Calibration Scheme Research Articles

A Comprehensive Evaluation of Machine Learning on Coral Trace Element Paleothermometers for Sea Surface Temperature Reconstruction

AbstractThis research introduces a novel approach to reconstruct sea surface temperature (SST) by developing a universal coral thermometer using machine learning (ML) algorithms on monthly resolved Porites coral proxies and SST data. A total of 1,202 data sets from 19 corals, covering SSTs ranging from 21.5 to 31.5°C, with proxies including Sr/Ca, Mg/Ca, Li/Mg, U/Ca, and B/Ca ratios were analyzed. The data were divided into four sub‐datasets by regional and taxon constraints. An exhaustive analysis was conducted, training 1,612 models using various proxy combinations and ML strategies to assess the impact of the non‐SST effect on the universality of ML models. The results indicated that the non‐SST effect is more significantly attributed to regional variations than to taxon differences, underscoring the importance of regional factors in Porites coral proxy‐based SST reconstructions. Sr/Ca and Li/Mg proxies were identified as the most indicative of SST, showing clearer relationships with temperature than other proxies. Non‐linear approaches achieved a Root Mean Square Error (RMSE) of less than 0.90°C, which further decreased to 0.72°C upon incorporating specific regional and taxon constraints. In an independent test set focusing exclusively on Li/Mg and Sr/Ca proxies, the tree‐based algorithms particularly excelled, achieving an average RMSE improvement of at least 0.52°C over the Universal Multi‐Trace Element Calibration Scheme and the Li/Mg empirical equation. This research underscores the potential of applying ML to coral‐based SST reconstructions, especially highlighting the effectiveness of tree‐based algorithms and the suitability of Sr/Ca and Li/Mg proxies for accurate temperature estimations.

A multi-step calibration strategy for reliable parameter determination of salt rock mechanics constitutive models

The storage of renewable hydrogen in salt caverns requires fast injection and production rates to cope with the imbalance between energy production and consumption. This raises concerns about the mechanical stability of salt caverns under such operational conditions. The use of appropriate constitutive models for salt mechanics is an important step in investigating this issue, therefore many constitutive models with several parameters have been presented in the literature. However, a robust calibration strategy to reliably determine which model and parameter set represents the given rock, based on stress–strain data sets, remains an unsolved challenge. In this paper, for the first time in the community, we present a multi-step strategy to determine a single parameter set based on many deformation data sets for salt rocks. Towards this end, we first develop a comprehensive constitutive model able to capture all relevant nonlinear deformation physics of transient, reverse, and steady-state creep. The determination of the single set of representative material parameters is then achieved by framing the calibration process as an optimization problem, for which the global Particle Swarm Optimization algorithm is employed. To allow for dynamic data integration, a multi-step calibration strategy is developed for a situation where experiments are included one at a time, as they become available. Additionally, due to the existing mild heterogeneity in the experimental rock samples, our optimization strategy is made flexible to allow for this slight heterogeneity. The devised optimization strategy, based on the multi-physics comprehensive constitutive modeling framework, results in a single set of representative material properties of all the deformation data sets. As a rigorous mathematical analysis for the presented method and the lack of relevant experimental data sets, we consider a wide range of synthetic experimental data sets, inspired by the existing sparse relevant data in the literature. The results of our performance analyses show that the proposed calibration strategy is robust. Moreover, the results become increasingly more accurate as more data sets become available.

Isotopic spike 190Os as internal standard and empirical coefficient LA-ICP-MS combined with Sb fire assay for the determination of ultra-trace platinum group elements in geochemical samples

