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Institution

Jožef Stefan Institute

FacilityLjubljana, Slovenia
About: Jožef Stefan Institute is a facility organization based out in Ljubljana, Slovenia. It is known for research contribution in the topics: Liquid crystal & Dielectric. The organization has 3828 authors who have published 12614 publications receiving 291025 citations.


Papers
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Journal ArticleDOI
TL;DR: Diluted magnetic semiconductors with a Curie temperature exceeding 300 K are promising candidates for spintronic devices and spin-based electronic technologies.
Abstract: Diluted magnetic semiconductors with a Curie temperature exceeding 300 K are promising candidates for spintronic devices and spin-based electronic technologies We review recent achievements in the field of one of them: Co-doped ZnO at the nanoparticulate scale

124 citations

Journal ArticleDOI
TL;DR: The AcerMC Monte Carlo Event Generator as discussed by the authors is dedicated for the generation of Standard Model background processes at pp LHC collisions, which is based on the multi-channel self-optimizing approach as proposed in NEXTCALIBUR event generator.

124 citations

Journal ArticleDOI
TL;DR: In this paper, a simple but effective "on water" bromination of ketones with an aqueous H2O2-HBr system is described, which is characterised by the use of inexpensive reagents, a lower impact on the environment and the absence of organic waste that make it a good alternative to existing Bromination methods.

124 citations

Journal ArticleDOI
TL;DR: A new methodology for learning and adaption of manipulation skills that involve physical contact with the environment, based on dynamic movement primitives and quaternion representation of orientation, which provide a mathematical machinery for efficient and stable adaptation.
Abstract: We propose a new methodology for learning and adaption of manipulation skills that involve physical contact with the environment. Pure position control is unsuitable for such tasks because even small errors in the desired trajectory can cause significant deviations from the desired forces and torques. The proposed algorithm takes a reference Cartesian trajectory and force/torque profile as input and adapts the movement so that the resulting forces and torques match the reference profiles. The learning algorithm is based on dynamic movement primitives and quaternion representation of orientation, which provide a mathematical machinery for efficient and stable adaptation. Experimentally we show that the robot's performance can be significantly improved within a few iteration steps, compensating for vision and other errors that might arise during the execution of the task. We also show that our methodology is suitable both for robots with admittance and for robots with impedance control.

124 citations

Journal ArticleDOI
TL;DR: In this paper, low-density foam glasses from cathode-ray-tube panel glass using carbon and MnO 2 as the foaming agents were prepared using fine glass powder.

124 citations


Authors

Showing all 3879 results

NameH-indexPapersCitations
Vladimir Cindro129115782000
Igor Mandić128106579498
Jure Leskovec12747389014
Matej Orešič8235226830
P. Križan7874926408
Jose Miguel Miranda7633618080
Vito Turk7427123205
Andrii Tykhonov7327024864
Masashi Yokoyama7331018817
Kostya Ostrikov7276321442
M. Starič7153019136
Boris Turk6723127006
Bostjan Kobe6627917592
Jure Zupan6122812054
Mario Sannino6028117144
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202331
202268
2021755
2020770
2019653
2018576