This paper reviews existing forms of density-based, partitional and hierarchical clustering methods in the context of flight data analysis. Advantages and disadvantages are fully explored with a focus on proposing a clustering-based ensemble framework for monitoring flight data in order to search for anomalies during flight operation. Case studies in selected flight scenarios are provided to demonstrate the potential of clustering methods and their integration with reasoning techniques in detecting abnormal flights.

The lichen species Xanthoparmelia chlorochroa is toxic when consumed by domestic sheep, cattle, and Rocky Mountain elk. Clinical signs exhibited by poisoned animals include red urine, ataxia, and muscular weakness that rapidly progresses to recumbency. Elk are unable to recover once becoming recumbent; however, most affected cattle can recover if offered suitable feed shortly following the onset of signs. At present, the pathogenesis and specific toxin(s) are unknown. As part of an effort to elucidate the proximate toxin, a method using ultra-performance LC coupled to MS/MS with negative-ion electrospray ionization has been developed to compare salazinic, norstictic, and usnic acid concentrations in X. chlorochroa collected from locales associated with lichen poisonings. Compounds were extracted from lichen samples with acetone and sonication. The stationary phase was a Waters Acquity UPLCTM BEH C18 (50 2.1 mm; 1.7 m particle size) column. The mobile phase consisted of an acetonitrilewater gradient. The precision of the method was confirmed by an SD below 0.4 (n = 9) for triplicate samples. LOD values were 200, 100, and 50 ng/mL for salazinic, norstictic, and usnic acids, respectively.

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