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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: In this paper, the association of prenatal mercury exposure from maternal fish consumption with child neurodevelopment in northern Italy was examined by using the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III).

87 citations

Journal ArticleDOI
25 Jun 2003
TL;DR: This paper presents a humanoid robotic shoulder complex and the kinematics of humanoid humeral pointing as performed by this complex, which is composed of a parallel mechanism which serves as the innermost shoulder girdle and a serial mechanism which serving as the outermost spherical glenohumeral joint.
Abstract: This paper presents a humanoid robotic shoulder complex and the kinematics of humanoid humeral pointing as performed by this complex. The humanoid shoulder complex is composed of two subsystems, a parallel mechanism which serves as the innermost shoulder girdle and a serial mechanism which serves as the outermost spherical glenohumeral joint. These two subsystems are separated by an offset distance and a twist angle. The subsystems operate cooperatively as an offset double pointing system. Humanoid humeral pointing is defined as a configuration in which the displacement of the shoulder girdle and the humerus are coplanar, and in which a ratio between an inclination angle in each subsystem achieves a constant value consistent with human humeral pointing. One redundant degree of freedom remains in the humanoid shoulder girdle, and it can be used to optimize system configuration and operating criteria, such as avoiding the singular cones of the humanoid glenohumeral joint.

87 citations

Book ChapterDOI
06 Sep 2007
TL;DR: The results of the experiments show that the proposed approach has a comparable performance to that of random forests, with the added advantage of being applicable to any base-level algorithm without the need to randomize the latter.
Abstract: Random forests are one of the best performing methods for constructing ensembles They derive their strength from two aspects: using random subsamples of the training data (as in bagging) and randomizing the algorithm for learning base-level classifiers (decision trees) The base-level algorithm randomly selects a subset of the features at each step of tree construction and chooses the best among these We propose to use a combination of concepts used in bagging and random subspaces to achieve a similar effect The latter randomly select a subset of the features at the start and use a deterministic version of the base-level algorithm (and is thus somewhat similar to the randomized version of the algorithm) The results of our experiments show that the proposed approach has a comparable performance to that of random forests, with the added advantage of being applicable to any base-level algorithm without the need to randomize the latter

87 citations

Journal ArticleDOI
P. Abreu1, Marco Aglietta2, Marco Aglietta3, Eun-Joo Ahn4  +556 moreInstitutions (65)
TL;DR: In this paper, the authors present a radio analysis framework for the analysis of radio measurements of cosmic ray air showers of the Pierre Auger Radio Array (AERA) in conjunction with the surface particle detectors and fluorescence telescopes.
Abstract: The advent of the Auger Engineering Radio Array (AERA) necessitates the development of a powerful framework for the analysis of radio measurements of cosmic ray air showers. As AERA performs "radio-hybrid" measurements of air shower radio emission in coincidence with the surface particle detectors and fluorescence telescopes of the Pierre Auger Observatory, the radio analysis functionality had to be incorporated in the existing hybrid analysis solutions for fluorescence and surface detector data. This goal has been achieved in a natural way by extending the existing Auger Offline software framework with radio functionality. In this article, we lay out the design, highlights and features of the radio extension implemented in the Auger Offline framework. Its functionality has achieved a high degree of sophistication and offers advanced features such as vectorial reconstruction of the electric field, advanced signal processing algorithms, a transparent and efficient handling of FFTs, a very detailed simulation of detector effects, and the read-in of multiple data formats including data from various radio simulation codes. The source code of this radio functionality can be made available to interested parties on request. (C) 2011 Elsevier B.V. All rights reserved.

87 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present numerical results within the one-dimensional disordered Hubbard model for several characteristic indicators of the many-body localization (MBL), and they find that even at strong disorder all signatures consistently show that while charge degree of freedom is nonergodic, the spin is delocalized and ergodic.
Abstract: We present numerical results within the one-dimensional disordered Hubbard model for several characteristic indicators of the many-body localization (MBL). Considering traditionally studied charge disorder (i.e., the same disorder strength for both spin orientations) we find that even at strong disorder all signatures consistently show that while charge degree of freedom is nonergodic, the spin is delocalized and ergodic. This indicates the absence of the full MBL in the model that has been simulated in recent cold-atom experiments. Full localization can be restored if spin-dependent disorder is used instead.

87 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