Relevant bibliographies by topics / Huber function

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Huber function'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Huber function"

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Guitton, Antoine, and William W. Symes. "Robust inversion of seismic data using the Huber norm." GEOPHYSICS 68, no. 4 (2003): 1310–19. http://dx.doi.org/10.1190/1.1598124.

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The “Huber function” (or “Huber norm” ) is one of several robust error measures which interpolates between smooth (ℓ2) treatment of small residuals and robust (ℓ1) treatment of large residuals. Since the Huber function is differentiable, it may be minimized reliably with a standard gradient‐based optimizer. We propose to minimize the Huber function with a quasi‐Newton method that has the potential of being faster and more robust than conjugate‐gradient methods when solving nonlinear problems. Tests with a linear inverse problem for velocity analysis with both synthetic and field data suggest t
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Akkaya, Deniz, and Mustafa Ç. Pınar. "Minimizers of Sparsity Regularized Huber Loss Function." Journal of Optimization Theory and Applications 187, no. 1 (2020): 205–33. http://dx.doi.org/10.1007/s10957-020-01745-3.

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Gutiérrez, Osvaldo, Ismael de la Rosa, Jesús Villa, Efrén González, and Nivia Escalante. "Semi-Huber potential function for image segmentation." Optics Express 20, no. 6 (2012): 6542. http://dx.doi.org/10.1364/oe.20.006542.

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Wang, Yong, Shiqiang Hu, and Shandong Wu. "Object tracking based on Huber loss function." Visual Computer 35, no. 11 (2018): 1641–54. http://dx.doi.org/10.1007/s00371-018-1563-1.

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Ha, Taeyoung, Wookeen Chung, and Changsoo Shin. "Waveform inversion using a back-propagation algorithm and a Huber function norm." GEOPHYSICS 74, no. 3 (2009): R15—R24. http://dx.doi.org/10.1190/1.3112572.

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Waveform inversion faces difficulties when applied to real seismic data, including the existence of many kinds of noise. The [Formula: see text]-norm is more robust to noise with outliers than the least-squares method. Nevertheless, the least-squares method is preferred as an objective function in many algorithms because the gradient of the [Formula: see text]-norm has a singularity when the residual becomes zero. We propose a complex-valued Huber function for frequency-domain waveform inversion that combines the [Formula: see text]-norm (for small residuals) with the [Formula: see text]-norm
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Gaveau, Bernard, and Jacques Vauthier. "The Dirichlet Problem on the Heisenberg Group III: Harmonic Measure of a certain Half-Space." Canadian Journal of Mathematics 38, no. 3 (1986): 666–71. http://dx.doi.org/10.4153/cjm-1986-034-5.

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0. Introduction. In this short note we give an explicit computation of the harmonic measure of a half space x > 0 in the 3-dimensional Heisenberg group in terms of a degenerate hypergeometric function. A probabilistic argument reduces the whole problem to a Hermite-type equation on a half line, that we can solve in terms of the function G(l/4, 1/2; x2).A preliminary attempt to compute this kernel was done in [1] p. 107 and, cited by Huber [4]. Unfortunately a small mistake was made in [1] and the problem was still open until now. The first author is very grateful to Prof. Huber for having p
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Balasundaram, S., and Subhash Chandra Prasad. "Robust twin support vector regression based on Huber loss function." Neural Computing and Applications 32, no. 15 (2019): 11285–309. http://dx.doi.org/10.1007/s00521-019-04625-8.

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Gupta, Deepak, Barenya Bikash Hazarika, and Mohanadhas Berlin. "Robust regularized extreme learning machine with asymmetric Huber loss function." Neural Computing and Applications 32, no. 16 (2020): 12971–98. http://dx.doi.org/10.1007/s00521-020-04741-w.

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Dong, Hongwei, and Liming Yang. "Training robust support vector regression machines for more general noise." Journal of Intelligent & Fuzzy Systems 39, no. 3 (2020): 2881–92. http://dx.doi.org/10.3233/jifs-191429.

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Symmetric loss functions are widely used in regression algorithms to focus on estimating the means. Huber loss, a symmetric smooth loss function, has been proved that it can be optimized with high efficiency and certain robustness. However, mean estimators may be poor when the noise distribution is asymmetric (even outliers caused heavy-tailed distribution noise) and estimators beyond the means are necessary. Under the circumstances, quantile regression is a natural choice which estimates quantiles instead of means through asymmetric loss functions. In this paper, an asymmetric Huber loss func
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Liu, Zhe. "Huber Estimation for Uncertain Autoregressive Model." Journal of Uncertain Systems 14, no. 02 (2021): 2150010. http://dx.doi.org/10.1142/s1752890921500100.

