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You searched for +publisher:"Virginia Tech" +contributor:("Yu, Guoqiang"). Showing records 1 – 30 of 34 total matches.

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Virginia Tech

1. Mishra, Sourav. Collimator width Optimization in X-ray Luminescent Computed Tomography.

Degree: MS, Computer Engineering, 2013, Virginia Tech

 X-ray Luminescent Computed Tomography (XLCT) is a new imaging modality which is under extensive trials at present. The modality works by selective excitation of X-ray… (more)

Subjects/Keywords: X-ray Luminescence; Computed Tomography; Monte Carlo Methods

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APA (6th Edition):

Mishra, S. (2013). Collimator width Optimization in X-ray Luminescent Computed Tomography. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51118

Chicago Manual of Style (16th Edition):

Mishra, Sourav. “Collimator width Optimization in X-ray Luminescent Computed Tomography.” 2013. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/51118.

MLA Handbook (7th Edition):

Mishra, Sourav. “Collimator width Optimization in X-ray Luminescent Computed Tomography.” 2013. Web. 11 Apr 2021.

Vancouver:

Mishra S. Collimator width Optimization in X-ray Luminescent Computed Tomography. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/51118.

Council of Science Editors:

Mishra S. Collimator width Optimization in X-ray Luminescent Computed Tomography. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/51118


Virginia Tech

2. Aggarwal, Deepti. Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge.

Degree: MS, Electrical Engineering, 2015, Virginia Tech

 Plants have developed specific responses to external stimuli such as drought, cold, high salinity in soil, and precipitation in addition to internal developmental stimuli. These… (more)

Subjects/Keywords: Signal Transduction Pathways; Gene Expression; Inference Engine

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APA (6th Edition):

Aggarwal, D. (2015). Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/56601

Chicago Manual of Style (16th Edition):

Aggarwal, Deepti. “Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge.” 2015. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/56601.

MLA Handbook (7th Edition):

Aggarwal, Deepti. “Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge.” 2015. Web. 11 Apr 2021.

Vancouver:

Aggarwal D. Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/56601.

Council of Science Editors:

Aggarwal D. Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/56601


Virginia Tech

3. Chen, Yang. Robust Prediction of Large Spatio-Temporal Datasets.

Degree: MS, Computer Science and Applications, 2013, Virginia Tech

 This thesis describes a robust and efficient design of Student-t based Robust Spatio-Temporal Prediction, namely, St-RSTP, to provide estimation based on observations over spatio-temporal neighbors.… (more)

Subjects/Keywords: Robust Prediction; Expectation Propagation; Student's t Model; Bayesian Hierarchical Model; Spatio-Temporal Process

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APA (6th Edition):

Chen, Y. (2013). Robust Prediction of Large Spatio-Temporal Datasets. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23098

Chicago Manual of Style (16th Edition):

Chen, Yang. “Robust Prediction of Large Spatio-Temporal Datasets.” 2013. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/23098.

MLA Handbook (7th Edition):

Chen, Yang. “Robust Prediction of Large Spatio-Temporal Datasets.” 2013. Web. 11 Apr 2021.

Vancouver:

Chen Y. Robust Prediction of Large Spatio-Temporal Datasets. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/23098.

Council of Science Editors:

Chen Y. Robust Prediction of Large Spatio-Temporal Datasets. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23098


Virginia Tech

4. Blake, Patrick Michael. Biclustering and Visualization of High Dimensional Data using VIsual Statistical Data Analyzer.

Degree: MS, Electrical Engineering, 2019, Virginia Tech

 Many data sets have too many features for conventional pattern recognition techniques to work properly. This thesis investigates techniques that alleviate these difficulties. One such… (more)

Subjects/Keywords: high-dimensional data; biclustering; VISDA; VISDApy

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APA (6th Edition):

Blake, P. M. (2019). Biclustering and Visualization of High Dimensional Data using VIsual Statistical Data Analyzer. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87392

Chicago Manual of Style (16th Edition):

Blake, Patrick Michael. “Biclustering and Visualization of High Dimensional Data using VIsual Statistical Data Analyzer.” 2019. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/87392.

