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You searched for +publisher:"University of Southern California" +contributor:("Mendel, Jerry M."). Showing records 1 – 17 of 17 total matches.

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University of Southern California

1. Ghods, Parham. Data assimilation for fractured shale gas reservoirs using ensemble Kalman filter.

Degree: PhD, Petroleum Engineering, 2012, University of Southern California

 Production of shale gas reservoirs depends on natural and hydraulic fractures, which represent a significant challenge in numerical simulation. Unknown fracture characteristics such as location,… (more)

Subjects/Keywords: dual porosity dual permeability; ensemble Kalman filter; fracture modeling; numerical simulation; shale gas reservoirs; tight gas reservoirs

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APA (6th Edition):

Ghods, P. (2012). Data assimilation for fractured shale gas reservoirs using ensemble Kalman filter. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200831/rec/1761

Chicago Manual of Style (16th Edition):

Ghods, Parham. “Data assimilation for fractured shale gas reservoirs using ensemble Kalman filter.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200831/rec/1761.

MLA Handbook (7th Edition):

Ghods, Parham. “Data assimilation for fractured shale gas reservoirs using ensemble Kalman filter.” 2012. Web. 20 Oct 2019.

Vancouver:

Ghods P. Data assimilation for fractured shale gas reservoirs using ensemble Kalman filter. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200831/rec/1761.

Council of Science Editors:

Ghods P. Data assimilation for fractured shale gas reservoirs using ensemble Kalman filter. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200831/rec/1761


University of Southern California

2. Kwak, Youngmin. Advanced liquid simulation techniques for computer graphics applications.

Degree: PhD, Electrical Engineering (Multimedia & Creative Technology), 2010, University of Southern California

 The particle level set method (PLSM) and the lattice Boltzmann method (LBM) have been two major physics-based liquid simulation techniques used in computer graphics to… (more)

Subjects/Keywords: fluid simulation; hybrid lattice Boltzmann method; lattice Boltzmann method; multicomponent multiphase lattice Boltzmann method; particle level set method

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APA (6th Edition):

Kwak, Y. (2010). Advanced liquid simulation techniques for computer graphics applications. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/368016/rec/545

Chicago Manual of Style (16th Edition):

Kwak, Youngmin. “Advanced liquid simulation techniques for computer graphics applications.” 2010. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/368016/rec/545.

MLA Handbook (7th Edition):

Kwak, Youngmin. “Advanced liquid simulation techniques for computer graphics applications.” 2010. Web. 20 Oct 2019.

Vancouver:

Kwak Y. Advanced liquid simulation techniques for computer graphics applications. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/368016/rec/545.

Council of Science Editors:

Kwak Y. Advanced liquid simulation techniques for computer graphics applications. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/368016/rec/545


University of Southern California

3. Korjani, Mohammad Mehdi. Intelligent knowledge acquisition systems: from descriptive to predictive models.

Degree: PhD, Electrical Engineering, 2015, University of Southern California

 Linguistic summarization is a data mining or knowledge discovery approach that describes a pattern in a database. Using techniques to generate linguistic summaries not only… (more)

Subjects/Keywords: breakdown of democracy; causal condition; causal combination; data mining; footprint of uncertainty; fuzzy set qualitative comparative analysis; fsQCA; fuzzy sets; interval type‐2 fuzzy sets; interval‐valued fsQCA; level 2 fuzzy sets; linguistic summarization; nonlinear regression; prediction; regression; type‐1 fuzzy sets; type‐1 fsQCA

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APA (6th Edition):

Korjani, M. M. (2015). Intelligent knowledge acquisition systems: from descriptive to predictive models. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/603949/rec/3556

Chicago Manual of Style (16th Edition):

Korjani, Mohammad Mehdi. “Intelligent knowledge acquisition systems: from descriptive to predictive models.” 2015. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/603949/rec/3556.

MLA Handbook (7th Edition):

Korjani, Mohammad Mehdi. “Intelligent knowledge acquisition systems: from descriptive to predictive models.” 2015. Web. 20 Oct 2019.

Vancouver:

Korjani MM. Intelligent knowledge acquisition systems: from descriptive to predictive models. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/603949/rec/3556.

