Research on Spatial Localization Method of Magnetic Nanoparticle Samples Based on Second Harmonic Waves by Zheyan Wang, Ping Huang, Fuyin Zheng, Hongli Yu, Yue Li, Zhichuan Qiu, Lingke Gai, Zhiyao Liu, Shi Bai

“…The experimental results validated the method’s high accuracy, with axial detection distance and concentration reduction errors of only 4.8% and 4.1%, respectively. This research paves the way for handheld probes capable of tomographic tracer detection, offering a novel approach for advancing magnetically sensitive biomedical detection technologies.…”
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Groundwater Pollution Concentration Estimation with Modified Kalman Filter Method by Nenik Estuningsih, Fatmawati Fatmawati

“…The model order reduction method used in this research is the LMI (Linear Matrix Inequality) method because the model reduction error using the LMI method is the smallest error compared to the reduction error using the Balanced Truncation method or the Singular Pertrubation Approximation method. …”
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Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization by Chuan-ming SONG, Yan-wen GUO, Xiang-hai WANG, Dan LIU

“…To further predict the precision of the proposed algorithm, a bit resolution reduction error-motion vector precision model was built by exploiting the auto-correlation function. …”
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Analytical Reduction of Nonlinear Metabolic Networks Accounting for Dynamics in Enzymatic Reactions by Claudia López Zazueta, Olivier Bernard, Jean-Luc Gouzé

“…Here, we propose a rigorous approach to reduce metabolic models using quasi-steady-state reduction based on Tikhonov’s theorem, with a characterized and bounded reduction error. We assume that the metabolic network can be represented with Michaelis-Menten enzymatic reactions that evolve at different time scales. …”
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Effect of bit-size reduced half-precision floating-point format on image pixel characterization for AI applications by J. Jean Jenifer Nesam, S. Sankar Ganesh, Sitharthan Ramachandran

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An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics by Z. Tan, D. Xu, S. Taraphdar, J. Ma, G. Bisht, L. R. Leung

“…Our analysis further revealed that the dominant uncertainty sources of the downscaled hydrodynamics are different, with flow velocity dominated by the dimensionality reduction error, which we reduced by using a regionalized training procedure. …”
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