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Traditional time analysis deals with observations in chronological order assuming the observations are precise numbers under the framework of probability theory, whereas data are imprecisely collected in many cases. This paper characterizes the imprecisely observed data as uncertain variables and estimates the unknown parameters in the uncertain autoregressive model using Huber loss function, which is more flexible compared with other robust estimations for a pre-given [Formula: see text] that regulates the amount of robustness. Then prediction value and prediction interval of the future value
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Dissertations / Theses on the topic "Huber function"

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Huber, Elisabeth [Verfasser], and Karl-Peter [Akademischer Betreuer] Hopfner. "The schlafen core domain: from structure to function / Elisabeth Huber ; Betreuer: Karl-Peter Hopfner." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2018. http://d-nb.info/1203544936/34.

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SAKANIWA, Kohichi, Isao YAMADA, Toshinori OHTSUKA, and Hiroshi HASEGAWA. "An Edge-Preserving Super-Precision for Simultaneous Enhancement of Spacial and Grayscale Resolutions." Institute of Electronics, Information and Communication Engineers, 2008. http://hdl.handle.net/2237/14995.

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Zavareh, Milad [Verfasser], and Tobias [Akademischer Betreuer] Huber. "Impact of interaction of diabetes mellitus and impaired renal function onprognosis and the incidence of acute kidney injury in patients undergoingtranscatheter aortic valve replacement (TAVI) / Milad Zavareh ; Betreuer: Tobias Huber." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2020. http://d-nb.info/1208834010/34.

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Tongur, Can. "Seasonal Adjustment and Dynamic Linear Models." Doctoral thesis, Stockholms universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-89496.

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Dynamic Linear Models are a state space model framework based on the Kalman filter. We use this framework to do seasonal adjustments of empirical and artificial data. A simple model and an extended model based on Gibbs sampling are used and the results are compared with the results of a standard seasonal adjustment method. The state space approach is then extended to discuss direct and indirect seasonal adjustments. This is achieved by applying a seasonal level model with no trend and some specific input variances that render different signal-to-noise ratios. This is illustrated for a system c
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Huber, Eva Maria [Verfasser], Michael [Akademischer Betreuer] Groll, Robert [Akademischer Betreuer] Huber, and Bernhard [Akademischer Betreuer] Rieger. "Structural and functional characterization of the immunoproteasome / Eva Maria Huber. Gutachter: Michael Groll ; Robert Huber ; Bernhard Rieger. Betreuer: Michael Groll." München : Universitätsbibliothek der TU München, 2013. http://d-nb.info/1034420909/34.

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Baek, Sohee [Verfasser], Robert [Akademischer Betreuer] Huber, and Sevil [Akademischer Betreuer] Weinkauf. "Structural and Functional Analysis of the Natural JNK1 Inhibitor Quercetagetin : Structure of the Stapled p53 Peptide Bound to HDM2 / Sohee Baek. Gutachter: Sevil Weinkauf ; Robert Huber. Betreuer: Robert Huber." München : Universitätsbibliothek der TU München, 2014. http://d-nb.info/1050817494/34.

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Schneider, Elisabeth Veronika [Verfasser], Robert [Akademischer Betreuer] Huber, and Adelbert [Akademischer Betreuer] Bacher. "Structural and functional characterization of human protein kinases exemplified on the human cyclin-dependent kinase 8, cyclin C complex / Elisabeth Veronika Schneider. Gutachter: Robert Huber ; Adelbert Bacher. Betreuer: Robert Huber." München : Universitätsbibliothek der TU München, 2012. http://d-nb.info/1035502852/34.

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Schneider, Elisabeth V. [Verfasser], Robert [Akademischer Betreuer] Huber, and Adelbert [Akademischer Betreuer] Bacher. "Structural and functional characterization of human protein kinases exemplified on the human cyclin-dependent kinase 8, cyclin C complex / Elisabeth Veronika Schneider. Gutachter: Robert Huber ; Adelbert Bacher. Betreuer: Robert Huber." München : Universitätsbibliothek der TU München, 2012. http://nbn-resolving.de/urn:nbn:de:bvb:91-diss-20120920-1108725-0-3.

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Huber, Laurentius [Verfasser], Harald [Akademischer Betreuer] Möller, and David [Gutachter] Norris. "Mapping Human Brain Activity by Functional Magnetic Resonance Imaging of Blood Volume / Laurentius Huber ; Gutachter: David Norris ; Betreuer: Harald Möller." Leipzig : Universitätsbibliothek Leipzig, 2015. http://d-nb.info/1239565232/34.

