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Dept: Electrical and Computer Engineering

You searched for subject:(Data modeling). Showing records 1 – 30 of 31 total matches.

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University of Texas – Austin

1. Zhang, Yuqun. Modeling and predicting data for business intelligence.

Degree: Electrical and Computer Engineering, 2016, University of Texas – Austin

 Business intelligence is an area where data and actionable information can be analyzed and provided to make more informed business actions. In general, any technique… (more)

Subjects/Keywords: Business intelligence; Data modeling; Data prediction

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

APA (6th Edition):

Zhang, Y. (2016). Modeling and predicting data for business intelligence. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46572

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):

Zhang, Yuqun. “Modeling and predicting data for business intelligence.” 2016. Thesis, University of Texas – Austin. Accessed July 19, 2019. http://hdl.handle.net/2152/46572.

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

MLA Handbook (7th Edition):

Zhang, Yuqun. “Modeling and predicting data for business intelligence.” 2016. Web. 19 Jul 2019.

Vancouver:

Zhang Y. Modeling and predicting data for business intelligence. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2152/46572.

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

Council of Science Editors:

Zhang Y. Modeling and predicting data for business intelligence. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46572

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


Virginia Tech

2. Zaghlool, Shaza B. Dynamic Causal Modeling Across Network Topologies.

Degree: PhD, Electrical and Computer Engineering, 2014, Virginia Tech

 Dynamic Causal Modeling (DCM) uses dynamical systems to represent the high-level neural processing strategy for a given cognitive task. The logical network topology of the… (more)

Subjects/Keywords: Dynamic Causal Modeling; Expectation-Maximization; Missing Data

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APA (6th Edition):

Zaghlool, S. B. (2014). Dynamic Causal Modeling Across Network Topologies. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/46874

Chicago Manual of Style (16th Edition):

Zaghlool, Shaza B. “Dynamic Causal Modeling Across Network Topologies.” 2014. Doctoral Dissertation, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/46874.

MLA Handbook (7th Edition):

Zaghlool, Shaza B. “Dynamic Causal Modeling Across Network Topologies.” 2014. Web. 19 Jul 2019.

Vancouver:

Zaghlool SB. Dynamic Causal Modeling Across Network Topologies. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/46874.

Council of Science Editors:

Zaghlool SB. Dynamic Causal Modeling Across Network Topologies. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/46874


University of Florida

3. Yao, Jin. A Machine Learning Framework for Cancer Progression Modeling.

Degree: PhD, Electrical and Computer Engineering, 2015, University of Florida

 Cancer is a complex system. The dynamics of this system is driven by genetic variation and selection, the twin characteristics of an evolutionary system. In… (more)

Subjects/Keywords: Algorithms; Breast cancer; Cancer; Data models; Datasets; Genes; High dimensional spaces; Machine learning; Modeling; Tumors; cancer  – modeling

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APA (6th Edition):

Yao, J. (2015). A Machine Learning Framework for Cancer Progression Modeling. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047379

Chicago Manual of Style (16th Edition):

Yao, Jin. “A Machine Learning Framework for Cancer Progression Modeling.” 2015. Doctoral Dissertation, University of Florida. Accessed July 19, 2019. http://ufdc.ufl.edu/UFE0047379.

MLA Handbook (7th Edition):

Yao, Jin. “A Machine Learning Framework for Cancer Progression Modeling.” 2015. Web. 19 Jul 2019.

Vancouver:

Yao J. A Machine Learning Framework for Cancer Progression Modeling. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2019 Jul 19]. Available from: http://ufdc.ufl.edu/UFE0047379.

Council of Science Editors:

Yao J. A Machine Learning Framework for Cancer Progression Modeling. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0047379


Virginia Tech

4. Wu, Hao. Probabilistic Modeling of Multi-relational and Multivariate Discrete Data.

Degree: PhD, Electrical and Computer Engineering, 2017, Virginia Tech

Modeling and discovering knowledge from multi-relational and multivariate discrete data is a crucial task that arises in many research and application domains, e.g. text mining,… (more)

Subjects/Keywords: Multivariate Discrete Data; Multi-relational Data; Maximum Entropy Modeling; Subjective Interestingness; Latent Variable Model; Multivariate Poisson Regression; Covariance Estimation.

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APA (6th Edition):

Wu, H. (2017). Probabilistic Modeling of Multi-relational and Multivariate Discrete Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/74959

Chicago Manual of Style (16th Edition):

Wu, Hao. “Probabilistic Modeling of Multi-relational and Multivariate Discrete Data.” 2017. Doctoral Dissertation, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/74959.

MLA Handbook (7th Edition):

Wu, Hao. “Probabilistic Modeling of Multi-relational and Multivariate Discrete Data.” 2017. Web. 19 Jul 2019.

Vancouver:

Wu H. Probabilistic Modeling of Multi-relational and Multivariate Discrete Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/74959.

Council of Science Editors:

Wu H. Probabilistic Modeling of Multi-relational and Multivariate Discrete Data. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/74959


Virginia Tech

5. Rathinavel, Kruthika. Design and Implementation of a Secure Web Platform for a Building Energy Management Open Source Software.

Degree: MS, Electrical and Computer Engineering, 2015, Virginia Tech

 Commercial buildings consume more than 40% of the total energy consumption in the United States. Almost 90% of these buildings are small- and medium-sized buildings… (more)

Subjects/Keywords: building energy management system web platform; open source; data modeling; user interface and security

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APA (6th Edition):

Rathinavel, K. (2015). Design and Implementation of a Secure Web Platform for a Building Energy Management Open Source Software. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/55271

Chicago Manual of Style (16th Edition):

Rathinavel, Kruthika. “Design and Implementation of a Secure Web Platform for a Building Energy Management Open Source Software.” 2015. Masters Thesis, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/55271.

