Iterative Correction Research Articles

Using Iterative Correction to Improve the Accuracy of the Blind-Hole Welding Residual Stress Test.

An iterative correction method for the stress release coefficient, leveraging numerical simulation, has been innovatively developed to address the significant error issues associated with the blind-hole method in high-stress residual stress testing of steel structures. This method effectively reduces measurement error in high residual stress regions through a discriminant iteration process. The finite element analysis technology was employed to accurately simulate the blind-hole method's test process, and additionally, Python was utilized for customizing the secondary development of ABAQUS software, thereby automating and optimizing the method. When compared with simulation and experimental data from the welding process, the efficiency, accuracy, and reliability of the correction method have been verified. The proposed method eliminates the need for tedious calibration experiments inherent in traditional methods, significantly enhancing the test's automation level and convergence speed, and ensuring measurement accuracy, which provides an innovative solution for the accurate evaluation of residual stress in steel structures.

A Software Tool for the True Height Analysis of Ionograms Using the Iterative Gradient Correction (IGC) Method

AbstractDeriving the precise true height electron density profile from the measured ionosonde virtual heights is quite a challenging problem. Recently, Ankita and Tulasi Ram (2023, https://doi.org/10.1029/2023RS007808) presented a new method, Iterative Gradient Correction (IGC) method, for true height analysis that uses HF radio wave propagation path computations to reconstruct the true height profile. Through iterative corrections on electron density gradients between successive points, the IGC method minimizes errors below a specified tolerance at each point and reconstructs a complete electron density profile. The derived profiles from the IGC method are found to be accurate when compared with Incoherent Scatter Radar and Global Navigation Satellite System—Radio Occultation observations. To facilitate true height analysis by IGC method for a wider user community, a MATLAB‐based software has been developed and is outlined in this report. The software can be installed on any Windows platform and is designed with a user‐friendly interface for easy and efficient application by the users. It can analyze multiple scaled ionograms in a single run and outputs the real height profiles in ASCII format. Further, the software also captures important ionospheric parameters such as the base altitudes and peak frequencies of E‐ and F‐layers (e.g., hE, hF, foE, and foF2) etc., from the computed true height profiles and tabulates in a separate output file for the ready use. The software also provides the option for extrapolation of true height profile into top‐side ionosphere up to a user‐specified height and reconstructs the complete vertical electron density profile.

A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes.

The application of high-throughput chromosome conformation capture (Hi-C) technology enables the construction of chromosome-level assemblies. However, the correction of errors and the anchoring of sequences to chromosomes in the assembly remain significant challenges. In this study, we developed a deep learning-based method, AutoHiC, to address the challenges in chromosome-level genome assembly by enhancing contiguity and accuracy. Conventional Hi-C-aided scaffolding often requires manual refinement, but AutoHiC instead utilizes Hi-C data for automated workflows and iterative error correction. When trained on data from 300+species, AutoHiC demonstrated a robust average error detection accuracy exceeding 90%. The benchmarking results confirmed its significant impact on genome contiguity and error correction. The innovative approach and comprehensive results of AutoHiC constitute a breakthrough in automated error detection, promising more accurate genome assemblies for advancing genomics research.

The Curriculum Practice of Cross Domain Competence Oriented Aesthetic Education－Taking Height Measurement On The Tree

