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Applied Sciences
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Advances in Cognitive Systems Applications
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Advances in Cognitive Systems Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 November 2022) | Viewed by 2631

Special Issue Editor

Prof. Dr. Dong-Han Ham

E-Mail Website
Guest Editor
Department of Industrial Engineering, Chonnam National University, Gwangju 61186, Republic of Korea
Interests: cognitive systems engineering; human–computer interaction; system safety engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues，

Cognitive engineering can be defined as a discipline that aims to develop human-centered systems for supporting human cognitive activities such as reasoning, decision-making, and problem solving. However, cognitive engineering is primarily concerned with the cognitive interaction between human users and IT-based systems that can be regarded as artificial cognitive systems. For this reason, it draws on concepts, principles, frameworks, models, and processes from cognition-related disciplines such as cognitive science, human factors, information science, human–computer interaction, cybernetics, etc. In addition, as it emphasizes the joint optimization of human users and IT-based systems, systems thinking serves as a conceptual foundation underlying cognitive engineering. Currently, we can observe that a synergistic cognitive performance of human users and IT-based systems is increasingly important in a range of work domains. In principle, it can be said that cognitive engineering can be applied to any work domain in which human users need to interact with IT-based systems and human cognitive activities are important in terms of productivity, safety, security, and so on. The typical research topics of cognitive engineering include：

cognitive task analysis, cognitive performance modeling, cognition and complexity, cognitive interaction theories and models, cognitive performance evaluation, human-centered approach to supporting cognition, information displays for supporting cognitive interaction, training systems development, cognition and system safety, human errors and reliability, human-centered artificial intelligence (AI), human–AI interaction, and so on.  

Prof. Dong-Han Ham
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cognitive science
  • cognitive engineering
  • cognitive ergonomics
  • human–computer interaction
  • human–centered artificial intelligence
  • joint cognitive systems

Published Papers (1 paper)

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Research

21 pages, 1606 KiB  
Article
Information Requirements of a Decision Support System for Severe Accident Management in Nuclear Power Plants
by Shelly Salim, Eun-Bi Choi and Dong-Han Ham
Appl. Sci. 2022, 12(8), 3803; https://doi.org/10.3390/app12083803 - 09 Apr 2022
Viewed by 1639
Abstract
In nuclear power plants, a severe accident is a critical accident involving significant nuclear core damage and it is managed by using a set of Severe Accident Management Guidelines (SAMG). Prepared as a guideline that provides lists of suggestions rather than strict instructions, [...] Read more.
In nuclear power plants, a severe accident is a critical accident involving significant nuclear core damage and it is managed by using a set of Severe Accident Management Guidelines (SAMG). Prepared as a guideline that provides lists of suggestions rather than strict instructions, SAMG’s contents require frequent decision-making by the operators, causing high cognitive load and creating an error-prone situation that is also amplified by the stressful environment during the severe accident mitigation efforts. A decision support system (DSS), designed by considering the human decision-making process and the system’s holistic view, can help the operators in making informed and appropriate decisions. In this study, we aim to identify the information requirements in designing such DSS for severe accident management of nuclear power plants. We combined two methods: Functional Resonance Analysis Method (FRAM) and decision ladder to identify the information requirements. FRAM provides a systematic analysis of the functions involved in severe accident management and decision ladder captures the human decision-making processes. We developed the FRAM model and the decision ladder model based on SAMG’s contents to identify the set of information requirements. The identified information requirements and their implementation suggestions are provided. This study is the first step in designing a decision support system that considers human cognitive load and holistic system concepts. The method used in this study shall contribute to the design and implementation of a DSS capable of supporting the operators in achieving safer decision-making, not only in nuclear power plants’ severe accident management but also in similar safety-critical systems. Full article
(This article belongs to the Special Issue Advances in Cognitive Systems Applications)
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