Carleton University

About: Carleton University is a education organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 15852 authors who have published 39650 publications receiving 1106610 citations.

A Distributed Consensus-Based Cooperative Spectrum-Sensing Scheme in Cognitive Radios

Abstract: In cognitive radio (CR) networks, secondary users can cooperatively sense the spectrum to detect the presence of primary users. In this paper, we propose a fully distributed and scalable cooperative spectrum-sensing scheme based on recent advances in consensus algorithms. In the proposed scheme, the secondary users can maintain coordination based on only local information exchange without a centralized common receiver. Unlike most of the existing decision rules, such as the or-rule or the 1-out-of-N rule, we use the consensus of secondary users to make the final decision. Simulation results show that the proposed consensus scheme can have significant lower missing detection probabilities and false alarm probabilities in CR networks. It is also demonstrated that the proposed scheme not only has proven sensitivity in detecting the primary user's presence but also has robustness in choosing a desirable decision threshold.

Factor structure of the Hare Psychopathy Checklist: Youth Version (PCL: YV) in incarcerated adolescents.

Abstract: Two studies are reported on the underlying dimensions of the psychopathy construct in adolescents as measured by the Hare Psychopathy Checklist-Youth Version (PCL: YV; Forth, Kosson, & Hare, 2003). In Study 1, the PCL: YV item ratings for 505 male adolescents incarcerated in 5 different settings in North America were used to test the fit of 3 models that have been hypothesized to represent the structure of psychopathy in adults. A 4th model based on parceling PCL: YV items was also tested. In Study 2, these models were tested with a sample of 233 male adolescents incarcerated in 2 facilities in the United Kingdom. Model fit results indicated that the 18-item 4-factor model developed by Hare (2003) and a modified version of a 13-item 3-factor model developed by Cooke and Michie (2001) were associated with generally good fit. Because the 4-factor model is a less saturated model than the 3-factor model (better parameter to data point ratio), it survived a riskier test of disconfirmation. Implications for the nature of psychopathy in youth are discussed.

Measurement of the Higgs Boson Mass from the H → γγ and H → ZZ* → 4ℓ Channels in pp Collisions at Center-of-Mass Energies of 7 and 8 TeV with the ATLAS Detector

Abstract: An improved measurement of the mass of the Higgs boson is derived from a combined fit to the reconstructed invariant mass spectra of the decay channels H -> gamma gamma and H -> ZZ* -> 4l. The analysis uses the pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at center-of-mass energies of 7 TeV and 8 TeV, corresponding to an integrated luminosity of 25 fb(-1). The measured value of the Higgs boson mass is m(H) = 125.36 +/- 0.37(stat) +/- 0.18 (syst) GeV. This result is based on improved energy-scale calibrations for photons, electrons, and muons as well as other analysis improvements, and supersedes the previous result from ATLAS. Upper limits on the total width of the Higgs boson are derived from fits to the invariant mass spectra of the H -> gamma gamma and H -> ZZ* -> 4l decay channels.

Robust Sliding Mode Control for Robot Manipulators

Abstract: In the face of large-scale parametric uncertainties, the single-model (SM)-based sliding mode control (SMC) approach demands high gains for the observer, controller, and adaptation to achieve satisfactory tracking performance. The main practical problem of having high-gain-based design is that it amplifies the input and output disturbance as well as excites hidden unmodeled dynamics, causing poor tracking performance. In this paper, a multiple model/control-based SMC technique is proposed to reduce the level of parametric uncertainty to reduce observer-controller gains. To this end, we split uniformly the compact set of unknown parameters into a finite number of smaller compact subsets. Then, we design a candidate SMC corresponding to each of these smaller subsets. The derivative of the Lyapunov function candidate is used as a resetting criterion to identify a candidate model that approximates closely the plant at each instant of time. The key idea is to allow the parameter estimate of conventional adaptive sliding mode control design to be reset into a model that best estimates the plant among a finite set of candidate models. The proposed method is evaluated on a 2-DOF robot manipulator to demonstrate the effectiveness of the theoretical development.