Gas Analysis and Monitoring Systems for the RPC Detector of CMS at LHC

The Resistive Plate Chambers (RPC) detector of the CMS experiment at the LHC proton collider (CERN, Switzerland) will employ an online gas analysis and monitoring system of the freon-based gas mixture used. We give an overview of the CMS RPC gas system, describe the project parameters and first results on gas-chromatograph analysis. Finally, we report on preliminary results for a set of monitor RPC.Comment: 9 pages, 8 figures. Presented by Stefano Bianco (Laboratori Nazionali di Frascati dell'INFN) at the IEEE NSS, San Diego (USA), October 200

The CMS RPC gas gain monitoring system: an overview and preliminary results

The status of the CMS RPC Gas Gain Monitoring (GGM) system developed at the Frascati Laboratory of INFN (Istituto Nazionale di Fisica Nucleare) is reported on. The GGM system is a cosmic ray telescope based on small RPC detectors operated with the same gas mixture used by the CMS RPC system. The GGM gain and efficiency are continuously monitored on-line, thus providing a fast and accurate determination of any shift in working point conditions. The construction details and the first result of GGM commissioning are described.Comment: 8 pages, 9 figures, uses lnfprepCMS.sty, presented by L. Benussi at RPC07, Mumbai, INDIA 200

A Multi-modal Brain Image Registration Framework for US-guided Neuronavigation Systems - Integrating MR and US for Minimally Invasive Neuroimaging

US-guided neuronavigation exploits the simplicity of use and minimal invasiveness of Ultrasound (US) imaging and the high tissue resolution and signal-to-noise ratio of Magnetic Resonance Imaging (MRI) to guide brain surgeries. More specifically, the intra-operative 3D US images are combined with pre-operative MR images to accurately localise the course of instruments in the operative field with minimal invasiveness. Multi-modal image registration of 3D US and MR images is an essential part of such system. In this paper, we present a complete software framework that enables the registration US and MR brain scans based on a multi resolution deformable transform, tackling elastic deformations (i.e. brain shifts) possibly occurring during the surgical procedure. The framework supports also simpler and faster registration techniques, based on rigid or affine transforms, and enables the interactive visualisation and rendering of the overlaid US and MRI volumes. The registration was experimentally validated on a public dataset of realistic brain phantom images, at different levels of artificially induced deformations

W2WNet: A two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality

Ideally, Convolutional Neural Networks (CNNs) should be trained with high quality images with minimum noise and correct ground truth labels. Nonetheless, in many real-world scenarios, such high quality is very hard to obtain, and datasets may be affected by any sort of image degradation and mislabelling issues. This negatively impacts the performance of standard CNNs, both during the training and the inference phase. To address this issue we propose Wise2WipedNet (W2WNet), a new two-module Convolutional Neural Network, where a Wise module exploits Bayesian inference to identify and discard spurious images during the training and a Wiped module takes care of the final classification, while broadcasting information on the prediction confidence at inference time. The goodness of our solution is demonstrated on a number of public benchmarks addressing different image classification tasks, as well as on a real-world case study on histological image analysis. Overall, our experiments demonstrate that W2WNet is able to identify image degradation and mislabelling issues both at training and at inference time, with positive impact on the final classification accuracy

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Performance and Operation of the CMS Electromagnetic Calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented

Gas analysis and monitoring systems for the RPC detector of CMS at LHC

1-9, arXiv:physics/0701014. Publisher: Los AlamosNational Laboratoty, CODEN: LNPHF9 available at http://arxiv.org/PS_cache/physics/pdf/0701/0701014v1.pd