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*** REVIEW FORM ID: 351456::200766
*** SUBMISSION NUMBER: 15
*** TITLE: A Multi-Experts Methodology for Early Detection and Diagnosis of Mechanical Defects
*** AUTHORS: (anonymous)
*** PC MEMBER: Lipo Wang
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*** REVIEW:
---  Please provide a detailed review, including justification for
---  your scores. This review will be sent to the authors unless
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The paper presents a multi-expert method for mechanical defect detection.
It uses some practical/real data, which is good. But it is not clear
how novel the method is. The paper can be accepted if the following minor 
changes are made: it would be beneficial to mention more relevant work in detection 
with soft computing techniques, for example,

V. Mitra, Chia-Jiu Wang, and S. Banerjee, "Lidar detection of underwater objects using a neuro-SVM-based architecture," IEEE Transactions on Neural Networks, no.17, pp.717-731, 2006. 

L.P. Wang and X.J. Fu, Data Mining with Computational Intelligence, Springer, Berlin, 2005.


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*** OVERALL EVALUATION: 2

---  3 (strong accept)
---  2 (accept)
---  1 (weak accept)
---  0 (borderline paper)
---  -1 (weak reject)
---  -2 (reject)
---  -3 (strong reject)

*** REVIEWER'S CONFIDENCE:3

---  4 (expert)
---  3 (high)
---  2 (medium)
---  1 (low)
---  0 (null)

*** RELEVANCE TO THIS CONFERENCE: 4

---  5 (excellent)
---  4 (good)
---  3 (fair)
---  2 (poor)
---  1 (very poor)

*** ORIGINALITY/UNIQUENESS: 3

---  5 (excellent)
---  4 (good)
---  3 (fair)
---  2 (poor)
---  1 (very poor)

*** ENGLISH READABILITY: 4

---  5 (excellent)
---  4 (good)
---  3 (fair)
---  2 (poor)
---  1 (very poor)

*** PAPER ORGANIZATION/PRESENTATION: 4

---  5 (excellent)
---  4 (good)
---  3 (fair)
---  2 (poor)
---  1 (very poor)

*** HAS GOOD SURVEY BEEN DONE?: 4

---  5 (excellent)
---  4 (good)
---  3 (fair)
---  2 (poor)
---  1 (very poor)

*** END
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