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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
TL;DR: This mini-review presents new researches on the development of aerobic granular processes, extended treatments for complicated pollutants, granulation mechanisms and enhancements of granule stability in long-term operation or storage, and the reuse of waste biomass as renewable resources.

132 citations

Journal ArticleDOI
TL;DR: This review focuses on integrating studies on algae pertinent to human skin care, health and therapy to identify serviceable algae functions in skin treatments to facilitate practical applications in this high-potential area.

132 citations

Journal ArticleDOI
TL;DR: The modification and extension of TOPSIS to a group decision environment is investigated in this article, where the authors adopt the Minkowski distance function to solve the over-weighted problem in the original top-SIS technique, the grey number operations to deal with the problem of uncertain information, and the aggregation approach to integrate experts' evaluations.

132 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined the relationship between family firms and earnings management by considering the influence of board independence and found that family firms are positively related to earnings management, and that board independence is important for an emerging market to mitigate the earnings management behavior carried out by family firms.

132 citations

Journal ArticleDOI
TL;DR: The FALA system rapidly and accurately locates and analyses cephalometric landmarks in lateral cephalograms, and has the potential to significantly improve the clinical work flow in orthodontic treatment.
Abstract: Cephalometric tracing is a standard analysis tool for orthodontic diagnosis and treatment planning. The aim of this study was to develop and validate a fully automatic landmark annotation (FALA) system for finding cephalometric landmarks in lateral cephalograms and its application to the classification of skeletal malformations. Digital cephalograms of 400 subjects (age range: 7–76 years) were available. All cephalograms had been manually traced by two experienced orthodontists with 19 cephalometric landmarks, and eight clinical parameters had been calculated for each subject. A FALA system to locate the 19 landmarks in lateral cephalograms was developed. The system was evaluated via comparison to the manual tracings, and the automatically located landmarks were used for classification of the clinical parameters. The system achieved an average point-to-point error of 1.2 mm, and 84.7% of landmarks were located within the clinically accepted precision range of 2.0 mm. The automatic landmark localisation performance was within the inter-observer variability between two clinical experts. The automatic classification achieved an average classification accuracy of 83.4% which was comparable to an experienced orthodontist. The FALA system rapidly and accurately locates and analyses cephalometric landmarks in lateral cephalograms, and has the potential to significantly improve the clinical work flow in orthodontic treatment.

132 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