MLA Handbook (7th Edition):

Rathinavel, Kruthika. “Design and Implementation of a Secure Web Platform for a Building Energy Management Open Source Software.” 2015. Web. 19 Jul 2019.

Vancouver:

Rathinavel K. Design and Implementation of a Secure Web Platform for a Building Energy Management Open Source Software. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/55271.

Council of Science Editors:

Rathinavel K. Design and Implementation of a Secure Web Platform for a Building Energy Management Open Source Software. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/55271


Virginia Tech

6. Zhang, Yuji. Module_based Analysis of Biological Data for Network Inference and Biomarker Discovery.

Degree: PhD, Electrical and Computer Engineering, 2010, Virginia Tech

 Systems biology comprises the global, integrated analysis of large-scale data encoding different levels of biological information with the aim to obtain global insight into the… (more)

Subjects/Keywords: Network Modeling; Data Integration; Gene Module Identification; Gene Regulatory Module; Biomarker Discovery

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APA (6th Edition):

Zhang, Y. (2010). Module_based Analysis of Biological Data for Network Inference and Biomarker Discovery. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28482

Chicago Manual of Style (16th Edition):

Zhang, Yuji. “Module_based Analysis of Biological Data for Network Inference and Biomarker Discovery.” 2010. Doctoral Dissertation, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/28482.

MLA Handbook (7th Edition):

Zhang, Yuji. “Module_based Analysis of Biological Data for Network Inference and Biomarker Discovery.” 2010. Web. 19 Jul 2019.

Vancouver:

Zhang Y. Module_based Analysis of Biological Data for Network Inference and Biomarker Discovery. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/28482.

Council of Science Editors:

Zhang Y. Module_based Analysis of Biological Data for Network Inference and Biomarker Discovery. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/28482


Virginia Tech

7. Chen, Xi. Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis.

Degree: PhD, Electrical and Computer Engineering, 2016, Virginia Tech

 Computational biology currently faces challenges in a big data world with thousands of data samples across multiple disease types including cancer. The challenging problem is… (more)

Subjects/Keywords: NGS Data Analysis; Transcriptional Regulatory Network; Genomic Mutation; Bayesian Modeling; Expectation-Maximization; Gibbs Sampling

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APA (6th Edition):

Chen, X. (2016). Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71706

Chicago Manual of Style (16th Edition):

Chen, Xi. “Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis.” 2016. Doctoral Dissertation, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/71706.

MLA Handbook (7th Edition):

Chen, Xi. “Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis.” 2016. Web. 19 Jul 2019.

Vancouver:

Chen X. Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/71706.

Council of Science Editors:

Chen X. Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/71706


Georgia Tech

8. Kim, Pilho. E-model: event-based graph data model theory and implementation.

Degree: PhD, Electrical and Computer Engineering, 2009, Georgia Tech

 The necessity of managing disparate data models is increasing within all IT areas. Emerging hybrid relational-XML systems are under development in this context to support… (more)

Subjects/Keywords: Database architectures; Multimedia databases; Modeling structured; Textual and multimedia data; Graphs and networks; Linked representations; Modeling and management; Data models; Database models; Schema and subschema; Data translation; Database design; Data structures (Computer science); Databases; Multimedia systems; Application program interfaces (Computer software)

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APA (6th Edition):

Kim, P. (2009). E-model: event-based graph data model theory and implementation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29608

Chicago Manual of Style (16th Edition):

Kim, Pilho. “E-model: event-based graph data model theory and implementation.” 2009. Doctoral Dissertation, Georgia Tech. Accessed July 19, 2019. http://hdl.handle.net/1853/29608.

MLA Handbook (7th Edition):

Kim, Pilho. “E-model: event-based graph data model theory and implementation.” 2009. Web. 19 Jul 2019.

Vancouver:

Kim P. E-model: event-based graph data model theory and implementation. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/1853/29608.

Council of Science Editors:

Kim P. E-model: event-based graph data model theory and implementation. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/29608


The Ohio State University

9. Xu, Zichen. Energy Modeling and Management for Data Services in Multi-Tier Mobile Cloud Architectures.

Degree: PhD, Electrical and Computer Engineering, 2016, The Ohio State University

 Researchers' prediction about the emergence of very small and very large computing devices is becoming true. Computer userscreate personal content from their mobile devices and… (more)

Subjects/Keywords: Computer Engineering; Computer Science; Energy modeling, energy management, distributed data services, cost-effective optimization, computing system design

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APA (6th Edition):

Xu, Z. (2016). Energy Modeling and Management for Data Services in Multi-Tier Mobile Cloud Architectures. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1468272637

Chicago Manual of Style (16th Edition):

Xu, Zichen. “Energy Modeling and Management for Data Services in Multi-Tier Mobile Cloud Architectures.” 2016. Doctoral Dissertation, The Ohio State University. Accessed July 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468272637.

MLA Handbook (7th Edition):

Xu, Zichen. “Energy Modeling and Management for Data Services in Multi-Tier Mobile Cloud Architectures.” 2016. Web. 19 Jul 2019.

Vancouver:

Xu Z. Energy Modeling and Management for Data Services in Multi-Tier Mobile Cloud Architectures. [Internet] [Doctoral dissertation]. The Ohio State University; 2016. [cited 2019 Jul 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1468272637.

