Brunel University London

About: Brunel University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Context (language use) & Large Hadron Collider. The organization has 10918 authors who have published 29515 publications receiving 893330 citations. The organization is also known as: Brunel & University of Brunel.

Measurement of Higgs boson production and properties in the WW decay channel with leptonic final states

Abstract: A search for the standard model Higgs boson decaying to a W-boson pair at the LHC is reported. The event sample corresponds to an integrated luminosity of 4.9 fb−1 and 19.4 fb−1 collected with the CMS detector in pp collisions at s√ = 7 and 8 TeV, respectively. The Higgs boson candidates are selected in events with two or three charged leptons. An excess of events above background is observed, consistent with the expectation from the standard model Higgs boson with a mass of around 125 GeV. The probability to observe an excess equal or larger than the one seen, under the background-only hypothesis, corresponds to a significance of 4.3 standard deviations for m H = 125.6 GeV. The observed signal cross section times the branching fraction to WW for m H = 125.6 GeV is 0.72+0.20−0.18 times the standard model expectation. The spin-parity J P = 0+ hypothesis is favored against a narrow resonance with J P = 2+ or J P = 0− that decays to a W-boson pair. This result provides strong evidence for a Higgs-like boson decaying to a W-boson pair.

Review of the Report of the Special Representative of the Secretary-General on the Issue of Human Rights and Transnational Corporations and Other Business Enterprises, Professor John Ruggie to the United Nations Human Rights Council, Protect, Respect and Remedy: A Framework for Business and Human Rights Ah/Hrc/8/5, 7 April 2008

Abstract: The responsibilities of Transnational Corporations (TNCs) in the area of human rights have been on the international agenda for sometime now and have gain more momentum in the last two decades. In the past, several attempts were made under the auspices of the United Nations to devise a framework for controlling Transnational corporations without much success. In the face of increasing allegation of human rights abuses by TNCs, the United Nations Sub-commission on the Promotion and Protection of Human Rights approved the 'Norms on Responsibilities of Transnational Corporations and other Business Enterprises with Regard to Human Rights' (Norms).

A General Software Defect-Proneness Prediction Framework

Abstract: BACKGROUND - Predicting defect-prone software components is an economically important activity and so has received a good deal of attention. However, making sense of the many, and sometimes seemingly inconsistent, results is difficult. OBJECTIVE - We propose and evaluate a general framework for software defect prediction that supports 1) unbiased and 2) comprehensive comparison between competing prediction systems. METHOD - The framework is comprised of 1) scheme evaluation and 2) defect prediction components. The scheme evaluation analyzes the prediction performance of competing learning schemes for given historical data sets. The defect predictor builds models according to the evaluated learning scheme and predicts software defects with new data according to the constructed model. In order to demonstrate the performance of the proposed framework, we use both simulation and publicly available software defect data sets. RESULTS - The results show that we should choose different learning schemes for different data sets (i.e., no scheme dominates), that small details in conducting how evaluations are conducted can completely reverse findings, and last, that our proposed framework is more effective and less prone to bias than previous approaches. CONCLUSIONS - Failure to properly or fully evaluate a learning scheme can be misleading; however, these problems may be overcome by our proposed framework.