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Institution

Eindhoven University of Technology

EducationEindhoven, Noord-Brabant, Netherlands
About: Eindhoven University of Technology is a education organization based out in Eindhoven, Noord-Brabant, Netherlands. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 22309 authors who have published 52936 publications receiving 1584164 citations. The organization is also known as: Technische Hogeschool Eindhoven & TU/e.


Papers
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Journal ArticleDOI
TL;DR: A framework for adaptive hypermedia systems (AHS) is introduced and some popular methods and techniques for adaptation are described, to illustrate the potential benefits of using adaptation in hypermedia applications.
Abstract: The navigational freedom in conventional hypermedia applications leads to comprehension and orientation problems (Nielsen 1990). Adaptive hypermedia attempts to overcome these problems by adapting the presentation of information and the overall link structure, based on a user model. This paper introduces a framework for adaptive hypermedia systems (AHS). It briefly describes some popular methods and techniques for adaptation. Examples and evaluations of existing AHS are used to illustrate the potential benefits of using adaptation in hypermedia applications.

318 citations

Journal ArticleDOI
TL;DR: Temperature-sensitive liposomes co-encapsulating doxorubicin and 250 mM [Gd(HPDO3A)(H₂O)] were evaluated for HIFU-mediated drug delivery under MR image guidance and a good correlation between the ΔR₁, the uptake and the gadolinium concentration in the tumor was found.

318 citations

Journal ArticleDOI
TL;DR: In this article, a detailed historical case study of the transition from surface water to piped water and personal hygiene (1870-1930) is used to analyse how these changes influenced each other in a co-evolution process.

318 citations

Book ChapterDOI
05 Sep 2006
TL;DR: This paper describes how machine learning techniques can be leveraged for decision mining, and presents a Decision Miner implemented within the ProM framework.
Abstract: Process-aware Information Systems typically log events (e.g., in transaction logs or audit trails) related to the actual business process executions. Proper analysis of these execution logs can yield important knowledge that can help organizations to improve the quality of their services. Starting from a process model, which can be discovered by conventional process mining algorithms, we analyze how data attributes influence the choices made in the process based on past process executions. Decision mining, also referred to as decision point analysis, aims at the detection of data dependencies that affect the routing of a case. In this paper we describe how machine learning techniques can be leveraged for this purpose, and we present a Decision Miner implemented within the ProM framework.

318 citations

Journal ArticleDOI
TL;DR: An extensive overview on a number of extensions to the lattice Boltzmann method which allow to study multiphase and multicomponent flows on a pore scale level are given.
Abstract: Over the last two decades, lattice Boltzmann methods have become an increasingly popular tool to compute the flow in complex geometries such as porous media. In addition to single phase simulations allowing, for example, a precise quantification of the permeability of a porous sample, a number of extensions to the lattice Boltzmann method are available which allow to study multiphase and multicomponent flows on a pore scale level. In this article we give an extensive overview on a number of these diffuse interface models and discuss their advantages and disadvantages. Furthermore, we shortly report on multiphase flows containing solid particles, as well as implementation details and optimization issues.

318 citations


Authors

Showing all 22539 results

NameH-indexPapersCitations
Hans Clevers199793169673
Richard H. Friend1691182140032
J. Fraser Stoddart147123996083
Jean-Luc Brédas134102685803
Ulrich S. Schubert122222985604
Christoph J. Brabec12089668188
Daniel I. Sessler11997360318
Can Li116104960617
Vikram Deshpande11173244038
D. Grahame Hardie10927653856
Wil M. P. van der Aalst10872542429
Jacob A. Moulijn10875447505
Vincent M. Rotello10876652473
Silvia Bordiga10749841413
David N. Reinhoudt107108248814
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202397
2022345
20212,907
20203,096
20192,584