1.

Record Nr.

UNISA990002285220203316

Autore

ONADO, Marco

Titolo

Banca e sistema finanziario / Marco Onado

Pubbl/distr/stampa

Bologna : Il Mulino, 1988

Descrizione fisica

315 p. ; 22 cm

Collana

La nuova scienza , Serie di economia

Disciplina

332

Soggetti

Banche - Italia

Collocazione

COLL. AW 38 bis

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910782214403321

Autore

Killick Tim

Titolo

British short fiction in the early nineteenth century [[electronic resource] ] : the rise of the tale / / Tim Killick

Pubbl/distr/stampa

Aldershot, England ; ; Burlington, VT, : Ashgate, c2008

ISBN

1-315-57029-7

1-317-17146-2

1-317-17145-4

1-281-79858-4

9786611798581

0-7546-8212-9

Descrizione fisica

1 online resource (200 p.)

Disciplina

823/.0109

Soggetti

English fiction - 19th century - History and criticism

Literary form - History - 19th century

Short stories, English - History and criticism

Short story

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa



Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. [165]-187) and index.

Nota di contenuto

Cover; Contents; Acknowledgements; Introduction; 1 Overview: Short Fiction in the Early Nineteenth Century; 2 Washington Irving: Geoffrey Crayon and the Market for Short Fiction; 3 Improving Stories: Women Writers, Morality, and Short Fiction; 4 Regionalism and Folklore: Local Stories and Traditional Forms; Conclusion: Short Fiction in the 1830's; Bibliography; Index

Sommario/riassunto

Contextualizing British short fiction within the broader context of Romantic-era print culture, Tim Killick argues that authors such as Washington Irving, Mary Russell Mitford, and James Hogg championed the use of short fiction during a period predominantly associated with novel-writing and poetry. His book makes a convincing case for the evolution of short fiction into a self-conscious and modern genre, with its own techniques and imperatives, separate from those of the novel.

3.

Record Nr.

UNINA9910896181303321

Autore

Franke Jürgen

Titolo

Statistical Machine Learning for Engineering with Applications / / edited by Jürgen Franke, Anita Schöbel

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024

ISBN

3-031-66253-9

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (393 pages)

Collana

Lecture Notes in Statistics, , 2197-7186 ; ; 227

Altri autori (Persone)

SchöbelAnita

Disciplina

006.31

Soggetti

Statistics

Machine learning

Statistical Theory and Methods

Machine Learning

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences

Aprenentatge automàtic

Estadística

Llibres electrònics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa



Livello bibliografico

Monografia

Nota di contenuto

- An Introduction of Statistical Learning for Engineers -- Machine Learning for Inline Surface Inspection Systems - Challenges, Approaches, and Application Example -- Gaussian Process Regression for the Prediction of Cable Bundle Characteristics -- Machine Learning for Predictive Maintenance in Production Environments -- Detecting Healthcare Fraud Using Hybrid Machine Learning for Document Digitization -- Cracks in concrete -- Machine learning methods for prediction of breakthrough curves in reactive porous media -- Segmentation and Aggregation in Text Classification -- Hardware-aware Neural Architecture Search -- Optimal Experimental Design Supported by Machine Learning Regression Models -- Data Analytics, Artificial Intelligence and Machine Learning in Mobility and Vehicle Engineering.

Sommario/riassunto

This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related methods. For ease of reading, technical details are avoided as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed. The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis. The focus is on fundamental ideas, applicability and the pitfalls of machine learning in industry and science, where data are often scarce. Requiring only very basic background in statistics, the book is ideal for self-study or short courses for engineering and science students.