Jožef Stefan Institute

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.

Advances in Robot Kinematics

Abstract: From the Publisher: This book presents the most recent research advances in the theory, design, control and application of robotic systems, which are intended for a variety of purposes such as manipulation, manufacturing, automation, surgery, locomotion and biomechanics. The issues addressed are fundamentally kinematic in nature, including synthesis, calibration, redundancy, force control, dexterity, inverse and forward kinematics, kinematic singularities, as well as over-constrained systems. Methods used include line geometry, quaternion algebra, screw algebra, and linear algebra. These methods are applied to both parallel and serial multi-degree-of-freedom systems. The results should interest researchers, teachers, and students, in fields of engineering and mathematics related to robot theory, design, control and application.

javaPlex: A research software package for persistent (co)homology

Abstract: The computation of persistent homology has proven a fundamental component of the nascent field of topological data analysis and computational topology. We describe a new software package for topological computation, with design focus on needs of the research community. This tool, replacing previous jPlex and Plex, enables researchers to access state of the art algorithms for persistent homology, cohomology, hom complexes, filtered simplicial complexes, filtered cell complexes, witness complex constructions, and many more essential components of computational topology.

Technology developments and first measurements of Low Gain Avalanche Detectors (LGAD) for high energy physics applications

Abstract: This paper introduces a new concept of silicon radiation detector with intrinsic multiplication of the charge, called Low Gain Avalanche Detector (LGAD). These new devices are based on the standard Avalanche Photo Diodes (APD) normally used for optical and X-ray detection applications. The main differences to standard APD detectors are the low gain requested to detect high energy charged particles, and the possibility to have fine segmentation pitches: this allows fabrication of microstrip or pixel devices which do not suffer from the limitations normally found [1] in avalanche detectors. In addition, a moderate multiplication value will allow the fabrication of thinner devices with the same output signal of standard thick substrates. The investigation of these detectors provides important indications on the ability of such modified electrode geometry to control and optimize the charge multiplication effect, in order to fully recover the collection efficiency of heavily irradiated silicon detectors, at reasonable bias voltage, compatible with the voltage feed limitation of the CERN High Luminosity Large Hadron Collider (HL-LHC) experiments [2] . For instance, the inner most pixel detector layers of the ATLAS tracker will be exposed to fluences up to 2×10 16 1 MeV n eq /cm 2 , while for the inner strip detector region fluences of 1×10 15 n eq /cm 2 are expected. The gain implemented in the non-irradiated devices must retain some effect also after irradiation, with a higher multiplication factor with respect to standard structures, in order to be used in harsh environments such those expected at collider experiments.

The evaluation of waste, surface and ground water quality using the Allium test procedure.

Abstract: The bulbs of Allium cepa were grown in test liquids of various pollution levels as follows: undiluted industrial and municipal waste water; biological treatment plant output water; water from the Drava river upstream and downstream of the city of Maribor; and non-chlorinated drinking water as a negative control test. The paper presents the response of the Allium cepa genetic material to the presence of potential cytotoxic and genotoxic substances in test liquids and the suitability of the Allium cepa testing procedure as a method for short-term determination of water pollution level. The suitability of the Allium test procedure as a system for environmental monitoring is presented. The influence of water pollution on macroscopic and cytologic parameters of the common onion by application of the biological testing method was examined. The macroscopic parameter was inhibition of root growth. The cytological parameters were: aberrant cells in metaphase and anaphase, index of micronuclei appearance and inhibition of cell division. The possibility of categorization the different polluted test liquids into quality classes is presented according to the influence of the test liquids on macroscopic and cytologic parameters. Test liquids are divided into 8 quality classes: the first class is the least polluted surface waters, the second and the third classes are more polluted surface water, the fourth and the fifth classes are biological treatment plant output waters, the sixth till the eighth quality classes are untreated waste waters. The most polluted test liquids (untreated industrial and municipal waste waters) caused sublethal and even lethal effects. The most polluted tested liquids cause the inhibition of root growth over 50% (even up to 74%), decrease of mitotic index over 36% (even up to 66%), increase of presence of interphase cells with micronuclei over 3% and increase of presence of aberrant cells for more than 10 times in comparison to control test.

Multi-relational data mining: an introduction

Abstract: Data mining algorithms look for patterns in data. While most existing data mining approaches look for patterns in a single data table, multi-relational data mining (MRDM) approaches look for patterns that involve multiple tables (relations) from a relational database. In recent years, the most common types of patterns and approaches considered in data mining have been extended to the multi-relational case and MRDM now encompasses multi-relational (MR) association rule discovery, MR decision trees and MR distance-based methods, among others. MRDM approaches have been successfully applied to a number of problems in a variety of areas, most notably in the area of bioinformatics. This article provides a brief introduction to MRDM, while the remainder of this special issue treats in detail advanced research topics at the frontiers of MRDM.