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Python-assisted biological knowledge acquisition method to trigger design inspiration
Design inspiration comes from the continuous stimulation of external information and the continuous accumulation of knowledge. In order to obtain an ideal design inspiration from nature, researchers have proposed a large number of biological information retrieval and knowledge acquisition methods. B...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9098421/ https://www.ncbi.nlm.nih.gov/pubmed/35550565 http://dx.doi.org/10.1038/s41598-022-11833-1 |
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author | Zha, Z. M. Zhang, H. Aggidis, G. A. |
author_facet | Zha, Z. M. Zhang, H. Aggidis, G. A. |
author_sort | Zha, Z. M. |
collection | PubMed |
description | Design inspiration comes from the continuous stimulation of external information and the continuous accumulation of knowledge. In order to obtain an ideal design inspiration from nature, researchers have proposed a large number of biological information retrieval and knowledge acquisition methods. But how to purposefully acquire valuable biological knowledge in order to effectively stimulate design inspiration and produce the novel and feasible designs idea is still an urgent problem to be solved. This paper proposes a method for acquiring valuable biological knowledge to efficiently stimulate inspiration and quickly conceive solutions in engineering design. First, keywords, such as the functional requirements and key components of design objects, are selected as the engineering terminologies. Next, biological keywords related to the engineering terminologies are searched from the biological dictionary and biology websites. Then in order to retrieve enough biological knowledge, these biological keywords are expanded manually and automatically respectively based on Thesaurus Webpage and WordNet database, and expanded keywords are filtered according to repeated words and different forms of the same words. Finally, in the biological knowledge base, biological keywords that had been filtered are used to obtain biological knowledge with Python web crawler programming. Through an example of application for ship equipment, the effectiveness of the method is verified. |
format | Online Article Text |
id | pubmed-9098421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90984212022-05-14 Python-assisted biological knowledge acquisition method to trigger design inspiration Zha, Z. M. Zhang, H. Aggidis, G. A. Sci Rep Article Design inspiration comes from the continuous stimulation of external information and the continuous accumulation of knowledge. In order to obtain an ideal design inspiration from nature, researchers have proposed a large number of biological information retrieval and knowledge acquisition methods. But how to purposefully acquire valuable biological knowledge in order to effectively stimulate design inspiration and produce the novel and feasible designs idea is still an urgent problem to be solved. This paper proposes a method for acquiring valuable biological knowledge to efficiently stimulate inspiration and quickly conceive solutions in engineering design. First, keywords, such as the functional requirements and key components of design objects, are selected as the engineering terminologies. Next, biological keywords related to the engineering terminologies are searched from the biological dictionary and biology websites. Then in order to retrieve enough biological knowledge, these biological keywords are expanded manually and automatically respectively based on Thesaurus Webpage and WordNet database, and expanded keywords are filtered according to repeated words and different forms of the same words. Finally, in the biological knowledge base, biological keywords that had been filtered are used to obtain biological knowledge with Python web crawler programming. Through an example of application for ship equipment, the effectiveness of the method is verified. Nature Publishing Group UK 2022-05-12 /pmc/articles/PMC9098421/ /pubmed/35550565 http://dx.doi.org/10.1038/s41598-022-11833-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zha, Z. M. Zhang, H. Aggidis, G. A. Python-assisted biological knowledge acquisition method to trigger design inspiration |
title | Python-assisted biological knowledge acquisition method to trigger design inspiration |
title_full | Python-assisted biological knowledge acquisition method to trigger design inspiration |
title_fullStr | Python-assisted biological knowledge acquisition method to trigger design inspiration |
title_full_unstemmed | Python-assisted biological knowledge acquisition method to trigger design inspiration |
title_short | Python-assisted biological knowledge acquisition method to trigger design inspiration |
title_sort | python-assisted biological knowledge acquisition method to trigger design inspiration |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9098421/ https://www.ncbi.nlm.nih.gov/pubmed/35550565 http://dx.doi.org/10.1038/s41598-022-11833-1 |
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