Council of Science Editors:

Korjani MM. Intelligent knowledge acquisition systems: from descriptive to predictive models. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/603949/rec/3556


University of Southern California

4. Zhai, Daoyuan. Advanced learning systems for highly uncertain environments.

Degree: PhD, Electrical Engineering, 2012, University of Southern California

 Data quality, which broadly refers to both data frequency and accuracy, has been the key factor that determines the performances of most of today's machine… (more)

Subjects/Keywords: extended kalman filter; extended kalman smoother; quantum-behaved particle swarm algorithm; type-2 fuzzy logic sets and systems

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APA (6th Edition):

Zhai, D. (2012). Advanced learning systems for highly uncertain environments. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/205925/rec/544

Chicago Manual of Style (16th Edition):

Zhai, Daoyuan. “Advanced learning systems for highly uncertain environments.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/205925/rec/544.

MLA Handbook (7th Edition):

Zhai, Daoyuan. “Advanced learning systems for highly uncertain environments.” 2012. Web. 20 Oct 2019.

Vancouver:

Zhai D. Advanced learning systems for highly uncertain environments. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/205925/rec/544.

Council of Science Editors:

Zhai D. Advanced learning systems for highly uncertain environments. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/205925/rec/544


University of Southern California

5. Wu, Dongrui. Intelligent systems for decision support.

Degree: PhD, Electrical Engineering, 2009, University of Southern California

 This research is focused on multi-criteria decision-making (MCDM) under uncertainties, especially linguistic uncertainties. This problem is very important because many times linguistic information, in addition… (more)

Subjects/Keywords: intelligent systems; multi-criteria decision-making; fuzzy logic; information fusion; linguistic uncertainty

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APA (6th Edition):

Wu, D. (2009). Intelligent systems for decision support. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/231254/rec/3559

Chicago Manual of Style (16th Edition):

Wu, Dongrui. “Intelligent systems for decision support.” 2009. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/231254/rec/3559.

MLA Handbook (7th Edition):

Wu, Dongrui. “Intelligent systems for decision support.” 2009. Web. 20 Oct 2019.

Vancouver:

Wu D. Intelligent systems for decision support. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/231254/rec/3559.

Council of Science Editors:

Wu D. Intelligent systems for decision support. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/231254/rec/3559


University of Southern California

6. Rajati, Mohammad Reza. Advances in linguistic data-oriented uncertainty modeling, reasoning, and intelligent decision making.

Degree: PhD, Electrical Engineering, 2015, University of Southern California

 In this dissertation, we focus on data oriented uncertainty modeling, reasoning, and inference, and their applications to intelligent systems that implement the paradigm of Computing… (more)

Subjects/Keywords: fuzzy logic; fuzzy systems; computing with words; extension principle; linguistic probability; novel weighted averages; intelligent systems; decision making; reasoning; belief structures; enhanced oil recovery; data oriented

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APA (6th Edition):

Rajati, M. R. (2015). Advances in linguistic data-oriented uncertainty modeling, reasoning, and intelligent decision making. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/568987/rec/554

Chicago Manual of Style (16th Edition):

Rajati, Mohammad Reza. “Advances in linguistic data-oriented uncertainty modeling, reasoning, and intelligent decision making.” 2015. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/568987/rec/554.

MLA Handbook (7th Edition):

Rajati, Mohammad Reza. “Advances in linguistic data-oriented uncertainty modeling, reasoning, and intelligent decision making.” 2015. Web. 20 Oct 2019.

Vancouver:

Rajati MR. Advances in linguistic data-oriented uncertainty modeling, reasoning, and intelligent decision making. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/568987/rec/554.

Council of Science Editors:

Rajati MR. Advances in linguistic data-oriented uncertainty modeling, reasoning, and intelligent decision making. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/568987/rec/554


University of Southern California

7. Kumlu, Deniz. Autonomous ship recognition from color images.

Degree: MS, Electrical Engineering, 2012, University of Southern California

 Autonomous ship recognition is an active area for military and commercial applications like harbor surveillance. Accurate identification of unknown contacts is critical in military intelligence.… (more)

Subjects/Keywords: object recognition; ship recognition; image processing; Hough transform; connected component analysis; segmentation; feature extraction; spatial pyramid; random projection; support vector machines

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APA (6th Edition):

Kumlu, D. (2012). Autonomous ship recognition from color images. (Masters Thesis). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/64052/rec/1006

Chicago Manual of Style (16th Edition):

Kumlu, Deniz. “Autonomous ship recognition from color images.” 2012. Masters Thesis, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/64052/rec/1006.