MLA Handbook (7th Edition):

Blake, Patrick Michael. “Biclustering and Visualization of High Dimensional Data using VIsual Statistical Data Analyzer.” 2019. Web. 11 Apr 2021.

Vancouver:

Blake PM. Biclustering and Visualization of High Dimensional Data using VIsual Statistical Data Analyzer. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/87392.

Council of Science Editors:

Blake PM. Biclustering and Visualization of High Dimensional Data using VIsual Statistical Data Analyzer. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87392


Virginia Tech

5. Hou, Xuchu. Accurate Identification of Significant Aberrations in Cancer Genome: Implementation and Applications.

Degree: MS, Computer Engineering, 2013, Virginia Tech

 Somatic Copy Number Alterations (CNAs) are common events in human cancers. Identifying CNAs and Significant Copy number Aberrations (SCAs) in cancer genomes is a critical… (more)

Subjects/Keywords: Copy Number Alterations; Normal Tissue Contamination; Significant Copy number Aberrations; Concurrent Computing

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APA (6th Edition):

Hou, X. (2013). Accurate Identification of Significant Aberrations in Cancer Genome: Implementation and Applications. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19235

Chicago Manual of Style (16th Edition):

Hou, Xuchu. “Accurate Identification of Significant Aberrations in Cancer Genome: Implementation and Applications.” 2013. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/19235.

MLA Handbook (7th Edition):

Hou, Xuchu. “Accurate Identification of Significant Aberrations in Cancer Genome: Implementation and Applications.” 2013. Web. 11 Apr 2021.

Vancouver:

Hou X. Accurate Identification of Significant Aberrations in Cancer Genome: Implementation and Applications. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/19235.

Council of Science Editors:

Hou X. Accurate Identification of Significant Aberrations in Cancer Genome: Implementation and Applications. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19235


Virginia Tech

6. Gaebel, Ethan Daniel. Looks Good To Me (LGTM): Authentication for Augmented Reality.

Degree: MS, Computer Science and Applications, 2016, Virginia Tech

 Augmented reality is poised to become the next dominant computing paradigm over the course of the next decade. With the three-dimensional graphics and interactive interfaces… (more)

Subjects/Keywords: augmented reality; authentication; looks good to me; lgtm; mixed reality; hologram; holograms; wireless localization; localization

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APA (6th Edition):

Gaebel, E. D. (2016). Looks Good To Me (LGTM): Authentication for Augmented Reality. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71638

Chicago Manual of Style (16th Edition):

Gaebel, Ethan Daniel. “Looks Good To Me (LGTM): Authentication for Augmented Reality.” 2016. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/71638.

MLA Handbook (7th Edition):

Gaebel, Ethan Daniel. “Looks Good To Me (LGTM): Authentication for Augmented Reality.” 2016. Web. 11 Apr 2021.

Vancouver:

Gaebel ED. Looks Good To Me (LGTM): Authentication for Augmented Reality. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/71638.

Council of Science Editors:

Gaebel ED. Looks Good To Me (LGTM): Authentication for Augmented Reality. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/71638


Virginia Tech

7. Raman, Pujita. Speaker Identification and Verification Using Line Spectral Frequencies.

Degree: MS, Electrical Engineering, 2015, Virginia Tech

 State-of-the-art speaker identification and verification (SIV) systems provide near perfect performance under clean conditions. However, their performance deteriorates in the presence of background noise. Many… (more)

Subjects/Keywords: Speech; Speaker; Noise; Identification; Verification; Recognition; Feature; Line Spectral Frequency; Gaussian Mixture Model; Transition; Vowel

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APA (6th Edition):

Raman, P. (2015). Speaker Identification and Verification Using Line Spectral Frequencies. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/52964

Chicago Manual of Style (16th Edition):

Raman, Pujita. “Speaker Identification and Verification Using Line Spectral Frequencies.” 2015. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/52964.