In this work, a novel method of antimony fire assay (Sb-FA) enrichment combined with laser ablation ICP-MS (LA-ICP-MS) for the determination of ultra-trace platinum group elements (PGEs) in geological samples was established. The purification and recycling technology of ultra-clean and high-purity fire assay collector Sb2O3 was proposed, in addition, high-purity quartz crucible was developed to replace the usual clay crucible, then the blank values of PGEs were as low as 0.0007–0.0028 ng g−1 (for 20 g sample). 190Os isotopic diluent was used as internal standard (IS) and quantitatively added into the fire assay ingredients, and fully mixed and balanced with the PGEs in the real samples by means of high temperature melting, cupellation and horizontal rotation of crucible and dish. Both 190Os and PGEs in the real sample were pre-concentrated in microgram level Sb granules (100 mg) through Sb-remaining cupellation. After grinding and polishing, 195Pt, 105Pd, 101Ru, 103Rh, 193Ir, total 189Os and 190Os enriched in Sb slices were determined by LA-ICP-MS, 190Os in the internal standard was calculated by isotope dilution equations. The Certified Reference Materials (CRMs) for PGEs were treated by the same procedure to obtain completely matrix matched Sb slices to solve the problem of no internationally recognized uniform PGEs standard materials for LA-ICP-MS determination. Due to the similar distribution trends of different PGEs in Sb slices by LA-ICP-MS imaging, then matrix-matched internal standard calibration strategy was used to reduce the element fractionation effect and improve the determination precision and accuracy of LA-ICP-MS. The laser frequency, energy density, denudation diameter and dwell times were optimized. Under the optimal conditions, empirical coefficient method was used to fit the standard curve and excellent curve fitting of PGEs were obtained with the correlation coefficient between 0.9990 and 0.9999. The method detection limits (LODs) for PGEs ranged from 0.00042 to 0.010 ng g−1. The established method was successfully applied to analyze real geochemical samples and various matrix Certified Reference Materials (CRMs) domestic and international, the determined values were in good agreement with the results of Sb-FA ICP-MS and the certified values.

High-precision micro-total analysis of sodium ions in breast milk

Measuring sodium ion concentration in breast milk can provide crucial health information for both mother and infant, including early signs of low-grade infection and reduced milk supply. Traditional sensing methods are slow, bulky, expensive, and require skilled operators. Here, we develop a coverslip-sized, high-precision lab-on-a-chip device that processes and detects sodium ions in human breast milk. The device uses micro-electrodialysis to extract sodium ions into a simple acceptor solution with 92 ± 3 % efficiency and employs a graphene ion-selective sensor for high-performance quantification. We demonstrate a straightforward calibration strategy, enabling the device to measure breast-milk sodium ion levels in 141 seconds, with accuracy comparable to inductively coupled plasma mass spectrometry. Our approach offers a promising pathway to efficient, point-of-care diagnosis of conditions associated with metal-ion levels in complex liquid-biopsy samples.

A 1024-Channel Simultaneous Electrophysiological and Electrochemical Neural Recording System with In-Pixel Digitization and Crosstalk Compensation.

Simultaneous electrophysiological and chemical recording allows for multi-modal neural instrumentation and provides insights into chemical synapses and ion channels across the cell membrane. However, intermodal interference can hinder highly synchronized recording in large-scale systems with high temporal and spatial resolution. In this work, we propose a 1024-channel lab-on-CMOS system for dual-modal neural recording with in-pixel digitization and interference suppression. A foreground calibration scheme with tunable capacitance is implemented in-pixel to compensate for the crosstalk between electrical and chemical recording. Active pixels for both electrical and chemical modalities are designed based on a pulse width modulation (PWM) analog-to-digital conversion scheme. CMOS-compatible post-processing is implemented to realize in-pixel electrodes and chemical sensing membranes. The prototype, implemented in a 180nm CMOS technology, occupies a total area of 33mm2 with 1024 pixels, and each unit pixel includes one electrical recording site and two chemical recording sites, with dimensions of 150μm×130 μm. The total system power consumption is 19.68mW at a frame rate of 9k and 3k for electrical and chemical imaging respectively. The in-vitro experiment demonstrated the concurrent high density electrophysilogical and electrochemical recording with sub millisecond temporal resolution.

Systematical and universal calibration scheme for division-of-aperture polarimetric camera

Division-of-aperture polarimetric (DoAP) camera has been widely used to obtain polarization images of scene owing to its feature in simultaneous acquisition of polarization information, real-time measurement and compact system. However, practical applications of DoAP imaging inevitably involve calibrating the camera from several aspects, which is very essential but the related reports are relatively lacking in current research. In this paper, we proposed a systematical and universal calibration scheme for the DoAP camera, which includes the lens distortion correction, the image registration, the polarization channel calibration and the Stokes parameters modification. Accordingly, a software for calibration and imaging processing, which consists of four modules, is designed to collectively facilitate the efficient and accurate execution of all calibration steps. In order to achieve real-time polarimetric imaging, the lens distortion correction and the image registration were done by means of lookup tables. Experimental results by using a full-Stokes DoAP camera we fabricated indicate that, via the lens distortion correction and the image registration, the alignment error between two images with a mean absolute error (MAE) less than 0.16 pixels can be obtained, resulting in the aligned images having an average increase of 64.53 % for the structural similarity index (SSIM) and that of 84.97 % for the peak signal to noise ratio (PSNR), respectively; and further via the polarization channel calibration and the Stokes parameters modification, the MAE of 0.0146 for the degree of polarization (DoP) and that of 0.3544° for the angle of polarization (AoP) are obtained, respectively. This proposed calibration scheme for DoAP camera is systematic, automatic and robust, which is benefit of improving the polarization detection accuracy, enhancing the camera calibration efficiency and thus promoting its polarimetric imaging performance.

