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Institution

University of Stuttgart

EducationStuttgart, Germany
About: University of Stuttgart is a(n) education organization based out in Stuttgart, Germany. It is known for research contribution in the topic(s): Laser & Finite element method. The organization has 27715 authors who have published 56370 publication(s) receiving 1363382 citation(s). The organization is also known as: Universität Stuttgart.


Papers
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Book
01 Jan 2008
TL;DR: In this article, the authors present an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections.
Abstract: Class-tested and coherent, this groundbreaking new textbook teaches web-era information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.

11,798 citations

Journal ArticleDOI
D. Andrae1, U. Huermann1, Michael Dolg1, Hermann Stoll1, H. Preu1 
TL;DR: In this paper, nonrelativistic and quasirelativisticab initio pseudopotentials substituting the M(Z−28)+-core orbitals of the second row transition elements and the M (Z−60)+- core orbitals, respectively, and optimized (8s7p6d)/[6s5p3d]-GTO valence basis sets for use in molecular calculations were generated.
Abstract: Nonrelativistic and quasirelativisticab initio pseudopotentials substituting the M(Z−28)+-core orbitals of the second row transition elements and the M(Z−60)+-core orbitals of the third row transition elements, respectively, and optimized (8s7p6d)/[6s5p3d]-GTO valence basis sets for use in molecular calculations have been generated. Additionally, corresponding spin-orbit operators have also been derived. Atomic excitation and ionization energies from numerical HF as well as from SCF pseudopotential calculations using the derived basis sets differ in most cases by less than 0.1 eV from corresponding numerical all-electron results. Spin-orbit splittings for lowlying states are in reasonable agreement with corresponding all-electron Dirac-Fock (DF) results.

6,341 citations

Journal ArticleDOI
TL;DR: In this paper, the correlation contributions to ionization energies, electron affinities and dissociation energies of first-row atoms, ions and molecules were calculated using density functionals.
Abstract: Two recently published density functionals (A.D. Becke, J. Chem. Phys. 88 (1988) 1053 and C. Lee, W. Yang and R.G. Parr, Phys. Rev. B 37 (1988) 785) are used to calculate the correlation energies of first-row atoms, ions and molecules. The correlation contributions to ionization energies, electron affinities and dissociation energies thus obtained are of comparable quality to those of other density functionals.

5,865 citations

Journal ArticleDOI
TL;DR: Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.
Abstract: It is suggested that the motion of pedestrians can be described as if they would be subject to ``social forces.'' These ``forces'' are not directly exerted by the pedestrians' personal environment, but they are a measure for the internal motivations of the individuals to perform certain actions (movements). The corresponding force concept is discussed in more detail and can also be applied to the description of other behaviors. In the presented model of pedestrian behavior several force terms are essential: first, a term describing the acceleration towards the desired velocity of motion; second, terms reflecting that a pedestrian keeps a certain distance from other pedestrians and borders; and third, a term modeling attractive effects. The resulting equations of motion of nonlinearly coupled Langevin equations. Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.

4,832 citations

Journal ArticleDOI
TL;DR: The steep dispersion of the Fano resonance profile promises applications in sensors, lasing, switching, and nonlinear and slow-light devices.
Abstract: Since its discovery, the asymmetric Fano resonance has been a characteristic feature of interacting quantum systems. The shape of this resonance is distinctively different from that of conventional symmetric resonance curves. Recently, the Fano resonance has been found in plasmonic nanoparticles, photonic crystals, and electromagnetic metamaterials. The steep dispersion of the Fano resonance profile promises applications in sensors, lasing, switching, and nonlinear and slow-light devices.

3,211 citations


Authors

Showing all 27715 results

NameH-indexPapersCitations
Yi Chen2174342293080
Robert J. Lefkowitz214860147995
Michael Kramer1671713127224
Andrew G. Clark140823123333
Stephen D. Walter11251357012
Fedor Jelezko10341342616
Ulrich Gösele10260346223
Dirk Helbing10164256810
Ioan Pop101137047540
Niyazi Serdar Sariciftci9959154055
Matthias Komm9983243275
Hans-Joachim Werner9831748508
Richard R. Ernst9635253100
Xiaoming Sun9638247153
Feng Chen95213853881
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202249
20212,587
20202,646
20192,654
20182,525
20172,568