<p>本研究在探究國小低年級跨領域素養導向美感課程「身高樹」之實施歷程、困境、解決策略及實施成效。研究者以翰林版國小二級國語教材結合自編美感課程教材做為跨領域美感課程，以TSING國小2年級學生為對象，進行為期6個月的課程實踐，將課程設計理念及實踐經驗視為作品（works of art），辨析其美感性質。透過學生學習檔案、課程觀察紀錄、回饋單、省思札記、跨領域美感教學課程檢核表等，取得質性研究資料，進行分析與討論。本研究主要發現如下：一、以跨域統整架構情境化的課程，透過滾動式修正，可發展素養導向美感課程。二、跨領域素養導向教學美感課程發展時可透過教師營造生活美感體驗機會、小組合作、正向鼓勵、典範學習等進行有機整合，解決教學時數問題。三、跨領域素養導向美感課程「身高樹」，利用校園空間營造美學教育，探索體驗，增加學生對環境美的感知能力，能有效提升低年級學生學習興趣及成效。四、參與專業社群、增能研習等歷程，透過社群專業對話，認識核心素養，並進行課程實踐歷程探究，建立分享機制，與夥伴共同進行教學改良與精進，亦可促進教師專業成長。</p> <p> </p><p>This study investigates the implementation process, challenges, solutions, and impacts of the “Height Measurement on The Tree,” a cross-disciplinary and competency-oriented aesthetic program designed for junior elementary school students. The researcher designed this cross-disciplinary aesthetic course by integrating the Hanlin version of the second-grade Chinese textbook with a self-compiled aesthetic course textbook and conducted a six-month teaching session with a group of second-grade Tsing primary school students. This study examines their aesthetic nature by treating the course design and practical experience as works of art. Qualitative research data were collected from students’ learning files, class observation records, feedback sheets, reflection notes, and cross-disciplinary aesthetic teaching curriculum checklists. Based on the analysis and discussion of the data, this study reaches the following conclusions: 1.A cross-disciplinary, contextually adapted course framework with iterative corrections can facilitate the development of cross-disciplinary and competency-oriented aesthetic courses. 2.The issue of limited teaching hours can be addressed through the organic integration of courses, which includes creating an aesthetic experience of life, fostering group collaboration, providing positive reinforcement, and promoting model-based learning. 3.Participation in the ""Height Measurement on The Tree,"" a cross-disciplinary and competency-oriented aesthetic program, significantly enhances junior students’ learning interest and improves learning outcomes. 4.Teachers can advance their professional growth by engaging in professional communities and participating in enhanced programs. Effective course design can overcome the limitations related to scheduling and disciplinary constraints, aligning with actual learning contexts. Teachers can learn to integrate multimedia into their teaching by strengthening their expertise in art. By exploring the teaching process and establishing mechanisms for sharing, more educators can recognize the potential of a new curriculum. Administrators should consider a broader range of feedback to improve the curriculum.</p> <p> </p>

A model predictive Stackelberg solution to orbital pursuit-evasion game

In this paper, we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information. In the proposed problem, the interplay between two spacecraft gives rise to a dynamic and real-time game, complicated further by the presence of J2 perturbation. The primary challenge lies in crafting control strategies that are both efficient and applicable to real-time game problems within a nonlinear system. To overcome this challenge, we introduce the model prediction and iterative correction technique proposed in model predictive static programming, enabling the generation of strategies in analytical iterative form for nonlinear systems. Subsequently, we proceed by integrating this model predictive framework into a simplified Stackelberg equilibrium formulation, tailored to address the practical complexities of leader–follower pursuit-evasion scenarios. Simulation results validate the effectiveness and exceptional efficiency of the proposed solution within a receding horizon framework.

Research on Parameter Correction of Distribution Network Model Based on CIM Model and Measurement Data

The construction of an energy distribution network can improve the system’s ability to absorb new energy, and its stable and efficient operation has become more and more important. The security and stability analysis of a distribution network needs accurate distribution network model parameters as support. At present, the installation of PMU equipment in China’s distribution network synchronous phase angle measurement unit is limited, which brings challenges to the parameter correction of the distribution network. In this paper, an automatic correction algorithm of distribution network parameters based on the CIM model and measurement data is proposed for the distribution network system without PMU. Firstly, the distribution network topology construction technology based on XML files and key fields of the distribution network is proposed, and the non/small impedance devices (such as switches) are merged and reduced. The breadth-first traversal algorithm is used to verify the connectivity of the constructed topology. Then, based on the topology construction and the least squares method, an iterative parameter correction technique is constructed. Finally, the accuracy and effectiveness of the proposed algorithm are verified in a standard IEEE 33-bus system distribution network and an example of the China Southern Power Grid. The topology connections constructed based on the CIM model have significantly enhanced the efficiency of parameter correction.

