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1. |
Record Nr. |
UNISA990003632420203316 |
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Autore |
SOLOMON, Eldra Pearl |
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Titolo |
Biologia / Eldra P. Solomon, Linda R. Berg, Diana W. Martin ; edizione italiana a cura di Paolo Audisio ... [et al.] |
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Pubbl/distr/stampa |
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ISBN |
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Edizione |
[5. ed] |
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Descrizione fisica |
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XXXII, 1291, [113] p. : ill. ; 29 cm |
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Altri autori (Persone) |
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BERG, Linda R. |
MARTIN, Diana W. |
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Disciplina |
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Soggetti |
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Collocazione |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Trad. dell'8. ed. americana |
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2. |
Record Nr. |
UNINA9910786531903321 |
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Autore |
Kayes Gillyanne |
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Titolo |
Singing and the actor / / Gillyanne Kayes |
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Pubbl/distr/stampa |
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London, England ; ; New York, New York : , : Bloomsbury Methuen Drama, , 2013 |
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©2004 |
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ISBN |
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1-4081-1652-9 |
1-4742-6102-7 |
1-4081-4968-0 |
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Edizione |
[Second edition.] |
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Descrizione fisica |
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1 online resource (209 p.) |
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Disciplina |
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Soggetti |
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Singing - Instruction and study |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Cover; Contents; Acknowledgements; Foreword; Section 1: HOW THE VOICE WORKS; 1 How do I make the notes?; 2 My voice won''t come out at auditions; 3 But I thought I wasn''t supposed to feel anything!; 4 What exactly is support?; Section 2: TRAINING YOUR VOICE; 5 Developing the three octave siren; 6 The nasal port; 7 Dynamic control and projection; 8 Tuning the oral resonator; 9 Twang, the singer''s formant; Section 3: WORKING THE TEXT; 10 Putting it together; 11 Singing the text; 12 Creating voice qualities; 13 The act of singing; Afterword; Glossary; A; B; C; F; G; H; I; L; M; N; O; P; R; S |
VList of exercises and song assignments; Index; A; B; C; D; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; V; W; Index of song titles |
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Sommario/riassunto |
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<P>Classical singing training is no longer relevant for the theatre performer today. So how does an actor train his singing voice? </P> <P>Now in its second edition, this practical handbook takes the reader through <B>a step-by-step training programme relevant to the modern singing actor and dancer</B>. A variety of contemporary voice qualities including belting and twang are explained, with exercises for each topic. </P> |
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3. |
Record Nr. |
UNINA9910739476403321 |
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Autore |
Lopes Noel |
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Titolo |
Machine Learning for Adaptive Many-Core Machines - A Practical Approach / / by Noel Lopes, Bernardete Ribeiro |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (251 p.) |
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Collana |
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Studies in Big Data, , 2197-6503 ; ; 7 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Artificial intelligence |
Operations research |
Decision making |
Computational Intelligence |
Artificial Intelligence |
Operations Research/Decision Theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Introduction -- Supervised Learning -- Unsupervised and Semi-supervised Learning -- Large-Scale Machine Learning. |
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Sommario/riassunto |
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The overwhelming data produced everyday and the increasing performance and cost requirements of applications is transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data. This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a Big Learning framework. It is not intended to be a comprehensive survey of the state of the art of the whole field of machine learning for Big Data. Its purpose is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML algorithms, not viewed |
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as a universal solution for the Big Data challenges but rather as part of the answer, which may require the use of different strategies coupled together. |
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