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Institution

National Taiwan University of Science and Technology

EducationTaipei, Taipei, Taiwan
About: National Taiwan University of Science and Technology is a education organization based out in Taipei, Taipei, Taiwan. It is known for research contribution in the topics: Fuzzy logic & Control theory. The organization has 16288 authors who have published 21577 publications receiving 426294 citations. The organization is also known as: Taiwan Tech & Taiwantech.


Papers
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Journal ArticleDOI
21 Mar 2012-Langmuir
TL;DR: A simple technique was developed to fabricate tunable micropatterned substrates based on mussel-inspired surface modification and provides a powerful tool for development of a functional patterned substrate for various applications.
Abstract: A simple technique was developed to fabricate tunable micropatterned substrates based on mussel-inspired surface modification. Polydopamine (PDA) was developed on polydimethylsiloxane (PDMS) stamps and was easily imprinted to several substrates such as glass, silicon, gold, polystyrene, and poly(ethylene glycol) via microcontact printing. The imprinted PDA retained its unique reactivity and could modulate the chemical properties of micropatterns via secondary reactions, which was illustrated in this study. PDA patterns imprinted onto a cytophobic and nonfouling substrates were used to form patterns of cells or proteins. PDA imprints reacted with nucleophilic amines or thiols to conjugate molecules such as poly(ethylene glycol) for creating nonfouling area. Gold nanoparticles were immobilized onto PDA-stamped area. The reductive ability of PDA transformed silver ions to elemental metals as an electroless process of metallization. This facile and economic technique provides a powerful tool for development of a functional patterned substrate for various applications.

137 citations

Journal ArticleDOI
TL;DR: It is demonstrated that poly(SBMA-co-AA) copolymers adsorbed on polyelectrolyte-base films via electrostatic interaction improve hemocompatibility effectively and are applicable for various substrates including TCPS, PU, and PDMS.

137 citations

Journal ArticleDOI
TL;DR: This study proposes a novel dynamic clustering approach based on particle swarm optimization (PSO) and genetic algorithm (GA) (DCPG) algorithm that can automatically cluster data by examining the data without a pre-specified number of clusters.

137 citations

Journal ArticleDOI
TL;DR: The results suggest that a serious consideration of contingent variables is crucial for improving e-learning system satisfaction, and two contingent variables, gender and job status, significantly influenced the perceptions of predictors and students' satisfaction with the e- learning system.
Abstract: This study investigated the impact of contingent variables on the relationship between four predictors and students' satisfaction with e-learning. Five hundred and twenty-two university students from 10 intact classes engaging in online instruction were asked to answer questionnaires about their learning styles, perceptions of the quality of the proposed predictors and satisfaction with e-learning systems. The results of analysis of variance and structural equation modelling analyses showed that two contingent variables, gender and job status, significantly influenced the perceptions of predictors and students' satisfaction with the e-learning system. This study also found a statistically significant moderating effect of two contingent variables, student job status and learning styles, on the relationship between predictors and e-learning system satisfaction. The results suggest that a serious consideration of contingent variables is crucial for improving e-learning system satisfaction. The implications of these results for the management of e-learning systems are discussed. [ABSTRACT FROM AUTHOR]

136 citations

Journal ArticleDOI
TL;DR: The results show that ISE fully mediates the relationship between peer support and learners' persistence in e-learning, and partially mediates learners' perceived learning and satisfaction, and it is noteworthy that the findings do not support direct group-level contextual effects of group potency.
Abstract: The present study intends to explore the role of collectivism and group potency at group level in predicting individual Internet self-efficacy (ISE) and individual e-learning outcomes for people aged over 45. Group learning has been widely discussed in the research into online formats. However, less study has been carried out about how collectivism and collective group potency affect individual learning decisions, especially using the technique of Hierarchical Linear Modeling (HLM) for cross-level analysis, which provides the solution of case dependency between group members. This study examines the mediation effects of ISE between peer support and e-learning outcomes. It also explores the contextual effects of group potency, and the moderation effects of collectivism and group potency at an individual level. The results show that ISE fully mediates the relationship between peer support and learners' persistence in e-learning, and partially mediates learners' perceived learning and satisfaction. It is noteworthy that the findings do not support direct group-level contextual effects of group potency. Instead, the results suggest that group potency moderates ISE-perceived learning and ISE-satisfaction relationships. On the other hand, collectivism also moderates the relationship between peer support and ISE. This study highlights the group-level effects of group potency, and suggests that adult educators design and deliver e-learning courses with an emphasis on facilitating group processes.

136 citations


Authors

Showing all 16326 results

NameH-indexPapersCitations
Gerbrand Ceder13768276398
Jong-Sung Yu124105172637
Tai-Shung Chung11987954067
En-Tang Kang9776338498
Koon Gee Neoh9568335008
Kisuk Kang9334531810
Duu-Jong Lee9197937292
Shyi-Ming Chen9042522172
Pi-Tai Chou9061430922
Chin Chung Tsai8340923043
Chung-Yuan Mou8342025075
Yuan T. Lee7844720517
Gwo-Hshiung Tzeng7746526807
Kuei-Hsien Chen7565224809
Shen-Ming Chen7294924444
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202332
2022130
20211,399
20201,354
20191,267
20181,115