MLA Handbook (7th Edition):

Kumlu, Deniz. “Autonomous ship recognition from color images.” 2012. Web. 20 Oct 2019.

Vancouver:

Kumlu D. Autonomous ship recognition from color images. [Internet] [Masters thesis]. University of Southern California; 2012. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/64052/rec/1006.

Council of Science Editors:

Kumlu D. Autonomous ship recognition from color images. [Masters Thesis]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/64052/rec/1006


University of Southern California

8. Zheng, Yingying. Data-driven performance and fault monitoring for oil production operations.

Degree: PhD, Chemical Engineering, 2012, University of Southern California

 The business objectives of a smart oilfield include: enhancing oil production, monitoring plant operations, improving product quality and ensuring worker and environmental safety. One of… (more)

Subjects/Keywords: data-driven; performance monitoring; fault monitoring; data reconstruction; oil production

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APA (6th Edition):

Zheng, Y. (2012). Data-driven performance and fault monitoring for oil production operations. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/107964/rec/1774

Chicago Manual of Style (16th Edition):

Zheng, Yingying. “Data-driven performance and fault monitoring for oil production operations.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/107964/rec/1774.

MLA Handbook (7th Edition):

Zheng, Yingying. “Data-driven performance and fault monitoring for oil production operations.” 2012. Web. 20 Oct 2019.

Vancouver:

Zheng Y. Data-driven performance and fault monitoring for oil production operations. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/107964/rec/1774.

Council of Science Editors:

Zheng Y. Data-driven performance and fault monitoring for oil production operations. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/107964/rec/1774


University of Southern California

9. Tepperman, Joseph. Hierarchical methods in automatic pronunciation evaluation.

Degree: PhD, Electrical Engineering, 2009, University of Southern California

 Technology that can automatically categorize pronunciations and estimate scores of pronunciation quality has many potential applications, most notably for second-language learners interested in practicing their… (more)

Subjects/Keywords: automatic speech recognition; pronunciation evaluation

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APA (6th Edition):

Tepperman, J. (2009). Hierarchical methods in automatic pronunciation evaluation. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/246807/rec/3161

Chicago Manual of Style (16th Edition):

Tepperman, Joseph. “Hierarchical methods in automatic pronunciation evaluation.” 2009. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/246807/rec/3161.

MLA Handbook (7th Edition):

Tepperman, Joseph. “Hierarchical methods in automatic pronunciation evaluation.” 2009. Web. 20 Oct 2019.

Vancouver:

Tepperman J. Hierarchical methods in automatic pronunciation evaluation. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/246807/rec/3161.

Council of Science Editors:

Tepperman J. Hierarchical methods in automatic pronunciation evaluation. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/246807/rec/3161


University of Southern California

10. Jahangiri, Hamid Reza. Optimization of coupled CO₂ sequestration and enhanced oil recovery.

Degree: PhD, Petroleum Engineering, 2012, University of Southern California

 Sequestration of carbon dioxide (CO₂) in depleted or partially depleted oil reservoirs is a plausible option to reduce CO₂ emissions into the atmosphere. Carbon dioxide… (more)

Subjects/Keywords: CO₂ sequestration; enhanced oil recovery; co-optimization; net present value; ensemble based optimization

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APA (6th Edition):

Jahangiri, H. R. (2012). Optimization of coupled CO₂ sequestration and enhanced oil recovery. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/13500/rec/4605

Chicago Manual of Style (16th Edition):

Jahangiri, Hamid Reza. “Optimization of coupled CO₂ sequestration and enhanced oil recovery.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/13500/rec/4605.

MLA Handbook (7th Edition):

Jahangiri, Hamid Reza. “Optimization of coupled CO₂ sequestration and enhanced oil recovery.” 2012. Web. 20 Oct 2019.

Vancouver:

Jahangiri HR. Optimization of coupled CO₂ sequestration and enhanced oil recovery. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/13500/rec/4605.

