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Institution

Chung Yuan Christian University

EducationTaoyuan City, Taiwan
About: Chung Yuan Christian University is a education organization based out in Taoyuan City, Taiwan. It is known for research contribution in the topics: Membrane & Fuzzy logic. The organization has 9819 authors who have published 11623 publications receiving 213139 citations. The organization is also known as: Tiong-gôan-tāi-ha̍k & CYCU.


Papers
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Journal ArticleDOI
TL;DR: It is suggested that niclosamide and nitazoxanide were able to inhibit Chikungunya virus entry and transmission, which might provide a basis for the development of novel human drug therapies against CHIKV and other alphavirus infections.

86 citations

Journal ArticleDOI
TL;DR: Reduction technologies published in the last decade related to remediation of PCBs will be reviewed here, including catalytic hydrodechlorination with H(2), Fe-based reductive dechlorination, and other reductiveDechlorination methods are specifically reviewed.

86 citations

Journal ArticleDOI
TL;DR: Vapernot et al. as mentioned in this paper proposed a new method to induce phase inversion, the so-called vapor induced phase separation (VIPS), which is based on the idea of phase separation.

86 citations

Journal ArticleDOI
TL;DR: In this article, a new constant current voltage driver forms a bridge-type floating drain-source follower configuration applicable to the determination of H+ ion concentration, which can be integrated with a ISFET-based microsystem by standard CMOS technology.
Abstract: A new constant-current voltage driver forms a bridge-type floating drain-source follower configuration applicable to the determination of H+ ion concentration. The proposed circuit maintains the ion-selective field effect transistor (ISFET) in an accurate constant drain-source voltage and current situation with good noise rejection capability. Simulation results show accurate response for ISFET applications. The presented electronic circuit can be integrated with a ISFET-based microsystem by standard CMOS technology.

86 citations

Journal ArticleDOI
TL;DR: Experimental lessons demonstrate that semantic rules in conjunction with ontologies not only solve sequencing problems but also achieve a durable knowledge base and a reliable system.
Abstract: Curriculum content sequencing involves managing a learning route to help users achieve learning goals. A conventional learning route consists of ordered content and is primarily based on a single course material. In an e-learning system, amount of similar course contents are available. These contents are expected to mutually substitute for one another in creating flexible learning routes. Owing to inconsistency in materials editing and cataloging, composing contents based on multiple sources leads to sequencing complexity. Most significantly, most e-learning systems lack a sequencing mechanism for dominating content composition. This study utilizes a knowledge-intensive approach to create a general sequencing knowledge base. This approach includes two components: (1) ontology is used to represent abstract views of content sequencing and course materials and (2) added semantic rules are used to represent relationships between individuals. Following knowledge base creation, both practical curriculum sequences and course materials can be inserted as factual knowledge. A reliable knowledge base can be established using inference power. An example involving mathematics course in elementary school education is designed using Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL). Experimental lessons demonstrate that semantic rules in conjunction with ontologies not only solve sequencing problems but also achieve a durable knowledge base and a reliable system.

86 citations


Authors

Showing all 9844 results

NameH-indexPapersCitations
Simon Lin12675469084
Xiaodong Li104130049024
Yu Wang92168747472
Leaf Huang9235025867
Duu-Jong Lee9197937292
Yen Wei8564925805
Ru-Shi Liu8273826699
Kazuhiko Ishihara7771324795
Gwo-Hshiung Tzeng7746526807
Huan-Tsung Chang7640521476
Hari M. Srivastava76112642635
Jianhua Yang7455427839
Yen Wei6830917527
Hsisheng Teng6721314408
Kevin C.-W. Wu6627815193
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202271
2021590
2020633
2019569
2018514