| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910785200803321 |
|
|
Autore |
Castillo Greg |
|
|
Titolo |
Cold war on the home front [[electronic resource] ] : the soft power of midcentury design / / Greg Castillo |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Minneapolis, : University of Minnesota Press, 2010 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Descrizione fisica |
|
1 online resource (306 p.) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Consumer goods - United States - History - 20th century |
Consumer goods - Soviet Union - History - 20th century |
Capitalism - United States - History - 20th century |
Socialism - United States - History - 20th century |
Cold War |
Propaganda, American |
Propaganda, Soviet |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Description based upon print version of record. |
|
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references and index. |
|
|
|
|
|
|
Nota di contenuto |
|
Contents; INTRODUCTION: Domesticity as a Weapon; 1 Household Affluence and Its Discontents; 2 Cultural Revolutions in Tandem; 3 Better Living through Modernism; 4 Stalinism by Design; 5 People's Capitalism and Capitalism's People; 6 The Trojan House Goes East; 7 Consuming Socialism; EPILOGUE: Critical Masses; Acknowledgments; Notes; Index |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
Amid a display of sunshine-yellow electric appliances in a model home at the 1959 American National Exhibition in Moscow, Soviet Premier Nikita Khrushchev and U.S. Vice President Richard Nixon squared off on the merits of their respective economic systems. One of the signature events of the cold war, the impromptu Kitchen Debate has been widely viewed as the opening skirmish in a propaganda war over which superpower could provide a better standard of living for its citizens. However, as Greg Castillo shows in Cold War on the Home Front, this debate and the American National Exhibition itself w |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9910366611103321 |
|
|
Autore |
Zhang Wengang |
|
|
Titolo |
MARS Applications in Geotechnical Engineering Systems : Multi-Dimension with Big Data / / by Wengang Zhang |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2020.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (XXI, 240 p. 99 illus., 64 illus. in color.) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Engineering geology |
Engineering—Geology |
Foundations |
Hydraulics |
Geotechnical engineering |
Big data |
Computer input-output equipment |
Geoengineering, Foundations, Hydraulics |
Geotechnical Engineering & Applied Earth Sciences |
Big Data |
Big Data/Analytics |
Input/Output and Data Communications |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Introduction -- MARS methodology -- Simple MARS modeling examples -- MARS use in prediction of collapse potential for compacted soils -- MARS use in prediction of diaphragm wall deflections in soft clays -- MARS use in HP-pile drivability assessment -- MARS use in assessment of soil liquefaction -- MARS use in evaluating entry-type excavation stability -- Summary and conclusions. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This book presents the application of a comparatively simple nonparametric regression algorithm, known as the multivariate adaptive regression splines (MARS) surrogate model, which can be used to approximate the relationship between the inputs and outputs, and express that relationship mathematically. The book first describes the |
|
|
|
|
|
|
|
|
|
|
MARS algorithm, then highlights a number of geotechnical applications with multivariate big data sets to explore the approach’s generalization capabilities and accuracy. As such, it offers a valuable resource for all geotechnical researchers, engineers, and general readers interested in big data analysis. . |
|
|
|
|
|
| |