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Huser, Annina Maria [Verfasser]. "Biogenic amines in the Drosophila melanogaster larval central nervous system : an anatomical and behavioural function description / Annina Maria Huser." Konstanz : Bibliothek der Universität Konstanz, 2018. http://d-nb.info/1162443855/34.

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Books on the topic "Huber function"

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Franzius, Claudio, Franz C. Mayer, and Jürgen Neyer, eds. Die Neuerfindung Europas. Nomos Verlagsgesellschaft mbH & Co. KG, 2019. http://dx.doi.org/10.5771/9783845292700.

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The volume summarises the contributions to the fourth conference of the Working Group "Law and Politics in the European Union", which was jointly organised with the Friedrich-Ebert-Stiftung in Berlin in April 2017. We started by investigating how narratives develop and what functions they have in the integration process. Does the "Europe of the Fatherlands" lead us into a European Union that is more strongly shaped by the national identity of the member states than before? What remains of the legal community? Is "peace" an outdated narrative? Why is it so difficult to reform the "Europe of wel
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Book chapters on the topic "Huber function"

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Castro, Jordi. "A CTA Model Based on the Huber Function." In Privacy in Statistical Databases. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11257-2_7.

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Puthiyottil, Anagha, S. Balasundaram, and Yogendra Meena. "L1-Norm Support Vector Regression in Primal Based on Huber Loss Function." In Proceedings of ICETIT 2019. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30577-2_16.

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Marino, Giuseppe. "Approximating Fixed Points For Nonexpansive Maps in Hubert Spaces." In Approximation Theory, Spline Functions and Applications. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2634-2_27.

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Albright, Thomas D. "Neuroscienze per l’architettura." In La mente in architettura. Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-286-7.12.

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Discusses the Indian design treatise the Vaastu Veda in relation to visual neuroscience. Relates visual perception in architecture to functional organisation of the brain. Relates Hubel and Weisel’s orientation sensitivity to the sense of order and pleasure imparted by the regularity of colonnades and cable stay bridges. Suggests aspects of perception facilitated by neuronal architecture and the dynamic between familiarity and novelty, plasticity and visual attunement.
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Lu, Zhao, and Jing Sun. "Soft-constrained Linear Programming Support Vector Regression for Nonlinear Black-box Systems Identification." In Artificial Intelligence for Advanced Problem Solving Techniques. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-705-8.ch005.

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As an innovative sparse kernel modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In the support vector regression, Vapnik developed the -insensitive loss function as a trade-off between the robust loss function of Huber and one that enables sparsity within the support vectors. The use of support vector kernel expansion provides us a potential avenue to represent nonlinear dynamical systems and underpin advanced analysis. However, in the standard quadratic programming support vector regression (QP-SVR), its implementation is more computationally expensive and enough model sparsity can not be guaranteed. In an attempt to surmount these drawbacks, this article focus on the application of soft-constrained linear programming support vector regression (LP-SVR) in nonlinear black-box systems identification, and the simulation results demonstrates that the LP-SVR is superior to QP-SVR in model sparsity and computational efficiency
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Scanlon, Sandra. "Every Way Out." In US Presidential Elections and Foreign Policy. University Press of Kentucky, 2017. http://dx.doi.org/10.5810/kentucky/9780813169057.003.0009.

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The prominence of foreign policy—specifically the Vietnam War—during the 1968 presidential election has long been recognized by scholars. This chapter examines the campaigns of the three presidential candidates and argues that Richard Nixon framed his foreign policies in terms of widely shared concepts of American national identity. Unlike Hubert Humphrey, Nixon actively utilized positive polarization and framed the Vietnam War as an American domestic struggle rather than as an international one. During the final weeks of the campaign, Nixon’s message on foreign policy and his championing of law and order were thereby reconciled. This campaigning style redefined the function of foreign policy during presidential elections and presented Nixon with a far greater ideological triumph than his narrow victory would suggest.
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"Generalization Performance of Some Learning Problems in Hubert Functional Spaces." In Advances in Neural Information Processing Systems 14. The MIT Press, 2002. http://dx.doi.org/10.7551/mitpress/1120.003.0074.

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Inkpin, Andrew. "Phenomenology and Semantics." In Disclosing the World. The MIT Press, 2016. http://dx.doi.org/10.7551/mitpress/9780262033916.003.0010.

