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There are limitations of traditional methods and deep learning methods in terms of interpretability, generalization, and quantification of uncertainty in industrial fault diagnosis, and there are core problems of insufficient credibility in…

Systems and Control · Electrical Eng. & Systems 2025-10-07 Yue wu

We propose a symbolic execution method for analyzing the safety of software under fault attacks both accurately and efficiently. Fault attacks leverage physically injected hardware faults in an embedded system to break the safety of a…

Software Engineering · Computer Science 2026-04-27 Yuzhou Fang , Chenyu Zhou , Jingbo Wang , Chao Wang

Empathetic Conversational Systems (ECS) are built to respond empathetically to the user's emotions and sentiments, regardless of the application domain. Current ECS studies evaluation approaches are restricted to offline evaluation…

Computation and Language · Computer Science 2024-07-29 Aravind Sesagiri Raamkumar , Siyuan Brandon Loh

The mutations of a complex systemic disease like cancer can be modeled as stuck-at faults in the Boolean system paradigm. For a class of multiple faults, the fault identification is exceptionally significant under the incomplete access of…

Systems and Control · Computer Science 2018-09-11 Anuj Deshpande , Ritwik Kumar Layek

This paper presents adaptive conformal selection (ACS), an interactive framework for model-free selection with guaranteed error control. Building on conformal selection (Jin and Cand\`es, 2023b), ACS generalizes the approach to support…

Methodology · Statistics 2025-07-22 Yu Gui , Ying Jin , Yash Nair , Zhimei Ren

Self-adaptive systems are expected to mitigate disruptions by continually adjusting their configuration and behaviour. This mitigation is often reactive. Typically, environmental or internal changes trigger a system response only after a…

Software Engineering · Computer Science 2022-05-10 Xinwei Fang , Radu Calinescu , Colin Paterson , Julie Wilson

In healthcare and biomedical applications, extreme computational requirements pose a significant barrier to adopting representation learning. Representation learning can enhance the performance of deep learning architectures by learning…

Machine Learning · Computer Science 2023-08-22 Pranav Singh , Jacopo Cirrone

Fully autonomous vehicles (AVs), i.e., AVs with autonomy level 5, are expected to dominate road transportation in the near-future and contribute trillions of dollars to the global economy. The general public, government organizations, and…

Software Engineering · Computer Science 2019-07-03 Saurabh Jha , Timothy Tsai , Siva Hari , Michael Sullivan , Zbigniew Kalbarczyk , Stephen W. Keckler , Ravishankar K. Iyer

Software systems are increasingly used in application domains characterised by uncertain environments, evolving requirements and unexpected failures; sudden system malfunctioning raises serious issues of security, safety, loss of comfort or…

Software Engineering · Computer Science 2019-04-04 Simos Gerasimou , Thomas Vogel , Ada Diaconescu

The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Systems Engineering (EDSE). While this "digital thread" has the potential to drive innovation, the…

Software Engineering · Computer Science 2026-03-19 H. Sinan Bank , Daniel R. Herber

Multi-agent LLM systems are increasingly used to solve complex tasks through decomposition, debate, specialization, and ensemble reasoning. However, these systems are usually evaluated in terms of robustness: whether performance is…

Multiagent Systems · Computer Science 2026-05-07 Jose Manuel de la Chica , Juan Manuel Vera , Jairo Rodríguez

The Internet of Things (IoT) connects millions of devices of different cyber-physical systems (CPSs) providing the CPSs additional (implicit) redundancy during runtime. However, the increasing level of dynamicity, heterogeneity, and…

Systems and Control · Computer Science 2019-03-12 Denise Ratasich , Michael Platzer , Radu Grosu , Ezio Bartocci

The rise of the Internet of Things and Cyber-Physical Systems has introduced new challenges on ensuring secure and robust communication. The growing number of connected devices increases network complexity, leading to higher latency and…

Cryptography and Security · Computer Science 2025-09-03 Marco Stadler , Michael Vierhauser , Michael Riegler , Daniel Waghubinger , Johannes Sametinger

Modern cloud-native systems require adapting dynamically to changing operational conditions, including service outages, traffic surges, and evolving user requirements. While existing benchmarks provide valuable testbeds for performance and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-30 Simon Bliudze , Giuseppe De Palma , Saverio Giallorenzo , Ivan Lanese , Gianluigi Zavattaro , Brice Arléon Zemtsop Ndadji

A three species food chain model is studied analytically as well as numerically. Integrability of the model is studied using Painleve analysis while chaotic behaviour is studied using numerical techniques, such as calculation of Lyapunov…

chao-dyn · Physics 2008-02-03 M. P. Joy

This paper presents a method for performing Uncertainty Quantification in high-dimensional uncertain spaces by combining arbitrary polynomial chaos with a recently proposed scheme for sensitivity enhancement (1). Including available…

Numerical Analysis · Mathematics 2024-02-09 Nick Pepper , Francesco Montomoli , Kyriakos Kantarakias

Many software engineering techniques, such as fault localization, operate based on relevance relationships between tests and code. These relationships are often inferred through the use of dynamic test execution information (test execution…

Software Engineering · Computer Science 2022-03-23 Jeongju Sohn , Mike Papadakis

Self-adaptive systems (SASs) adjust their behavior at runtime in response to internal or external change. The MAPE-K model, which includes Monitors, Analyzers, Planners, Executors, and shared Knowledge, is a reference for structuring…

Software Engineering · Computer Science 2025-09-15 Daniel San Martín , Guisella Angulo , Valter Vieira de Camargo

Sensor technology developments provide a basis for effective fault diagnosis in manufacturing systems. However, the limited number of sensors due to physical constraints or undue costs hinders the accurate diagnosis in the actual process.…

Machine Learning · Computer Science 2023-10-26 Jihoon Chung , Zhenyu Kong

Trustworthiness in neural networks is crucial for their deployment in critical applications, where reliability, confidence, and uncertainty play pivotal roles in decision-making. Traditional performance metrics such as accuracy and…

Machine Learning · Computer Science 2025-09-05 Koffi Ismael Ouattara , Ioannis Krontiris , Theo Dimitrakos , Frank Kargl
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