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Institution

Concordia University

EducationMontreal, Quebec, Canada
About: Concordia University is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Control theory & Population. The organization has 13565 authors who have published 31084 publications receiving 783525 citations. The organization is also known as: Sir George Williams University & Loyola College, Montreal.


Papers
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Journal ArticleDOI
26 Mar 1976-Science
TL;DR: Rats learned to press a lever for intravenous injections of amphetamine or apomorphine, and learned to avoid the taste of saccharin which was associated with experimenter-administered amphetamine, having both positively reinforcing and aversive properties.
Abstract: Rats learned to press a lever for intravenous injections of amphetamine or apomorphine. They also learned to avoid the taste of saccharin which was associated with experimenter-administered amphetamine or with self-administered apomorphine. Thus these, and presumably other, self-administered drugs serve as compound pharmacological stimuli, having both positively reinforcing and aversive properties.

306 citations

Journal ArticleDOI
TL;DR: The photooxidative degradation of sulforhodamine-B dye (SRB) taking place in visible-light illuminated platinized titania dispersions is revisited to examine the influence of metallic platinum dope.
Abstract: The photooxidative degradation of sulforhodamine-B dye (SRB) taking place in visible-light illuminated platinized titania dispersions is revisited to examine the influence of metallic platinum dope...

305 citations

Proceedings ArticleDOI
27 Feb 2018
TL;DR: In this paper, the authors adopt and incorporate CapsNets for the problem of brain tumor classification to design an improved architecture which maximizes the accuracy of the classification problem at hand.
Abstract: Brain tumor is considered as one of the deadliest and most common form of cancer both in children and in adults. Consequently, determining the correct type of brain tumor in early stages is of significant importance to devise a precise treatment plan and predict patient's response to the adopted treatment. In this regard, there has been a recent surge of interest in designing Convolutional Neural Networks (CNNs) for the problem of brain tumor type classification. However, CNNs typically require large amount of training data and can not properly handle input transformations. Capsule networks (referred to as CapsNets) are brand new machine learning architectures proposed very recently to overcome these shortcomings of CNNs, and posed to revolutionize deep learning solutions. Of particular interest to this work is that Capsule networks are robust to rotation and affine transformation, and require far less training data, which is the case for processing medical image datasets including brain Magnetic Resonance Imaging (MRI) images. In this paper, we focus to achieve the following four objectives: (i) Adopt and incorporate CapsNets for the problem of brain tumor classification to design an improved architecture which maximizes the accuracy of the classification problem at hand; (ii) Investigate the over-fitting problem of CapsNets based on a real set of MRI images; (iii) Explore whether or not CapsNets are capable of providing better fit for the whole brain images or just the segmented tumor, and; (iv) Develop a visualization paradigm for the output of the CapsNet to better explain the learned features. Our results show that the proposed approach can successfully overcome CNNs for the brain tumor classification problem.

304 citations

Journal ArticleDOI
TL;DR: This paper reviews literature dealing with buyer vendor coordination models that have used quantity discount as coordination mechanism under deterministic environment and classified the various models.

303 citations

Journal ArticleDOI
TL;DR: In this article, a literature review of the existing body of empirically-based studies relating to the causes and implications of how the ethical climate of a company ultimately affects the incidence of workplace deviance is performed.
Abstract: Purpose – The purpose of this article is to perform a literature review of the existing body of empirically‐based studies relating to the causes and implications of how the ethical climate of a company ultimately affects the incidence of workplace deviance.Design/methodology/approach – The article examines the issue of ethical contexts and climates within organizations, as measured by the Ethical Climate Questionnaire developed in 1987 by Victor and Cullen , and their implications in the daily work lives of participants. The causes of unethical behaviour, including the presence of counter norms, the environment in which a firm operates, and organizational commitment, as well as the manifestation of this behaviour in the form of workplace deviance, are reviewed. Finally, current trends in preventing workplace deviance are investigated, including promoting a strong culture of ethics, and the use of “toxic handlers”, individuals who take it upon themselves to handle the frustrations of fellow employees.Findi...

303 citations


Authors

Showing all 13754 results

NameH-indexPapersCitations
Alan C. Evans183866134642
Michael J. Meaney13660481128
Chao Zhang127311984711
Charles Spence11194951159
Angappa Gunasekaran10158640633
Kaushik Roy97140242661
Muthiah Manoharan9649744464
Stephen J. Simpson9549030226
Roy A. Wise9525239509
Dario Farina9483232786
Yavin Shaham9423929596
Elazer R. Edelman8959329980
Fikret Berkes8827149585
Ke Wu87124233226
Nick Serpone8547430532
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202375
2022343
20211,859
20201,861
20191,734
20181,680