MLA Handbook (7th Edition):

Raman, Pujita. “Speaker Identification and Verification Using Line Spectral Frequencies.” 2015. Web. 11 Apr 2021.

Vancouver:

Raman P. Speaker Identification and Verification Using Line Spectral Frequencies. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/52964.

Council of Science Editors:

Raman P. Speaker Identification and Verification Using Line Spectral Frequencies. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/52964


Virginia Tech

8. Chang, Yi Tan. A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis.

Degree: MS, Computer Engineering, 2018, Virginia Tech

 This thesis consists of two projects in which various machine learning approaches and statistical analysis for the integration of biomedical data analysis were explored, developed… (more)

Subjects/Keywords: Data integration; machine learning; pathway enrichment; pathway prioritization; matrix completion; treatment recommendation.

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APA (6th Edition):

Chang, Y. T. (2018). A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83813

Chicago Manual of Style (16th Edition):

Chang, Yi Tan. “A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis.” 2018. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/83813.

MLA Handbook (7th Edition):

Chang, Yi Tan. “A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis.” 2018. Web. 11 Apr 2021.

Vancouver:

Chang YT. A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/83813.

Council of Science Editors:

Chang YT. A Study of Machine Learning Approaches for Integrated Biomedical Data Analysis. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83813


Virginia Tech

9. Adhikari, Rajendra. Algorithms and Simulation Framework for Residential Demand Response.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

 The total power generation and consumption has to always match in the electric grid. When there is a mismatch because the generation is less than… (more)

Subjects/Keywords: Demand Response; DR Simulation Framework; Aggregated HVAC Control; Regulation; Load Reduction; Residential Building Control

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APA (6th Edition):

Adhikari, R. (2019). Algorithms and Simulation Framework for Residential Demand Response. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87585

Chicago Manual of Style (16th Edition):

Adhikari, Rajendra. “Algorithms and Simulation Framework for Residential Demand Response.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/87585.

MLA Handbook (7th Edition):

Adhikari, Rajendra. “Algorithms and Simulation Framework for Residential Demand Response.” 2019. Web. 11 Apr 2021.

Vancouver:

Adhikari R. Algorithms and Simulation Framework for Residential Demand Response. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/87585.

Council of Science Editors:

Adhikari R. Algorithms and Simulation Framework for Residential Demand Response. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87585


Virginia Tech

10. Flowers, Bryse Austin. Adversarial RFML: Evading Deep Learning Enabled Signal Classification.

Degree: MS, Computer Engineering, 2019, Virginia Tech

 Deep learning is beginning to permeate many commercial products and is being included in prototypes for next generation wireless communications devices. This technology can provide… (more)

Subjects/Keywords: Adversarial Signal Processing; Cognitive Radio Security; Machine Learning; Modulation Identification; Radio Frequency Machine Learning

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APA (6th Edition):

Flowers, B. A. (2019). Adversarial RFML: Evading Deep Learning Enabled Signal Classification. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91987

Chicago Manual of Style (16th Edition):

Flowers, Bryse Austin. “Adversarial RFML: Evading Deep Learning Enabled Signal Classification.” 2019. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/91987.

MLA Handbook (7th Edition):

Flowers, Bryse Austin. “Adversarial RFML: Evading Deep Learning Enabled Signal Classification.” 2019. Web. 11 Apr 2021.

Vancouver:

Flowers BA. Adversarial RFML: Evading Deep Learning Enabled Signal Classification. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/91987.

Council of Science Editors:

Flowers BA. Adversarial RFML: Evading Deep Learning Enabled Signal Classification. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91987


Virginia Tech

11. Mukherjee, Anway. Power-Performance-Predictability: Managing the Three Cornerstones of Resource Constrained Real-Time System Design.

