Institution
University of Stuttgart
Education•Stuttgart, Germany•
About: University of Stuttgart is a education organization based out in Stuttgart, Germany. It is known for research contribution in the topics: Laser & Finite element method. The organization has 27715 authors who have published 56370 publications receiving 1363382 citations. The organization is also known as: Universität Stuttgart.
Papers published on a yearly basis
Papers
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TL;DR: A general concept is presented which allows of setting up mathematical models for stochastic and quasi deterministic dynamic processes in social systems and the master equation for the probability distribution over appropriately chosen personal and material macrovariables of the society is presented.
Abstract: A general concept is presented which allows of setting up mathematical models for stochastic and quasi deterministic dynamic processes in social systems. The basis of this concept is the master equation for the probability distribution over appropriately chosen personal and material macrovariables of the society. The probabilistic transition rates depend on motivation potentials governing the decisions and actions of the social agents. The transition from the probability distribution to quasi-meanvalues leads to in general nonlinear coupled differential equations for the macrovariables of the chosen social sector. Up to now several models about population dynamics, collective political opinion formation, dynamics of economic processes and the formation of settlements have been published.
323 citations
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TL;DR: In this paper, five potential drivers of green supply management performance were identified in the literature review: Green supply management capabilities, the strategic level of the purchasing department, the level of environmental commitment, the degree of green supplier assessment, and the role of green collaboration with suppliers.
322 citations
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01 Aug 2010TL;DR: The passive-aggressive perceptron algorithm as a Hash Kernel is implemented and substantially improves the parsing times and takes into account the features of negative examples built during the training, which has lead to a higher accuracy.
Abstract: In addition to a high accuracy, short parsing and training times are the most important properties of a parser. However, parsing and training times are still relatively long. To determine why, we analyzed the time usage of a dependency parser. We illustrate that the mapping of the features onto their weights in the support vector machine is the major factor in time complexity. To resolve this problem, we implemented the passive-aggressive perceptron algorithm as a Hash Kernel. The Hash Kernel substantially improves the parsing times and takes into account the features of negative examples built during the training. This has lead to a higher accuracy. We could further increase the parsing and training speed with a parallel feature extraction and a parallel parsing algorithm. We are convinced that the Hash Kernel and the parallelization can be applied successful to other NLP applications as well such as transition based dependency parsers, phrase structrue parsers, and machine translation.
322 citations
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TL;DR: In this paper, the use of zeolites as media for hydrogen storage was investigated using different pore architecture and composition at temperatures from 293 to 573K and pressures from 2.5 to 10.0 MPa.
321 citations
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TL;DR: In this paper, the authors derive macroscopic traffic equations from specific gas-kinetic equations, dropping some of the assumptions and approximations made in previous papers, and the resulting partial differential equations for the vehicle density and average velocity contain a non-local interaction term which is very favorable for a fast and robust numerical integration, so that several thousand freeway kilometers can be simulated in real-time.
Abstract: We derive macroscopic traffic equations from specific gas-kinetic equations, dropping some of the assumptions and approximations made in previous papers. The resulting partial differential equations for the vehicle density and average velocity contain a non-local interaction term which is very favorable for a fast and robust numerical integration, so that several thousand freeway kilometers can be simulated in real-time. The model parameters can be easily calibrated by means of empirical data. They are directly related to the quantities characterizing individual driver-vehicle behavior, and their optimal values have the expected order of magnitude. Therefore, they allow to investigate the influences of varying street and weather conditions or freeway control measures. Simulation results for realistic model parameters are in good agreement with the diverse non-linear dynamical phenomena observed in freeway traffic.
320 citations
Authors
Showing all 28043 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
Robert J. Lefkowitz | 214 | 860 | 147995 |
Michael Kramer | 167 | 1713 | 127224 |
Andrew G. Clark | 140 | 823 | 123333 |
Stephen D. Walter | 112 | 513 | 57012 |
Fedor Jelezko | 103 | 413 | 42616 |
Ulrich Gösele | 102 | 603 | 46223 |
Dirk Helbing | 101 | 642 | 56810 |
Ioan Pop | 101 | 1370 | 47540 |
Niyazi Serdar Sariciftci | 99 | 591 | 54055 |
Matthias Komm | 99 | 832 | 43275 |
Hans-Joachim Werner | 98 | 317 | 48508 |
Richard R. Ernst | 96 | 352 | 53100 |
Xiaoming Sun | 96 | 382 | 47153 |
Feng Chen | 95 | 2138 | 53881 |