Council of Science Editors:

Xu Z. Energy Modeling and Management for Data Services in Multi-Tier Mobile Cloud Architectures. [Doctoral Dissertation]. The Ohio State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1468272637


University of California – Irvine

10. Faezi, Sina. Data-Driven Modeling for Minimizing the Side-Channel Information Leakage in Additive Manufacturing.

Degree: Electrical and Computer Engineering, 2017, University of California – Irvine

 Cyber-physical additive manufacturing systems consists of tight integration of cyber and physical domains. This results in new cross-domain vulnerabilities that poses unique security challenges. One… (more)

Subjects/Keywords: Computer engineering; Electrical engineering; Additive Manufacturing; Cyber-Physical System; Data-Driven Modeling; Machine Learning; Mutual Information; Side-Channel Security

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APA (6th Edition):

Faezi, S. (2017). Data-Driven Modeling for Minimizing the Side-Channel Information Leakage in Additive Manufacturing. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/3pt318zr

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):

Faezi, Sina. “Data-Driven Modeling for Minimizing the Side-Channel Information Leakage in Additive Manufacturing.” 2017. Thesis, University of California – Irvine. Accessed July 19, 2019. http://www.escholarship.org/uc/item/3pt318zr.

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

MLA Handbook (7th Edition):

Faezi, Sina. “Data-Driven Modeling for Minimizing the Side-Channel Information Leakage in Additive Manufacturing.” 2017. Web. 19 Jul 2019.

Vancouver:

Faezi S. Data-Driven Modeling for Minimizing the Side-Channel Information Leakage in Additive Manufacturing. [Internet] [Thesis]. University of California – Irvine; 2017. [cited 2019 Jul 19]. Available from: http://www.escholarship.org/uc/item/3pt318zr.

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

Council of Science Editors:

Faezi S. Data-Driven Modeling for Minimizing the Side-Channel Information Leakage in Additive Manufacturing. [Thesis]. University of California – Irvine; 2017. Available from: http://www.escholarship.org/uc/item/3pt318zr

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


University of Windsor

11. Tan, Qingyuan. Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems.

Degree: PhD, Electrical and Computer Engineering, 2018, University of Windsor

 The incorporation of electronic components into modern Internal Combustion, IC, engine systems have facilitated the reduction of fuel consumption and emission from IC engine operations.… (more)

Subjects/Keywords: Data-driven Optimization; Extremum Seeking Control; Field Programmable Gate Array; Internal Combustion Engine; Nonlinear System Modeling; Real-time Control

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APA (6th Edition):

Tan, Q. (2018). Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems. (Doctoral Dissertation). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/7625

Chicago Manual of Style (16th Edition):

Tan, Qingyuan. “Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems.” 2018. Doctoral Dissertation, University of Windsor. Accessed July 19, 2019. https://scholar.uwindsor.ca/etd/7625.

MLA Handbook (7th Edition):

Tan, Qingyuan. “Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems.” 2018. Web. 19 Jul 2019.

Vancouver:

Tan Q. Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems. [Internet] [Doctoral dissertation]. University of Windsor; 2018. [cited 2019 Jul 19]. Available from: https://scholar.uwindsor.ca/etd/7625.

Council of Science Editors:

Tan Q. Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems. [Doctoral Dissertation]. University of Windsor; 2018. Available from: https://scholar.uwindsor.ca/etd/7625


University of Florida

12. Su, Hung. Parallel Performance Wizard - Framework and Techniques for Parallel Application Optimization.

Degree: PhD, Electrical and Computer Engineering, 2010, University of Florida

 Developing a high-performance parallel application is difficult. Given the complexity of high-performance parallel programs, developers often must rely on performance analysis tools to help them… (more)

Subjects/Keywords: Compilers; Computer programming; Data collection; Data processing; Distance functions; Instrumentation; Modeling; Parallel programming; Programming models; Scalability; analysis, automatic, bottleneck, framework, mpi, optimization, parallel, performance, pgas, ppw, shmem, tool, upc

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APA (6th Edition):

Su, H. (2010). Parallel Performance Wizard - Framework and Techniques for Parallel Application Optimization. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0042186

Chicago Manual of Style (16th Edition):

Su, Hung. “Parallel Performance Wizard - Framework and Techniques for Parallel Application Optimization.” 2010. Doctoral Dissertation, University of Florida. Accessed July 19, 2019. http://ufdc.ufl.edu/UFE0042186.

MLA Handbook (7th Edition):

Su, Hung. “Parallel Performance Wizard - Framework and Techniques for Parallel Application Optimization.” 2010. Web. 19 Jul 2019.

Vancouver:

Su H. Parallel Performance Wizard - Framework and Techniques for Parallel Application Optimization. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Jul 19]. Available from: http://ufdc.ufl.edu/UFE0042186.

Council of Science Editors:

Su H. Parallel Performance Wizard - Framework and Techniques for Parallel Application Optimization. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0042186


University of Florida

13. Jhee, Hojin. Multi-Resolution Image Fusion using Multi-Scale Estimation Framework.

Degree: PhD, Electrical and Computer Engineering, 2010, University of Florida

 Recently, we have been experiencing remarkable advance in remote sensing technology and it allows us to capture large classes of natural processes and phenomenon at… (more)

Subjects/Keywords: Covariance; Data smoothing; Dyadics; High resolution; Image processing; Image resolution; Kalman filters; Multiscale modeling; Pixels; Topographical elevation; estimation, imagefusion, kalman, multiresolution, quadtree

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APA (6th Edition):

Jhee, H. (2010). Multi-Resolution Image Fusion using Multi-Scale Estimation Framework. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041618

Chicago Manual of Style (16th Edition):

Jhee, Hojin. “Multi-Resolution Image Fusion using Multi-Scale Estimation Framework.” 2010. Doctoral Dissertation, University of Florida. Accessed July 19, 2019. http://ufdc.ufl.edu/UFE0041618.

MLA Handbook (7th Edition):

Jhee, Hojin. “Multi-Resolution Image Fusion using Multi-Scale Estimation Framework.” 2010. Web. 19 Jul 2019.

