Kalymnian music and dance in Tarpon Springs, Florida

Thesis (M.A.)--Boston UniversityGreek immigrants from the Dodecanese island of Kalyrnnos have dominated the social, political, and economic life of Tarpon Springs, Florida since their arrival in the first decades of the twentieth century. Remarkably unlike the typical urban immigrant experience, this dynamic has allowed the Kalyrnnian-American community of Tarpon Springs to negotiate its relationship with American society from a position of relative power, without the immediate need to compromise linguistic, social, or occupational identity for the sake of survival. The cultural and artistic traditions of Kalymnos-foremost among them music and dancing-have played a central role in the construction of Kalyrnnian-American identity in Tarpon Springs, and have enabled a creative negotiation on the community's own terms ofthe states of"hyphenated being" that characterize immigrant communities. In this thesis, I examine the ways in which Kalymnian Tarponites use embodied musical movement as a resonant bridge between competing cultural allegiances, a means of imaginative travel in search of emotional fulfillment, and a venue to perform notions of distinction and belonging. For Kalymnian residents of Tarpon Springs, the embodied music and dance traditions of Kalyrnnos function as mobile sites of tension and transcendence, are imbued with a new set of self-sufficient meanings, and serve as a passport to cross the blurry borders of transnational being

What\u27s News At Rhode Island College

https://digitalcommons.ric.edu/whats_news/1473/thumbnail.jp

Computational Analysis of Greek folk music of the Aegean islands

Αν και έχουν αναπτυχθεί νεότερα και πιο ανεπτυγμένα μοντέλα υπολογιστικής μουσικής ανάλυσης με στόχο την αύξηση διαθέσιμης πληροφορίας στον κλάδο της μουσικολογίας, υπάρχει πολύ λίγη έρευνα στην υπολογιστική ανάλυση δημοτικής μουσικής γενικότερα και ελληνικής δημοτικής μουσικής ειδικότερα. Στόχος της παρούσας εργασίας είναι η διερεύνηση ποικίλων τύπων μουσικών χαρακτηριστικών και προτύπων στη δημοτική μουσική των νησιών του Αιγαίου και η παροχή χρήσιμης πληροφορίας σχετικά με τη δομή και το περιεχόμενο του εν λόγω είδους. Επιπρόσθετα, με στόχο τη σύγκριση μουσικών αποσπασμάτων χορών Συρτού και Μπάλου, αλλά και γεωγραφικών περιοχών από τις οποίες προέρχονται, 73 αποσπάσματα συγκεντρώθηκαν συνολικά σε μια βάση δεδομένων και αναλύθηκαν. Η εξαγωγή χαρακτηριστικών και η ανάλυση προτύπων ανέδειξαν μελωδικές και ρυθμικές διαφορές τόσο ανάμεσα στα δύο είδη χορών όσο και στις διάφορες νησιωτικές περιοχές, ενώ υπήρξαν επίσης ποικίλες ομοιότητες σε όλο το σύνολο των δεδομένων.While newer, advanced computational music analysis models have been developed with the intentions of increasing available information in this field, very little research exists on the computational analysis of folk music in general and Greek folk music in specific. The aim of this study was to examine various types of musical features and patterns in the folk music of the Aegean islands and provide useful information about the structure and the content of this music style. In addition, to compare the tunes of Syrtos and Mpalos dances, but also the various island regions from which they originate, a total of 73 tunes were included in the constructed dataset and the analyses. Feature extraction and pattern analysis revealed that there are indeed melodic and temporal differences both between the two dance types and between the island regions, while there were also various important similarities throughout the whole dataset

The integration of dance as a dramatic element in broadway musical theatre

This study traces the development and growth of dance on the Broadway stage and the parallel growth of the effectiveness of choreography in enhancing the musical Theatre libretto. The study surveys the origins and early evolution of stage dance in the United States from 1775 to the introduction of ballet choreography in 1922. It concludes with an examination of Selected scripts which use choreography to dramatize the musical Theatre libretto, 1922 to 1990

November 14, 1983

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia

Towards the Use of Similarity Distances to Music Genre Classification: a Comparative Study

Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets -or clusters- and then generating in an automatic way a new song which is somehow "inspired" in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is.This work was supported by IT900-16 Research Team from the Basque Government

Analysis Of Behaviors In Crowd Videos

In this dissertation, we address the problem of discovery and representation of group activity of humans and objects in a variety of scenarios, commonly encountered in vision applications. The overarching goal is to devise a discriminative representation of human motion in social settings, which captures a wide variety of human activities observable in video sequences. Such motion emerges from the collective behavior of individuals and their interactions and is a significant source of information typically employed for applications such as event detection, behavior recognition, and activity recognition. We present new representations of human group motion for static cameras, and propose algorithms for their application to variety of problems. We first propose a method to model and learn the scene activity of a crowd using Social Force Model for the first time in the computer vision community. We present a method to densely estimate the interaction forces between people in a crowd, observed by a static camera. Latent Dirichlet Allocation (LDA) is used to learn the model of the normal activities over extended periods of time. Randomly selected spatio-temporal volumes of interaction forces are used to learn the model of normal behavior of the scene. The model encodes the latent topics of social interaction forces in the scene for normal behaviors. We classify a short video sequence of n frames as normal or abnormal by using the learnt model. Once a sequence of frames is classified as an abnormal, iii the regions of anomalies in the abnormal frames are localized using the magnitude of interaction forces. The representation and estimation framework proposed above, however, has a few limitations. This algorithm proposes to use a global estimation of the interaction forces within the crowd. It, therefore, is incapable of identifying different groups of objects based on motion or behavior in the scene. Although the algorithm is capable of learning the normal behavior and detects the abnormality, but it is incapable of capturing the dynamics of different behaviors. To overcome these limitations, we then propose a method based on the Lagrangian framework for fluid dynamics, by introducing a streakline representation of flow. Streaklines are traced in a fluid flow by injecting color material, such as smoke or dye, which is transported with the flow and used for visualization. In the context of computer vision, streaklines may be used in a similar way to transport information about a scene, and they are obtained by repeatedly initializing a fixed grid of particles at each frame, then moving both current and past particles using optical flow. Streaklines are the locus of points that connect particles which originated from the same initial position. This approach is advantageous over the previous representations in two aspects: first, its rich representation captures the dynamics of the crowd and changes in space and time in the scene where the optical flow representation is not enough, and second, this model is capable of discovering groups of similar behavior within a crowd scene by performing motion segmentation. We propose a method to distinguish different group behaviors such as divergent/convergent motion and lanes using this framework. Finally, we introduce flow potentials as a discriminative feature to iv recognize crowd behaviors in a scene. Results of extensive experiments are presented for multiple real life crowd sequences involving pedestrian and vehicular traffic. The proposed method exploits optical flow as the low level feature and performs integration and clustering to obtain coherent group motion patterns. However, we observe that in crowd video sequences, as well as a variety of other vision applications, the co-occurrence and inter-relation of motion patterns are the main characteristics of group behaviors. In other words, the group behavior of objects is a mixture of individual actions or behaviors in specific geometrical layout and temporal order. We, therefore, propose a new representation for group behaviors of humans using the interrelation of motion patterns in a scene. The representation is based on bag of visual phrases of spatio-temporal visual words. We present a method to match the high-order spatial layout of visual words that preserve the geometry of the visual words under similarity transformations. To perform the experiments we collected a dataset of group choreography performances from the YouTube website. The dataset currently contains four categories of group dances

Northern Junket, Vol. 13, No. 2

The Ralph Page collection of country dance materials was gathered by Ralph Page and spans the years 1778-1989