Council of Science Editors:

Jahangiri HR. Optimization of coupled CO₂ sequestration and enhanced oil recovery. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/13500/rec/4605


University of Southern California

11. Hao, Minshen. Aggregation and modeling using computational intelligence techniques.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 In waterflood management, there exists several models to describe a petroleum reservoir for predicting the future production rates using scheduled injection rates. Most of them… (more)

Subjects/Keywords: aggregation; computing with words; computational intelligence techniques; general type‐2 fuzzy sets; interval type‐2 fuzzy sets; similarity measure; uncertainty modeling; interval type‐2 word models

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APA (6th Edition):

Hao, M. (2014). Aggregation and modeling using computational intelligence techniques. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/413110/rec/585

Chicago Manual of Style (16th Edition):

Hao, Minshen. “Aggregation and modeling using computational intelligence techniques.” 2014. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/413110/rec/585.

MLA Handbook (7th Edition):

Hao, Minshen. “Aggregation and modeling using computational intelligence techniques.” 2014. Web. 20 Oct 2019.

Vancouver:

Hao M. Aggregation and modeling using computational intelligence techniques. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/413110/rec/585.

Council of Science Editors:

Hao M. Aggregation and modeling using computational intelligence techniques. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/413110/rec/585


University of Southern California

12. DeVore, Charles Edward. Damage detection using substructure identification.

Degree: PhD, Civil Engineering (Structural Engineering), 2013, University of Southern California

 As civil infrastructure ages, occupants and users are placed at risk. Due to limited funding, agencies are required to push structures past their original design… (more)

Subjects/Keywords: substructure identification; structural health monitoring; structural control; structural dynamics

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APA (6th Edition):

DeVore, C. E. (2013). Damage detection using substructure identification. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/229995/rec/1753

Chicago Manual of Style (16th Edition):

DeVore, Charles Edward. “Damage detection using substructure identification.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/229995/rec/1753.

MLA Handbook (7th Edition):

DeVore, Charles Edward. “Damage detection using substructure identification.” 2013. Web. 20 Oct 2019.

Vancouver:

DeVore CE. Damage detection using substructure identification. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/229995/rec/1753.

Council of Science Editors:

DeVore CE. Damage detection using substructure identification. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/229995/rec/1753


University of Southern California

13. Kazemzadeh, Abe. Natural language description of emotion.

Degree: PhD, Computer Science, 2013, University of Southern California

 This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current… (more)

Subjects/Keywords: natural language processing; emotions; definite descriptions; dialog systems; intersubjectivity; sequential Bayesian update; Socratic epistemology; crowd-sourcing; dialog agent; EMO20Q; question-asking; fuzzy logic; interval type-2 fuzzy sets; human-computer interaction

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APA (6th Edition):

Kazemzadeh, A. (2013). Natural language description of emotion. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/298137/rec/4332

Chicago Manual of Style (16th Edition):

Kazemzadeh, Abe. “Natural language description of emotion.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/298137/rec/4332.

MLA Handbook (7th Edition):

Kazemzadeh, Abe. “Natural language description of emotion.” 2013. Web. 20 Oct 2019.

Vancouver:

Kazemzadeh A. Natural language description of emotion. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/298137/rec/4332.

Council of Science Editors:

Kazemzadeh A. Natural language description of emotion. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/298137/rec/4332


University of Southern California

14. Bolourchi Yazdi, Seyed Ali. Studies into computational intelligence approaches for the identification of complex nonlinear systems.

Degree: PhD, Civil Engineering (Structural Engineering), 2016, University of Southern California

 This study builds on major advances in the field of Computational Intelligence to develop a state‐of‐the‐art data‐driven methodology that provides parsimonious optimized computational models in… (more)

Subjects/Keywords: computational intelligence; evolutionary computation; large volume of data; genetic programming; expression trees; genetic algorithms; computer algebra; nonlinear systems; hysteretic systems; human spine; differential equations; parsimonious models; system identification; intelligent selection; dimensionality reduction; experimental data

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APA (6th Edition):

Bolourchi Yazdi, S. A. (2016). Studies into computational intelligence approaches for the identification of complex nonlinear systems. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/386427/rec/6151

Chicago Manual of Style (16th Edition):

Bolourchi Yazdi, Seyed Ali. “Studies into computational intelligence approaches for the identification of complex nonlinear systems.” 2016. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/386427/rec/6151.

