{"title":"Research on similarity bias in dual objective visual search based on nuclear power human-machine interface icons","authors":"","doi":"10.1016/j.ergon.2024.103656","DOIUrl":null,"url":null,"abstract":"<div><div>Using icons from nuclear power interface as the research object, this study explored how icon similarity affected the performance of dual objective visual search. Firstly, the process of generating similarity bias was described from the perspective of human cognitive processing. The feature attributes of nuclear power icons were extracted, and then associated and mapped with similarity bias attributes. Secondly, a total of 16 instruction icons, device icons, and component icons were selected to propose icon coding logic for different similarity dimensions, and similarity experimental materials were designed. Finally, a dual objective search experiment with a 4 × 4 matrix was conducted to explore the impact of graph similarity on search performance and to determine the priority of perceptual similarity, semantic similarity, and memory similarity. High-level (H) similarity between the two targets resulted in superior visual search performance (p = 0.01 between the response times of similarity high and medium/low). Improving experiential familiarity enhanced search performance in cases of low-level (L) (p = 0.021) and medium-level (M) (p ≤ 0.009) icon similarity, but had no significant impact on search performance in cases of high-level (H) similarity (p ≥ 0.269). Compared to semantic similarity, enhancing perceptual similarity was more likely to improve search performance(p = 0.024).</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Industrial Ergonomics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169814124001124","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
Using icons from nuclear power interface as the research object, this study explored how icon similarity affected the performance of dual objective visual search. Firstly, the process of generating similarity bias was described from the perspective of human cognitive processing. The feature attributes of nuclear power icons were extracted, and then associated and mapped with similarity bias attributes. Secondly, a total of 16 instruction icons, device icons, and component icons were selected to propose icon coding logic for different similarity dimensions, and similarity experimental materials were designed. Finally, a dual objective search experiment with a 4 × 4 matrix was conducted to explore the impact of graph similarity on search performance and to determine the priority of perceptual similarity, semantic similarity, and memory similarity. High-level (H) similarity between the two targets resulted in superior visual search performance (p = 0.01 between the response times of similarity high and medium/low). Improving experiential familiarity enhanced search performance in cases of low-level (L) (p = 0.021) and medium-level (M) (p ≤ 0.009) icon similarity, but had no significant impact on search performance in cases of high-level (H) similarity (p ≥ 0.269). Compared to semantic similarity, enhancing perceptual similarity was more likely to improve search performance(p = 0.024).
期刊介绍:
The journal publishes original contributions that add to our understanding of the role of humans in today systems and the interactions thereof with various system components. The journal typically covers the following areas: industrial and occupational ergonomics, design of systems, tools and equipment, human performance measurement and modeling, human productivity, humans in technologically complex systems, and safety. The focus of the articles includes basic theoretical advances, applications, case studies, new methodologies and procedures; and empirical studies.