Vancouver:

Jhee H. Multi-Resolution Image Fusion using Multi-Scale Estimation Framework. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Jul 19]. Available from: http://ufdc.ufl.edu/UFE0041618.

Council of Science Editors:

Jhee H. Multi-Resolution Image Fusion using Multi-Scale Estimation Framework. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0041618


Virginia Tech

14. Hassan, Ahmed Mohamed Elsayed. Designing, Modeling, and Optimizing Transactional Data Structures.

Degree: PhD, Electrical and Computer Engineering, 2015, Virginia Tech

 Transactional memory (TM) has emerged as a promising synchronization abstraction for multi-core architectures. Unlike traditional lock-based approaches, TM shifts the burden of implementing threads synchronization… (more)

Subjects/Keywords: Transactional Memory; STM; HTM; Transactional Boosting; Concurrent Data Structures; Optimistic Semantic Synchronization; Lazy List; Balanced Trees; Hybrid Transactions; Semantic Validation; Remote Transaction Commit; Modeling; Linearizability

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APA (6th Edition):

Hassan, A. M. E. (2015). Designing, Modeling, and Optimizing Transactional Data Structures. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/56656

Chicago Manual of Style (16th Edition):

Hassan, Ahmed Mohamed Elsayed. “Designing, Modeling, and Optimizing Transactional Data Structures.” 2015. Doctoral Dissertation, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/56656.

MLA Handbook (7th Edition):

Hassan, Ahmed Mohamed Elsayed. “Designing, Modeling, and Optimizing Transactional Data Structures.” 2015. Web. 19 Jul 2019.

Vancouver:

Hassan AME. Designing, Modeling, and Optimizing Transactional Data Structures. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/56656.

Council of Science Editors:

Hassan AME. Designing, Modeling, and Optimizing Transactional Data Structures. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/56656

15. Michel, Jonas Reinhardt. Supporting device-to-device search and sharing of hyper-localized data.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 Supporting emerging mobile applications in densely populated environments requires connecting mobile users and their devices with the surrounding digital landscape. Specifically, the volume of digitally-available… (more)

Subjects/Keywords: Pervasive computing; Distributed systems; Mobile computing; Dynamic networks; Search algorithms; Data modeling; Graph databases; Mobile applications; Time varying graphs; Mobile middleware; Device-to-device communication; Spatiotemporal trajectories

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APA (6th Edition):

Michel, J. R. (2015). Supporting device-to-device search and sharing of hyper-localized data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31018

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):

Michel, Jonas Reinhardt. “Supporting device-to-device search and sharing of hyper-localized data.” 2015. Thesis, University of Texas – Austin. Accessed July 19, 2019. http://hdl.handle.net/2152/31018.

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

MLA Handbook (7th Edition):

Michel, Jonas Reinhardt. “Supporting device-to-device search and sharing of hyper-localized data.” 2015. Web. 19 Jul 2019.

Vancouver:

Michel JR. Supporting device-to-device search and sharing of hyper-localized data. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2152/31018.

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

Council of Science Editors:

Michel JR. Supporting device-to-device search and sharing of hyper-localized data. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31018

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

16. Zinnecker, Alicia M. Modeling for Control Design of an Axisymmetric Scramjet Engine Isolator.

Degree: PhD, Electrical and Computer Engineering, 2012, The Ohio State University

 Renewed interest in scramjet propulsion has motivated efforts to construct models of the scramjet engine flow path that capture transient flow dynamics to an extent… (more)

Subjects/Keywords: Aerospace Engineering; Electrical Engineering; scramjet engines; engine modeling; unstart; disturbance rejection control; physics-based modeling; data-based modeling

modeling of unstart in a cold-flow isolator [24–27]. The data-based modeling effort… …methodologies, and data-based modeling methodologies. Although the usefulness of the physics-based… …construction of an accurate, control-oriented physics-based model. The data-based modeling effort… …1 1.1 Modeling and control of scramjet engines: An overview of the state of the art… …2.1 CFD Grid and Data Collection . . . . . . . . . . . . . . 2.2 Two-dimensional Euler… 

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APA (6th Edition):

Zinnecker, A. M. (2012). Modeling for Control Design of an Axisymmetric Scramjet Engine Isolator. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1354215841

Chicago Manual of Style (16th Edition):

Zinnecker, Alicia M. “Modeling for Control Design of an Axisymmetric Scramjet Engine Isolator.” 2012. Doctoral Dissertation, The Ohio State University. Accessed July 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354215841.

MLA Handbook (7th Edition):

Zinnecker, Alicia M. “Modeling for Control Design of an Axisymmetric Scramjet Engine Isolator.” 2012. Web. 19 Jul 2019.

Vancouver:

Zinnecker AM. Modeling for Control Design of an Axisymmetric Scramjet Engine Isolator. [Internet] [Doctoral dissertation]. The Ohio State University; 2012. [cited 2019 Jul 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1354215841.

Council of Science Editors:

Zinnecker AM. Modeling for Control Design of an Axisymmetric Scramjet Engine Isolator. [Doctoral Dissertation]. The Ohio State University; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1354215841


Virginia Tech

17. Bank, Jason Noah. Propagation of Electromechanical Disturbances across Large Interconnected Power Systems and Extraction of Associated Modal Content from Measurement Data.

