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.

Formulaic Sequences: Acquisition, Processing and Use

Abstract: 1. Preface 2. Formulaic sequences in action: An introduction (by Schmitt, Norbert) 3. Measurement of formulaic sequences (by Read, John) 4. Formulaic performance in conventionalised varieties of speech (by Kuiper, Koenraad) 5. Knowledge and acquisition of formulaic sequences: A longitudinal study (by Schmitt, Norbert) 6. Individual differences and their effects on formulaic sequence acquisition (by Dornyei, Zoltan) 7. Social-cultural integration and the development of formulaic sequences (by Adolphs, Svenja) 8. Are corpus-derived recurrent clusters psycholinguistically valid? (by Schmitt, Norbert) 9. The eyes have it: An eye-movement study into the processing of formulaic sequences (by Underwood, Geoffrey) 10. Exploring the processing of formulaic sequences through a self-paced reading task (by Schmitt, Norbert) 11. Comparing knowledge of formulaic sequences across L1, L2, L3, and L4 (by Spottl, Carol) 12. The effect of typographic salience on the look up and comprehension of unknown formulaic sequences (by Bishop, Hugh) 13. 'Here's one I prepared earlier': Formulaic language learning on television (by Wray, Alison) 14. Facilitating the acquisition of formulaic sequences: An exploratory study in an EAP context (by Jones, Martha A.) 15. Index

UAV Trajectory Optimization for Data Offloading at the Edge of Multiple Cells

Abstract: In future mobile networks, it is difficult for static base stations (BSs) to support the rapidly increasing data services, especially for cell-edge users. Unmanned aerial vehicle (UAV) is a promising method that can assist BSs to offload the data traffic, due to its high mobility and flexibility. In this correspondence, we focus on the UAV trajectory at the edges of three adjacent cells to offload traffic for BSs. In the proposed scheme, the sum rate of UAV-served edge users is maximized subject to the rate requirements for all the users, by optimizing the UAV trajectory in each flying cycle. The optimization is a mixed-integer nonconvex problem, which is difficult to solve. Thus, it is transformed into two convex problems, and an iterative algorithm is proposed to solve it by optimizing the UAV trajectory and edge user scheduling alternately. Simulation results are presented to show the effectiveness of the proposed scheme.

Confronting collinearity: comparing methods for disentangling the effects of habitat loss and fragmentation

Abstract: Estimating the relative importance of habitat loss and fragmentation is necessary to estimate the potential benefits of specific management actions and to ensure that limited conservation resources are used efficiently. However, estimating relative effects is complicated because the two processes are highly correlated. Previous studies have used a wide variety of statistical methods to separate their effects and we speculated that the published results may have been influenced by the methods used. We used simulations to determine whether, under identical conditions, the following 7 methods generate different estimates of relative importance for realistically correlated landscape predictors: residual regression, model or variable selection, averaged coefficients from all supported models, summed Akaike weights, classical variance partitioning, hierarchical variance partitioning, and a multiple regression model with no adjustments for collinearity. We found that different methods generated different rankings of the predictors and that some metrics were strongly biased. Residual regression and variance partitioning were highly biased by correlations among predictors and the bias depended on the direction of a predictor’s effect (positive vs. negative). Our results suggest that many efforts to deal with the correlation between amount and fragmentation may have done more harm than good. If confounding effects are controlled and adequate thought is given to the ecological mechanisms behind modeled predictors, then standardized partial regression coefficients are unbiased estimates of the relative importance of amount and fragmentation, even when predictors are highly correlated.

Jet energy measurement and its systematic uncertainty in proton-proton collisions at s√=7 TeV with the ATLAS detector

Abstract: The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton-proton collision data with a centre-of-mass energy of [Formula: see text] TeV corresponding to an integrated luminosity of [Formula: see text][Formula: see text]. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti-[Formula: see text] algorithm with distance parameters [Formula: see text] or [Formula: see text], and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a [Formula: see text] boson, for [Formula: see text] and pseudorapidities [Formula: see text]. The effect of multiple proton-proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region ([Formula: see text]) for jets with [Formula: see text]. For central jets at lower [Formula: see text], the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton-proton collisions and test-beam data, which also provide the estimate for [Formula: see text] TeV. The calibration of forward jets is derived from dijet [Formula: see text] balance measurements. The resulting uncertainty reaches its largest value of 6 % for low-[Formula: see text] jets at [Formula: see text]. Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5-3 %.