Degree: PhD, Computer Engineering, 2019, Virginia Tech

 Today's real-world problems demand real-time solutions. These solutions need to be practically feasible, and scale well with increasing end user demands. They also need to… (more)

Subjects/Keywords: Real-Time Systems; Trusted Execution; Voltage-Frequency Scaling; Android

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APA (6th Edition):

Mukherjee, A. (2019). Power-Performance-Predictability: Managing the Three Cornerstones of Resource Constrained Real-Time System Design. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/95472

Chicago Manual of Style (16th Edition):

Mukherjee, Anway. “Power-Performance-Predictability: Managing the Three Cornerstones of Resource Constrained Real-Time System Design.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/95472.

MLA Handbook (7th Edition):

Mukherjee, Anway. “Power-Performance-Predictability: Managing the Three Cornerstones of Resource Constrained Real-Time System Design.” 2019. Web. 11 Apr 2021.

Vancouver:

Mukherjee A. Power-Performance-Predictability: Managing the Three Cornerstones of Resource Constrained Real-Time System Design. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/95472.

Council of Science Editors:

Mukherjee A. Power-Performance-Predictability: Managing the Three Cornerstones of Resource Constrained Real-Time System Design. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/95472


Virginia Tech

12. Cai, Mengmeng. A Profit-Neutral Double-price-signal Retail Electricity Market Solution for Incentivizing Price-responsive DERs Considering Network Constraints.

Degree: PhD, Electrical Engineering, 2020, Virginia Tech

 The electricity market plays a critical role in ensuring the economic and secure operation of the power system. The progress made by distributed energy resources… (more)

Subjects/Keywords: Retail Electricity Market; Load Forecasting; Battery Arbitrage; Bi-level Optimization; Deep Learning

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APA (6th Edition):

Cai, M. (2020). A Profit-Neutral Double-price-signal Retail Electricity Market Solution for Incentivizing Price-responsive DERs Considering Network Constraints. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99094

Chicago Manual of Style (16th Edition):

Cai, Mengmeng. “A Profit-Neutral Double-price-signal Retail Electricity Market Solution for Incentivizing Price-responsive DERs Considering Network Constraints.” 2020. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/99094.

MLA Handbook (7th Edition):

Cai, Mengmeng. “A Profit-Neutral Double-price-signal Retail Electricity Market Solution for Incentivizing Price-responsive DERs Considering Network Constraints.” 2020. Web. 11 Apr 2021.

Vancouver:

Cai M. A Profit-Neutral Double-price-signal Retail Electricity Market Solution for Incentivizing Price-responsive DERs Considering Network Constraints. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/99094.

Council of Science Editors:

Cai M. A Profit-Neutral Double-price-signal Retail Electricity Market Solution for Incentivizing Price-responsive DERs Considering Network Constraints. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99094


Virginia Tech

13. Youssef, Ibrahim Mohamed. Multi-Platform Molecular Data Integration and Disease Outcome Analysis.

Degree: PhD, Electrical Engineering, 2016, Virginia Tech

 One of the most common measures of clinical outcomes is the survival time. Accurately linking cancer molecular profiling with survival outcome advances clinical management of… (more)

Subjects/Keywords: survival analysis; Cox proportional hazards model; molecular data integration; intratumor vascular heterogeneity

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APA (6th Edition):

Youssef, I. M. (2016). Multi-Platform Molecular Data Integration and Disease Outcome Analysis. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73580

Chicago Manual of Style (16th Edition):

Youssef, Ibrahim Mohamed. “Multi-Platform Molecular Data Integration and Disease Outcome Analysis.” 2016. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/73580.

MLA Handbook (7th Edition):

Youssef, Ibrahim Mohamed. “Multi-Platform Molecular Data Integration and Disease Outcome Analysis.” 2016. Web. 11 Apr 2021.

Vancouver:

Youssef IM. Multi-Platform Molecular Data Integration and Disease Outcome Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/73580.

