scispace - formally typeset
Search or ask a question
Institution

Ryerson University

EducationToronto, Ontario, Canada
About: Ryerson University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 7671 authors who have published 20164 publications receiving 394976 citations. The organization is also known as: Ryerson Polytechnical Institute & Ryerson Institute of Technology.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, an active damping control method is proposed for the reduction in line current THD of high-power current-source rectifiers operating at a switching frequency of only 540 Hz.
Abstract: The use of active damping to reduce the total harmonic distortion (THD) of the line current for medium-voltage (2.3-7.2 kV) high-power pulsewidth-modulation (PWM) current-source rectifiers is investigated. The rectifier requires an LC filter connected at its input terminals, which constitutes an LC resonant mode. The lightly damped LC filter is prone to series and parallel resonances when tuned to a system harmonic either from the utility or from the PWM rectifier. These issues are traditionally addressed at the design stage by properly choosing the filter resonant frequency. This approach may result in a limited performance since the LC resonant frequency is a function of the power system impedance, which usually varies with power system operating conditions. In this paper, an active damping control method is proposed for the reduction in line current THD of high-power current-source rectifiers operating at a switching frequency of only 540 Hz. Two types of LC resonances are investigated: the parallel resonance excited by harmonic currents drawn by the rectifier and the series resonance caused by harmonic pollution in the source voltage. It is demonstrated through simulation and experiments that the proposed active damping control can effectively reduce the line-current THD caused by both parallel and series resonances.

175 citations

Journal ArticleDOI
01 Jul 2021
TL;DR: A comprehensive survey of deep learning applications for object detection and scene perception in autonomous vehicles examines the theory underlying self-driving vehicles from deep learning perspective and current implementations, followed by their critical evaluations.
Abstract: This article presents a comprehensive survey of deep learning applications for object detection and scene perception in autonomous vehicles. Unlike existing review papers, we examine the theory underlying self-driving vehicles from deep learning perspective and current implementations, followed by their critical evaluations. Deep learning is one potential solution for object detection and scene perception problems, which can enable algorithm-driven and data-driven cars. In this article, we aim to bridge the gap between deep learning and self-driving cars through a comprehensive survey. We begin with an introduction to self-driving cars, deep learning, and computer vision followed by an overview of artificial general intelligence. Then, we classify existing powerful deep learning libraries and their role and significance in the growth of deep learning. Finally, we discuss several techniques that address the image perception issues in real-time driving, and critically evaluate recent implementations and tests conducted on self-driving cars. The findings and practices at various stages are summarized to correlate prevalent and futuristic techniques, and the applicability, scalability and feasibility of deep learning to self-driving cars for achieving safe driving without human intervention. Based on the current survey, several recommendations for further research are discussed at the end of this article.

175 citations

Journal ArticleDOI
TL;DR: This panel report describes the key findings and best practices that were identified, with an emphasis on what has changed since the BI Congress efforts in 2009 and 2010, and serves as a "call to action" for universities regarding the need to respond to emerging market needs in BI/BA, including “Big Data.”
Abstract: In December 2012, the AIS Special Interest Group on Decision Support, Knowledge and Data Management Systems (SIGDSS) and the Teradata University Network (TUN) cosponsored the Business Intelligence Congress 3 and conducted surveys to assess academia’s response to the growing market need for students with Business Intelligence (BI) and Business Analytics (BA) skill sets. This panel report describes the key findings and best practices that were identified, with an emphasis on what has changed since the BI Congress efforts in 2009 and 2010. The article also serves as a “call to action” for universities regarding the need to respond to emerging market needs in BI/BA, including “Big Data.” The IS field continues to be well positioned to be the leader in creating the next generation BI/BA workforce. To do so, we believe that IS leaders need to continuously refine BI/BA curriculum to keep pace with the turbulent BI/BA marketplace.

175 citations

Journal ArticleDOI
TL;DR: In this article, the development and applicability of Vapex is brought up in context of the availability of oil from natural sources, challenges of oil recovery, environmental factors, and cost economics.
Abstract: The vapor extraction of heavy oil and bitumen, or Vapex, has emerged as a very promising recovery process since its invention in 1991. The principal reason is the environmental friendliness of Vapex together with its cost-effective nature vis-a-vis other recovery processes. This paper assimilates and presents the research and technological contributions made toward Vapex. The development and applicability of Vapex is brought up in context of the availability of oil from natural sources, challenges of oil recovery, environmental factors, and cost economics. Significant findings and salient features of several experimental and theoretical studies on Vapex are included. Various factors that influence the operation of Vapex are discussed. Important issues are identified that need further investigations for the continued enhancement of Vapex. It is expected that this paper will serve as a useful reference tool for the engineers and scientists interested in Vapex.

175 citations

Journal ArticleDOI
TL;DR: In this paper, the authors presented two models (classical and VMI-CS coordination) for a two-level closed-loop supply chain with a manufacturer and a retailer with a facility to remanufacture used items.

175 citations


Authors

Showing all 7846 results

NameH-indexPapersCitations
Eleftherios P. Diamandis110106452654
Michael D. Taylor9750542789
Peter Nijkamp97240750826
Anthony B. Miller9341636777
Muhammad Shahbaz92100134170
Rakesh Kumar91195939017
Marc A. Rosen8577030666
Bjorn Ottersten81105828359
Barry Wellman7721934234
Bin Wu7346424877
Xinbin Feng7241319193
Roy Freeman6925422707
Xiaokang Yang6851817663
Amir H. Gandomi6737522192
Konstantinos N. Plataniotis6359516695
Network Information
Related Institutions (5)
University of Western Ontario
99.8K papers, 3.7M citations

92% related

University of British Columbia
209.6K papers, 9.2M citations

91% related

McGill University
162.5K papers, 6.9M citations

91% related

University of Alberta
154.8K papers, 5.3M 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
20241
2023240
2022338
20211,773
20201,708
20191,490