We present a work in progress of a computer vision application that would directly impact the delivery of healthcare in underdeveloped countries. We describe the development of an image-based smartphone application prototype for ear biometrics. The application targets the public health problem of managing medical records at on-site medical clinics in less developed countries where many individuals do not hold IDs. The domain presents challenges for an ear biometric system, including varying scale, rotation, and illumination. It was not clear which feature descriptors would work best for the application, so a comparative study of three ear biometric extraction techniques was performed, one of which was used to develop an iOS application prototype to establish the identity of an individual using a smartphone camera image. A pilot study was then conducted on the developed application to test feasibility in naturalistic settings.
Considering it the duty of every member of this Society to communicate any information in his power, which may tend to elucidate a point in ancient history, or any subject intimately connected therewith; I take the liberty of laying before the Society a Greek brass coin, which has been in my possession several years, together with some observations on it.
This article analyzes the distribution of three- and four-voice vertical sonorities in a repertoire of French ars antiqua and ars nova motets. Rather than selecting the subjectively important sonorities within a piece—an effort that would rely on the analyst’s judgment of the overarching contrapuntal goals—this study uses computational musicological methods to analyze and categorize the distribution of sonorities across individual motets and groups of motets that occur at regular time intervals across the course of the compositions. This study offers some preliminary observations and conclusions about sonority usage in the late medieval French motet repertoire.
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