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You searched for subject:(Thick Slab). Showing records 1 – 2 of 2 total matches.

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University of Toronto

1. Quach, Phillip T. Understanding and Safely Predicting the Shear Response of Large-scale Reinforced Concrete Structures.

Degree: 2016, University of Toronto

Infrastructure commonly built today incorporates very thick reinforced concrete members that serve as critical elements in the load-carrying system of the structure. Certain design codes specify that members such as mat foundations and transfer slabs in high-rise buildings can be designed without shear reinforcement, allowing for more economical constructability. Omission of shear reinforcement results in structures being susceptible to the well-established size effect, and thus prone to brittle shear failures. The research comprised in this thesis focuses on investigating the applicability of international design codes in predicting the shear strength of very thick concrete members. To this end, a specimen representing a 4 m thick slab strip and a 300 mm thick companion strip were constructed and tested to failure. Results from the experimental program support the recommendation to use at least minimum shear reinforcement in large-scale structures to yield safe designs.

M.A.S.

Advisors/Committee Members: Collins, Michael P., Bentz, Evan C., Civil Engineering.

Subjects/Keywords: Deep Beam; Failure; Reinforced Concrete; Shear; Structure; Thick Slab; 0543

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Quach, P. T. (2016). Understanding and Safely Predicting the Shear Response of Large-scale Reinforced Concrete Structures. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/73110

Chicago Manual of Style (16th Edition):

Quach, Phillip T. “Understanding and Safely Predicting the Shear Response of Large-scale Reinforced Concrete Structures.” 2016. Masters Thesis, University of Toronto. Accessed July 19, 2019. http://hdl.handle.net/1807/73110.

MLA Handbook (7th Edition):

Quach, Phillip T. “Understanding and Safely Predicting the Shear Response of Large-scale Reinforced Concrete Structures.” 2016. Web. 19 Jul 2019.

Vancouver:

Quach PT. Understanding and Safely Predicting the Shear Response of Large-scale Reinforced Concrete Structures. [Internet] [Masters thesis]. University of Toronto; 2016. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/1807/73110.

Council of Science Editors:

Quach PT. Understanding and Safely Predicting the Shear Response of Large-scale Reinforced Concrete Structures. [Masters Thesis]. University of Toronto; 2016. Available from: http://hdl.handle.net/1807/73110


Linköping University

2. Forsberg, Daniel. An efficient wavelet representation for large medical image stacks.

Degree: Electrical Engineering, 2007, Linköping University

Like the rest of the society modern health care has to deal with the ever increasing information flow. Imaging modalities such as CT, MRI, US, SPECT and PET just keep producing more and more data. Especially CT and MRI and their 3D image stacks cause problems in terms of how to effectively handle these data sets. Usually a PACS is used to manage the information flow. Since a PACS often is implemented with a server-client setup, the management of these large data sets requires an efficient representation of medical image stacks that minimizes the amount of data transmitted between server and client and that efficiently supports the workflow of a practitioner. In this thesis an efficient wavelet representation for large medical image stacks is proposed for the use in a PACS. The representation supports features such as lossless viewing, random access, ROI-viewing, scalable resolution, thick slab viewing and progressive transmission. All of these features are believed to be essential to form an efficient tool for navigation and reconstruction of an image stack. The proposed wavelet representation has also been implemented and found to be better in terms of memory allocation and amount of data transmitted between server and client when compared to prior solutions. Performance tests of the implementation has also shown the proposed wavelet representation to have a good computational performance.

Subjects/Keywords: medical image stacks; wavelet representation; progressive transmission; random access; thick slab viewing; Computer Vision and Robotics (Autonomous Systems); Datorseende och robotik (autonoma system)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Forsberg, D. (2007). An efficient wavelet representation for large medical image stacks. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8394

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Forsberg, Daniel. “An efficient wavelet representation for large medical image stacks.” 2007. Thesis, Linköping University. Accessed July 19, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8394.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Forsberg, Daniel. “An efficient wavelet representation for large medical image stacks.” 2007. Web. 19 Jul 2019.

Vancouver:

Forsberg D. An efficient wavelet representation for large medical image stacks. [Internet] [Thesis]. Linköping University; 2007. [cited 2019 Jul 19]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8394.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Forsberg D. An efficient wavelet representation for large medical image stacks. [Thesis]. Linköping University; 2007. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8394

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.