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In TCM theory, the syndrome is crucial to diagnose diseases and treat patients. In syndrome identification, the relation of symptoms usually correlates with syndrome and represents the pattern of syndrome at symptomatic level. Hence, we learn models for classifying syndromes in depression using 4 different algorithms, which are naive Bayes, Bayes network, SVM and C4.5. From the results of classification,...
Anomaly detection is to identify abnormal behaviors of a system. It plays an important role in Prognostics and System Health Management (PHM) which is applied to monitor spacecraft's performance, detect faults, identify the root cause of the fault, and predict the remaining useful life (RUL) in order to increase safety and reduce downtime of spacecraft in—orbit.
Counting of different classes of white blood cells in bone marrow smears can give pathologists valuable information regarding various hematological disorders. For automation imaging analysis techniques, precise segmentation of white blood cells is quite challenging due to the complex contents in bone marrow smears. Far more different from traditional color imaging analysis methods, we introduced multispectral...
For time-variation and nonlinearity of vehicle image classifier design in complicated environment, a novel classifier based on Immune Clone Concentration Clustering Algorithm (ICCCA) was proposed, inspired by the clone selection theory in the natural immune system. It overcame the defects of traditional classification algorithms as multi-restraint and trap of local optimum. It also avoided the high...
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