96 resultados para Music Cognition


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Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates.

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Judaism and Emotion breaks with stereotypes that, until recently, branded Judaism as a rigid religion of laws and prohibitions. Instead, authors from different fields of research discuss the subject of Judaism and emotion from various scholarly perspectives; they present an understanding of Judaism that does not exclude spirituality and emotions from Jewish thought. In doing so, the contributions account for the relation between the representation of emotion and the actual emotions that living and breathing human beings feel in their everyday lives. While scholars of rabbinic studies and theology take a historical-critical and socio-historical approach to the subject, musicologists and scholars of religious studies focus on the overall research question of how the literary representations of emotion in Judaism are related to ritual and musical performances within Jewish worship. They describe in a more holistic fashion how Judaism serves to integrate various aspects of social life. In doing so, they examine the dynamic interrelationship between Judaism, cognition, and culture.

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Recognizing the increasing amount of information shared on Social Networking Sites (SNS), in this study we aim to explore the information processing strategies of users on Facebook. Specifically, we aim to investigate the impact of various factors on user attitudes towards the posts on their Newsfeed. To collect the data, we program a Facebook application that allows users to evaluate posts in real time. Applying Structural Equation Modeling to a sample of 857 observations we find that it is mostly the affective attitude that shapes user behavior on the network. This attitude, in turn, is mainly determined by the communication intensity between users, overriding comprehensibility of the post and almost neglecting post length and user posting frequency.