through-the-wall radar imaging for rescue missions by Tumaini Edgar, Abdi T. Abdalla, Abdullah F. Ally

“…In all tested scenarios, the LBFGS-based algorithm consistently reconstructed images within the four-minute threshold, achieving satisfactory mean square error values and outperforming traditional sparse reconstruction algorithms. …”
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Machine learning assisted CFD optimization of fuel-staging natural gas burners for enhanced combustion efficiency and reduced NOx emissions by Muhammad Mubashir, Dekui Shen, Habib Kraiem, Aymen Flah, Nahar F. Alshammari, Muhammad Mubashar Hanif

“…Future work will focus on experimental validation and the adaptability of the burner to alternative fuels such as hydrogen-rich blends and biogas, aiming to extend the applicability of this approach across diverse industrial settings.…”
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Periodic table-based compositional descriptors for accelerating electrochemical material discovery: Li-ion conductors and oxygen evolution electrocatalysts by Yen-Ju Wu, Yibin Xu, Lei Fang, Wenqin Peng, Ken Sakaushi, Meiqi Zhang, Masao Arai, Yukinori Koyama

“…The discovery of high-performance electrochemical materials is essential for sustainable energy technologies, yet conventional methods rely on trial-and-error experiments, time-consuming computations, and detailed structural data. …”
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Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm by Juncheng Fu, Zhengxiang Song, Jinhao Meng, Chunling Wu

“…The results show that IBKA-DHKELM achieves the smallest error, with an RMSE of only 0.0062, demonstrating exceptional non-linear fitting capability, high predictive accuracy, and good robustness.…”
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A student academic performance prediction model based on the interval belief rule base by Wenkai Zhou, Yunsong Li, Jiaxing Li, Tianhao Zhang, Xiping Duan, Ning Ma, Yuhe Wang

“…Finally, case studies on graduate applications and GPA of students demonstrate that the mean squared error (MSE) of the IBRB-C is 0.0024 and 0.1014, respectively. …”
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Geo-referencing Autonomous Vehicles Using LoD2 and HD Maps: Performance Assessment in Simulated Urban Environments by M. Wahbah, L. Ramme, D. Ernst, S. Vogel, I. Neumann, H. Alkhatib

“…However, due to their geometric simplifications, the applicability of LoD2 maps for AV pose estimation remains uncertain. …”
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Data Augmentation and Deep Learning Methods for Pressure Prediction in Ignition Process of Solid Rocket Motors by Huixin Yang, Pengcheng Yu, Yan Cui, Bixuan Lou, Xiang Li

“…By comparison, the AGN-CBiLSTM method has a higher prediction accuracy with a percentage error of 3.27% between the predicted and actual data. …”
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An Active RIS-Aided DFRC System for Improved Multi-User Communications by Ravi Patel, Aayush Singh, Keshav Singh, Shahid Mumtaz, Chih-Peng Li, Sudip Biswas

“…We develop a optimization algorithm that leverages weighted minimum mean square error (WMMSE) and fractional programming techniques to maximize the weighted sum rate (WSR) for communication users while ensuring robust radar detection performance. …”
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Prediction of post-irradiation swelling rate of 316L stainless steel based on Variational Autoencoders and interpretable machine learning by Chengcheng Liu, Hang Su

“…This study aims to enhance the predictive accuracy of the swelling rate of irradiated 316L stainless steel, particularly in high-tech applications such as nuclear energy. By comparing various machine learning models, it was found that the Extreme Trees Regression (ETR) model performed best on the test set, achieving an R2 of 0.79 and a Root Mean Square Error (RMSE) of 1.65 %. …”
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Building Damage Visualization Through Three-Dimensional Reconstruction and Window Detection by Ittetsu Kuniyoshi, Itsuki Nagaike, Sachie Sato, Yue Bao

“…Future work will focus on enhancing point cloud interpolation and refining machine learning-based damage classification for broader applicability.…”
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TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research by William Ndzimbong, Cyril Fourniol, Loic Themyr, Nicolas Thome, Yvonne Keeza, Benoît Sauer, Pierre-Thierry Piéchaud, Arnaud Méjean, Jacques Marescaux, Daniel George, Didier Mutter, Alexandre Hostettler, Toby Collins

“…Abstract Inter-modal image registration (IMIR) and image segmentation with abdominal Ultrasound (US) data have many important clinical applications, including image-guided surgery, automatic organ measurement, and robotic navigation. …”
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An Adaptive Three-Dimensional Self-Masking Strategy for the Micro-Fabrication of Quartz-MEMS with Out-of-Plane Vibration Units by Yide Dong, Chunyan Yin, Guangbin Dou, Litao Sun

“…The unit exhibited a repeatability error below 1.13%, confirming the precision and reliability of the proposed fabrication strategy.…”
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