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[null,"1.","Record Nr.",null,"UNISALENTO991000878039707536"]
[null,null,"Autore",null,"Birman, M. Sh."]
[null,null,"Titolo",null,"Estimates and asymptotics for discrete spectra of integral and differential equations / M. Sh. Birman, editor"]
[null,null,"Pubbl/distr/stampa",null,"Providence, R.I. : American Mathematical Society, c1991"]
[null,null,"ISBN",null,"0821841068"]
[null,null,"Descrizione fisica",null,"x, 204 p. ; 27 cm"]
[null,null,"Collana",null,"Advances in soviet mathematics, ISSN 10518037 ; 7"]
[null,null,"Classificazione",null,"AMS 34L20"]
[{"$nulls":4},"AMS 35-06"]
[{"$nulls":4},"AMS 35J10"]
[{"$nulls":4},"AMS 35P20"]
[{"$nulls":4},"AMS 35P30"]
[{"$nulls":4},"AMS 45A05"]
[{"$nulls":4},"AMS 47A05"]
[{"$nulls":4},"AMS 47B99"]
[{"$nulls":4},"AMS 47G30"]
[null,null,"Disciplina",null,"515.353"]
[null,null,"Soggetti",null,"Differential equations-asymptotic theory"]
[{"$nulls":4},"Integral equations-asymptotic theory"]
[{"$nulls":4},"Schrodinger operator-Spectra"]
[{"$nulls":4},"Spectral theory (Mathematics)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"The papers of this collection contain adapted expositions of a series of talks on spectral theory given to the Leningrad Seminar on Mathematical Physics in the academic year of 1989-90.\": editor's preface."]
[{"$nulls":4},"Includes bibliographical references"]
[null,"2.","Record Nr.",null,"UNINA9910404080803321"]
[null,null,"Autore",null,"Etcheverry Venturini Lorena"]
[null,null,"Titolo",null,"Overcoming Data Scarcity in Earth Science"]
[null,null,"Pubbl/distr/stampa",null,"MDPI - Multidisciplinary Digital Publishing Institute, 2020"]
[null,null,"ISBN",null,"3-03928-211-5"]
[null,null,"Descrizione fisica",null,"1 online resource (94 p.)"]
[null,null,"Soggetti",null,"History of engineering and technology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response's complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales."]