Mapping the knowledge domains of smart textile: visualization analysis-based studies

2021 ◽  
pp. 1-9
Author(s):  
ZhiQun Liu ◽  
Ping Jin ◽  
YiQiu Yin ◽  
FangPing Yin
Keyword(s):  
Knowledge Domains ◽  
Visualization Analysis ◽  
Smart Textile

Visualization analysis on stretch-and-fold mechanism of chaotic attractors

2014 ◽  
Vol 1 ◽  
pp. 443-446
Author(s):  
Yutaka Shimada ◽  
Takuya Kobayashi ◽  
Tohru Ikeguchi ◽  
Kazuyuki Aihara
Keyword(s):  
Chaotic Attractors ◽  
Visualization Analysis

Document- and Keyword-based Author Co-citation Analysis

2018 ◽  
Vol 2 (2) ◽  
pp. 70-82 ◽  
Author(s):  
Binglu Wang ◽  
Yi Bu ◽  
Win-bin Huang
Keyword(s):  
Citation Analysis ◽  
Semantic Similarity ◽  
Method Validation ◽  
New Method ◽  
Global Network ◽  
Network Visualization ◽  
Knowledge Domain ◽  
Knowledge Domains ◽  
Domain Mapping ◽  
The Relationship

AbstractIn the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.

scholarly journals Coding as Literacy in Preschool: A Case Study

2021 ◽  
Vol 11 (5) ◽  
pp. 198
Author(s):  
Ana Francisca Monteiro ◽  
Maribel Miranda-Pinto ◽  
António José Osório
Keyword(s):  
Elementary Education ◽  
Developmentally Appropriate ◽  
Computational Thinking ◽  
School Subject ◽  
New Literacy ◽  
Computational Approaches ◽  
Knowledge Domains ◽  
And Robotics ◽  
Initial Framework

Coding is increasingly recognized as a new literacy that should be encouraged at a young age. This understanding has recontextualized computer science as a compulsory school subject and has informed several developmentally appropriate approaches to computation, including for preschool children. This study focuses on the introduction of three approaches to computation in preschool (3–6 years), specifically computational thinking, programming, and robotics, from a cross-curricular perspective. This paper presents preliminary findings from one of the case studies currently being developed as part of project KML II—Laboratory of Technologies and Learning of Programming and Robotics for Preschool and Elementary School. The purpose of the KML II project is to characterize how approaches to computation can be integrated into preschool and elementary education, across different knowledge domains. The conclusions point to “expression and communication” as an initial framework for computational approaches in preschool, but also to multidisciplinary and more creative methodological activities that offer greater scope for the development of digital and computational competences, as well as for personal and social development.

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