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Institution

University of California

EducationOakland, California, United States
About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a plane strain bimaterial block with an initial central crack is analyzed numerically for a plane-strain bimmaterial block and the resistance to crack initiation and the crack speed history is predicted without invoking any ad hoc failure criterion.
Abstract: Dynamic crack growth is analyzed numerically for a plane strain bimaterial block with an initial central crack. The material on each side of the bond line is characterized by an isotropic hyperelastic constitutive relation. A cohesive surface constitutive relation is also specified that relates the tractions and displacement jumps across the bond line and that allows for the creation of new free surface. The resistance to crack initiation and the crack speed history are predicted without invoking any ad hoc failure criterion. Full finite strain transient analyses are carried out, with two types of loading considered; tensile loading on one side of the specimen and crack face loading. The crack speed history and the evolution of the crack tip stress state are investigated for parameters characterizing a PMMA/Al bimaterial. Additionally, the separate effects of elastic modulus mismatch and elastic wave speed mismatch on interface crack growth are explored for various PMMA-artificial material combinations. The mode mixity of the near tip fields is found to increase with increasing crack speed and in some cases large scale contact occurs in the vicinity of the crack tip. Crack speeds that exceed the smaller of the two Rayleigh wave speeds are also found.

220 citations

Book ChapterDOI
TL;DR: This document1 contains definitions of a wide range of concepts specific to and widely used within temporal databases, as well as discussions of the adopted names.
Abstract: This document1 contains definitions of a wide range of concepts specific to and widely used within temporal databases. In addition to providing definitions, the document also includes explanations of concepts as well as discussions of the adopted names.

220 citations

Journal ArticleDOI
TL;DR: In this article, a new realization of asymmetric dark matter is presented, in which the dark matter and lepton asymmetries are generated simultaneously through two-sector leptogenesis.
Abstract: We present a new realization of asymmetric dark matter in which the dark matter and lepton asymmetries are generated simultaneously through two-sector leptogenesis. The right-handed neutrinos couple both to the Standard Model and to a hidden sector where the dark matter resides. This framework explains the lepton asymmetry, dark matter abundance and neutrino masses all at once. In contrast to previous realizations of asymmetric dark matter, the model allows for a wide range of dark matter masses, from keV to 10 TeV. In particular, very light dark matter can be accommodated without violating experimental constraints. We discuss several variants of our model that highlight interesting phenomenological possibilities. In one, late decays repopulate the symmetric dark matter component, providing a new mechanism for generating a large annihilation rate at the present epoch and allowing for mixed warm/cold dark matter. In a second scenario, dark matter mixes with the active neutrinos, thus presenting a distinct method to populate sterile neutrino dark matter through leptogenesis. At late times, oscillations and dark matter decays lead to interesting indirect detection signals.

220 citations

Book ChapterDOI
13 Oct 2003
TL;DR: In this article, learning-based anomaly detection systems build models of the expected behavior of applications by analyzing events that are generated during their normal operation, and subsequent events are analyzed to identify deviations, given the assumption that anomalies usually represent evidence of an attack.
Abstract: Learning-based anomaly detection systems build models of the expected behavior of applications by analyzing events that are generated during their normal operation. Once these models have been established, subsequent events are analyzed to identify deviations, given the assumption that anomalies usually represent evidence of an attack.

220 citations

Book ChapterDOI
01 Jan 1993
TL;DR: In 1990, the 9 Fermat number was factored into primes by means of a new algorithm, the number field sieve, which was proposed by John Pollard as mentioned in this paper.
Abstract: In 1990, the ninth Fermat number was factored into primes by means of a new algorithm, the “number field sieve”, which was proposed by John Pollard. The present paper is devoted to the description and analysis of a more general version of the number field sieve. It should be possible to use this algorithm to factor arbitrary integers into prime factors, not just integers of a special form like the ninth Fermat number. Under reasonable heuristic assumptions, the analysis predicts that the time needed by the general number field sieve to factor n is exp((c+o(1))(logn)1/3(loglogn)2/3) (for n → ∞), where c=(64/9)1/3=1.9223. This is asymptotically faster than all other known factoring algorithms, such as the quadratic sieve and the elliptic curve method.

220 citations


Authors

Showing all 55232 results

NameH-indexPapersCitations
Meir J. Stampfer2771414283776
George M. Whitesides2401739269833
Michael Karin236704226485
Fred H. Gage216967185732
Rob Knight2011061253207
Martin White1962038232387
Simon D. M. White189795231645
Scott M. Grundy187841231821
Peidong Yang183562144351
Patrick O. Brown183755200985
Michael G. Rosenfeld178504107707
George M. Church172900120514
David Haussler172488224960
Yang Yang1712644153049
Alan J. Heeger171913147492
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202322
2022105
2021775
20201,069
20191,225
20181,684