Size Effect on the Ductile Fracture of the Aluminium Alloy 2024-T351

BackgroundReliably calibrated criteria are needed for an accurate prediction of fracture of various components. However, there is not always a sufficient amount of material available. Therefore, miniature testing provides an alternative that is researched together with the following calibration of the ductile fracture criteria and investigating the size effect.ObjectiveThe aim is to design miniature testing equipment and specimens for tensile testing, which covers various stress states. This is supplemented by the small punch test, which has the same specimen thickness, taken from the literature to broaden the portfolio for calibration. The second part deals with conducting the finite element analysis, which provided a basis for the calibration of the phenomenological ductile fracture criterion applicable to crack-free bodies to indicate the crack initiation.MethodsThe steel frame to test thin specimens is designed with optical measurement of deformations. The finite element method is used, within Abaqus and user subroutines, to simulate the tests to obtain the variables needed for the calibration. In addition, the calibration of the criterion using machine learning is explored.ResultsThe feasibility of the proposed experimental program is tested on the aluminium alloy 2024-T351. Moreover, the numerical simulations, which showed a good match with experiments in terms of force responses, adds to the knowledge of modelling in the scope of continuum damage mechanics.ConclusionsThe presented results provide a material basis for the aluminium alloy studied on a lower scale, while they broaden the testing possibilities and analyses the calibration strategies for the best failure predictability possible.

In situ Lu–Hf dating of allanite by LA-ICP-MS/MS: Implications for geochronology

Allanite is a common REE-rich accessory mineral found in various igneous and metamorphic rocks, and can record a variety of geological processes. Therefore, allanite geochronology has the potential to answer a range of important geological questions. Allanite U–Th–Pb geochronology is hampered by common open-system behavior in the system. In this study, we demonstrate the feasibility of in situ allanite Lu–Hf dating by LA–ICP–MS/MS. A total of nine allanite samples from different rock types (e.g., granite, pegmatite) were investigated. These allanite samples have ages ranging from ca. 2650 to ca.100 Ma, and Lu contents ranging from several to hundreds of μg g−1 levels and relatively high Lu/Hf ratios (> 30). At a mass shift of +82, the isobaric interferences 176Lu and 176Yb have extremely low reaction rates of ∼0.003 % and ∼ 0.0003 %, respectively, indicating the isobaric interference corrections are insignificant for the allanite samples (mean 175Lu/177Hf = ∼814; mean 172Yb/177Hf = ∼719). A two-step calibration strategy was proposed for the 176Lu/176Hf and 177Hf/176Hf ratio corrections using NIST SRM 610 (for instrument drift) and LE2808 (for matrix effect). The nine allanite samples contain common Hf contents (f176Hf) of ∼5 % to >90 %, and the data are plotted in inverse isochron diagrams. Unanchored inverse isochron ages exhibit a large deviation in accuracy (5–10 %), whilst anchored isochron ages have a better accuracy of <5 %. The uncertainty of anchor initial 176Hf/177Hf values was investigated and, in general, was insignificant (< 2.8 %) for samples with f176Hf < 80 %. Our results demonstrate that in situ allanite Lu–Hf dating by LA-ICP-MS/MS is feasible and can yield precise and accurate ages (< 5 %). Lu–Hf geochronometer captures the high-temperature process and may be more resistant during the late thermal event. Thus, it provides an alternative solution for those samples which are suffered by open-system behavior in U-Th-Pb system.