MLA Handbook (7th Edition):

Bolourchi Yazdi, Seyed Ali. “Studies into computational intelligence approaches for the identification of complex nonlinear systems.” 2016. Web. 20 Oct 2019.

Vancouver:

Bolourchi Yazdi SA. Studies into computational intelligence approaches for the identification of complex nonlinear systems. [Internet] [Doctoral dissertation]. University of Southern California; 2016. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/386427/rec/6151.

Council of Science Editors:

Bolourchi Yazdi SA. Studies into computational intelligence approaches for the identification of complex nonlinear systems. [Doctoral Dissertation]. University of Southern California; 2016. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/386427/rec/6151


University of Southern California

15. Ashrafulla, Syed. Causality and consistency in electrophysiological signals.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 Model‐based approaches to electrophysiological signal processing provide low‐variance estimates of the activity and relationships within neurological systems. In this dissertation, we develop a method for… (more)

Subjects/Keywords: signal processing; correlation; causality; autoregression; conditional heteroscedasticity; brain; electroencephalography; magnetoencephalography; electrophysiology

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APA (6th Edition):

Ashrafulla, S. (2014). Causality and consistency in electrophysiological signals. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256

Chicago Manual of Style (16th Edition):

Ashrafulla, Syed. “Causality and consistency in electrophysiological signals.” 2014. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256.

MLA Handbook (7th Edition):

Ashrafulla, Syed. “Causality and consistency in electrophysiological signals.” 2014. Web. 20 Oct 2019.

Vancouver:

Ashrafulla S. Causality and consistency in electrophysiological signals. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256.

Council of Science Editors:

Ashrafulla S. Causality and consistency in electrophysiological signals. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256


University of Southern California

16. Low, Tze-Ping. Physical layer multicasting with opportunistic multicast scheduling.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 Physical layer multicasting with optimized opportunistic scheduling is studied for cellular networks, where the problem of efficiently transmitting a common set of fountain-encoded data from… (more)

Subjects/Keywords: wireless multicast; opportunistic scheduling; physical layer multicasting; order statistics; extreme value theory

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

APA (6th Edition):

Low, T. (2011). Physical layer multicasting with opportunistic multicast scheduling. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/621298/rec/5048

Chicago Manual of Style (16th Edition):

Low, Tze-Ping. “Physical layer multicasting with opportunistic multicast scheduling.” 2011. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/621298/rec/5048.

MLA Handbook (7th Edition):

Low, Tze-Ping. “Physical layer multicasting with opportunistic multicast scheduling.” 2011. Web. 20 Oct 2019.

Vancouver:

Low T. Physical layer multicasting with opportunistic multicast scheduling. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/621298/rec/5048.

Council of Science Editors:

Low T. Physical layer multicasting with opportunistic multicast scheduling. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/621298/rec/5048


University of Southern California

17. Liu, Feilong. Intelligent signal processing for oilfield waterflood management.

Degree: PhD, Electrical Engineering, 2008, University of Southern California

 This thesis addresses two problems about water-flood management: (1) infer reservoir heterogeneity using measured injection and production rates, and (2) construct a decision support system… (more)

Subjects/Keywords: oilfield waterflood management; reservoir connectivity; injector-producer relationship; regional impact; extended kalman filter; decision support system; computing with words; fuzzistics; interval approach

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

APA (6th Edition):

Liu, F. (2008). Intelligent signal processing for oilfield waterflood management. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/54766/rec/3558

Chicago Manual of Style (16th Edition):

Liu, Feilong. “Intelligent signal processing for oilfield waterflood management.” 2008. Doctoral Dissertation, University of Southern California. Accessed October 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/54766/rec/3558.

MLA Handbook (7th Edition):

Liu, Feilong. “Intelligent signal processing for oilfield waterflood management.” 2008. Web. 20 Oct 2019.

Vancouver:

Liu F. Intelligent signal processing for oilfield waterflood management. [Internet] [Doctoral dissertation]. University of Southern California; 2008. [cited 2019 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/54766/rec/3558.

Council of Science Editors:

Liu F. Intelligent signal processing for oilfield waterflood management. [Doctoral Dissertation]. University of Southern California; 2008. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/54766/rec/3558

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