Network Analysis of Design Automation Literature

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Tinghao Guo ◽  
Jiarui Xu ◽  
Yue Sun ◽  
Yilin Dong ◽  
Neal Davis ◽  
...  
Keyword(s):  
Engineering Design ◽  
Design Automation ◽  
Design Research ◽  
Learning Algorithm ◽  
Small World ◽  
Citation Network ◽  
Research Literature ◽  
Future Research ◽  
Data Set ◽  
Topic Distribution

In this paper, we present the results of a study of citation and co-authorship networks for articles published at the ASME Design Automation Conference (DAC) during the years 2002–2015. Two topic-modeling methods are presented for studying the DAC literature: A frequency-based model was developed to explore DAC topic distribution and evolution, as well as citation analysis for each core topic. Correlation analysis and association-rule mining were used to discover relationships between topics. A new unsupervised learning algorithm, propagation mergence (PM), was created to address identified shortcomings of existing methods and applied to study the existing DAC citation network. Influential articles and important article clusters were identified and effective visualizations created. We also investigated the DAC co-authorship network by identifying key authors and showing that the network structure exhibits small-world-network properties. The resulting insights, obtained by the both the proposed and existing methods, may be beneficial to the engineering design research community, especially with respect to determining future research directions and possible actions for improvement. The data set used here is limited; expanding to include additional relevant conference proceedings and journal articles in the future would offer a more complete understanding of the engineering design research literature.

Network Analysis of Design Automation Literature

2017 ◽  
Author(s):  
Tinghao Guo ◽  
Jiarui Xu ◽  
Yue Sun ◽  
Yilin Dong ◽  
Neal E. Davis ◽  
...  
Keyword(s):  
Engineering Design ◽  
Design Automation ◽  
Design Research ◽  
Learning Algorithm ◽  
Small World ◽  
Citation Network ◽  
Research Literature ◽  
Rule Mining ◽  
Data Set ◽  
Topic Distribution

In this paper we present a study of citation and co-authorship networks for articles from the ASME Design Automation Conference (DAC) during the years 2002–2015. We identify key authors, show that the co-authorship network exhibits the small world network property, and reveal other insights from network structure. Results from two topic modeling methods are presented. A frequency-based model was developed to explore DAC topic distribution and evolution. Citation analysis was also conducted for each core topic. A correlation matrix and association rule mining were used to discover topic relations and to gain insights for research gaps and recommendations. A recently developed unsupervised learning algorithm, propagation mergence (PM), was applied to the DAC citation network. Influential papers and major clusters were identified and visualizations are presented. The resulting insights may be beneficial to the engineering design research community, especially with respect to determining future directions and possible actions for improvement. The data set used here is limited. Expanding to include additional relevant conference proceedings and journal articles in the future would offer a more complete understanding of the engineering design research literature.

Roles of externalisation activities in the design process

2016 ◽  
Vol 11 (1) ◽  
pp. 34
Author(s):  
Maral Babapour Chafi
Keyword(s):  
Design Process ◽  
Design Research ◽  
Research Literature ◽  
Physical Models ◽  
Future Research ◽  
Knowledge Gaps ◽  
Design Processes ◽  
Digital Modelling

Designers engage in various activities, dealing with different materials and media to externalise and represent their form ideas. This paper presents a review of design research literature regarding externalisation activities in design process: sketching, building physical models and digital modelling. The aim has been to review research on the roles of media and representations in design processes, and highlight knowledge gaps and questions for future research.

scholarly journals Experiential Learning vs Systematic Prescriptions in Engineering Design: A Crossroads for Education

2018 ◽  
Author(s):  
G. R. Gressfc ◽  
S. Li ◽  
R. W. Brennan
Keyword(s):  
Engineering Design ◽  
Design Methodology ◽  
Design Research ◽  
Great Difficulty ◽  
Research Literature ◽  
Classical Design ◽  
Classical Methodology ◽  
Successful Design ◽  
Research And Education ◽  
Visual Domain

