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The damage and fracture of materials are technologically of enormous interest due to their economic and human cost. They cover a wide range of phenomena like e.g. cracking of glass, aging of concrete, the failure of fiber networks in the…

Materials Science · Physics 2015-06-24 D. Sornette

In this review article, we discuss connections between the physics of disordered systems, phase transitions in inference problems, and computational hardness. We introduce two models representing the behavior of glassy systems, the spiked…

Disordered Systems and Neural Networks · Physics 2022-12-07 David Gamarnik , Cristopher Moore , Lenka Zdeborová

This work is devoted to the formulation and derivation of the $\alpha{-}\kappa{-}\mu{/}$gamma distribution which corresponds to a physical fading model. The proposed distribution is composite and is constituted by the…

Information Theory · Computer Science 2015-05-15 Paschalis C. Sofotasios , Steven Freear

A slender thread of elastic hydrogel is susceptible to a surface instability that is reminiscent of the classical Rayleigh-Plateau instability of liquid jets. The final, highly nonlinear states that are observed in experiments arise from a…

Soft Condensed Matter · Physics 2020-12-16 Anupam Pandey , Minkush Kansal , Miguel A. Herrada , Jens Eggers , Jacco H. Snoeijer

Metastable failure is a recent abstraction of a pattern of failures that occurs frequently in real-world distributed storage systems. In this paper, we propose a formal analysis and modeling of metastable failures in replicated storage…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-16 Farzad Habibi , Tania Lorido-Botran , Ahmad Showail , Daniel C. Sturman , Faisal Nawab

A new portmanteau test statistic is proposed for detecting nonlinearity in time series data. In this paper, we elaborate on the Toeplitz autocorrelation matrix to the autocorrelation and cross-correlation of residuals and squared residuals…

Statistics Theory · Mathematics 2022-09-01 Esam Mahdi , Thomas J. Fisher

A novel data-driven constitutive modeling approach is proposed, which combines the physics-informed nature of modeling based on continuum thermodynamics with the benefits of machine learning. This approach is demonstrated on…

Computational Engineering, Finance, and Science · Computer Science 2023-04-28 Kshitiz Upadhyay , Jan N. Fuhg , Nikolaos Bouklas , K. T. Ramesh

In this paper, a generalization for the Birnbaum Saunders distribution, which has been applied to the modelling of fatigue failure times and reliability studies, is considered. The maximum likelihood estimators and statistical inference for…

Statistics Theory · Mathematics 2021-09-06 Beenu Thomas , Chacko V M

Despite enormous efforts over the last decades to establish the relationship between concrete proportioning and strength, a robust knowledge-based model for accurate concrete strength predictions is still lacking. As an alternative to…

Machine Learning · Computer Science 2020-05-01 Boya Ouyang , Yuhai Li , Yu Song , Feishu Wu , Huizi Yu , Yongzhe Wang , Mathieu Bauchy , Gaurav Sant

A test of the null hypothesis that a hazard rate is monotone nondecreasing, versus the alternative that it is not, is proposed. Both the test statistic and the means of calibrating it are new. Unlike previous approaches, neither is based on…

Statistics Theory · Mathematics 2007-06-13 Peter Hall , Ingrid Van Keilegom

This paper investigates correlation properties of fluctuations in fatigue crack growth of polycrystalline materials, such as ductile alloys, that are commonly encountered in structures and machinery components of complex electromechanical…

Materials Science · Physics 2015-06-25 Nicola Scafetta , Asok Ray , Bruce J. West

Scientific applications typically generate large volumes of floating-point data, making lossy compression one of the most effective methods for data reduction, thereby lowering storage requirements and improving performance in large-scale…

Performance · Computer Science 2024-12-11 Youyuan Liu , Taolue Yang , Sian Jin

Spatiotemporal data analysis is pivotal across various domains, such as transportation, meteorology, and healthcare. The data collected in real-world scenarios are often incomplete due to device malfunctions and network errors.…

Machine Learning · Computer Science 2024-03-25 Yakun Chen , Kaize Shi , Zhangkai Wu , Juan Chen , Xianzhi Wang , Julian McAuley , Guandong Xu , Shui Yu

Recordings of complex neural population responses provide a unique opportunity for advancing our understanding of neural information processing at multiple scales and improving performance of brain computer interfaces. However, most…

Neurons and Cognition · Quantitative Biology 2022-07-12 Lazaros Mitskopoulos , Theoklitos Amvrosiadis , Arno Onken

This article deals with the multiscale modeling of stress transfer characteristics of nano-reinforced polymer composite reinforced with regularly staggered carbon fibers. The distinctive feature of construction of nano-reinforced composite…

Materials Science · Physics 2017-02-06 S. I. Kundalwal , S. A. Meguid

In this article, we propose a data-driven methodology for combining the solutions of a set of competing turbulence models. The individual model predictions are linearly combined for providing an ensemble solution accompanied by estimates of…

Fluid Dynamics · Physics 2023-01-24 Maximilien de Zordo-Banliat , Grégory Dergham , Xavier Merle , Paola Cinnella

The general fluctuation theory is reviewed with special attention to the role played by different ensembles, and is extended to incorporate stationary metastable states obtained in the long time limit. The fluctuation in a quantity depends…

Statistical Mechanics · Physics 2007-05-23 P. D. Gujrati

Fiber bundle models (FBM's) have been used to model the failure of fibrous composites as load-sharing systems since the 1960's when Rosen (1964 and 1965) conducted some remarkable experiments on unidirectional fibrous composites. These…

Applications · Statistics 2019-03-07 Shuang Li , James Lynch

A framework for the generation of bridge-specific fragility utilizing the capabilities of machine learning and stripe-based approach is presented in this paper. The proposed methodology using random forests helps to generate or update…

Computational Engineering, Finance, and Science · Computer Science 2018-07-27 Sujith Mangalathu , Jong-Su Jeon

Data imbalance in training data often leads to biased predictions from trained models, which in turn causes ethical and social issues. A straightforward solution is to carefully curate training data, but given the enormous scale of modern…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Moon Ye-Bin , Nam Hyeon-Woo , Wonseok Choi , Nayeong Kim , Suha Kwak , Tae-Hyun Oh
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