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.

Smart Modeling of Microwave Devices

Abstract: Modeling and computer-aided design (CAD) techniques are essential for microwave design, especially with the drive towards first-pass design success. We have described neural networks for microwave modeling and design. Neural networks are suitable when modeling a required relationship for which analytical formulas are hard to derive, or for which the computational effort is too high. This relationship can be either of the IO relationship of the overall model (straight neural network model), the output-input relationship (inverse model), a relationship between existing model and desired data (neuro-SM), or relationship of a subpart of the overall model (knowledge based neural network). Neural networks are fast to evaluate, and the neural network formulas are easy to implement into microwave CAD. The simplicity of adding input neurons or hidden neurons makes neural network flexible in handling functions of different dimensions and of different degree of nonlinearity. We have also demonstrated that neural networks are helpful in developing parametric or scalable models for passive and active microwave devices.

Gain scores in research can be highly reliable

Abstract: Many investigators have concluded that difference scores and gain scores, such as differences between pretest and posttest measures resulting from an experimental treatment or period of instruction, have questionable value in research in part because of their low reliability (e.g., Linn & Slinde, 1977; Lord, 1963; O'Connor, 1972). Cronbach and Furby (1970, p. 80) recommended that "... investigators who ask questions regarding gain scores ... frame their questions in other ways." These conclusions are based on certain assumptions which at first glance appear reasonable about the values of parameters in a well known formula for the reliability of differences. (See, for example, Lord, 1963.) In this paper we will show that a reliability coefficient calculated from the formula can be high, provided one makes other assumptions about the values of pretest and posttest reliability coefficients and standard deviations. Furthermore, there is reason to believe that the revised assumptions are more realistic than the usual ones in testing practice.

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

Abstract: A search for the Standard Model Higgs boson produced in association with a top-quark pair, , is presented. The analysis uses 20.3 fb(-1) of pp collision data at , collected with the ATLAS detector at the Large Hadron Collider during 2012. The search is designed for the decay mode and uses events containing one or two electrons or muons. In order to improve the sensitivity of the search, events are categorised according to their jet and b-tagged jet multiplicities. A neural network is used to discriminate between signal and background events, the latter being dominated by +jets production. In the single-lepton channel, variables calculated using a matrix element method are included as inputs to the neural network to improve discrimination of the irreducible background. No significant excess of events above the background expectation is found and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95 % confidence level. The ratio of the measured signal cross section to the Standard Model expectation is found to be assuming a Higgs boson mass of 125 Gev.