PPT-Cultural Parameters of Musical Similarity

Basic Issues in Folksong Research 5162011 1 Eleanor SelfridgeField Basic Factors in Folksong Research Format considerations Repertory considerations Cultural considerations 5162011. Presented by:. Akshay. Kumar. Pankaj. . Prateek. Are these similar?. Number ‘1’ vs. color ‘red’. Number ‘1’ vs. ‘small’. Horse vs. Rider. True vs. false . ‘. Monalisa. ’ vs. ‘Virgin of the rocks’. a cross cultural dissection. What is Universalism?. “The single harmony produced by all the heavenly bodies singing and dancing together springs from one source and ends by achieving one purpose, and has rightly bestowed the name not of ‘disordered’ but of ‘ordered universe’ upon the whole” –Aristotle (. from . GOMMA. Michael . Hartung. , Lars Kolb, . Anika. . Groß. , Erhard Rahm. Database . Research Group. University of . Leipzig. 9th . Intl. . . Conf. . on Data Integration. in . the. Life . Sciences. Liam O'Sullivan. Electronic . and Electrical Engineering, . Trinity College Dublin, Ireland. Trinity College Dublin. Tailoring Tabletop Interfaces for Musical Control. Proliferation of . multitouch. . these theories have explanatory power domains partially role of relational judgments. Previous structural and aspects of notion of relational similarity by the fact that and her some ways there is in Warm Up. 1.. . If . ∆. QRS.  . ∆. ZYX. , identify the pairs of congruent angles and the pairs of congruent sides.. Solve each proportion.. 2.. . 3.. . . x . = 9. x . = 18. . Q. The two large-scale video documentaries of rock Case-based reasoning. Introduction. Common term in everyday language, where two objects usually are considered similar if they look or sound similar. Similarity is a core concept within CBR. From a CBR perspective: «Two problems are similar if they have similar solutions». Public Lecture by Anthony Seeger. Sir Zelman Cowan School of Music. Monash University. 1. 2. This evening event . Focuses on a song that I hope you will sing the chorus to. Describes the context of ecomusicology and cultural diversity. a Multi-Layered Indexing Approach. Yongjiang Liang, . Peixiang Zhao. CS @ FSU. zhao@cs.fsu.edu. Outline. Introduction. State-of-the-art solutions. ML-Index & similarity search. Experiments. Conclusion. CS159 . Fall . 2014. Admin. Assignment 4. Quiz #2 Thursday. Same . rules as quiz #1. First 30 minutes of class. Open book and . notes. Assignment 5 out on Thursday. Quiz #2. Topics. Linguistics 101. Parsing. Text Similarity. Motivation. People can express the same concept (or related concepts) in many different ways. For example, “the plane leaves at 12pm” vs “the flight departs at noon”. Text similarity is a key component of Natural Language Processing. Quiz. Which pair of words exhibits the greatest similarity?. 1. Deer-elk. 2. Deer-horse. 3. Deer-mouse. 4. Deer-roof. Quiz Answer. Which pair of words exhibits the greatest similarity?. 1. Deer-elk. 2. Deer-horse. /r and . Metabolic . Parameters . METABOLIK. DRV/r . versus . ATV/r . and Metabolic Parameters . METABOLIK. : . Study Design . Source. : . Aberg. JA, et al. AIDS Res Hum Retroviruses. . 2012;28:. 1184-95..