The systematic, non-experiential prescriptions of classical design methodology continue to have a strong presence in large segments of design research and education while another segment sees domain experience and consequent intuition and creativity as being key to successful design. In this paper the two approaches are outlined and the empirical research literature in human behaviour is employed to discern discrepancies and potential weaknesses. Results show that gaining experience in a domain intrinsically changes how one designs, which the classical methodology does not account for. For example, only designers with tactile and visual domain experience can abstract functions per the dictates of the classical (non-experiential) methodology, which means that they cannot have used the methodology to learn basic design in the first place – or did so only with great difficulty. This and other conflicts pose problems for the education of engineering design students, and to fathom their extent this paper surveys engineering design textbooks offered in Canada and the U. S.; all of the books are found to embrace the classical methodology. If they are to remain involved in preparing students for entry into industry then some aspects of their contained classical methodology must be supplanted by experiential approaches to design educatio

scholarly journals Bio-Inspired Design: An Overview Investigating Open Questions From the Broader Field of Design-by-Analogy

2014 ◽  
Vol 136 (11) ◽  
Author(s):  
Katherine Fu ◽  
Diana Moreno ◽  
Maria Yang ◽  
Kristin L. Wood
Keyword(s):  
Design Research ◽  
Current Knowledge ◽  
Research Literature ◽  
Future Research ◽  
Cognitive Mechanisms ◽  
Open Questions ◽  
The Future ◽  
Design By Analogy ◽  
Research Questions ◽  
Tools And Methods

Bio-inspired design and the broader field of design-by-analogy have been the basis of numerous innovative designs throughout history; yet there remains much to be understood about these practices of design, their underlying cognitive mechanisms, and preferred ways in which to teach and support them. In this paper, we work to unify the broader design-by-analogy research literature with that of the bio-inspired design field, reviewing the current knowledge of designer cognition, the seminal supporting tools and methods for bio-inspired design, and postulating the future of bio-inspired design research from the larger design-by-analogy perspective. We examine seminal methods for supporting bio-inspired design, highlighting the areas well aligned with current findings in design-by-analogy cognition work and noting important areas for future research identified by the investigators responsible for these seminal tools and methods. Supplemental to the visions of these experts in bio-inspired design, we suggest additional projections for the future of the field, posing intriguing research questions to further unify the field of bio-inspired design with its broader resident field of design-by-analogy.

scholarly journals Literature Trend Identification of Sustainable Technology Innovation: A Bibliometric Study Based on Co-Citation and Main Path Analysis

2020 ◽  
Vol 12 (20) ◽  
pp. 8664
Author(s):  
Ben Zhang ◽  
Lei Ma ◽  
Zheng Liu
Keyword(s):  
Path Analysis ◽  
Technology Innovation ◽  
Relevant Literature ◽  
Citation Network ◽  
Development Trend ◽  
Research Literature ◽  
Future Research ◽  
Sustainable Technology ◽  
Main Path ◽  
Main Path Analysis

In the past 20 years, there have been increasingly more studies on sustainable technology innovation (STI), possessing a significance for sustainable development. This paper aims to provide a research landscape, since the systematic understanding of STI is still inadequate. Through bibliometric analysis, it explores the literature distribution characteristics and the literature citation network. Based on the relevant literature data in the Web of Science (WOS), the study visually analyzes the development trend, topic distribution, burst literature, and co-citation network of the research literature, and extracts the evolution path of literature citation by using the main path analysis method. Through the analysis of co-citation and main path, 13 clusters in the co-citation network are found, which are further extracted as the main path network containing 82 nodes. Furthermore, this paper summarized the bibliometric landscape and discussed the frontier STI research topics. The comprehensive framework contributes to the understanding of STI themes and identifying future research agenda.

scholarly journals SEMANTIC NETWORKS FOR ENGINEERING DESIGN: A SURVEY

2021 ◽  
Vol 1 ◽  
pp. 2621-2630
Author(s):  
Ji Han ◽  
Serhad Sarica ◽  
Feng Shi ◽  
Jianxi Luo
Keyword(s):  
Engineering Design ◽  
Language Processing ◽  
Large Scale ◽  
Design Research ◽  
Semantic Network ◽  
Semantic Networks ◽  
Future Research ◽  
Research Directions ◽  
Engineering Data ◽  
Future Research Directions

