Configuration-oriented symbolic test sequence construction method for EFSM

2005 ◽  
Author(s):  
Shuhao Li ◽  
Ji Wang ◽  
Xin Wang ◽  
Zhi-Chang Qi
Keyword(s):  
Construction Method ◽  
Test Sequence ◽  
Symbolic Test

Optimizing Diagnostic Test Sequences: The Probability Modifying Plot

1999 ◽  
Vol 38 (01) ◽  
pp. 50-55 ◽  
Author(s):  
P. F. de Vries Robbé ◽  
A. L. M. Verbeek ◽  
J. L. Severens
Keyword(s):  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Decision Trees ◽  
Diagnostic Tests ◽  
Test Sequence ◽  
Optimal Sequence ◽  
Specific Test ◽  
Total Cost ◽  
Modelling Techniques

Abstract:The problem of deciding the optimal sequence of diagnostic tests can be structured in decision trees, but unmanageable bushy decision trees result when the sequence of two or more tests is investigated. Most modelling techniques include tests on the basis of gain in certainty. The aim of this study was to explore a model for optimizing the sequence of diagnostic tests based on efficiency criteria. The probability modifying plot shows, when in a specific test sequence further testing is redundant and which costs are involved. In this way different sequences can be compared. The model is illustrated with data on urinary tract infection. The sequence of diagnostic tests was optimized on the basis of efficiency, which was either defined as the test sequence with the least number of tests or the least total cost for testing. Further research on the model is needed to handle current limitations.

Construction Method of Equivalent Systems for Bulk Power System

2009 ◽  
Vol 129 (5) ◽  
pp. 715-716
Author(s):  
Shoichi Minami ◽  
Satoshi Morii ◽  
Suo Lian ◽  
Shunji Kawamoto
Keyword(s):  
Power System ◽  
Construction Method ◽  
Equivalent Systems ◽  
Bulk Power

Objective Video Quality Method Based on Mutual Information and Human Visual System

2012 ◽  
Vol 58 (2) ◽  
pp. 147-152
Author(s):  
Michal Mardiak ◽  
Jaroslav Polec
Keyword(s):  
Mutual Information ◽  
Visual System ◽  
Human Visual System ◽  
Quality Evaluation ◽  
Video Quality ◽  
Evaluation Criteria ◽  
Test Sequence ◽  
Quality Metric ◽  
Two Stages ◽  
Video Quality Metric

Objective Video Quality Method Based on Mutual Information and Human Visual SystemIn this paper we present the objective video quality metric based on mutual information and Human Visual System. The calculation of proposed metric consists of two stages. In the first stage of quality evaluation whole original and test sequence are pre-processed by the Human Visual System. In the second stage we calculate mutual information which has been utilized as the quality evaluation criteria. The mutual information was calculated between the frame from original sequence and the corresponding frame from test sequence. For this testing purpose we choose Foreman video at CIF resolution. To prove reliability of our metric were compared it with some commonly used objective methods for measuring the video quality. The results show that presented objective video quality metric based on mutual information and Human Visual System provides relevant results in comparison with results of other objective methods so it is suitable candidate for measuring the video quality.

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