Council of Science Editors:

Youssef IM. Multi-Platform Molecular Data Integration and Disease Outcome Analysis. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/73580


Virginia Tech

14. Fu, Yi. Differential Dependency Network and Data Integration for Detecting Network Rewiring and Biomarkers.

Degree: PhD, Electrical Engineering, 2020, Virginia Tech

 We witnessed the start of the human genome project decades ago and stepped into the era of omics since then. Omics are comprehensive approaches for… (more)

Subjects/Keywords: molecular data integration; differential network analysis; biomarker

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APA (6th Edition):

Fu, Y. (2020). Differential Dependency Network and Data Integration for Detecting Network Rewiring and Biomarkers. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/96634

Chicago Manual of Style (16th Edition):

Fu, Yi. “Differential Dependency Network and Data Integration for Detecting Network Rewiring and Biomarkers.” 2020. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/96634.

MLA Handbook (7th Edition):

Fu, Yi. “Differential Dependency Network and Data Integration for Detecting Network Rewiring and Biomarkers.” 2020. Web. 11 Apr 2021.

Vancouver:

Fu Y. Differential Dependency Network and Data Integration for Detecting Network Rewiring and Biomarkers. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/96634.

Council of Science Editors:

Fu Y. Differential Dependency Network and Data Integration for Detecting Network Rewiring and Biomarkers. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/96634


Virginia Tech

15. Wirsing, Karlton E. Multifractal Analysis of Geomagnetically Induced Currents using Wavelet Leaders.

Degree: PhD, Electrical Engineering, 2020, Virginia Tech

 Earth’s weather affects all of us every day. The solar space environment has weather of its own that affects us as well. Storms of a… (more)

Subjects/Keywords: Wavelet; Fractal; Wavelet Leader; Multifractal; Geomagnetically Induced Currents

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APA (6th Edition):

Wirsing, K. E. (2020). Multifractal Analysis of Geomagnetically Induced Currents using Wavelet Leaders. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/98781

Chicago Manual of Style (16th Edition):

Wirsing, Karlton E. “Multifractal Analysis of Geomagnetically Induced Currents using Wavelet Leaders.” 2020. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/98781.

MLA Handbook (7th Edition):

Wirsing, Karlton E. “Multifractal Analysis of Geomagnetically Induced Currents using Wavelet Leaders.” 2020. Web. 11 Apr 2021.

Vancouver:

Wirsing KE. Multifractal Analysis of Geomagnetically Induced Currents using Wavelet Leaders. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/98781.

Council of Science Editors:

Wirsing KE. Multifractal Analysis of Geomagnetically Induced Currents using Wavelet Leaders. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/98781


Virginia Tech

16. Wang, Yizhi. Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

 Astrocyte is an important type of glial cell in the brain. Unlike neurons, astrocyte cannot be electrically excited. However, the concentrations of many different molecules… (more)

Subjects/Keywords: Astrocyte activity; Image analysis; Curve alignment; Graphical model

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APA (6th Edition):

Wang, Y. (2019). Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/95988

Chicago Manual of Style (16th Edition):

Wang, Yizhi. “Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/95988.

MLA Handbook (7th Edition):

Wang, Yizhi. “Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.” 2019. Web. 11 Apr 2021.

Vancouver:

Wang Y. Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/95988.

Council of Science Editors:

Wang Y. Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/95988


Virginia Tech

17. Xu, Yijun. Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

 It is a well-known fact that a power system contains many sources of uncertainties. These uncertainties coming from the loads, the renewables, the model and… (more)

Subjects/Keywords: Uncertainty Quantification; Dynamic State Estimation; Generalized Polynomial Chaos; Multi-Element Polynomial Chaos; ANOVA; Polynomial-Chaos-Based Kalman Filter; Response Surface; Bayesian Inference; Markov Chain Monte Carlo.

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APA (6th Edition):

Xu, Y. (2019). Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/97876

Chicago Manual of Style (16th Edition):

Xu, Yijun. “Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/97876.