AbstractThere have been growing uses of semantic networks in the past decade, such as leveraging large-scale pre-trained graph knowledge databases for various natural language processing (NLP) tasks in engineering design research. Therefore, the paper provides a survey of the research that has employed semantic networks in the engineering design research community. The survey reveals that engineering design researchers have primarily relied on WordNet, ConceptNet, and other common-sense semantic network databases trained on non-engineering data sources to develop methods or tools for engineering design. Meanwhile, there are emerging efforts to mine large scale technical publication and patent databases to construct engineering-contextualized semantic network databases, e.g., B-Link and TechNet, to support NLP in engineering design. On this basis, we recommend future research directions for the construction and applications of engineering-related semantic networks in engineering design research and practice.

scholarly journals Semantic Networks for Engineering Design: State of the Art and Future Directions

2021 ◽  
pp. 1-45
Author(s):  
Ji Han ◽  
Serhad Sarica ◽  
Feng Shi ◽  
Jianxi Luo
Keyword(s):  
Engineering Design ◽  
Large Scale ◽  
Design Research ◽  
State Of The Art ◽  
Semantic Network ◽  
Semantic Networks ◽  
Knowledge Bases ◽  
Data Sources ◽  
Future Research ◽  
Support Engineering

Abstract In the past two decades, there has been increasing use of semantic networks in engineering design for supporting various activities, such as knowledge extraction, prior art search, idea generation and evaluation. Leveraging large-scale pre-trained graph knowledge databases to support engineering design-related natural language processing (NLP) tasks has attracted a growing interest in the engineering design research community. Therefore, this paper aims to provide a survey of the state-of-the-art semantic networks for engineering design and propositions of future research to build and utilize large-scale semantic networks as knowledge bases to support engineering design research and practice. The survey shows that WordNet, ConceptNet and other semantic networks, which contain common-sense knowledge or are trained on non-engineering data sources, are primarily used by engineering design researchers to develop methods and tools. Meanwhile, there are emerging efforts in constructing engineering and technical-contextualized semantic network databases, such as B-Link and TechNet, through retrieving data from technical data sources and employing unsupervised machine learning approaches. On this basis, we recommend six strategic future research directions to advance the development and uses of large-scale semantic networks for artificial intelligence applications in engineering design.

scholarly journals Roles of externalisation activities in the design process

2016 ◽  
Vol 11 ◽  
pp. 34-46
Author(s):  
Maral Babapour Chafi
Keyword(s):  
Design Process ◽  
Design Research ◽  
Research Literature ◽  
Physical Models ◽  
Future Research ◽  
Knowledge Gaps ◽  
Design Processes ◽  
Digital Modelling

Designers engage in various activities, dealing with different materials and media to externalise and represent their form ideas. This paper presents a review of design research literature regarding externalisation activities in design process: sketching, building physical models and digital modelling. The aim has been to review research on the roles of media and representations in design processes, and highlight knowledge gaps and questions for future research.

Research Progress of Coal Villages in China Based on Literatures Analysis

2014 ◽  
Vol 1010-1012 ◽  
pp. 1301-1306
Author(s):  
Lin Lin Cheng ◽  
Jun Tao Ren ◽  
Peng Fei Wang ◽  
Lu Ma ◽  
Shu Jiang
Keyword(s):  
Quantitative Research ◽  
Research Literature ◽  
Research Progress ◽  
Future Research ◽  
China National Knowledge Infrastructure ◽  
Research Papers ◽  
Coal Resources ◽  
Knowledge Infrastructure ◽  
Topic Distribution ◽  
Coal Enterprises

Using China National Knowledge Infrastructure as the retrieve source, research papers of villages overlapping coal resources in recent 48 years are analyzed from the aspects of time distribution, periodical distribution, topic distribution etc. Then the content of research literature is analyzed qualitatively and the research progress is revealed. The results show that: The total amount of literature is less, the gross number is only 331; Besides core journals, the ordinary journals occupies the large proportion among the journals on which the research papers published; It can generally be divided into two research themes, that is coal mining technology under villages and relocation of village overlapping coal resources. Compared with the first, the study of village relocation is weak, and much more study is in a shallow level; The research subject is single, and the technical personnel and workers at the basic level of coal enterprises occupy a large proportion. Although the village relocation involves a lot of land issues, the research of land scholars on this field is not much. To strengthen and broaden the research of relocation of villages overlapping coal resources is the trend of future research in this field. Comprehensive and quantitative research from the land, management, ecology, environment and other multi angle, multi domain, multi discipline should be conducted.

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