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This chapter focuses on Heidegger’s claim (chapter 2) that propositional content has a prepredicative foundation to assess the relationship between a phenomenological approach to language and standard semantics-based approaches that assume the primacy of propositional content. Having clarified the distinction between these two approaches and various possibilities for interpreting Heidegger’s claim, it argues against a weak foundation claim, according to which prepredicative factors do not affect the philosophical adequacy of the semantic notions of propositional and conceptual content, and instead defends a stronger claim – ‘moderate’ functional foundation – based on differences in the functioning of prepredicative factors and semantic properties. This claim is then situated in the context of a debate between Hubert Dreyfus and John McDowell about the role of concepts in prereflective intelligence, in which it offers a midway between their respective extremes of nonconceptual coping and pervasive conceptualism.
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Holland, Barbara Jane. "Libraries in the Midst of the COVID-19 Pandemic." In Advances in Library and Information Science. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6449-3.ch007.

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The South China Morning Post reported China's first confirmed COVID-19 case may be traced as early as November 17, 2019. On December 8, 2019, Wuhan, China had its first patient with symptoms similar to coronavirus. The disease was believed to have emerged in the Huanan seafood market. By December 15, the total number of infections stood at 27—the first double-digit daily rise was reported on December 17—and by December 20, the total number of confirmed cases had reached 60. December 31, 2019, China informs the World Health Organization (WHO) about a cluster of cases of pneumonia in Wuhan, Hubei Province. The virus is still not understood. March 11, 2020, the WHO assesses that COVID-19 can be officially described as a pandemic due to the rapid increase in the number of cases outside China. As coronavirus cases began to skyrocket, libraries had to function in unique situations. The purpose of this chapter is to provide an in-depth review of libraries and case studies amid the COVID 19 pandemic.
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Conference papers on the topic "Huber function"

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Guitton, Antoine, and William W. Symes. "Robust and stable velocity analysis using the Huber function." In SEG Technical Program Expanded Abstracts 1999. Society of Exploration Geophysicists, 1999. http://dx.doi.org/10.1190/1.1820710.

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Xin, Lei, Feng Li, Xue Yang, Shijie Sun, Yu Zhou, and Zhijia Liu. "A Huber Function based Restoration Algorithm for Astronomy Image Compression." In 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2021. http://dx.doi.org/10.1109/i2mtc50364.2021.9459970.

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Khammar, Amirhamzeh, Mohsen Arefi, and Mohammad Ghasem Akbari. "Robust fuzzy varying coefficient regression model based on Huber loss function." In 2020 8th Iranian Joint Congress on Fuzzy and intelligent Systems (CFIS). IEEE, 2020. http://dx.doi.org/10.1109/cfis49607.2020.9238742.

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Wang, Zenghan, Dan Li, Sirui Wu, Yue Huang, Zan Yang, and Wei Nai. "Huber Loss Function Based on Cockroach Swarm Algorithm with T-Distribution Parameters." In 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2021. http://dx.doi.org/10.1109/iaeac50856.2021.9390734.

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Zhang, Zhenyuan, Haoran Chen, Yuxiang Huang, and Wei-Jen Lee. "Quantile Huber Function Guided TCN for Short-Term Consumer-Side Probabilistic Load Forecasting." In 2020 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia). IEEE, 2020. http://dx.doi.org/10.1109/icpsasia48933.2020.9208545.

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Chreiky, Robert, Gilles Delmaire, Matthieu Puigt, Gilles Roussel, and Antoine Abche. "Informed Split Gradient Non-negative Matrix factorization using Huber cost function for source apportionment." In 2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2016. http://dx.doi.org/10.1109/isspit.2016.7886011.

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Ma, Shuang, Dan Li, Tingiuan Hu, Yidan Xing, Zan Yang, and Wei Nai. "Huber Loss Function Based on Variable Step Beetle Antennae Search Algorithm with Gaussian Direction." In 2020 12th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). IEEE, 2020. http://dx.doi.org/10.1109/ihmsc49165.2020.00062.

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Geebelen, K., A. Wagner, S. Gros, J. Swevers, and M. Diehl. "Moving Horizon Estimation with a huber penalty function for robust pose estimation of tethered airplanes." In 2013 American Control Conference (ACC). IEEE, 2013. http://dx.doi.org/10.1109/acc.2013.6580805.

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Thakulsukanant, Kornkamol, and Vorapoj Patanavijit. "An alternative single-image super resolution framework employing high frequency prediction using a robust huber rational function." In 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS). IEEE, 2015. http://dx.doi.org/10.1109/iciibms.2015.7439537.

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Gros, Sebastien, and Moritz Diehl. "NMPC based on Huber penalty functions to handle large deviations of quadrature states." In 2013 American Control Conference (ACC). IEEE, 2013. http://dx.doi.org/10.1109/acc.2013.6580317.

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