Heavy flavor production at HERA

Recent results of open charm and beauty production in electron proton scattering at HERA are presented. In photoproduction, the measured cross sections for charm exceed fixed order NLO QCD calculations. Experimental evidence supports the hypothesis that a significant fraction of photoproduction events with charm can be described by resolved photon processes, where the charm quark is a constituent of the resolved photon. In deep inelastic scattering the NLO calculations give in general a fairly reasonable description of the observed charm cross sections. The measurements of the structure function $F_2^{cc}$ show that, at large photon virtualities and low x, the events with charm constitute a major part of the total ep cross section. The beauty cross sections both in photoproduction and in DIS exceed NLO predictions.Comment: 6 pages, 9 figures in eps, talk given at XXXI International Symposium on Multiparticle Dynamics, Sept 1-7, 2001, Datong China. URL http://ismd31.ccnu.edu.cn

Radiation Hardness and Linearity Studies of CVD Diamonds

We report on the behavior of CVD diamonds under intense electromagnetic radiation and on the response of the detector to high density of deposited energy. Diamonds have been found to remain unaffected after doses of 10 MGy of MeV-range photons and the diamond response to energy depositions of up to 250 GeV/cm^3 has been found to be linear to better than 2 %. These observations make diamond an attractive detector material for a calorimeter in the very forward region of the detector proposed for TESLA.Comment: 4 pages, 5 figures; Proceeding for the topical Seminar on Innovative Particle and Radiation Detectors Siena, 21-24 October 2002; to appear in Nucl.Phys. B (Proceedings Supplement

Online Visual Robot Tracking and Identification using Deep LSTM Networks

Collaborative robots working on a common task are necessary for many applications. One of the challenges for achieving collaboration in a team of robots is mutual tracking and identification. We present a novel pipeline for online visionbased detection, tracking and identification of robots with a known and identical appearance. Our method runs in realtime on the limited hardware of the observer robot. Unlike previous works addressing robot tracking and identification, we use a data-driven approach based on recurrent neural networks to learn relations between sequential inputs and outputs. We formulate the data association problem as multiple classification problems. A deep LSTM network was trained on a simulated dataset and fine-tuned on small set of real data. Experiments on two challenging datasets, one synthetic and one real, which include long-term occlusions, show promising results.Comment: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017. IROS RoboCup Best Paper Awar