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Wei-Jen Wang
Researcher at National Central University
Publications - 67
Citations - 695
Wei-Jen Wang is an academic researcher from National Central University. The author has contributed to research in topics: Information hiding & Cloud computing. The author has an hindex of 13, co-authored 66 publications receiving 622 citations. Previous affiliations of Wei-Jen Wang include Rensselaer Polytechnic Institute.
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Adaptive scheduling for parallel tasks with QoS satisfaction for hybrid cloud environments
TL;DR: The proposed Adaptive-Scheduling-with-QoS-Satisfaction algorithm, namely AsQ, for the hybrid cloud environment to raise the resource utilization rate of the private cloud and to diminish task response time as much as possible and achieves a total optimization regarding cost and deadline constraints.
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A dynamic causal model for evoked and induced responses
Chun Chuan Chen,Chun Chuan Chen,Stefan J. Kiebel,Stefan J. Kiebel,James M. Kilner,Nick S. Ward,Klaas E. Stephan,Klaas E. Stephan,Wei-Jen Wang,Karl J. Friston +9 more
TL;DR: This work proposes a Dynamic Causal Model that models evoked and induced responses at the same time and provides empirical evidence that induced responses are more likely to reflect backward message passing in the brain, while evokes and induced components share certain characteristics and mechanisms.
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VQ Applications in Steganographic Data Hiding Upon Multimedia Images
TL;DR: It is shown that an irreversible method is very likely a VQ-based data-hiding method that produces a stego-image as its output, and it can embed more secret data than a reversible method.
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Reversible steganography based on side match and hit pattern for VQ-compressed images
TL;DR: The experimental results show that the proposed reversible steganographic method for vector quantization (VQ) compressed images has higher capacity, better visual quality, and lower running time.
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Data embedding for vector quantization image processing on the basis of adjoining state-codebook mapping
TL;DR: Experimental results indicate that the proposed reversible image information hiding scheme based on vector quantization has better compression bit rate and larger embedding capacity when it is compared with recent similar studies.