Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Radiation Dose and Imaging
Abstract
This comprehensive review provides a detailed analysis of the 50 mSv annual occupational radiation dose limit as codified in the U.S. Nuclear Regulatory Commission (NRC) regulation 10 C.F.R. § 20.1201(a)(i). The paper traces the historical development of radiation protection standards from the early 20th century to the present, explaining the evolution from tolerance doses to the current system of dose limits based on stochastic and deterministic risk. It examines the physical and biological basis of dose limits, including the concepts of Total Effective Dose Equivalent (TEDE), committed dose, and the distinction between whole-body and organ-specific limits. The review provides a detailed comparison between the U.S. NRC limit of 50 mSv per year and the international recommendations of the International Commission on Radiological Protection (ICRP) and the International Atomic Energy Agency (IAEA), which recommend a 5‑year average of 20 mSv per year with a maximum of 50 mSv in any single year. The paper discusses the ALARA principle, dose reduction strategies, recordkeeping requirements, and the implications for health physics practice. It also addresses criticisms of the current system and considers future directions for occupational dose limits in light of emerging scientific evidence on low-dose radiation effects and the increasing use of AI and automation in radiation monitoring.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
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