Degree: PhD, Electrical and Computer Engineering, 2009, Virginia Tech

 Changes in power system operating conditions cause dynamic changes in angle and frequency. These disturbances propagate throughout the system area with finite speed. This propagation… (more)

Subjects/Keywords: Electromechanical Wave Propagation; Interarea Modes; Measurement Data Visualization; Power System Dynamics; Processing of Measurement Data; System Modeling and Reduction

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APA (6th Edition):

Bank, J. N. (2009). Propagation of Electromechanical Disturbances across Large Interconnected Power Systems and Extraction of Associated Modal Content from Measurement Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73008

Chicago Manual of Style (16th Edition):

Bank, Jason Noah. “Propagation of Electromechanical Disturbances across Large Interconnected Power Systems and Extraction of Associated Modal Content from Measurement Data.” 2009. Doctoral Dissertation, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/73008.

MLA Handbook (7th Edition):

Bank, Jason Noah. “Propagation of Electromechanical Disturbances across Large Interconnected Power Systems and Extraction of Associated Modal Content from Measurement Data.” 2009. Web. 19 Jul 2019.

Vancouver:

Bank JN. Propagation of Electromechanical Disturbances across Large Interconnected Power Systems and Extraction of Associated Modal Content from Measurement Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2009. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/73008.

Council of Science Editors:

Bank JN. Propagation of Electromechanical Disturbances across Large Interconnected Power Systems and Extraction of Associated Modal Content from Measurement Data. [Doctoral Dissertation]. Virginia Tech; 2009. Available from: http://hdl.handle.net/10919/73008


University of Texas – Austin

18. Park, Sangho. A hierarchical graphical model for recognizing human actions and interactions in video.

Degree: Electrical and Computer Engineering, 2004, University of Texas – Austin

 Understanding human behavior in video data is essential in numerous applications including smart surveillance, video annotation/retrieval, and human – computer interaction. Recognizing human interactions is… (more)

Subjects/Keywords: Computer vision; Motion perception (Vision) – Data processing; Electronic surveillance – Data processing; Graphical modeling (Statistics); Bayesian statistical decision theory

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APA (6th Edition):

Park, S. (2004). A hierarchical graphical model for recognizing human actions and interactions in video. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/2160

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):

Park, Sangho. “A hierarchical graphical model for recognizing human actions and interactions in video.” 2004. Thesis, University of Texas – Austin. Accessed July 19, 2019. http://hdl.handle.net/2152/2160.

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

MLA Handbook (7th Edition):

Park, Sangho. “A hierarchical graphical model for recognizing human actions and interactions in video.” 2004. Web. 19 Jul 2019.

Vancouver:

Park S. A hierarchical graphical model for recognizing human actions and interactions in video. [Internet] [Thesis]. University of Texas – Austin; 2004. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2152/2160.

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

Council of Science Editors:

Park S. A hierarchical graphical model for recognizing human actions and interactions in video. [Thesis]. University of Texas – Austin; 2004. Available from: http://hdl.handle.net/2152/2160

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

19. Kumar, Vinay. Multi-state PLS based data-driven predictive modeling for continuous process analytics.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 Today’s process control industry, which is extensively automated, generates huge amounts of process data from the sensors used to monitor the processes. These data if… (more)

Subjects/Keywords: PLS; Data mining; Algorithm; PCA; Data-driven; Analytics; Modeling; Simulation; NIPALS; GUI

…2 1.2 Data-driven Methods In Process Monitoring- A Survey… …13 1.4 A Comparative study of MLR, PCR PLS with Hypothetical Data… …27 Multistate-PLS based Predictive Modeling– A novel method… …41 Figure 3.2. Data generation options for training data… …42 Figure 3.3. Data generation options for testing data… 

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APA (6th Edition):

Kumar, V. (2012). Multi-state PLS based data-driven predictive modeling for continuous process analytics. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5243

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):

Kumar, Vinay. “Multi-state PLS based data-driven predictive modeling for continuous process analytics.” 2012. Thesis, University of Texas – Austin. Accessed July 19, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-5243.

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

MLA Handbook (7th Edition):

Kumar, Vinay. “Multi-state PLS based data-driven predictive modeling for continuous process analytics.” 2012. Web. 19 Jul 2019.

Vancouver:

Kumar V. Multi-state PLS based data-driven predictive modeling for continuous process analytics. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5243.

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

Council of Science Editors:

Kumar V. Multi-state PLS based data-driven predictive modeling for continuous process analytics. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5243

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


University of Florida

20. Hsu, Jia-Tzer, 1962-. CAD models and formulations for electro-/magneto-thermal simulation of power semiconductor and magnetic devices.

Degree: PhD, Electrical and Computer Engineering, 1995, University of Florida

Subjects/Keywords: Electric current; Hysteresis; Magnetic circuits; Magnetism; Magnets; Matrices; Modeling; Parametric models; Simulations; Two dimensional modeling; Magnetic devices  – Design and construction  – Data processing; Power semiconductors  – Design and construction  – Data processing

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APA (6th Edition):

Hsu, Jia-Tzer, 1. (1995). CAD models and formulations for electro-/magneto-thermal simulation of power semiconductor and magnetic devices. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00040324

Chicago Manual of Style (16th Edition):

Hsu, Jia-Tzer, 1962-. “CAD models and formulations for electro-/magneto-thermal simulation of power semiconductor and magnetic devices.” 1995. Doctoral Dissertation, University of Florida. Accessed July 19, 2019. http://ufdc.ufl.edu/AA00040324.

MLA Handbook (7th Edition):

Hsu, Jia-Tzer, 1962-. “CAD models and formulations for electro-/magneto-thermal simulation of power semiconductor and magnetic devices.” 1995. Web. 19 Jul 2019.

Vancouver:

Hsu, Jia-Tzer 1. CAD models and formulations for electro-/magneto-thermal simulation of power semiconductor and magnetic devices. [Internet] [Doctoral dissertation]. University of Florida; 1995. [cited 2019 Jul 19]. Available from: http://ufdc.ufl.edu/AA00040324.

