Neural correlates of sensorimotor adaptation: Thalamic contributions to learning from sensory prediction error by Shirin Mahdavi, Axel Lindner, Carsten Schmidt-Samoa, Anna-Lena Müsch, Peter Dechent, Melanie Wilke

“…Understanding the neural mechanism of sensorimotor adaptation is essential to reveal how the brain learns from errors, a process driven by sensory prediction errors. …”
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Individual differences in neurophysiological correlates of post-response adaptation: A model-based approach by Anna Grabowska, Filip Sondej, Julia Haaf, Michael D. Nunez, Magdalena Senderecka

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Social post-error adaptations across four NBA basketball seasons by Ayala Denul, Gilles Pourtois, Tom Loeys, Wim Notebaert

“…Lab studies often observe that people become more cautious after both own and others’ errors. Moreover, social error monitoring research suggests that cooperation elicits stronger adaptations to others’ errors than competition. …”
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Concurrent Contribution of Co-Contraction to Error Reduction During Dynamic Adaptation of the Wrist by Andria J Farrens, Kristin Schmidt, Hannah Cohen, Fabrizio Sergi

“…Compared to arm reaching tasks, we observed lower end magnitude of adaptation, and reductions in trajectory errors beyond those explained by adaptation. …”
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Channel Correlation-Based Adaptive Power Transmission for Free-Space Optical Communications by Bai-Shan Zhao, Peng-Fei Lv, Yan-Qing Hong

“…This paper proposes a channel correlation-based adaptive power transmission for FSO communications. …”
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Uncertainty evaluation of surface profile measurement error based on adaptive sparse grid polynomial chaos expansion by Ke Zhang, Xinya Zheng, Ruiyu Zhang

“…To address the challenge of balancing accuracy and computational efficiency in evaluating the measurement error and uncertainty of surface profile errors on complex free-form surfaces, this paper proposes an evaluation method combining adaptive sparse grids and polynomial chaos expansion. …”
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Self-Adaptive Moving Least Squares Measurement Based on Digital Image Correlation by Hengsi Zhu, Yurong Guo, Xiao Tan

“…Digital image correlation (DIC) is a non-contact measurement technique used to evaluate surface deformation of objects. …”
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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

“…By designing an incremental algorithm for computing regression coefficients, a multivariate data compression scheme based on self-adaptive regression with infinite norm error bound for WSNs is proposed. …”
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Improved UWB-based indoor positioning system via NLOS classification and error mitigation by Shoude Wang, Nur Syazreen Ahmad

“…The classification results are then utilized within an Adaptive Robust Extended Kalman Filter (AREKF) to establish an error model for mitigation. …”
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Adaptive resolution in speckle displacement measurement using optimized grid-based phase correlation and statistical refinement by Hamed Sabahno, Satyam Paul, Davood Khodadad

“…In this paper, we present an adaptive resolution approach for speckle displacement measurement that combines grid-based phase correlation with statistical refinement for enhanced accuracy and resolution.Unlike traditional phase correlation techniques that rely on global correlation, our method introduces a flexible grid-based framework with localized correlation and dynamic overlap adjustments. …”
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Adaptive rolling runoff forecasting model: Combining multi-source correlated sequences and extreme value encoding by Tao Wang, Jingzhe Liu, Yongming Cheng, Jingjing Duan, Yifei Zhao, Jing Zhao, Peiling Wang, Jiaqi Zhai

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Regional distributed photovoltaic power forecasting considering spatiotemporal correlation and meteorological coupling by HUANG Xiaoyan, GUO Sasa, CHEN Chengyou, XU Tengchong, HAN Xiao, WANG Tao

“…To address this， this paper proposes a regional distributed photovoltaic power forecasting method that considers spatiotemporal correlation and meteorological coupling. First， based on an analysis of the output characteristics of distributed photovoltaic power stations， an adaptive graph convolutional neural network combined with a long short-term memory network （LSTM） is used to extract the spatiotemporal features of the photovoltaic output. …”
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Research on Multi-Step Prediction of Pipeline Corrosion Rate Based on Adaptive MTGNN Spatio-Temporal Correlation Analysis by Mingyang Sun, Shiwei Qin

“…In order to comprehensively investigate the spatio-temporal dynamics of corrosion evolution under complex pipeline environments and improve the corrosion rate prediction accuracy, a novel framework for corrosion rate prediction based on adaptive multivariate time series graph neural network (MTGNN) multi-feature spatio-temporal correlation analysis is proposed. …”
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A Novel High-Fidelity Reversible Data Hiding Method Based on Adaptive Multi-pass Embedding by Xiaoxi Kong, Wenguang He, Zhanchuan Cai

“…Furthermore, we implement an adaptive strategy that dynamically selects multiple iteration parameters based on pixel content to obtain more expandable prediction errors and adjusts the modification of prediction errors accordingly. …”
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Research on short-term traffic flow prediction based on the PCC-IGA-LSTM model by Junxi Zhang, Shiru Qu, Yang Bi, Lijing Ma

Subjects: “…Pearson correlation coefficient (PCC)…”
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Quantum computer error structure probed by quantum error correction syndrome measurements by Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman

“…These results highlight the nontrivial structure that may be present in the noise of quantum error correction circuits, revealed by operator measurement statistics, and support the development of noise-tailored codes and decoders to adapt.…”
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An adaptive dual distillation framework for efficient remaining useful life prediction by Xiang Cheng, Jun Kit Chaw, Shafrida Sahrani, Mei Choo Ang, Saraswathy Shamini Gunasekaran, Moamin A. Mahmoud, Halimah Badioze Zaman, Yanfeng Zhao, Fuchen Ren

“…A-DDF outperforms previous methods, achieving a 12% decrease in relative error (MAPE), improving prediction accuracy and stability. …”
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Substantial Heritability Underlies Fairness Norm Adaptation Capability and its Neural Basis by Yuening Jin, Dang Zheng, Ruolei Gu, Qingchen Fan, Martin Dietz, Changshuo Wang, Xinying Li, Jie Chen, Yuanyuan Hu, Yuan Zhou

“…Abstract The present research uncovers the shared genetic underpinnings of fairness norm adaptation capability, its neural correlates, and long‐term mental health outcomes. …”
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An Adaptive Multi-Fidelity Surrogate Model for Uncertainty Propagation Analysis by Wei Xiao, Yingying Shen, Jiao Zhao, Luogeng Lv, Jiangtao Chen, Wei Zhao

“…To quantify the uncertainties in multi-dimensional flow field correlated responses caused by uncertain model parameters, this paper presents an adaptive multi-fidelity model based on gappy proper orthogonal decomposition (Gappy-POD), which integrates the two conventional approaches for enhancing the efficiency of surrogate modeling, namely, multi-fidelity modeling and adaptive sampling algorithms. …”
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Adaptive Artificial Neural Network-Based Proportional Integral Controllers and Extremum Seeking Energy Optimizer for Wind Systems by Hassan Rafia, Hamid Ouadi, Brahim Elbhiri

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