Full Envelope Control of Over-Actuated Fixed-Wing Vectored Thrust eVTOL by Emmanuel Enenakpogbe, James F. Whidborne, Linghai Lu

“…The control allocation allocates the overall control demand (virtual controls) to individual redundant effectors while performing control error minimisation, control channel prioritisation and control effort minimisation. …”
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A one-stage anchor-free keypoints detection model for fast electric vehicle charging port detection and pose extraction by Feifei Hou, Qiwen Meng, Xinyu Fan, Yijun Wang

“…Experiments demonstrate that in complex lighting scenarios, FasterEVPoints boasts 95% detection accuracy on a proprietary dataset with a positioning error of less than 2 cm at a 50 cm distance. Furthermore, when integrated into the you only look once X (YOLOX) framework with parameters comparable to YOLOX-Tiny, FasterEVPoints delivers similar accuracy while consuming only 73% of the computational load and 66% of the parameters compared to YOLOX-Tiny. …”
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A bioelectric router for adaptive isochronous neurostimulation enables multipolar bioelectric stimulation from a single source by Eashan Sahai, Jordan Hickman, Daniel J. Denman

“…The BRAINS board demonstrates no meaningful differences in Root Mean Square Error (RMSE) noise or signal-to-noise ratio compared to the baseline performance of the isolated stimulator alone. …”
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Effect of role-play technique on nursing students’ attitudes towards student-centred teaching: a Quasi-Experimental study by Dilay Necipoglu, Nida Aydin

“…Clinical trial number Not applicable.…”
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A Positioning System Design Based on Tunnel Magnetoresistance Sensors for Rapid Zoom Optical Lens by Junqiang Gong, Dameng Liu, Jianbin Luo

“…We quantify the magnetic interference of VCM through three-dimensional flux leakage mapping by FEM analysis, deriving an optimal sensor position <i>O</i>_S, with a 24 mm <i>y</i>-offset and 20 mm <i>z</i>-offset relative to the VCM’s origin <i>O</i>_V. The position error caused by interference remains below 5 μm with maximum deviations at trajectory endpoints of the moving group. …”
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An Eighth-Order Numerical Method for Spatial Variable-Coefficient Time-Fractional Convection–Diffusion–Reaction Equations by Yuelong Feng, Xindong Zhang, Leilei Wei

“…This work contributes to providing a better understanding of the dependability of the method by thoroughly examining convergence and conducting an error analysis. Numerical examples demonstrate the applicability, accuracy, and efficiency of the suggested technique, supplemented by comparisons with previous research.…”
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Economic Evaluation of the Investment in Sensor Equipment Based on Data Valuation in Prediction Model by Jeong-Gi Lee, Deok-Joo Lee

“…To support method selection, we also analyze the computational complexity of both approaches and derive error bounds. Through numerical experiments using real-world semiconductor manufacturing data, we demonstrate that sensor selection based on economic value can lead to significantly different outcomes compared to conventional methods. …”
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Real-Time Sign Language Recognition and Translation in Humanoid Robots Using Transformer-Based Model with a Knowledge Graph by Erick Busuulwa, Li-Hong Juang

“…We used the RWTH-PHOENIX-Weather 2014T dataset for initial training, achieving a BLEU score of 29.1 and a Word Error Rate (WER) of 18.2% surpassing the baseline model. …”
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Fitting Time Series Models to Fisheries Data to Ascertain Age by Kathleen S. Kirch, Norou Diawara, Cynthia M. Jones

“…ARIMA and unobserved components account for the dependence of observations and error, while copula incorporates a variety of marginal distributions and dependence structures. …”
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Classifying Economic Areas for Urban Planning using Deep Learning and Satellite Imagery in East Africa by Davy Uwizera, Dr. Charles Ruranga, Prof. Patrick McSharry

