Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

“…The integration of artificial intelligence has accelerated progress in both event prediction and error correction. However, significant challenges remain, particularly regarding the interpretability, generalizability, and real-time applicability of advanced models. …”
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Hybrid DNN-Based Flight Power Estimation Framework for Unmanned Aerial Vehicles by Minsu Kim, Minji Kim, Yukai Chen, Jaemin Kim, Donkyu Baek

“…The proposed modeling framework was evaluated with flight experiments, demonstrating a 6.12% root mean squared percentage error (RMSPE), which is 39.45% more accurate when compared with a conventional DNN-only power model. …”
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Evaluating MIMO-VLC System Performance: Modulation Techniques and Ambient Light Interference Effects by Emad S. Hassan, Abdoh Jabbari, Ayman A. Alharbi

“…The study evaluates the VLC systems in terms of bit error rate (BER), quality factor (Q-factor), and received power over varying link distances. …”
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Advancing Pet Biometric Identification: A State-of-the-Art Unified Framework for Dogs and Cats by Youssef Boulaouane, Mukhammed Garifulla, Joonho Lim, Daehyun Pak, Jeongtaek Lim

“…Traditional methods, such as collars, microchips, and tattoos, pose issues such as invasiveness, the need for specialized scanners, and the potential for loss or error. This study introduces an AI-powered biometric identification system using smartphone images to offer a convenient and accessible alternative. …”
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Fuzzy LQR-based control to ensure comfort in HVAC system with two different zones by Elif Çinar, Tayfun Abut

“…The effectiveness of the proposed method (FLQR) is demonstrated through a comprehensive performance evaluation using Mean Squared Error (MSE) metrics, confirming its potential for intelligent HVAC applications.…”
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Machine Learning‐Based Failure Prediction in Concrete Slabs and Cubes Under Impact Loading by Mohammad Hematibahar, Ahmed Deifalla, Adham E. Ragab, Gebre Tesfaldet

“…Design standards‐based statistical comparisons such as coefficient of determination and root mean square error are used to assess the efficacy of the generated models. …”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…The study identifies a critical transition at 100–300 samples where error rates drop sharply, with optimal performance requiring more than 600 samples. …”
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Human Daily Breathing Monitoring via Analysis of CSI Ratio Trajectories for WiFi Link Pairs on the I/Q Plane by Wei Zhuang, Yuhang Lu, Yixian Shen, Jian Su

“…It opens up possibilities for various intelligent applications, like advanced medical monitoring and sleep analysis. …”
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Finite element method in computer simulation for improved patient care in dentistry: A systematic review by Denis Yu. Dyachenko, Svetlana V. Dyachenko

“…This will reduce the number of visits, peri- and posttreatment error and complication rates for the improved patient’s quality of life and social rehabilitation.…”
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Toward Low-Cost Passive Motion Tracking With One Pair of Commodity Wi-Fi Devices by Wei Guo, Lei Jing

“…Experimental results in real indoor environment show that WiMT achieves great performance with a motion tracking median error of 7.28 cm and a nonmoving recognition accuracy of 92.6%.…”
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Uncertainty Quantification in Shear Wave Velocity Predictions: Integrating Explainable Machine Learning and Bayesian Inference by Ayele Tesema Chala, Richard Ray

“…The accurate prediction of shear wave velocity (Vs) is critical for earthquake engineering applications. However, the prediction is inevitably influenced by geotechnical variability and various sources of uncertainty. …”
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Dynamic Peak Threshold Estimation Method for Noise Mitigation in Hybrid PLC/VLC Systems by Irvine Mapfumo, Thokozani Shongwe

“…These distortions have multiple effects on communication channels, including higher bit error rate (BER), reduced signal-to-noise ratio (SNR), and restricted channel capacity. …”
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Studying bifurcations and chaotic dynamics in the generalized hyperelastic-rod wave equation through Hamiltonian mechanics by Ma Hongwei, Liu Ziming, Sun Yiqun, Guo Peng, Qi Jianming

“…Ultimately, we employed the Chebyshev method, renowned for its exceptional accuracy and numerical stability, to rigorously validate our analytical solutions, ensuring minimal error margins. Through these efforts, we have not only advanced the understanding of GHRWE but also provided new perspectives and tools for research in related fields.…”
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Sequential testing of complementary hypotheses about population density by Diego F. Rincon, Izzy McCabe, David W. Crowder

“…Although the test requires fewer samples, more incorrect decisions may be produced for purely sequential designs when densities are below the thresholds (type I error), compared with probability ratios. We show the new test is a powerful, easily implementable framework with applications in natural resource and pest management, whose outputs are easily interpretable for decision making.…”
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Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges by Alex M. Wonnacott, Anton E. Bowden, Ulrike H. Mitchell, David T. Fullwood

“…The inverse model accurately predicted key strain characteristics with a percent error as low as 0.5%. Together, the models provide new functionality for interpreting high-deflection strain sensors during dynamic strain measurement applications, including wearables sensors used for biomechanical modeling and analysis.…”
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MODEL AND ALGORITHMS FOR DETERMINING THE LOCATION AND POSITION OF AGRICULTURAL MACHINERY DURING THE MOVEMENT by Andrii Podorozhniak, Oleksii Balenko, Valentyn Sobol

“…Conclusions: to improve the accuracy of estimating the location and position agricultural machinery, algorithms complexation of indicators from different navigation systems should be used to reduce the total error. Research results can be applied in the development of new and modifications of existing navigation subsystems of agricultural machinery autonomous control systems.…”
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Optimized bio-signal reconstruction and watermarking via enhanced fractional orthogonal moments by Gaber Hassan, Khalid M. Hosny, Islam S. Fathi

“…The findings indicate that the proposed methodology exhibits significantly higher performance levels than current methodologies, with a 64.3% improvement in PSNR (reaching 147.08 dB compared to 89.74 dB in existing approaches), 89.7% reduction in MSE (0.0092 versus 0.09 average), and 84.1% decrease in bit error rate (0.25 versus 1.57) for watermarking applications. …”
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The Use of Machine Learning Algorithms for Water Quality Index Prediction in the Sai Gon River, Vietnam by Thuy Nguyen Thi Diem, Mai Nguyen Thi Huynh, Tra Tran Quang

“…Specifically, the XGB model exhibited the lowest error rates (RMSE = 1.630 and MAE = 0.782) and highest correlation (R2 = 0.960 and NSE = 0.953), followed by the GBM, SVR, and RBF models. …”
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Quantum-enhanced digital twin IoT for efficient healthcare task offloading by Ahmed K. Jameil, Hamed Al-Raweshidy

“…Empirical evaluations show that quantum preprocessing improved Task Offloading Success Rate (TOSR) by 32% and reduced the Error Rate (ER) by 80%, significantly outperforming traditional DT-based healthcare models. …”
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Humanoid Robots like Tesla Optimus and the Future of Supply Chains: Enhancing Efficiency, Sustainability, and Workforce Dynamics by Mohammad Shamsuddoha, Tasnuba Nasir, Mohammad Saifuddoha Fawaaz

“…According to Tesla, Optimus could significantly enhance supply chain efficiency by reducing error rates, streamlining workflows, and enabling 24/7 operations. …”
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