MLA Handbook (7th Edition):

Xu, Yijun. “Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods.” 2019. Web. 11 Apr 2021.

Vancouver:

Xu Y. Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/97876.

Council of Science Editors:

Xu Y. Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/97876


Virginia Tech

18. Chen, Lulu. Mathematical Modeling and Deconvolution for Molecular Characterization of Tissue Heterogeneity.

Degree: PhD, Computer Engineering, 2020, Virginia Tech

 Tissue samples are essentially mixtures of tissue or cellular subtypes where the proportions of individual subtypes vary across different tissue samples. Data deconvolution aims to… (more)

Subjects/Keywords: bioinformatics; deconvolution; unsupervised learning; convex analysis; feature selection; tissue heterogeneity; biomarkers

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APA (6th Edition):

Chen, L. (2020). Mathematical Modeling and Deconvolution for Molecular Characterization of Tissue Heterogeneity. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/96553

Chicago Manual of Style (16th Edition):

Chen, Lulu. “Mathematical Modeling and Deconvolution for Molecular Characterization of Tissue Heterogeneity.” 2020. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/96553.

MLA Handbook (7th Edition):

Chen, Lulu. “Mathematical Modeling and Deconvolution for Molecular Characterization of Tissue Heterogeneity.” 2020. Web. 11 Apr 2021.

Vancouver:

Chen L. Mathematical Modeling and Deconvolution for Molecular Characterization of Tissue Heterogeneity. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/96553.

Council of Science Editors:

Chen L. Mathematical Modeling and Deconvolution for Molecular Characterization of Tissue Heterogeneity. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/96553


Virginia Tech

19. Zhang, Xiangyu. A Data-driven Approach for Coordinating Air Conditioning Units in Buildings during Demand Response Events.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

 For power system operation, the demand and supply should be equal at all time. During peak hours, the demand becomes very high. One way to… (more)

Subjects/Keywords: smart grid; demand response; HVAC coordination; building thermal model; reinforcement learning

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APA (6th Edition):

Zhang, X. (2019). A Data-driven Approach for Coordinating Air Conditioning Units in Buildings during Demand Response Events. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87517

Chicago Manual of Style (16th Edition):

Zhang, Xiangyu. “A Data-driven Approach for Coordinating Air Conditioning Units in Buildings during Demand Response Events.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/87517.

MLA Handbook (7th Edition):

Zhang, Xiangyu. “A Data-driven Approach for Coordinating Air Conditioning Units in Buildings during Demand Response Events.” 2019. Web. 11 Apr 2021.

Vancouver:

Zhang X. A Data-driven Approach for Coordinating Air Conditioning Units in Buildings during Demand Response Events. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/87517.

Council of Science Editors:

Zhang X. A Data-driven Approach for Coordinating Air Conditioning Units in Buildings during Demand Response Events. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87517


Virginia Tech

20. Saha, Avijit. Development of a Software Platform with Distributed Learning Algorithms for Building Energy Efficiency and Demand Response Applications.

Degree: PhD, Electrical Engineering, 2017, Virginia Tech

 In the United States, over 40% of the country's total energy consumption is in buildings, most of which are either small-sized (<5,000 sqft) or medium-sized… (more)

Subjects/Keywords: Building Energy Management System; Energy Efficiency; Demand Response; Internet of Things; Reinforcement Learning

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APA (6th Edition):

Saha, A. (2017). Development of a Software Platform with Distributed Learning Algorithms for Building Energy Efficiency and Demand Response Applications. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/74423

Chicago Manual of Style (16th Edition):

Saha, Avijit. “Development of a Software Platform with Distributed Learning Algorithms for Building Energy Efficiency and Demand Response Applications.” 2017. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/74423.

MLA Handbook (7th Edition):

Saha, Avijit. “Development of a Software Platform with Distributed Learning Algorithms for Building Energy Efficiency and Demand Response Applications.” 2017. Web. 11 Apr 2021.