Transformer fusion for indoor RGB-D semantic segmentation

Fusing geometric cues with visual appearance is an imperative theme for RGB-D indoor semantic segmentation. Existing methods commonly adopt convolutional modules to aggregate multi-modal features, paying little attention to explicitly leveraging the long-range dependencies in feature fusion. Therefore, it is challenging for existing methods to accurately segment objects with large-scale variations. In this paper, we propose a novel transformer-based fusion scheme, named TransD-Fusion, to better model contextualized awareness. Specifically, TransD-Fusion consists of a self-refinement module, a calibration scheme with cross-interaction, and a depth-guided fusion. The objective is to first improve modality-specific features with self- and cross-attention, and then explore the geometric cues to better segment objects sharing a similar visual appearance. Additionally, our transformer fusion benefits from a semantic-aware position encoding which spatially constrains the attention to neighboring pixels. Extensive experiments on RGB-D benchmarks demonstrate that the proposed method performs well over the state-of-the-art methods by large margins.

A Calibration Scheme for a 800-Ms/s 14 Bit Pipelined ADC in 28-nm CMOS

Abstract A calibration scheme is proposed to compensate linear and nonlinear errors including offset, cap mismatch, second- and higher-order harmonics and memory induced errors in pipelined analog-to-digital converters (ADCs). The alternating minimization (AM) algorithm is proposed to accurately estimate the coefficients of the errors. As an accurate input value is hardly acquired in practical measurements, instead, the proposed scheme estimates the input and the error coefficients jointly. Once the error coefficient was calculated, it will be recorded in a lookup table (LUT). The scheme has been demonstrated in a 800-Ms/s 14-bit pipelined ADC fabricated in a 28nm CMOS process, which features a signal-to-noise ratio (SNR) and spurious-free dynamic range (SFDR) improvement of 2.49 dB and 11.49 dB at 800-Ms/s.

GGR Handbook of Rock and Mineral Analysis Chapter 7 Quadrupole Inductively Coupled Plasma‐Mass Spectrometry

This chapter (Quadrupole Inductively Coupled Plasma‐Mass Spectrometry) is a contribution to the Geostandards and Geoanalytical Research Handbook of Rock and Mineral Analysis – an online textbook that is a fully revised and updated edition of Handbook of the Silicate Rock Analysis (P. J. Potts, 1987, Blackie, Glasgow).Chapter 7 (from Section 2 of the handbook dealing with techniques for the determination of major and trace elements) describes both the history of ICP‐MS, including development of the plasma sampling interface and the operation of modern ICP‐MS instrumentation. Given their central importance to ICP‐MS operation, ion extraction through the sampling interface, ion transmission, ion separation (with a particular focus on the quadrupole mass filter) and counting are given particular attention. Discussion of the analytical characteristics of ICP‐MS particularly focusses on spectroscopic interferences (and their mitigation). Finally, an overview of geochemical analysis by ICP‐MS considers drift correction, calibration strategies, and laser ablation microsampling.

PAM: Research on posture alignment method for camera robot system

By acquiring the posture information of the rigid body with markers, the camera motion on the robot end-effector can be controlled remotely. The essential step of posture alignment in teleoperation is to calibrate the transformation matrix of the world coordinate system of the optical motion capture system and the robot base coordinate system. It was necessary to change the position and attitude of the camera robot in the studio frequently. At the same time, the studio was complex with strong personnel mobility, thus the world coordinate system of the optical tracking system in the studio was needed to be re-established frequently. These two points asked the pose calibration scheme of the camera robot in the optical tracking system to be convenient and universal. In this paper, a novel posture alignment method (PAM) was proposed, which was an automatic, accurate and quick method to complete the posture alignment for related coordinate systems without non-systematic errors. PAM was applied to teleoperation for camera robot by inverse movement matrix. The comparative experiments prove that the proposed method is better than manual method, with higher precision and stability, more flexible physical setting for reference coordinate system, and shorter operation time consuming. Meanwhile, PAM is more suitable for camera robot teleoperation than existed automatic method, because it does not require paying attention to the calibration postures.

