Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results

Jet size dependence of single jet suppression in lead-lead collisions at sqrt(s(NN)) = 2.76 TeV with the ATLAS detector at the LHC

Measurements of inclusive jet suppression in heavy ion collisions at the LHC provide direct sensitivity to the physics of jet quenching. In a sample of lead-lead collisions at sqrt(s) = 2.76 TeV corresponding to an integrated luminosity of approximately 7 inverse microbarns, ATLAS has measured jets with a calorimeter over the pseudorapidity interval |eta| < 2.1 and over the transverse momentum range 38 < pT < 210 GeV. Jets were reconstructed using the anti-kt algorithm with values for the distance parameter that determines the nominal jet radius of R = 0.2, 0.3, 0.4 and 0.5. The centrality dependence of the jet yield is characterized by the jet "central-to-peripheral ratio," Rcp. Jet production is found to be suppressed by approximately a factor of two in the 10% most central collisions relative to peripheral collisions. Rcp varies smoothly with centrality as characterized by the number of participating nucleons. The observed suppression is only weakly dependent on jet radius and transverse momentum. These results provide the first direct measurement of inclusive jet suppression in heavy ion collisions and complement previous measurements of dijet transverse energy imbalance at the LHC.Comment: 15 pages plus author list (30 pages total), 8 figures, 2 tables, submitted to Physics Letters B. All figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/HION-2011-02

Search for the Standard Model Higgs boson decaying into bb¯ produced in association with top quarks decaying hadronically in pp collisions at √s = 8 TeV with the ATLAS detector

A search for Higgs boson production in association with a pair of top quarks (tt¯ H) is performed, where the Higgs boson decays to bb¯, and both top quarks decay hadronically. The data used correspond to an integrated luminosity of 20.3 fb−1 of pp collisions at √s = 8 TeV collected with the ATLAS detector at the Large Hadron Collider. The search selects events with at least six energetic jets and uses a boosted decision tree algorithm to discriminate between signal and Standard Model background. The dominant multijet background is estimated using a dedicated data-driven technique. For a Higgs boson mass of 125 GeV, an upper limit of 6.4 (5.4) times the Standard Model cross section is observed (expected) at 95% confidence level. The best-fit value for the signal strength is μ = 1.6 ± 2.6 times the Standard Model expectation for mH = 125 GeV. Combining all tt¯ H searches carried out by ATLAS at √s = 8 and 7 TeV, an observed (expected) upper limit of 3.1 (1.4) times the Standard Model expectation is obtained at 95% confidence level, with a signal strength μ = 1.7 ± 0.8

Search for the Higgs boson produced in association with a W boson and decaying to four b-quarks via two spin-zero particles in pp collisions at 13 TeV with the ATLAS detector

This paper presents a dedicated search for exotic decays of the Higgs boson to a pair of new spin-zero particles, H → aa, where the particle a decays to b-quarks and has a mass in the range of 20–60 GeV. The search is performed in events where the Higgs boson is produced in association with a W boson, giving rise to a signature of a lepton (electron or muon), missing transverse momentum, and multiple jets from b-quark decays. The analysis is based on the full dataset of pp collisions at √s = 13 TeV recorded in 2015 by the ATLAS detector at the CERN Large Hadron Collider, corresponding to an integrated luminosity of 3.2 fb−1. No significant excess of events above the Standard Model prediction is observed, and a 95% confidence-level upper limit is derived for the product of the production cross section for pp → W H times the branching ratio for the decay H → aa → 4b. The upper limit ranges from 6.2 pb for an a-boson mass ma = 20 GeV to 1.5 pb for ma = 60 GeV

Genetic tuning of fuzzy inference within fuzzy classifier systems

In generating a suitable fuzzy classifier system, significant effort is often placed on the determination and the fine tuning of the fuzzy sets. However, in such systems little thought is given to the way in which membership functions are combined within the fuzzy rules. Often traditional fuzzy inference strategies are used which consequently provide no control over how strongly or weakly the inference is applied within these rules. Furthermore such strategies will allow no interaction between grades of membership. A number of theoretical fuzzy inference operators have been proposed for both regression and classification problems but they have not been investigated in the context of real-world applications. In this paper we propose a novel genetic algorithm framework for optimizing the strength of fuzzy inference operators concurrently with the tuning of membership functions for a given fuzzy classifier system. Each fuzzy system is generated using two well-established decision tree algorithms: C4.5 and CHAID. This will enable both classification and regression problems to be addressed within the framework. Each solution generated by the genetic algorithm will produce a set of fuzzy membership functions and also determine how strongly the inference will be applied within each fuzzy rule. We investigate several theoretical proven fuzzy inference techniques (T-norms) in the context of both classification and regression problems. The methodology proposed is applied to a number of real-world data sets in order to determine the effects of the simultaneous tuning of membership functions and inference parameters on the accuracy and robustness of fuzzy classifiers

Utilizing Data Mining for Predictive Modeling of Colorectal Cancer using Electronic Medical Records

Colorectal cancer (CRC) is a relatively common cause of death around the globe. Predictive models for the development of CRC could be highly valuable and could facilitate an early diagnosis and increased survival rates. Currently available predictive models are improving, but do not fully utilize the wealth of data available about patients in routine care nor do they take advantage of the developments in the area of data mining. In this paper, a first attempt to generate a predictive model using the CHAID decision tree learner based on anonymously extracted Electronic Medical Records is reported, showing an area under the curve (AUC) of .839 for the adult population and .702 for the age group between 55 and 75. © 2014 Springer International Publishing