Council of Science Editors:

Hsu, Jia-Tzer 1. CAD models and formulations for electro-/magneto-thermal simulation of power semiconductor and magnetic devices. [Doctoral Dissertation]. University of Florida; 1995. Available from: http://ufdc.ufl.edu/AA00040324


Georgia Tech

21. Yaman, Sibel. A multi-objective programming perspective to statistical learning problems.

Degree: PhD, Electrical and Computer Engineering, 2008, Georgia Tech

 It has been increasingly recognized that realistic problems often involve a tradeoff among many conflicting objectives. Traditional methods aim at satisfying multiple objectives by combining… (more)

Subjects/Keywords: Pattern recognition; Statistical language modeling; Automatic speech recognition; Multiobjective optimization; Speech processing systems; Electronic data processing; Interpolation; Approximation theory

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APA (6th Edition):

Yaman, S. (2008). A multi-objective programming perspective to statistical learning problems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/26470

Chicago Manual of Style (16th Edition):

Yaman, Sibel. “A multi-objective programming perspective to statistical learning problems.” 2008. Doctoral Dissertation, Georgia Tech. Accessed July 19, 2019. http://hdl.handle.net/1853/26470.

MLA Handbook (7th Edition):

Yaman, Sibel. “A multi-objective programming perspective to statistical learning problems.” 2008. Web. 19 Jul 2019.

Vancouver:

Yaman S. A multi-objective programming perspective to statistical learning problems. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/1853/26470.

Council of Science Editors:

Yaman S. A multi-objective programming perspective to statistical learning problems. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/26470

22. Wang, Xiao. Computational Modeling for Differential Analysis of RNA-seq and Methylation data.

Degree: PhD, Electrical and Computer Engineering, 2016, Virginia Tech

 Computational systems biology is an inter-disciplinary field that aims to develop computational approaches for a system-level understanding of biological systems. Advances in high-throughput biotechnology offer… (more)

Subjects/Keywords: Differential Analysis; Bayesian Modeling; Markov Random Field; RNA-seq Data Analysis; Markov Chain Monte Carlo (MCMC)

modeling the characteristics of the data of interest. We summarize the major contributions as… …differential analysis of RNA-seq data at isoform-level by joint modeling the variability of RNA-seq… …4 Figure 2.1 Between-sample variation and within-sample variation in RNA-seq data. (a… …simulation data sets at varying parameters  ,  0 : (a) histograms of SNRs of… …41 Figure 2.11 ROC curves of all competing methods on simulation data generated by… 

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APA (6th Edition):

Wang, X. (2016). Computational Modeling for Differential Analysis of RNA-seq and Methylation data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/72271

Chicago Manual of Style (16th Edition):

Wang, Xiao. “Computational Modeling for Differential Analysis of RNA-seq and Methylation data.” 2016. Doctoral Dissertation, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/72271.

MLA Handbook (7th Edition):

Wang, Xiao. “Computational Modeling for Differential Analysis of RNA-seq and Methylation data.” 2016. Web. 19 Jul 2019.

Vancouver:

Wang X. Computational Modeling for Differential Analysis of RNA-seq and Methylation data. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/72271.

Council of Science Editors:

Wang X. Computational Modeling for Differential Analysis of RNA-seq and Methylation data. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/72271

23. Jeong, Jae Hoon. Efficient verification/testing of system-on-chip through fault grading and analog behavioral modeling.

Degree: Electrical and Computer Engineering, 2013, University of Texas – Austin

 This dissertation presents several cost-effective production test solutions using fault grading and mixed-signal design verification cases enabled by analog behavioral modeling. Although the latest System-on-Chip… (more)

Subjects/Keywords: Fault grading; Analog behavioral modeling; Package-on-package; Test data reduction

…strategies and benefits of analog behavioral modeling techniques that I implemented are presented… …and actual verification cases shows the effectiveness of analog modeling for better quality… …1 4 Chapter 2. 9 Background Chapter 3. 3.1 3.2 3.3 3.4 Reduction of Test Data Volume… …Behavioral Modeling: Strategies and Methodologies Behavioral Modeling Strategies . . . . . . 7.1.1… …Top-Down Modeling . . . . . . . . 7.1.2 Bottom-up Modeling . . . . . . . . Industrial Trends… 

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APA (6th Edition):

Jeong, J. H. (2013). Efficient verification/testing of system-on-chip through fault grading and analog behavioral modeling. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/23091

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):

Jeong, Jae Hoon. “Efficient verification/testing of system-on-chip through fault grading and analog behavioral modeling.” 2013. Thesis, University of Texas – Austin. Accessed July 19, 2019. http://hdl.handle.net/2152/23091.

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

MLA Handbook (7th Edition):

Jeong, Jae Hoon. “Efficient verification/testing of system-on-chip through fault grading and analog behavioral modeling.” 2013. Web. 19 Jul 2019.

Vancouver:

Jeong JH. Efficient verification/testing of system-on-chip through fault grading and analog behavioral modeling. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2152/23091.