Advection-based multiframe iterative correction on PIV fields for improved pressure estimation

A novel method to improve the accuracy of pressure field estimation for advection-dominated flows from time-resolved Particle Image Velocimetry (PIV) data is proposed. Leveraging an advection model we can propagate in time velocity fields from each snapshot. The multiple time-series obtained from time propagation are used to smooth the nonphysical features in the original time-series. This correction is done iteratively. The technique reduces spatial noise by leveraging temporal information while simultaneously correcting temporal jitters using spatial data. Two validation methods are proposed to evaluate the method without knowing the true value of the pressure field. In this paper we provide a proof of the concept using a 3D synthetic dataset based on channel flow and a 2D PIV data set on the wake of a wing foil. Various noise models are tested by superimposing them onto the synthetic dataset, including Gaussian white noise and errors with spatial coherence. The results demonstrate that the proposed method outperforms conventional filters in improving the velocity and pressure fields from noisy velocity data, and in suppressing time jittering of the estimated pressure fields.

Simultaneous measurement of solid concentration and solid moisture in gas–solid two-phase flow using a dual-modality electrical sensor

Abstract In a gas–solid two-phase flow system, simultaneous measurement of solid concentration and solid moisture is essential for some applications. However, during the measurement process, solid concentration and solid moisture are coupled in the measurement signals when the measurement signal is sensitive to both solid concentration and moisture. This makes it challenging to measure them simultaneously in the same measurement field. To solve this issue, a novel measurement method is proposed in this study, which uses a dual-modality electrical sensor to achieve simultaneous measurement of solid concentration and solid moisture in gas–solid two-phase flow. The dual-modality electrical sensor features a simple structure and captures measurement signals of capacitance and angle of dielectric loss within the same measurement section. With the above signals which are both sensitive to solid concentration and moisture, an iterative correction calculation method is adopted to achieve the simultaneous measurement of solid concentration and solid moisture. During the calculation process, the measured parameters are decoupled and continuously corrected until the related error values meet the threshold requirement. Numerical simulation experiments under three typical distributions and physical experiments under roping flow are carried out to verify the proposed measurement method. The results prove the effectiveness of the proposed measurement method in the simultaneous measurement of solid concentration and solid moisture for gas–solid two-phase flow.

IMA-BLC: Iterative Median-Averaged Adaptive Black-Level Correction Method

IMA-BLC: Iterative Median-Averaged Adaptive Black-Level Correction Method

Iterative Motion Correction Technique with Deep Learning Reconstruction for Brain MRI: A Volunteer and Patient Study

Iterative Motion Correction Technique with Deep Learning Reconstruction for Brain MRI: A Volunteer and Patient Study

Versatile, fast, and accurate frequency excursions with a semiconductor laser

Achieving accurate arbitrary frequency excursions with a laser can be quite a technical challenge, especially when steep slopes (GHz/µs) are required, due to both deterministic and stochastic frequency fluctuations. In this work we present a multistage correction combining four techniques: pre-distorsion of the laser modulation, iterative correction, opto-electronic feedback loop, and feed-forward correction. This combination allows us not only to compensate for the non-instantaneous response of the laser to an input modulation but also to correct in real time the stochastic frequency fluctuations. We implement this multistage architecture on a commercial DBR laser and verify its efficiency, first, with monochromatic operation, and second, with highly demanding frequency excursions. We demonstrate that our multistage correction not only enables a strong reduction of the laser linewidth but also allows steep frequency excursions with a relative RMS frequency error well below 1% and a laser spectral purity consistently better than 100 kHz, even in the midst of gigahertz-scale frequency excursions.

An iterative crack tip correction algorithm discovered by physical deep symbolic regression

Digital image correlation is a widely used technique in the field of experimental mechanics. In fracture mechanics, determining the precise location of the crack tip is crucial. In this paper, we introduce a novel crack tip detection algorithm based on displacement and strain fields obtained by digital image correlation. Iterative crack tip correction formulas are discovered by applying deep symbolic regression guided by physical unit constraints to a dataset of simulated cracks under mode I, II and mixed-mode conditions with variable T-stress. For the training dataset, we fit the Williams series expansion with super-singular terms to the simulated displacement fields at randomly chosen origins around the actual crack tip. We analyse the discovered formulas and apply the most promising one to digital image correlation data obtained from uniaxial and biaxial fatigue crack growth experiments of AA2024-T3 sheet material. Throughout the experiments, the crack tip positions are reliably detected leading to improved stability of the crack propagation curves.

