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Related papers: Developing a Quantitative Resiliency Approach

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Maintaining stability in feedback systems, from aircraft and autonomous robots to biological and physiological systems, relies on monitoring their behavior and continuously adjusting their inputs. Incremental damage can make such control…

Software reliability is an important quality attrib-ute, often evaluated as either a function of time or of system structures. The goal of this study is to have this metric cover both for component-based software, be-cause its reliability…

Software Engineering · Computer Science 2007-05-23 Wen-Li Wang , Mei-Huei Tang

The purpose of the research presented in this article is to develop a dynamic system for forecasting and minimizing the risks of an industrial company based on their quantitative assessment. The article considers the conceptual apparatus of…

Risk Management · Quantitative Finance 2022-02-02 Denis S. Gusev , Elena G. Demidova , Olga A. Novikova

This work proposes a novel theoretical framework of robust limit analysis i.e. the computation of limit loads of structures in presence of uncertainties using limit analysis and robust optimization theories. We first derive generic robust…

Optimization and Control · Mathematics 2022-03-23 Jeremy Bleyer , Vincent Leclère

Reliable operation is a central motivation for deploying renewable-based microgrids. This paper presents a systematic rapid review that positions reliability as the central organizing principle for microgrid design. Specifically, this…

Optimization and Control · Mathematics 2026-04-23 Mohammed Zeehan Saleheen , Markus Wagner , Reza Razzaghi , Hao Wang

We discuss recent work for causal inference and predictive robustness in a unifying way. The key idea relies on a notion of probabilistic invariance or stability: it opens up new insights for formulating causality as a certain risk…

Methodology · Statistics 2018-12-21 Peter Bühlmann

We consider two approaches for assessing the reliability of the individual predictions of a classifier: Robustness Quantification (RQ) and Uncertainty Quantification (UQ). We explain the conceptual differences between the two approaches,…

Machine Learning · Computer Science 2026-03-25 Adrián Detavernier , Jasper De Bock

Enterprise engagement with open source has evolved from tactical adoption to strategic deep integration, exposing them to a complex risk landscape far beyond mere code. However, traditional risk management, narrowly focused on technical…

Software Engineering · Computer Science 2025-11-03 Wenhao Yang , Minghui Zhou , Daniel Izquierdo Cortázar , Yehui Wang

The design and operation of protective systems is an essential engineering responsibility. Ensuring public safety, while essential, must be accomplished at a feasible cost and within government regulation. Hence, protective system design…

Systems and Control · Electrical Eng. & Systems 2020-10-20 Martin Wortman , Ernest Kee , Pranav Kannan

IT Governance systems are increasingly required to keep todays organizations functioning. IT Governance requires a holistic system of interacting components, including processes, organizational structures, information, and others.…

Software Engineering · Computer Science 2024-05-09 Dirk Steuperaert , Geert Poels , Jan Devos

There is a constraining relation between the reliability of a quantum measurement and the extent to which the measurement process is, in principle, reversible. The greater the information that is gained, the less reversible the measurement…

Quantum Physics · Physics 2009-01-09 S. J. van Enk , M. G. Raymer

Uncertainty is prevalent in engineering design, data-driven problems, and decision making broadly. Due to inherent risk-averseness and ambiguity about assumptions, it is common to address uncertainty by formulating and solving conservative…

Optimization and Control · Mathematics 2024-04-05 Johannes O. Royset

Security assessment of large-scale, strongly nonlinear power grids containing thousands to millions of interacting components is a computationally expensive task. Targeting at reducing the computational cost, this paper introduces a…

Systems and Control · Computer Science 2017-11-01 Thanh Long Vu , Konstantin Turitsyn

Distribution grid reliability and resilience has become a major topic of concern for utilities and their regulators. In particular, with the increase in severity of extreme events, utilities are considering major investments in distribution…

Optimization and Control · Mathematics 2023-06-13 Alexandre Moreira , Miguel Heleno , Alan Valenzuela , Joseph H. Eto , Jaime Ortega , Cristina Botero

Hardware vulnerabilities are generally considered more difficult to fix than software ones because they are persistent after fabrication. Thus, it is crucial to assess the security and fix the vulnerabilities at earlier design phases, such…

The increasing reliance on AI-driven 5G/6G network infrastructures for mission-critical services highlights the need for reliability and resilience against sophisticated cyber-physical threats. These networks are highly exposed to novel…

Due to the variety of corporate risks in turmoil markets and the consequent financial distress especially in COVID-19 time, this paper investigates corporate resilience and compares different types of resilience that can be potential…

Risk Management · Quantitative Finance 2024-03-26 Elham Daadmehr

Active cyber defenses based on temporal platform diversity have been proposed as way to make systems more resistant to attacks. These defenses change the properties of the platforms in order to make attacks more complicated. Unfortunately,…

Cryptography and Security · Computer Science 2014-02-03 Kevin M. Carter , Hamed Okhravi , James Riordan

Reliability of complex Cyber-Physical Systems is necessary to guarantee availability and/or safety of the provided services. Diverse and complex fault tolerance policies are adopted to enhance reliability, that include a varied mix of…

Software Engineering · Computer Science 2022-08-26 Alessandro Fantechi , Gloria Gori , Marco Papini

Critical infrastructure increasingly incorporates embodied AI for monitoring, predictive maintenance, and decision support. However, AI systems designed to handle statistically representable uncertainty struggle with cascading failures and…

Artificial Intelligence · Computer Science 2026-03-18 Puneet Sharma , Christer Henrik Pursiainen
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