Geolocation error compensation method for geocoded SAR images using pixel-offset series without control points by Liqun Liu, Zhiwei Li, Yan Zhu, Yifan Zhang, Chenglong Cao, Xun Du, Kun Han, Haiqiang Fu

“…SAR spatial geolocation of synthetic aperture radar (SAR) is crucial for SAR/interferometric (In)SAR applications. Geolocation errors often arise owing to factors such as platform instability, instrument degradation, and environmental variations. …”
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Morgan-Voyce Polynomial Approach for Solution of High-Order Linear Differential-Difference Equations with Residual Error Estimation by Bengü TÜRKYILMAZ, Burcu GÜRBÜZ, Mehmet SEZER

“…Also, by using the Mean-Value Theorem and residual function, an efficient error estimation technique is proposed and some illustrative examples are presented to demonstrate the validity and applicability of the method.…”
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Morgan-Voyce Polynomial Approach for Solution of High-Order Linear Differential-Difference Equations with Residual Error Estimation by Bengü TÜRKYILMAZ, Burcu GÜRBÜZ, Mehmet SEZER

“…Also, by using the Mean-Value Theorem and residual function, an efficient error estimation technique is proposed and some illustrative examples are presented to demonstrate the validity and applicability of the method.…”
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Morgan-Voyce Polynomial Approach for Solution of High-Order Linear Differential-Difference Equations with Residual Error Estimation by Bengü TÜRKYILMAZ, Burcu GÜRBÜZ, Mehmet SEZER

“…Also, by using the Mean-Value Theorem and residual function, an efficient error estimation technique is proposed and some illustrative examples are presented to demonstrate the validity and applicability of the method.…”
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MIMO radar DOA element position error correction method based on overlapping reference element matrix reconstruction by Feng Tian, Tianyu Wei, Weibo Fu, Siyuan Wang

“…This method uses overlapping virtual array elements as references, corrects the array element position error by phase difference, and constructs an error compensation matrix to eliminate the virtual array position error. …”
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A Self-Adaptive Regression-Based Multivariate Data Compression Scheme with Error Bound in Wireless Sensor Networks by Jianming Zhang, Kun Yang, Lingyun Xiang, Yuansheng Luo, Bing Xiong, Qiang Tang

“…Wireless sensor networks (WSNs) have limited energy and transmission capacity, so data compression techniques have extensive applications. A sensor node with multiple sensing units is called a multimodal or multivariate node. …”
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Time‐interleaving design of error‐feedback sigma‐delta modulators with infinite impulse response noise transfer function by Francisco Colodro, Juana Maria Martinez‐Heredia, Jose L. Mora, Antonio Torralba

“…In many applications, DAC output has a small number of bits. …”
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Secrecy Rate Performance Analysis of Jammer-Aided Symbiotic Radio with Sensing Errors for Fifth Generation Wireless Networks by Muhammed Yusuf Onay

“…Although taking the sensing error into account degrades the system performance, the real-world applicability of the system with sensing error is more realistic. …”
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Analytical Formulation of Relationship Between Sensors and Euler Angle Errors for Arbitrary Stationary Alignment Based on Accelerometer and Magnetometer by Chang June Lee, Jung Keun Lee

“…However, the stationary alignment accuracy is affected by sensor error factors. Therefore, several studies have attempted to analyze and minimize the effects of these errors. …”
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Identification of Leverage Points in Principal Component Regression and r-k Class Estimators with AR(1) Error Structure by Tuğba Söküt

“…In the literature, the first leverage is considered separately due to the first-order autoregressive error structure. Therefore, the behaviours of first leverages obtained by principal component regression and r-k class estimators has been also investigated according to the autocorrelation coefficient and biasing parameter through applications. …”
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Active-learning-driven error control for data-driven state of charge estimation across the lithium battery lifecycle by Jinwei Xue, Xuzhi Du, Lei Zhao, Zhigang Yang, Chao Xia, Yuan Ma, Muhammad Jahidul Hoque, Wuchen Fu, Xiao Yan, Nenad Miljkovic

“…Experimental results show that with only four active retraining sessions over the full aging process, our method reduces average SOC estimation error to below 1.5 %, and maximum cycle-based average error to below 2 %. …”
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The Influence of the Spatial Co-Registration Error on the Estimation of Growing Stock Volume Based on Airborne Laser Scanning Metrics by Marek Lisańczuk, Krzysztof Mitelsztedt, Krzysztof Stereńczak

“…However, practical applications often require subsequent optimisation steps. …”
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Applicability of Anisotropic Failure Criteria and Associated Application with Layered Rocks by Wenxue Deng, Tianhong Yang, Honglei Liu, Feiyue Liu, HongLiang Xu

“…This paper examines the applicability of four failure criteria applied to layered rocks, namely, Pariseau’s model, linear empirical equation, nonlinear empirical equation (LEE and NLEE), and Jaeger’s plane-of-weakness model (JPW). …”
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DELIK LALU LINTAS YANG MENGAKIBATKAN MENINGGALNYA ORANG LAIN by Muh. Amiruddin

“…The condition of driver unpreparedness opens up great opportunities for severe accidents as well as endangering the safety of other road users.Careless, sleepy, unskilled, tired, not keeping distance, going too fast are examples of driver errors in general.…”
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Error Analysis and Adaptive-Robust Control of a 6-DoF Parallel Robot with Ball-Screw Drive Actuators by Navid Negahbani, Hermes Giberti, Enrico Fiore

“…Finally, a nonlinear adaptive-robust control algorithm for trajectory tracking, based on the minimization of the tracking error, is described and simulated.…”
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A General Numerical Error Compensation Method for NLFM Signal in SAR System Based on Non-Start–Stop Model by Gui Wang, Heng Zhang, Bo Li, Weidong Yu

“…Nonlinear frequency modulated (NLFM) signals can be used to enhance the resolution, anti-jamming capability, and imaging quality of synthetic aperture radar (SAR) systems through optimized design, demonstrating substantial application potential. However, in a SAR system using NLFM signals, the non-start–stop effect, caused by the continuous motion of the platform during pulse transmission and reception, introduces significant errors, resulting in target defocusing. …”
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Design, modeling and manufacture error identification of a new 6-degree-of-freedom (6-DOF) compliant parallel manipulator by H. Li, W. Chen, L. Yi, C. Leng, H. Wu

“…Additionally, a kinematic model of the whole manipulator has been formulated and, based on it, a manufacture error identification model has been established to identify the manufacture errors, which is crucial for improving the motion accuracy. …”
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Research on anti-error operation warning of power grid dispatching based on deep bidirectional gated recurrent neural network by Jinglong He, Dunlin Zhu, Sheng Yang, Jinming Liu, Tianyun Luo, Yuan Fu

“… To improve the security and overall efficiency of grid scheduling work and accurately optimize scheduling decisions, a grid scheduling error-proof operation warning method based on a deep bidirectional gated recurrent neural network is proposed. …”
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Submission of Documents on the Pharmacovigilance System as Part of the Registration Dossier within the Framework of the EAEU Procedures: Analysis of Requirements and Typical Errors by N. Yu. Velts, E. O. Zhuravleva, G. V. Kutekhova, N. V. Tereshkina

“…This study aimed to analyse the requirements for submitting either the PSMF or the SPS, depending on the EAEU marketing authorisation procedure, and to describe typical errors made by applicants when submitting these documents.DISCUSSION. …”
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Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm by Manzhi Yang, Hao Ren, Shijia Liu, Bin Feng, Juan Wei, Hongyu Ge, Bin Zhang

“…Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. …”
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