A multi-variable calibration framework at the grid scale for integrating streamflow with evapotranspiration data to improve the simulation of distributed hydrological model

Study regionThe Ganjiang River Basin, China Study focusParameter calibration is crucial for the accurate and reliable operation of hydrological models. Traditional methods face challenges in calibrating spatially heterogeneous parameters of distributed hydrological models, and existing multi-variable calibration strategies often fall short in comprehensively improving model performance, particularly in streamflow simulations. To address these challenges, this study proposes a multi-objective calibration framework that integrates observed streamflow data and satellite-based evapotranspiration (ET) data. The spatiotemporal information of the merged ET is utilized to calibrate six hydrological parameters of the Variable Infiltration Capacity (VIC) model at the grid scale, enhancing hydrological simulations for the Ganjiang River basin. New hydrological insightsCompared to the benchmark scheme based solely on streamflow, the proposed calibration framework improves simulations of area-average ET at the sub-basin scale and soil moisture content in the Ganjiang River basin, without compromising the accuracy of daily streamflow simulations. Additionally, notable enhancements are observed in monthly streamflow simulations. This study provides a promising and comprehensive calibration framework using satellite-based data to constrain parameters and enhance the performance of distributed hydrological models.

Adoptability assessment of HCDI and RCCI modes in plug-in parallel hybrid electric vehicles using sustainable fuels and model-based torque structure calibration strategies

In this research, a comparative analysis of plug-in hybrid electric vehicle (PHEV) engine was conducted with two advanced low temperature combustion (LTC) techniques viz. Homogeneous charge with direct injection (HCDI) and reactivity-controlled compression ignition (RCCI), utilizing alternative fuels diethyl ether (DEE) and ethanol. This was attempted to exhibit the promising potential of LTC based PHEV to achieve the highest efficiency and low emissions. The experimental results disclosed that DEE powered HCDI can achieve superior thermal efficiency with an impressive peak torque of 14 Nm. On the other hand, ethanol powered RCCI produced a peak torque of 17.5 Nm with remarkable emission reduction characteristics, especially CO2. It was vindicated that HCDI-PHEV outperformed the RCCI-PHEV in terms of fuel economy despite both HCDI and RCCI being lower than the conventional diesel PHEV. The NOx emissions from HCDI were almost negligible. About 20 % lower nitrogen oxide (NOx) emissions were recorded for RCCI respectively as compared to diesel (36 g/s). HCDI and RCCI showcased about 2 and 1.3 times higher soot emissions than diesel (7.12 g/s). Fuel economy was improved by 15 % and 43 % respectively under HCDI and RCCI modes over the conventional diesel mode of PHEV operation. When the PHEV was operated continuously for about 3.5 h, the battery's SOC dropped from 80 % to 45 % under diesel operation, whereas it only reached 50 % and 60 % under RCCI and HCDI mode operation. Low fuel consumption characteristics, acceptable torque production capabilities and ultralow NOx reduction potential established HCDI as the preferable choice for PHEV over RCCI.

Assignment of a Physical Energy Scale for the Dimensionless Interaction Energies within the PRIME20 Peptide Model.

We present a calibration scheme to determine the conversion factors from a coarse-grained stochastic approximation Monte Carlo approach using the PRIME20 peptide interaction model into atomistic force-field interaction energies at full explicit aqueous solvation. The conversion from coarse-grained to atomistic structures was done according to our previously established inverse coarse-graining protocol. We provide a physical energy scale for both the backbone hydrogen bonding interactions and the sidechain interactions by correlating the dimensionless energy descriptors of the PRIME20 model with the energies averaged over molecular dynamics simulations. The conversion factor for these interactions turns out to be around 2kJ/mol for the backbone interactions, and zero for the sidechain interactions. We discuss these surprisingly small values in terms of their molecular interpretation.

Acquisition parameters influence AI recognition of race in chest x-rays and mitigating these factors reduces underdiagnosis bias

A core motivation for the use of artificial intelligence (AI) in medicine is to reduce existing healthcare disparities. Yet, recent studies have demonstrated two distinct findings: (1) AI models can show performance biases in underserved populations, and (2) these same models can be directly trained to recognize patient demographics, such as predicting self-reported race from medical images alone. Here, we investigate how these findings may be related, with an end goal of reducing a previously identified underdiagnosis bias. Using two popular chest x-ray datasets, we first demonstrate that technical parameters related to image acquisition and processing influence AI models trained to predict patient race, where these results partly reflect underlying biases in the original clinical datasets. We then find that mitigating the observed differences through a demographics-independent calibration strategy reduces the previously identified bias. While many factors likely contribute to AI bias and demographics prediction, these results highlight the importance of carefully considering data acquisition and processing parameters in AI development and healthcare equity more broadly.

