kerostig | Tag : reliability https://kerostig.org/tag/reliability/ Derniers appels à publications avec le tag 'reliability'. Mon, 05 Oct 2026 10:15:16 GMT https://validator.w3.org/feed/docs/rss2.html https://github.com/jpmonette/feed fr kerostig | Tag : reliability https://kerostig.org/public/favicon/android-chrome-96x96.png https://kerostig.org/tag/reliability/ Notices : kerostig © 2026. Le texte des appels appartient à leurs éditeurs. <![CDATA[Reliable and Trustworthy Automated Software Engineering]]> https://kerostig.org/call/elsevier-reliable-and-trustworthy-automated-software-engineering/ elsevier-reliable-and-trustworthy-automated-software-engineering Wed, 30 Sep 2026 23:00:11 GMT

This special issue focuses on automated software engineering approaches that prioritize reliability and trustworthiness. The collection aims to bring together research addressing the challenges of developing software engineering tools and techniques that can be confidently relied upon in practice.

Appel publié par Journal of Systems and Software. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

  • May 31, 2027: Submission deadline
]]> <![CDATA[AI Techniques for Performance, Reliability, and Sustainability of Modern Software Systems]]> https://kerostig.org/call/elsevier-ai-techniques-for-performance-reliability-and-sustainability-of-modern-software-systems/ elsevier-ai-techniques-for-performance-reliability-and-sustainability-of-modern-software-systems Sun, 06 Sep 2026 09:51:06 GMT

This special issue invites research on the application of artificial intelligence methods to improve key aspects of modern software systems. The focus encompasses using AI to enhance system performance, increase reliability, and promote sustainability in software engineering and operations.

Appel publié par Journal of Systems and Software. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

  • September 30, 2026: Submission deadline
]]> <![CDATA[Advances in Reliability and Statistical Computing for Intelligent Systems]]> https://kerostig.org/call/springer-advances-in-reliability-and-statistical-computing-for-intelligent-systems/ springer-advances-in-reliability-and-statistical-computing-for-intelligent-systems Tue, 11 Aug 2026 21:25:02 GMT

Hoang Pham, Rutgers University

The special issue addresses the growing importance of reliability and statistical computing in artificial intelligence systems used in everyday applications and service industries. It seeks contributions covering both theoretical advances and practical implementations in these areas, with emphasis on papers demonstrating real-world applicability.

The special issue welcomes research on mathematical and statistical methods for reliability, machine learning approaches for intelligent systems, big data analysis techniques, and system dependability measures. Industrial applications are particularly valued, including case studies from fields such as robotics, healthcare, education, surveillance, and transportation.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

  • Mathematical reliability and statistical methods
  • Big data modeling and prediction
  • Statistical learning algorithms, models, and theories
  • Machine learning models for intelligent systems
  • Text mining and deep machine learning
  • Intelligent system dependability and performability
  • Reliability modeling and optimization
  • High-dimensional data analysis
  • Statistical inference for intelligent systems
  • Industrial case studies in intelligent systems

Timeline

  • October 30, 2026: Submission deadline
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