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

Council of Science Editors:

Jeong JH. Efficient verification/testing of system-on-chip through fault grading and analog behavioral modeling. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/23091

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

24. Deodhar, Meghana. Simultaneous partitioning and modeling : a framework for learning from complex data.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 While a single learned model is adequate for simple prediction problems, it may not be sufficient to represent heterogeneous populations that difficult classification or regression… (more)

Subjects/Keywords: Predictive modeling; Dyadic data with covariates; Co-clustering; Regression; Classification; Parallelism

…Simultaneous Partitioning and Modeling: A Framework for Learning from Complex Data… …automatically identify and discard irrelevant data points and features while modeling, in order to… …predictive modeling of multi-modal data, where one of the modes is implicitly ordered, e.g., time… …Modeling of Dyadic Data . . . . 2.2.1 Latent Factor Models . . . . . . . . . . . . . . . . . 2.3… …Models . . . . . . . . . . . . . 5.5 Modeling a Selected Data Subset… 

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APA (6th Edition):

Deodhar, M. (2010). Simultaneous partitioning and modeling : a framework for learning from complex data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-05-1284

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):

Deodhar, Meghana. “Simultaneous partitioning and modeling : a framework for learning from complex data.” 2010. Thesis, University of Texas – Austin. Accessed July 19, 2019. http://hdl.handle.net/2152/ETD-UT-2010-05-1284.

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

MLA Handbook (7th Edition):

Deodhar, Meghana. “Simultaneous partitioning and modeling : a framework for learning from complex data.” 2010. Web. 19 Jul 2019.

Vancouver:

Deodhar M. Simultaneous partitioning and modeling : a framework for learning from complex data. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-1284.

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

Council of Science Editors:

Deodhar M. Simultaneous partitioning and modeling : a framework for learning from complex data. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-1284

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


University of Florida

25. Wang, Ludong, 1961-. Local dynamic modeling with self-organizing feature maps.

Degree: PhD, Electrical and Computer Engineering, 1996, University of Florida

Subjects/Keywords: Architectural models; Dynamic modeling; Learning; Linear models; Mathematical vectors; Modeling; Neurons; Signals; Time series; Time series models; Chaotic behavior in systems; Dynamics  – Mathematical models; Self-organizing systems  – Data processing; Signal processing  – Mathematical models

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APA (6th Edition):

Wang, Ludong, 1. (1996). Local dynamic modeling with self-organizing feature maps. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00032516

Chicago Manual of Style (16th Edition):

Wang, Ludong, 1961-. “Local dynamic modeling with self-organizing feature maps.” 1996. Doctoral Dissertation, University of Florida. Accessed July 19, 2019. http://ufdc.ufl.edu/AA00032516.

MLA Handbook (7th Edition):

Wang, Ludong, 1961-. “Local dynamic modeling with self-organizing feature maps.” 1996. Web. 19 Jul 2019.

Vancouver:

Wang, Ludong 1. Local dynamic modeling with self-organizing feature maps. [Internet] [Doctoral dissertation]. University of Florida; 1996. [cited 2019 Jul 19]. Available from: http://ufdc.ufl.edu/AA00032516.

Council of Science Editors:

Wang, Ludong 1. Local dynamic modeling with self-organizing feature maps. [Doctoral Dissertation]. University of Florida; 1996. Available from: http://ufdc.ufl.edu/AA00032516


Georgia Tech

26. Shell, Michael David. Cascaded All-Optical Shared-Memory Architecture Packet Switches Using Channel Grouping Under Bursty Traffic.

Degree: PhD, Electrical and Computer Engineering, 2004, Georgia Tech

 This work develops an exact logical operation model to predict the performance of the all-optical shared-memory architecture (OSMA) class of packet switches and provides a… (more)

Subjects/Keywords: Packet switching; Optical buffering; Networks; Markov models; Channel grouping; Bursty traffic; Banyan networks; Asymmetric; Analytical modeling; All-optical networks; Shared-memory switches; Optical data processing; Packet switching (Data transmission) Mathematical models; Computer networks; Markov processes; Optical communications

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APA (6th Edition):

Shell, M. D. (2004). Cascaded All-Optical Shared-Memory Architecture Packet Switches Using Channel Grouping Under Bursty Traffic. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/4892

Chicago Manual of Style (16th Edition):

Shell, Michael David. “Cascaded All-Optical Shared-Memory Architecture Packet Switches Using Channel Grouping Under Bursty Traffic.” 2004. Doctoral Dissertation, Georgia Tech. Accessed July 19, 2019. http://hdl.handle.net/1853/4892.

MLA Handbook (7th Edition):

Shell, Michael David. “Cascaded All-Optical Shared-Memory Architecture Packet Switches Using Channel Grouping Under Bursty Traffic.” 2004. Web. 19 Jul 2019.

Vancouver:

Shell MD. Cascaded All-Optical Shared-Memory Architecture Packet Switches Using Channel Grouping Under Bursty Traffic. [Internet] [Doctoral dissertation]. Georgia Tech; 2004. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/1853/4892.

Council of Science Editors:

Shell MD. Cascaded All-Optical Shared-Memory Architecture Packet Switches Using Channel Grouping Under Bursty Traffic. [Doctoral Dissertation]. Georgia Tech; 2004. Available from: http://hdl.handle.net/1853/4892


Georgia Tech

27. Jiang, Jeng-Shiann. Measurement, Modeling, and Performance, of Indoor MIMO Channels.

Degree: PhD, Electrical and Computer Engineering, 2004, Georgia Tech

 The objective of this dissertation is to investigate the performance of the recently proposed MIMO technology in real indoor environments based on channel measurements centered… (more)

Subjects/Keywords: Channel modeling; Number-of-sources detection; Measurement; Array signal processing; Smart antenna; MIMO; Signal processing Digital techniques; Wireless communication systems; Data transmission systems

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APA (6th Edition):

Jiang, J. (2004). Measurement, Modeling, and Performance, of Indoor MIMO Channels. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/5035

Chicago Manual of Style (16th Edition):

Jiang, Jeng-Shiann. “Measurement, Modeling, and Performance, of Indoor MIMO Channels.” 2004. Doctoral Dissertation, Georgia Tech. Accessed July 19, 2019. http://hdl.handle.net/1853/5035.

