Results are presented from searches for the standard model Higgs boson in proton-proton collisions at root s = 7 and 8 TeV in the Compact Muon Solenoid experiment at the LHC, using data samples corresponding to integrated luminosities of up to 5.1 fb(-1) at 7 TeV and 5.3 fb(-1) at 8 TeV. The search is performed in five decay modes: gamma gamma, ZZ, W+W-, tau(+)tau(-), and b (b) over bar. An excess of events is observed above the expected background, with a local significance of 5.0 standard deviations, at a mass near 125 GeV, signalling the production of a new particle. The expected significance for a standard model Higgs boson of that mass is 5.8 standard deviations. The excess is most significant in the two decay modes with the best mass resolution, gamma gamma and ZZ; a fit to these signals gives a mass of 125.3 +/- 0.4(stat.) +/- 0.5(syst.) GeV. The decay to two photons indicates that the new particle is a boson with spin different from one. (C) 2012 CERN. Published by Elsevier B.V. All rights reserved

Recent results of the searches for Supersymmetry in final states with one or two leptons at CMS are presented. Many Supersymmetry scenarios, including the Constrained Minimal Supersymmetric extension of the Standard Model (CMSSM), predict a substantial amount of events containing leptons, while the largest fraction of Standard Model background events -which are QCD interactions -gets strongly reduced by requiring isolated leptons. The analyzed data was taken in 2011 and corresponds to an integrated luminosity of approximately L = 1 fb −1 . The center-of-mass energy of the pp collisions was √ s = 7 TeV.

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MapReduce is a powerful platform for large-scale data processing. To achieve good performance, a MapReduce scheduler must avoid unnecessary data transmission by enhancing the data locality (placing tasks on nodes that contain their input data). This paper develops a new MapReduce scheduling technique to enhance map task's data locality. We have integrated this technique into Hadoop default FIFO scheduler and Hadoop fair scheduler. To evaluate our technique, we compare not only MapReduce scheduling algorithms with and without our technique but also with an existing data locality enhancement technique (i.e., the delay algorithm developed by Facebook). Experimental results show that our technique often leads to the highest data locality rate and the lowest response time for map tasks. Furthermore, unlike the delay algorithm, it does not require an intricate parameter tuning process.

HighlightImage Harvest is an open-source software for high-throughput image processing and analysis that is integrated with the Open Science Grid and provides computational resources to process large image datasets.