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Recent advances in Structural Health Monitoring (SHM) have attracted industry interest, yet real-world applications, such as in ship structures remain scarce. Despite SHM's potential to optimise maintenance, its adoption in ships is limited…

Applications · Statistics 2026-04-17 Nicholas E. Silionis , Konstantinos N. Anyfantis

Seismic inversion is essential for geophysical exploration and geological assessment, but it is inherently subject to significant uncertainty. This uncertainty stems primarily from the limited information provided by observed seismic data,…

Geophysics · Physics 2024-09-12 Luping Qu , Mauricio Araya-Polo , Laurent Demanet

In recent years, Full-Waveform Inversion (FWI) has been extensively used to derive high-resolution subsurface velocity models from seismic data. However, due to the nonlinearity and ill-posed nature of the problem, FWI requires a good…

Fuzzy rule-based model is a powerful tool for imitating the human way of thinking and solving uncertainty-related problems as it allows for understandable and interpretable rule bases. The objective of this paper is to study the…

Artificial Intelligence · Computer Science 2020-06-16 Sujatha A , L Govindaraju , N Shivakumar

Insurance products frequently cover significant claims arising from a variety of sources. To model losses from these products accurately, actuarial models must account for high-severity claims. A widely used strategy is to apply a mixture…

Methodology · Statistics 2025-04-30 Sébastien Jessup , Mélina Mailhot , Mathieu Pigeon

Seismic full waveform inversion (FWI) is a powerful technique to generate high resolution images of the Earth's interior. However, significant uncertainty exists in all FWI solutions due to imperfect acquisition geometries, inherent noise…

Geophysics · Physics 2026-03-13 Xuebin Zhao , Andrew Curtis

This paper develops a multifidelity method that enables estimation of failure probabilities for expensive-to-evaluate models via information fusion and importance sampling. The presented general fusion method combines multiple probability…

This paper provides a new tool for multi-attribute multi-objective group decision-making with unknown weights and attributes' weights. An interval-valued generalized orthogonal fuzzy group decision-making method is proposed based on the…

Artificial Intelligence · Computer Science 2022-01-05 Benting Wan , Shufen Zhou

Instrumental variable methods are among the most commonly used causal inference approaches to deal with unmeasured confounders in observational studies. The presence of invalid instruments is the primary concern for practical applications,…

Methodology · Statistics 2023-04-18 Zijian Guo

We study the problem of statistically certifying viable initial sets (VISs) -- sets of initial conditions whose trajectories satisfy a given control specification. While VISs can be obtained from model-based methods, these methods typically…

Systems and Control · Electrical Eng. & Systems 2026-04-06 Elizabeth Dietrich , Hanna Krasowski , Vegard Flovik , Murat Arcak

In this paper, a new method based on TOPSIS and optimization models is proposed for multi-attribute group decision-making in the environment of interval-valued intuitionistic fuzzy sets.Firstly, by minimizing the sum of differences between…

Artificial Intelligence · Computer Science 2023-11-28 Qixiao Hu , Shiquan Zhang , Chaolang Hu , Yuetong Liu

This paper proposes a robust method for fault detection and severity estimation in multivariate time-series data to enhance predictive maintenance of mechanical systems. We use the Temporal Graph Convolutional Network (T-GCN) model to…

Systems and Control · Electrical Eng. & Systems 2025-04-07 Youngjae Jeon , Eunho Heo , Jinmo Lee , Taewon Uhm , Dongjin Lee

Fuzzy Cognitive Maps (FCMs) are considered a soft computing technique combining elements of fuzzy logic and recurrent neural networks. They found multiple application in such domains as modeling of system behavior, prediction of time…

Machine Learning · Computer Science 2021-03-16 Piotr Szwed

The rapid evolution of software development necessitates enhanced safety measures. Extracting information about software failures from companies is becoming increasingly more available through news articles. This research utilizes the…

Software Engineering · Computer Science 2024-08-09 Martin Detloff

Software vulnerabilities are commonly exploited as attack vectors in cyberattacks. Hence, it is crucial to identify vulnerable software configurations early to apply preventive measures. Effective vulnerability detection relies on…

Cryptography and Security · Computer Science 2024-12-24 Devesh Sawant , Manjesh K. Hanawal , Atul Kabra

This study implements a novel Fuzzy Cognitive Map (FCM) framework for addressing large complex socio-ecological problems. These are characterized as qualitative, dominated by uncertainty, human involvement with different and vague…

Social and Information Networks · Computer Science 2022-08-11 Mamoon Obiedat , Sandhya Samarasinghe

As cyber threats become more sophisticated, rapid and accurate vulnerability detection is essential for maintaining secure systems. This study explores the use of Large Language Models (LLMs) in software vulnerability assessment by…

Cryptography and Security · Computer Science 2025-06-13 David Farr , Kevin Talty , Alexandra Farr , John Stockdale , Iain Cruickshank , Jevin West

The field of intelligent connected in modern vehicles continues to expand, and the functions of vehicles become more and more complex with the development of the times. This has also led to an increasing number of vehicle vulnerabilities…

Artificial Intelligence · Computer Science 2026-02-27 Tian Zhang , Wenshan Guan , Hao Miao , Xiujie Huang , Zhiquan Liu , Chaonan Wang , Quanlong Guan , Liangda Fang , Zhifei Duan

In line with the IEC 61508 functional safety standard, it is required to assess the safety integrity of a system due to random hardware failures. For a rarely used function (operating in a low demand mode), the measurement used is average…

Probability · Mathematics 2015-01-21 F Brissaud , B Declerck

We aim to create the highest possible quality of treatment-control matches for categorical data in the potential outcomes framework. Matching methods are heavily used in the social sciences due to their interpretability, but most matching…

Machine Learning · Statistics 2019-06-11 Yameng Liu , Aw Dieng , Sudeepa Roy , Cynthia Rudin , Alexander Volfovsky