Crystal plasticity modeling of prior austenite orientation effects on deformation behaviors of martensitic steels under different strain paths

The influence of prior austenite grain (PAG) orientation on the deformation behavior of a low-carbon martensitic steel is investigated using crystal plasticity (CP) modeling with hierarchical representative volume elements (RVEs). The Kurdjumov-Sachs (K-S) relationship is refined for accurate PAG reconstruction in martensitic steel. A robust calibration strategy for CP parameters based on nanoindentation tests is developed by integrating analytical calculations with inverse methods. Virtual polycrystalline aggregates are subsequently generated by manipulating initial PAG orientations. The simulations reveal that assigning cube texture to PAGs enhances strain hardening of martensite under plane strain tension. Moreover, the RVEs with brass and copper orientated PAGs exhibit similar deformation behavior, and a more homogeneous strain distribution is realized in the RVE with PAG cube orientation. The influence of PAG orientation on stress and strain fields is correlated with lattice rotation behavior during deformation. Notably, different strain paths elicit distinct lattice rotation trajectories, wherein uniaxial tension and plane strain tension favor grains reorientation toward hard γ-fiber, whilst equi-biaxial tension drives the crystal matrix to concentrate on 〈001〉 and 〈011〉 directions. These findings provide insights into the intricate relationship between microstructural orientation and deformation behavior in martensitic steels, which is crucial for performance optimization.

The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) – Part 1: Instrument description and level 1 radiances

Abstract. The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) instrument combines a commercial Bruker EM27 spectrometer with a front-end viewing and calibration rig developed at Imperial College London. FINESSE is specifically designed to enable accurate measurements of surface emissivity, covering the range 400–1600 cm−1, and, as part of this remit, can obtain views over the full 360° angular range. In this part, Part 1, we describe the system configuration, outlining the instrument spectral characteristics, our data acquisition methodology, and the calibration strategy. As part of the process, we evaluate the stability of the system, including the impact of knowledge of blackbody (BB) target emissivity and temperature. We also establish a numerical description of the instrument line shape (ILS), which shows strong frequency-dependent asymmetry. We demonstrate why it is important to account for these effects by assessing their impact on the overall uncertainty budget on the level 1 radiance products from FINESSE. Initial comparisons of observed spectra with simulations show encouraging performance given the uncertainty budget.

Calibration guide for watershed modeling with distributed groundwater modeling: application for the SWAT+ model

ABSTRACT We present a new calibration strategy guide for coupled surface–subsurface hydrologic models. The goal is to reduce bias in environmental modeling and make calibration processes more consistent. The strategy guide enhances model efficiency and accuracy by focusing on changes to channel, soil, landscape, and aquifer properties. This approach is particularly beneficial when simulating important hydrologic features like baseflow and peaks and across different watersheds. Developed using the Soil and Water Assessment Tool (SWAT+) and the new gwflow module in six diverse US watersheds, each with unique hydrologic characteristics, the guide encourages improved calibration through routine use. It addresses specific issues related to the temporal distribution of streamflow and offers a robust method for enhancing model performance across a wide range of hydrologic conditions. By employing parameter estimation and sensitivity analysis, the approach ensures rigorous and objective calibration of SWAT+ and other models that include land, soil, aquifer, and water processes, leading to more accurate hydrologic modeling.

A novel optical orthogonality control approach based on noise propagation and its application in spin-exchange relaxation-free co-magnetometers

This paper presents a non-destructive optical orthogonality control method based on adaptive gradient descent for spin-exchange relaxation-free co-magnetometers (SERFCM). The spin-exchange optical pumping technique serves as the foundation of SERFCM measurement. Analyzing the impact of pump power fluctuation on the transverse polarizability of alkali metal atoms in the presence of non-orthogonal beams, considering stochastic noise propagation, is addressed. Subsequently, an optical orthogonal calibration scheme is proposed. Leveraging the proposed orthogonal calibration scheme, an adaptive gradient descent method based on the reference model is formulated, and simulation validates its effectiveness in addressing the rapid online optimization control of SERFCM optical quadrature. Experimental results indicate that the proposed optical orthogonal calibration scheme offers higher accuracy, with the proposed optical orthogonal control algorithm saving 34% of the time compared to the traditional algorithm. Finally, the stability of SERFCM is evaluated using Allan variance, demonstrating that the adjusted SERFCM enhances short-term stability by 84% at around 1s and long-term stability by 639% at around 300s.