scispace - formally typeset
Search or ask a question
Institution

University of Windsor

EducationWindsor, Ontario, Canada
About: University of Windsor is a education organization based out in Windsor, Ontario, Canada. It is known for research contribution in the topics: Population & Argumentation theory. The organization has 10654 authors who have published 22307 publications receiving 435906 citations. The organization is also known as: UWindsor & Assumption University of Windsor.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, a dialogue theory of explanation is proposed, defined as a transfer of understanding in a dialogue system in which a questioner and a respondent take part, where the questioner asks a special sort of why-question that asks for understanding of something and the respondent provides a reply that transfers understanding to the questioners.
Abstract: This paper offers a dialogue theory of explanation. A successful explanation is defined as a transfer of understanding in a dialogue system in which a questioner and a respondent take part. The questioner asks a special sort of why-question that asks for understanding of something and the respondent provides a reply that transfers understanding to the questioner. The theory is drawn from recent work on explanation in artificial intelligence (AI), especially in expert systems, but applies to scientific, legal and everyday conversational explanations.

93 citations

Journal ArticleDOI
TL;DR: The results of the study indicated that TPB could satisfactorily predict the behavioral intention with up to 44% variation of the intention being predicted by the model, and integrating the variables of trust and personal innovativeness into TPB model enhanced the prediction effect.

93 citations

Journal ArticleDOI
TL;DR: A method for simultaneously determining the operation allocation and material handling system selection in an FMS environment with multiple performance objectives is proposed.

93 citations

Journal ArticleDOI
TL;DR: This paper analyzed the power properties of the kernel-based and integrated conditional moment tests for a sequence of singular local alternatives, and showed that the kernelbased tests can be more powerful than the integrated conditional moments tests for these "singular" local alternatives.
Abstract: We point out the close relationship between the integrated conditional moment tests in Bierens (1982, Journal of Econometrics 20, 105–134) and Bierens and Ploberger (1997, Econometrica 65, 1129–1152) with the complex-valued exponential weight function and the kernel-based tests in Hardle and Mammen (1993, Annals of Statistics 21, 1926–1947), Li and Wang (1998, Journal of Econometrics 87, 145–165), and Zheng (1996, Journal of Econometrics 75, 263–289). It is well established that the integrated conditional moment tests of Bierens (1982) and Bierens and Ploberger (1997) are more powerful than kernel-based nonparametric tests against Pitman local alternatives. In this paper we analyze the power properties of the kernel-based tests and the integrated conditional moment tests for a sequence of “singular” local alternatives, and show that the kernel-based tests can be more powerful than the integrated conditional moment tests for these “singular” local alternatives. These results suggest that integrated conditional moment tests and kernel-based tests should be viewed as complements to each other. Results from a simulation study are in agreement with the theoretical results.

93 citations

Journal ArticleDOI
TL;DR: This tutorial summarizes blind spectrum sensing (BSS) approaches that require no prior knowledge of the licensed user’s signal characteristics, specifically for an interweave cognitive radio network model.
Abstract: Spectrum sensing is one of the essential tasks to have a cognitive radio system, which will allow an unlicensed user, called secondary user, to utilize the spectrum while the licensed user, called primary user, is not occupying it. The spectrum sensing approaches can be classified as blind and knowledge aided approaches. This tutorial summarizes blind spectrum sensing (BSS) approaches that require no prior knowledge of the licensed user’s signal characteristics, specifically for an interweave cognitive radio network model. The tutorial provides a thorough background, major implementations, and limitations of the BSS approaches, which are energy detector approach, maximum to minimum eigenvalue approach, maximum eigenvalue approach, covariance absolute value approach, and covariance Frobenius norm approach. Moreover, the tutorial compares these approaches based on performance metrics and complexity requirements. Furthermore, for a higher interference protection, the combination of two different spectrum sensing approaches, namely two-stage detection technique is presented and discussed. Besides, the tutorial discusses the challenges and possible future research directions. The fundamental objective of this tutorial is to provide insightful views and design aspects of BSS approach to researchers. For this purpose, the tutorial includes pseudo codes and simulation examples to illustrate more about the practical aspects of the above-mentioned approaches.

93 citations


Authors

Showing all 10751 results

NameH-indexPapersCitations
Jie Zhang1784857221720
Robert E. W. Hancock15277588481
Michael Lynch11242263461
David Zhang111102755118
Paul D. N. Hebert11153766288
Eleftherios P. Diamandis110106452654
Qian Wang108214865557
John W. Berry9735152470
Douglas W. Stephan8966334060
Rebecca Fisher8625550260
Mehdi Dehghan8387529225
Zhong-Qun Tian8164633168
Robert J. Letcher8041122778
Daniel J. Sexton7636925172
Bin Ren7347023452
Network Information
Related Institutions (5)
University of Waterloo
93.9K papers, 2.9M citations

94% related

Queen's University
78.8K papers, 2.8M citations

92% related

Arizona State University
109.6K papers, 4.4M citations

91% related

University of Western Ontario
99.8K papers, 3.7M citations

91% related

McMaster University
101.2K papers, 4.2M citations

91% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202327
2022178
20211,147
20201,005
20191,001
2018882