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1. |
Record Nr. |
UNISA990003071480203316 |
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Autore |
BARLASSINA, Felice M. |
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Titolo |
Parentela e trasmissione ereditaria in Senegal : fra tradizione e modernità / Felice M. Barlassina |
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Pubbl/distr/stampa |
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Torino : L'harmattan Italia, copyr, . 2000 |
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ISBN |
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Descrizione fisica |
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Collana |
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Disciplina |
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Soggetti |
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Diritto di famiglia - Senegal |
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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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2. |
Record Nr. |
UNINA9910557604303321 |
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Autore |
McClintock P. V. E |
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Titolo |
Physics of Ionic Conduction in Narrow Biological and Artificial Channels |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
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Descrizione fisica |
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1 online resource (306 p.) |
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Soggetti |
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Research and information: general |
Technology: general issues |
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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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Sommario/riassunto |
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The book reprints a set of important scientific papers applying physics and mathematics to address the problem of selective ionic conduction in narrow water-filled channels and pores. It is a long-standing problem, and an extremely important one. Life in all its forms depends on ion channels and, furthermore, the technological applications of artificial ion channels are already widespread and growing rapidly. They include desalination, DNA sequencing, energy harvesting, molecular sensors, fuel cells, batteries, personalised medicine, and drug design. Further applications are to be anticipated.The book will be helpful to researchers and technologists already working in the area, or planning to enter it. It gives detailed descriptions of a diversity of modern approaches, and shows how they can be particularly effective and mutually reinforcing when used together. It not only provides a snapshot of current cutting-edge scientific activity in the area, but also offers indications of how the subject is likely to evolve in the future. |
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3. |
Record Nr. |
UNINA9910300246703321 |
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Autore |
Biau Gérard |
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Titolo |
Lectures on the Nearest Neighbor Method / / by Gérard Biau, Luc Devroye |
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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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IX, 290 p. ; : il. en col |
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Collana |
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Springer Series in the Data Sciences, , 2365-5674 |
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Disciplina |
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Soggetti |
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Probabilities |
Pattern perception |
Statistics |
Probability Theory and Stochastic Processes |
Pattern Recognition |
Statistics and Computing/Statistics Programs |
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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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MSC 68Wxx ; 60Exx ; 62Exx ; 68T10 |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Part I: Density Estimation -- Order Statistics and Nearest Neighbors -- The Expected Nearest Neighbor Distance -- The k-nearest Neighbor Density Estimate -- Uniform Consistency -- Weighted k-nearest neighbor density estimates.- Local Behavior -- Entropy Estimation -- Part II: Regression Estimation -- The Nearest Neighbor Regression Function Estimate -- The 1-nearest Neighbor Regression Function Estimate -- LP-consistency and Stone's Theorem -- Pointwise Consistency -- Uniform Consistency -- Advanced Properties of Uniform Order Statistics -- Rates of Convergence -- Regression: The Noisless Case -- The Choice of a Nearest Neighbor Estimate -- Part III: Supervised Classification -- Basics of Classification -- The 1-nearest Neighbor Classification Rule -- The Nearest Neighbor Classification Rule. Appendix -- Index. |
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Sommario/riassunto |
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This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas |
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for understanding, analyzing and developing nearest neighbor methods. Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal). . |
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