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 article, the development of high strength zirconium alloys is described with particular reference to nuclear applications and the common terms used in the description of ZIRconium and its alloys and the specifications for industrial and nuclear service.

137 citations

Journal ArticleDOI
TL;DR: In this article, the authors validated two measures of self-efficacy (scheduling and task) through confirmatory factor analytic procedures in order to predict exercise behavior and behavioral intention in a structural equation model.
Abstract: Social cognitive theory (Bandura, 1986, 1995, 1997) has figured prominently among social psychological approaches taken to the investigation of exercise behavior The present study validated two measures of self-efficacy (scheduling and task) through confirmatory factor analytic procedures In a separate study, the resultant factors were then used as independent variables in the prediction of exercise behavior and behavioral intention in a structural equation model Task self-efficacy was found to be more related to behavioral intention than scheduling self-efficacy Scheduling self-efficacy was found to be more related to behavior than task self-efficacy or behavioral intention Results support different types and motivational functions of self-efficacy for exercise intentions and behavior

136 citations

Book ChapterDOI
01 Jan 2009
TL;DR: This chapter explains the role of proof burdens and standards in argumentation, illustrates them using legal procedures, and surveys the history of research on computational models of these concepts, including an original computational model which aims to integrate the features of these prior systems.
Abstract: This chapter explains the role of proof burdens and standards in argumentation, illustrates them using legal procedures, and surveys the history of research on computational models of these concepts It also presents an original computational model which aims to integrate the features of these prior systems The ‘mainstream’ conception of argumentation in the field of artificial intelligence is monological and deductive [6] Argumentation is viewed as taking place against the background of an inconsistent knowledge base, where the knowledge base is a set of propositions represented in some formal logic Argumentation in this conception is a method for deducing warranted propositions from an inconsistent knowledge base Which statements are warranted depends on attack relations among the arguments [10] which can be constructed from the knowledge base The notions of proof standards and burden of proof become relevant only when argumentation is viewed as a dialogical process for making justified decisions The input to the process is an initial claim or issue The goal of the process is to clarify and decide the issues, and produce a justification of the decision which can withstand a critical evaluation by a particular audience The role of the audience could be played by the respondent or a neutral-third party, depending on the type of dialogue The output of this process consists of: 1) a set of claims, 2) the decision to accept or reject each claim, 3) a theory of the generalizations of the domain and the facts of the particular case, and 4) a proof justifying the decision of each issues, showing how the decision is supported by the theory Notice that a theory or knowledge-base is part of the output of argumentation dialogues, not, as in the deductive conception, its input This is because, as has been

135 citations

Journal ArticleDOI
TL;DR: This paper presents a novel framework for recognizing streamed actions using Motion Capture (MoCap) data based on histograms of action poses, extracted from MoCap data, that are computed according to Hausdorff distance.

135 citations

Journal ArticleDOI
TL;DR: This paper focuses on the shift of emphasis from social to private responsibilities and raises new questions about the forces of private enterprise and market-based partnerships and based on extensive analysis of policy documents and public sector reform initiatives.
Abstract: In light of public sector reforms in Canada and elsewhere, this paper focuses on the shift of emphasis from social to private responsibilities and raises new questions about the forces of private enterprise and market-based partnerships Under neoliberal governmental agendas, privatizing responsibility links to three main developments: the reconsideration of the relations of public and private; the mobilization of responsible citizenship; and the formation of a cultural mentality of rule that works alongside these developments The research for this article is based on extensive analysis of policy documents and public sector reform initiatives, as well as interviews with Canadian federal public service employees

135 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