1.

Record Nr.

UNINA9910228474703321

Titolo

Vancouver express

Pubbl/distr/stampa

Vancouver, : Pugstem Publications

Descrizione fisica

1 online resource

Disciplina

071/.1133

Soggetti

Canadian newspapers (English) - British Columbia - Vancouver

Journaux canadiens-anglais - Colombie-Britannique - Vancouver

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Periodico

Note generali

Title varies on Friday issues.

Published Feb. 21-May 12, 1970; and, Nov. 3, 1978-June 22, 1979 during labour disputes at the Vancouver province and the Vancouver sun.



2.

Record Nr.

UNINA9910557717703321

Autore

Chinesta Francisco

Titolo

Empowering Materials Processing and Performance from Data and AI

Pubbl/distr/stampa

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

Descrizione fisica

1 online resource (156 p.)

Soggetti

Technology: general issues

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Sommario/riassunto

Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new materials and products. Additionally, this gives rise to new paradigms in bridging raw material data and processing to the induced properties and performance. This present topical issue is a compilation of contributions on novel ideas and concepts, addressing several key challenges using data and artificial intelligence, such as:- proposing new techniques for data generation and data mining;- proposing new techniques for visualizing, classifying, modeling, extracting knowledge, explaining and certifying data and data-driven models;- processing data to create data-driven models from scratch when other models are absent, too complex or too poor for making valuable predictions;- processing data to enhance existing physic-based models to improve the quality of the prediction capabilities and, at the same time, to enable data to be smarter; and- processing data to create data-driven enrichment of existing models when physics-based models exhibit limits within a hybrid paradigm.