MLA Handbook (7th Edition):

Jiang, Jeng-Shiann. “Measurement, Modeling, and Performance, of Indoor MIMO Channels.” 2004. Web. 19 Jul 2019.

Vancouver:

Jiang J. Measurement, Modeling, and Performance, of Indoor MIMO Channels. [Internet] [Doctoral dissertation]. Georgia Tech; 2004. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/1853/5035.

Council of Science Editors:

Jiang J. Measurement, Modeling, and Performance, of Indoor MIMO Channels. [Doctoral Dissertation]. Georgia Tech; 2004. Available from: http://hdl.handle.net/1853/5035


Louisiana State University

28. Ali, Ahsan-Abbas. Spectrum Allocation in Networks with Finite Sources and Data-Driven Characterization of Users' Stochastic Dynamics.

Degree: PhD, Electrical and Computer Engineering, 2015, Louisiana State University

 During emergency situations, the public safety communication systems (PSCSs) get overloaded with high traffic loads. Note that these PSCSs are finite source networks. The goal… (more)

Subjects/Keywords: spectrum allocation; traffic aware allocation; incidents and context aware allocation; public safety communications; trunked radio; finite source systems; cognitive radio; call admission and preemption control; control channel allocation; joint collision and congestion modeling; variable length Markov chain; context tree; Bayesian information criterion; sequence segmentation; call records data mining and analytics

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APA (6th Edition):

Ali, A. (2015). Spectrum Allocation in Networks with Finite Sources and Data-Driven Characterization of Users' Stochastic Dynamics. (Doctoral Dissertation). Louisiana State University. Retrieved from etd-05212015-210859 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3695

Chicago Manual of Style (16th Edition):

Ali, Ahsan-Abbas. “Spectrum Allocation in Networks with Finite Sources and Data-Driven Characterization of Users' Stochastic Dynamics.” 2015. Doctoral Dissertation, Louisiana State University. Accessed July 19, 2019. etd-05212015-210859 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3695.

MLA Handbook (7th Edition):

Ali, Ahsan-Abbas. “Spectrum Allocation in Networks with Finite Sources and Data-Driven Characterization of Users' Stochastic Dynamics.” 2015. Web. 19 Jul 2019.

Vancouver:

Ali A. Spectrum Allocation in Networks with Finite Sources and Data-Driven Characterization of Users' Stochastic Dynamics. [Internet] [Doctoral dissertation]. Louisiana State University; 2015. [cited 2019 Jul 19]. Available from: etd-05212015-210859 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3695.

Council of Science Editors:

Ali A. Spectrum Allocation in Networks with Finite Sources and Data-Driven Characterization of Users' Stochastic Dynamics. [Doctoral Dissertation]. Louisiana State University; 2015. Available from: etd-05212015-210859 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3695


University of Florida

29. Johnson, Michael Ray. Modeling and detection of limit cycle oscillations in thin-wing aircraft using adaptable linear models.

Degree: PhD, Electrical and Computer Engineering, 2003, University of Florida

Subjects/Keywords: Accelerometers; Aircraft wings; Data lines; Flight conditions; Flight tests; Flutter analysis; Modeling; Oscillators; Parametric models; Signals; Flutter (Aerodynamics); Neural networks (Computer science); Signal processing  – Digital techniques

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APA (6th Edition):

Johnson, M. R. (2003). Modeling and detection of limit cycle oscillations in thin-wing aircraft using adaptable linear models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039280

Chicago Manual of Style (16th Edition):

Johnson, Michael Ray. “Modeling and detection of limit cycle oscillations in thin-wing aircraft using adaptable linear models.” 2003. Doctoral Dissertation, University of Florida. Accessed July 19, 2019. http://ufdc.ufl.edu/AA00039280.

MLA Handbook (7th Edition):

Johnson, Michael Ray. “Modeling and detection of limit cycle oscillations in thin-wing aircraft using adaptable linear models.” 2003. Web. 19 Jul 2019.

Vancouver:

Johnson MR. Modeling and detection of limit cycle oscillations in thin-wing aircraft using adaptable linear models. [Internet] [Doctoral dissertation]. University of Florida; 2003. [cited 2019 Jul 19]. Available from: http://ufdc.ufl.edu/AA00039280.

Council of Science Editors:

Johnson MR. Modeling and detection of limit cycle oscillations in thin-wing aircraft using adaptable linear models. [Doctoral Dissertation]. University of Florida; 2003. Available from: http://ufdc.ufl.edu/AA00039280


University of Florida

30. Zang, Wei. Analytical Modeling and Analysis of Memory Access for Cache Tuning.

Degree: PhD, Electrical and Computer Engineering, 2013, University of Florida

Subjects/Keywords: Acceleration; Analytical estimating; Analytical models; Average speed; Data processing; Evictions; Index sets; Instructional material evaluation; Limited liability companies; Simulations; cache; configuration; modeling

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APA (6th Edition):

Zang, W. (2013). Analytical Modeling and Analysis of Memory Access for Cache Tuning. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045180

Chicago Manual of Style (16th Edition):

Zang, Wei. “Analytical Modeling and Analysis of Memory Access for Cache Tuning.” 2013. Doctoral Dissertation, University of Florida. Accessed July 19, 2019. http://ufdc.ufl.edu/UFE0045180.

MLA Handbook (7th Edition):

Zang, Wei. “Analytical Modeling and Analysis of Memory Access for Cache Tuning.” 2013. Web. 19 Jul 2019.

Vancouver:

Zang W. Analytical Modeling and Analysis of Memory Access for Cache Tuning. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Jul 19]. Available from: http://ufdc.ufl.edu/UFE0045180.

Council of Science Editors:

Zang W. Analytical Modeling and Analysis of Memory Access for Cache Tuning. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045180

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