Institution
Jožef Stefan Institute
Facility•Ljubljana, 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 published on a yearly basis
Papers
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TL;DR: In this article, a configurable charge-coupled device (CCD) detector is used in a scanning transmission x-ray microscope to record the transmitted intensity distribution for every pixel in a raster scan of the sample.
Abstract: A configurable charge-coupled-device (CCD) detector is used in a scanning transmission x-ray microscope to record the transmitted intensity distribution for every pixel in a raster scan of the sample. Real-time processing of the CCD frames gives simultaneous absorption and phase contrast image signals from a single scan. The CCD combines fast frame-transfer readout with very high sensitivity and makes use of x-ray to visible-light coupling to allow operation over a wide range of photon energies, from the oxygen K edge upwards. Tests on the Twinmic end station at the Elettra synchrotron are reported.
107 citations
TL;DR: In this paper, an electrochemical study was performed for Cu-xNi alloys (x = 10 to 40 wt%) and Cu and Ni metals in slightly alkaline solution, pH = 9.2, with constants a and b being strongly dependent on the nickel content in the alloy and the chloride concentration range.
107 citations
TL;DR: This paper provides a brief overview of the feature subset selection techniques that are commonly used in machine learning and shows performance of several methods on document categorization of real-world data.
Abstract: Dimensionality reduction is a commonly used step in machine learning, especially when dealing with a high dimensional space of features. The original feature space is mapped onto a new, reduced dimensionally space. The dimensionality reduction is usually performed either by selecting a subset of the original dimensions or/and by constructing new dimensions. This paper deals with feature subset selection for dimensionality reduction in machine learning. We provide a brief overview of the feature subset selection techniques that are commonly used in machine learning. Detailed description is provided for feature subset selection as commonly used on text data. For illustration, we show performance of several methods on document categorization of real-world data.
107 citations
TL;DR: Carboxymethylation of papain seems to have prevented the formation of the genuine binding geometry between a papain-like enzyme and a cystatin-type inhibitor as the authors observe it in the structure presented here.
106 citations
TL;DR: Two dimensional (2D) graphene and its derivatives modification with nanomaterials for formation of hybrid/nanocomposites undergo stimulus-induced optical and electrical changes which are important.
Abstract: Two dimensional (2D) graphene and its derivatives modification with nanomaterials for formation of hybrid/nanocomposites undergo stimulus-induced optical and electrical changes which are important ...
106 citations
Authors
Showing all 3879 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Vladimir Cindro | 129 | 1157 | 82000 |
| Igor Mandić | 128 | 1065 | 79498 |
| Jure Leskovec | 127 | 473 | 89014 |
| Matej Orešič | 82 | 352 | 26830 |
| P. Križan | 78 | 749 | 26408 |
| Jose Miguel Miranda | 76 | 336 | 18080 |
| Vito Turk | 74 | 271 | 23205 |
| Andrii Tykhonov | 73 | 270 | 24864 |
| Masashi Yokoyama | 73 | 310 | 18817 |
| Kostya Ostrikov | 72 | 763 | 21442 |
| M. Starič | 71 | 530 | 19136 |
| Boris Turk | 67 | 231 | 27006 |
| Bostjan Kobe | 66 | 279 | 17592 |
| Jure Zupan | 61 | 228 | 12054 |
| Mario Sannino | 60 | 281 | 17144 |