Nurliza Khaliddin

A New Discordancy Test in Circular Data Using Spacings Theory

In this article, we propose a new test of discordancy based on spacing theory in circular data. The test should provide a good alternative to existing tests of discordancy for detecting single or well-separated multiple outliers. On top of that, the new method can be generalized to identify a patch of outliers in data. The percentage points are calculated and the performance is examined. We first investigate the performance of the test for detecting a single outlier and show that the new test performs well compared to other known tests. We then show that the generalized test works well in detecting a patch of outliers in the data. As an illustration, a practical example based on an eye dataset obtained from a glaucoma clinic at the University of Malaya Medical Center, Malaysia is presented.

Arterial occlusion following embolization of an orbital arteriovenous malformation. A case report.

Orbital arteriovenous malformation is a rare condition which poses a management problem in view of the complexity of the vessels involved, and the potentially blinding and life-threatening complications from the modes of treatment. Treatment requires obliteration of the abnormal vascular communication. Vision may be adversely affected by the condition itself, as well as a result of invasive treatment modalities. This case reports such a situation where the visual outcome was severely affected following embolization of the feeding vessels.