“…These types of surveys are slow, costly and prone to human error. With the digital revolution, a lot of unstructured data is generated daily that is likely to contain useful proxy data for many economic variables. …”
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Scheduling of Mixed Fleet Passing Through River Bottleneck in Multiple Ways by De-Chang Li, Hua-Long Yang

“…To handle the nonlinear terms in the model, an outer approximation technique is applied to linearize the model while ensuring the approximation error remains controlled. The optimal value range of the nonlinear variables is also proven to ensure solution speed. …”
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Research on Security Enhancement for Abnormal Content Release in Unified Audio Video Information service Systems by FENG Junhao

“…Result & Conclusion The improved audio video information security management system demonstrates significant practical value, with both omission ratio and error detection rate controlled within 0.5% and 2.0%, respectively. …”
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Optimal Design of Welded Structure Using SVM by Sebghatullah Jueyendah, Carlos Humberto Martins

“…The values of the root mean square error of SVM-RBF in the prediction of the cost function are 0.00137 (correlation coefficient of R2=0.9999) and 0.217 (R2=0.9656) for training and testing, respectively. …”
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On Data Selection and Regularization for Underdetermined Vibro-Acoustic Source Identification by Laixu Jiang, Jingqiao Liu, Xin Jiang, Yuezhao Pang

“…The simulation results show that selecting hologram points using the effective independence method, combined with regularization via compressed sensing, significantly reduces the reconstruction error and enhances the modal assurance criterion value. …”
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Using Generative Adversarial Networks to Translate Microresistivity Image Logs of Carbonates Into Synthetic Core Images With Accurate Dunham Textures by Saira Baharuddin, Cédric M. John

“…The supervised pix2pixHD model trained using concatenated FMS pad images with a batch size of 4 produces the most realistic core images: these have low Root Mean Square Error, high Peak Signal to Noise Ratio and high Structural Similarity Index Method values when compared to the ground truth core images. …”
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Mathematical modeling of blood flow with copper and graphene nanoparticles in inclined stenotic arteries by Pooriya Majidi Zar, Zahra Poolaei Moziraji, Ali Ahmadi Azar

“…Simplifications under mild stenosis and low Reynolds number conditions enable analytical solutions via the homotopy perturbation method (HPM) and Akbari Ganji Method (AGM). The minimal error observed for axial velocity is  $${2.34\times 10}^{-10}$$ , while that for temperature is  $${8.87\times 10}^{-10}$$ . …”
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Harnessing machine learning for high-entropy alloy catalysis: a focus on adsorption energy prediction by Qi Wang, Yonggang Yao

“…However, these complexities pose grand challenges for traditional “trial-and-error” experimentation or computationally expensive “brute-force” ab initio calculations. …”
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Effects of Polypropylene Waste Addition as Coarse Aggregates in Concrete: Experimental Characterization and Statistical Analysis by D. C. Naveen, K. Naresh, B. S. Keerthi Gowda, Madhu Sudana Reddy G, C. Durga Prasad, Ragavanantham Shanmugam

“…A good correlation was obtained between the experimental and predicted values with an error (%) of less than 10. The decrease in mechanical properties with the increase in replacement levels of coarse aggregates in concrete was observed in both experimental and predicted approaches. …”
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Federated Learning With Sailfish-Optimized Ensemble Models for Anomaly Detection in IoT Edge Computing Environment by Aravam Babu, A. Bagubali

“…Extensive experiments on benchmark datasets confirm that the proposed method achieves higher anomaly detection efficiency with a lower error rate than existing methods. The results establish this framework as a scalable, privacy-preserving, and computationally efficient solution for anomaly detection in IoT edge environments, addressing critical limitations in security, latency, and data privacy in real-world applications.…”
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A novel quantile regression for fractiles based on unit logistic exponential distribution by Hanan Haj Ahmad, Kariema A. Elnagar

“…When applied to two real-world datasets—one from the medical field and the other from the economic sector—the ULE distribution consistently outperforms existing unit interval models, showcasing lower error rates and enhanced flexibility in tail behavior. …”
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