An Iterative 3D Correction plus 2D Inversion Procedure to Remove 3D Effects from 2D ERT Data along Embankments.

This paper addresses the problem of removing 3D effects as one of the most challenging problems related to 2D electrical resistivity tomography (ERT) monitoring of embankment structures. When processing 2D ERT monitoring data measured along linear profiles, it is fundamental to estimate and correct the distortions introduced by the non-uniform 3D geometry of the embankment. Here, I adopt an iterative 3D correction plus 2D inversion procedure to correct the 3D effects and I test the validity of the proposed algorithm using both synthetic and real data. The modelled embankment is inspired by a critical section of the Parma River levee in Colorno (PR), Italy, where a permanent ERT monitoring system has been in operation since November 2018. For each model of the embankment, reference synthetic data were produced in Res2dmod and Res3dmod for the corresponding 2D and 3D models. Using the reference synthetic data, reference 3D effects were calculated to be compared with 3D effects estimated by the proposed algorithm at each iteration. The results of the synthetic tests showed that even in the absence of a priori information, the proposed algorithm for correcting 3D effects converges rapidly to ideal corrections. Having validated the proposed algorithm through synthetic tests, the method was applied to the ERT monitoring data in the study site to remove 3D effects. Two real datasets from the study site, taken after dry and rainy periods, are discussed here. The results showed that 3D effects cause about ±50% changes in the inverted resistivity images for both periods. This is a critical artifact considering that the final objective of ERT monitoring data for such studies is to produce water content maps to be integrated in alarm systems for hydrogeological risk mitigation. The proposed algorithm to remove 3D effects is thus a rapid and validated solution to satisfy near-real-time data processing and to produce reliable results.

An iterative correction method for practically LPN solving

The LPN problem, lying at the core of many cryptographic constructions for lightweight and post-quantum cryptography, has recently received much attention. Accordingly, BKW, Gauss algorithm, and their improved or hybrid variants have been proposed to solve the LPN problem. In this paper, we propose an intelligent method for LPN solving from a wholly new perspective by iterative correcting the secret, which can successfully reduce the dimension of the LPN problem. While the challenge is that there are so many independent secret variables of the given checking parity equations with noise in LPN problems, a set of rules should be developed to effectively direct and correct the secret. To solve this problem, we skillfully introduce the genetic algorithm to simulate the process of iterative correction and further add vaccination technology to guide and speed up the iterative process. Owing to the small memory and data consumption of our algorithm, we conducted experiments and, for the first time, solved the largest practical LPN(256,1/8) instance in 30 days, which shows the superiority of our method. To the best of our knowledge, this is the first time the iterative correction method and the intelligent algorithm have been successfully applied to LPN problems.

Advancing LED technology: the FDCSP element’s breakthrough in mini and micro-LED packaging and backlight module enhancement

In this research, we introduce an advanced methodology for the calculation of bulk light sources tailored for free-form surface design, focusing on the principle of energy conservation. This method is especially relevant for the evolving needs of micro-LED packaging, highlighting its potential in this burgeoning field. Our work includes the development of an algorithm for creating freeform-designed chip-scale package (FDCSP) components. These components seamlessly integrate LEDs and lenses, underscoring our commitment to advancing free-form surface design in chip-level packaging. By adhering to the principle of energy conservation, our approach facilitates a meticulous comparison of simulation outcomes with predefined target functions. This enables the iterative correction of discrepancies, employing layering techniques to refine the design until the simulated results closely align with our goals, as demonstrated by an appropriate difference curve. The practical application of these simulations leads to the innovative design of FDCSP devices. Notably, these devices are not just suitable for traditional applications in backlight modules but are explicitly optimized for the emerging sector of micro-LED packaging. Our successful demonstration of these FDCSP devices within backlight modules represents a significant achievement. It underscores the effectiveness of our design strategy and its expansive potential to transform micro-LED packaging solutions. This research not only contributes to the theoretical understanding of energy conservation in lighting design but also paves the way for groundbreaking applications in micro-LED and backlight module technologies.

