1.

Record Nr.

UNISA990003071480203316

Autore

BARLASSINA, Felice M.

Titolo

Parentela e trasmissione ereditaria in Senegal : fra tradizione e modernità / Felice M. Barlassina

Pubbl/distr/stampa

Torino : L'harmattan Italia, copyr, . 2000

ISBN

88-87605-25-4

Descrizione fisica

235 p. ; 21 cm

Collana

Il politico e la memoria

Disciplina

346.663015

Soggetti

Diritto di famiglia - Senegal

Collocazione

0730

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia



2.

Record Nr.

UNINA9910557604303321

Autore

McClintock P. V. E

Titolo

Physics of Ionic Conduction in Narrow Biological and Artificial Channels

Pubbl/distr/stampa

Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021

Descrizione fisica

1 online resource (306 p.)

Soggetti

Research and information: general

Technology: general issues

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Sommario/riassunto

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.



3.

Record Nr.

UNINA9910300246703321

Autore

Biau Gérard

Titolo

Lectures on the Nearest Neighbor Method / / by Gérard Biau, Luc Devroye

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015

ISBN

3-319-25388-3

Edizione

[1st ed. 2015.]

Descrizione fisica

IX, 290 p. ; : il. en col

Collana

Springer Series in the Data Sciences, , 2365-5674

Disciplina

510

Soggetti

Probabilities

Pattern perception

Statistics

Probability Theory and Stochastic Processes

Pattern Recognition

Statistics and Computing/Statistics Programs

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

MSC 68Wxx ; 60Exx ; 62Exx ; 68T10

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

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.

Sommario/riassunto

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



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).   .