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Time Series Forecasting is at the core of many practical applications such as sales forecasting for business, rainfall forecasting for agriculture and many others. Though this problem has been extensively studied for years, it is still…

Machine Learning · Computer Science 2020-03-23 Anirban Chatterjee , Subhadip Paul , Uddipto Dutta , Smaranya Dey

Road accidents have become the eight leading cause of death all over the world. Lots of these accidents are due to a driver's inattention or lack of focus, due to fatigue. Various factors cause driver's fatigue. This paper considers all the…

Artificial Intelligence · Computer Science 2022-09-01 Alexandre Lambert , Manolo Dulva Hina , Celine Barth , Assia Soukane , Amar Ramdane-Cherif

The mathematical formulation of constitutive models to describe the path-dependent, i.e., inelastic, behavior of materials is a challenging task and has been a focus in mechanics research for several decades. There have been increased…

Computational Engineering, Finance, and Science · Computer Science 2023-09-06 Max Rosenkranz , Karl A. Kalina , Jörg Brummund , Markus Kästner

Load forecasts have become an integral part of energy security. Due to the various influencing factors that can be considered in such a forecast, there is also a wide range of models that attempt to integrate these parameters into a system…

Machine Learning · Computer Science 2022-10-19 Philipp Giese

A recent development which is poised to disrupt current structural engineering practice is the use of data obtained from physical structures such as bridges, viaducts and buildings. These data can represent how the structure responds to…

Applications · Statistics 2019-06-26 Alastair Gregory , Din-Houn Lau , Mark Girolami , Liam Butler , Mohammed Elshafie

Assessing the progression of muscle fatigue for daily exercises provides vital indicators for precise rehabilitation, personalized training dose, especially under the context of Metaverse. Assessing fatigue of multi-muscle…

Human-Computer Interaction · Computer Science 2024-12-03 Chunzhi Yi , Xiaolei Sun , Chunyu Zhang , Wei Jin , Jianfei Zhu , Haiqi Zhu , Baichun Wei

Scientific machine learning is increasingly used to build surrogate models, yet most models are trained under a restrictive assumption in which future data follow the same distribution as the training set. In practice, new experimental…

Machine Learning · Computer Science 2026-04-20 Mahmoud Elhadidy , Roshan M. D'Souza , Amirhossein Arzani

Cutting mechanics in soft solids have been a subject of study for several decades, an interest fuelled by the multitude of its applications, including material testing, manufacturing, and biomedical technology. Wire cutting is the simplest…

Soft Condensed Matter · Physics 2023-10-31 Bharath Antarvedi Goda , David Labonte , Mattia Bacca

Stress-strain curves, or more generally, stress functions, are an extremely important characterization of a material's mechanical properties. However, stress functions are often difficult to derive and are narrowly tailored to a specific…

Materials Science · Physics 2023-12-21 Garrett Blum , Ryan Doris , Diego Klabjan , Horacio Espinosa , Ron Szalkowski

Regression methods dominate the practice of biostatistical analysis, but biostatistical training emphasises the details of regression models and methods ahead of the purposes for which such modelling might be useful. More broadly,…

Methodology · Statistics 2024-09-12 John B. Carlin , Margarita Moreno-Betancur

The failure of overhead transmission lines in the United States can lead to significant economic losses and widespread blackouts, affecting the lives of millions. This study focuses on the reliability of transmission lines, specifically…

Numerical Analysis · Mathematics 2024-07-01 Prakash KC , Maryam Naghibolhosseini , Mohsen Zayernouri

Injuries to the lower extremity joints are often debilitating, particularly for professional athletes. Understanding the onset of stressful conditions on these joints is therefore important in order to ensure prevention of injuries as well…

Statistics Theory · Mathematics 2024-04-25 Patrick Bastian , Rupsa Basu , Holger Dette

This paper proposes a multitask learning framework for probabilistic model updating by jointly using strain and acceleration measurements. This framework can enhance the structural damage assessment and response prediction of existing steel…

Applications · Statistics 2024-02-01 Taro Yaoyama , Tatsuya Itoi , Jun Iyama

In a recent very interesting and illuminating proposal, Yao et al. (2014) have discussed the use of the strain energy release rate (SERR) as a parameter to characterize fatigue delamination growth in composite materials. They consider…

Materials Science · Physics 2020-12-08 M. Ciavarella , A. Papangelo , G. Cricri

The modeling of cascading failure in power systems is difficult because of the many different mechanisms involved; no single model captures all of these mechanisms. Understanding the relative importance of these different mechanisms is an…

Physics and Society · Physics 2016-11-17 Jiajia Song , Eduardo Cotilla-Sanchez , Goodarz Ghanavati , Paul D. H. Hines

Meta-analytic methods may be used to combine evidence from different sources of information. Quite commonly, the normal-normal hierarchical model (NNHM) including a random-effect to account for between-study heterogeneity is utilized for…

Methodology · Statistics 2020-02-25 Christian Röver , Tim Friede

We introduce a general framework for leveraging graph stream data for temporal prediction-based applications. Our proposed framework includes novel methods for learning an appropriate graph time-series representation, modeling and weighting…

Machine Learning · Computer Science 2020-09-22 Di Jin , Sungchul Kim , Ryan A. Rossi , Danai Koutra

Within the continuous endeavour of improving the efficiency and resilience of air transport, the trend of using concepts and metrics from statistical physics has recently gained momentum. This scientific discipline, which integrates…

Data Analysis, Statistics and Probability · Physics 2025-07-29 Felipe Olivares , Massimiliano Zanin

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-the-meter distributed energy resource system to sustain a site's…

Systems and Control · Electrical Eng. & Systems 2021-06-29 Sakshi Mishra , Kate Anderson

As a specific proportional hazard rates model, sequential order statistics can be used to describe the lifetimes of load-sharing systems. Inference for these systems needs to account for small sample sizes, which are prevalent in…

Methodology · Statistics 2019-09-17 Fabian Mies , Stefan Bedbur
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