Visual transductive learning via iterative label correction

Visual transductive learning via iterative label correction

2.5D finite element algorithm based on Drucker-Prager yield criterion

This note regards the embankment as an ideal elastic-plastic material, and introduces the Drucker-Prager yield criterion into 2.5-D FEM. Firstly, the pure elastic trial stress is applied, and the Drucker-Prager yield criterion is used to determine whether yielding will occur or not. Then, the backward Euler integration method and the tangent stiffness method are used to derive the consistent tangent modulus matrix, after which the iterative correction of plastic deformation is realized. Finally, an elastoplastic 2.5D FEM is proposed according to the procedures. Compared with the measured values and existing results, it was found that the elastic-plastic 2.5-D finite element algorithm proposed in this note has good consistency with the measured values. Due to the consideration of the plastic deformation of the foundation soil induced by train moving loads, the present results are slightly larger than those of existing elastic methods.

A method of three-dimensional muon imaging using cosmic ray ground array

Cosmic ray muon imaging technology is an effective non-destructive imaging technique. It is currently used to survey the internal structure of large-scale objects such as active volcanoes, pyramids, and some buildings. Additionally, it is used to detect high-Z materials in scenarios such as border security, nuclear reactor monitoring, and container inspection. All applications of cosmic ray muons require a detector to reveal and measure the flux or angular variations of muons. However, detectors may have specific characteristics for each application depending on the detection requirements. Unlike single-point track detectors, we propose using ground array detectors to investigate how ground array detection technology can be used for 3D reconstruction of objects. We use ground array detection technology for simulation studies and apply the Iterative Correction Algorithm (ICA) to reconstruct two-dimensional projections and obtain three-dimensional images of density distribution. We have also addressed the convergence problem and analyzed and optimized some parameters that may affect the detection results. The advantages of using ground arrays include their ability to simultaneously measure the transmittance flux data of muons in different directions, achieve multi-angle detection, and have a large field of view, enabling the collection of sufficient data for more accurate detection results. To verify the feasibility of our new method, we conducted a simple experimental validation on a cylindrical cement building located in the Large High Altitude Air Shower Observatory (LHAASO). By comparing the experimental results with the cement building in the array, we found that their shape structure and density information are basically consistent, demonstrating the effectiveness of our method.

Correction of self-absorption effect in laser-induced breakdown spectroscopy based on temperature iteration

Laser-induced breakdown spectroscopy (LIBS) is an ideal real-time on-line method for the detection of minor elements in alloy steel, but it needs to solve the undesired self-absorption effect in plasma. Since the plasma electron temperature (T), radiation particle number density and absorption path length (Nl) determine the degree of self-absorption and affect the corrected spectral line intensity, a new temperature iterative self-absorption correction method based on the plasma thermal equilibrium radiation model is proposed to continuously calculate and correct these two parameters. Compared with generally applied self-absorption correction methods, this method has obvious advantages of simple programming, high computational efficiency, and independence of the availability or accuracy of Stark broadening coefficients. The quantitative analysis results of Cu show that the linearity of calibration curves and the measurement accuracy of elemental content are significantly improved with the self-absorption correction. In addition, this method can directly obtain the accurate radiation particle number density and absorption path length, which benefits the plasma diagnostics and quantitative analysis.

Dynamic iterative correction algorithm for designing diffractive optical elements

When utilizing the Gerchberg–Saxton (GS) algorithm to design diffractive optical elements, correction coefficients are introduced to improve the quality of the design results. The main design idea is to correct the target information dynamically during the iterative calculation process. The effectiveness of the proposed method is demonstrated through the verification of beam shaping and phase-type hologram designs. Compared to the traditional GS algorithm, the results of beam shaping show that the light intensity nonuniformity and the root-mean-square error (RMSE) of the shaped spot are reduced by an order of magnitude. The results of phase-type holograms show that the reconstructed image’s peak signal-to-noise ratio (PSNR) is improved by about 12 dB. Finally, the paper also discusses the selection of correction coefficients, providing insights into the selection of optimal design correction coefficients. The simulation and experimental results show that the improved algorithm proposed in this paper is not only simple in design but also highly efficient in obtaining a high-quality phase structure, which is of great help in designing high-quality diffractive optical elements.