Vancouver:

Saha A. Development of a Software Platform with Distributed Learning Algorithms for Building Energy Efficiency and Demand Response Applications. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/74423.

Council of Science Editors:

Saha A. Development of a Software Platform with Distributed Learning Algorithms for Building Energy Efficiency and Demand Response Applications. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/74423


Virginia Tech

21. Drikas, Zachary Benjamin. New Techniques for Time-Reversal-Based Ultra-wideband Microwave Pulse Compression in Reverberant Cavities.

Degree: PhD, Electrical Engineering, 2020, Virginia Tech

 Generation of high-peak power, microwave ultra-short pulses (USPs) is desirable for ultra-wideband communications and remote sensing. A variety of microwave USP generators exist today, or… (more)

Subjects/Keywords: Ultra-short pulse (USP); pulse compression; ultra-wideband (UWB); time-reversal; reconfigurable cavity; dispersive cavity

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APA (6th Edition):

Drikas, Z. B. (2020). New Techniques for Time-Reversal-Based Ultra-wideband Microwave Pulse Compression in Reverberant Cavities. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/100998

Chicago Manual of Style (16th Edition):

Drikas, Zachary Benjamin. “New Techniques for Time-Reversal-Based Ultra-wideband Microwave Pulse Compression in Reverberant Cavities.” 2020. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/100998.

MLA Handbook (7th Edition):

Drikas, Zachary Benjamin. “New Techniques for Time-Reversal-Based Ultra-wideband Microwave Pulse Compression in Reverberant Cavities.” 2020. Web. 11 Apr 2021.

Vancouver:

Drikas ZB. New Techniques for Time-Reversal-Based Ultra-wideband Microwave Pulse Compression in Reverberant Cavities. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/100998.

Council of Science Editors:

Drikas ZB. New Techniques for Time-Reversal-Based Ultra-wideband Microwave Pulse Compression in Reverberant Cavities. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/100998

22. Amanzadeh, Leila. Architecting IoT-Enabled Smart Building Testbed.

Degree: MS, Electrical Engineering, 2018, Virginia Tech

 Smart building's benefits range from improving comfort of occupant, increased productivity, reduction in energy consumption and operating costs, lower CO2 emission, to improved life cycle… (more)

Subjects/Keywords: MIMO MPC; HVAC; Testbed; MIMO PID; Applying KVL/KCL automatically

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

APA (6th Edition):

Amanzadeh, L. (2018). Architecting IoT-Enabled Smart Building Testbed. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/85579

Chicago Manual of Style (16th Edition):

Amanzadeh, Leila. “Architecting IoT-Enabled Smart Building Testbed.” 2018. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/85579.

MLA Handbook (7th Edition):

Amanzadeh, Leila. “Architecting IoT-Enabled Smart Building Testbed.” 2018. Web. 11 Apr 2021.

Vancouver:

Amanzadeh L. Architecting IoT-Enabled Smart Building Testbed. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/85579.

Council of Science Editors:

Amanzadeh L. Architecting IoT-Enabled Smart Building Testbed. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/85579

23. Lu, Yingzhou. Multi-omics Data Integration for Identifying Disease Specific Biological Pathways.

Degree: MS, Computer Engineering, 2018, Virginia Tech

 Pathway analysis is an important task for gaining novel insights into the molecular architecture of many complex diseases. With the advancement of new sequencing technologies,… (more)

Subjects/Keywords: Biological Pathways; Multi-omics Data Integration; Muscular Dystrophy; Statistical significance test; Gene set enrichment analysis

…math.arizona.edu/~jwatkins/ttest.pdf [11] Yu, Guoqiang, et al. "Matched gene selection and… 

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APA (6th Edition):

Lu, Y. (2018). Multi-omics Data Integration for Identifying Disease Specific Biological Pathways. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83467

Chicago Manual of Style (16th Edition):

Lu, Yingzhou. “Multi-omics Data Integration for Identifying Disease Specific Biological Pathways.” 2018. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/83467.

MLA Handbook (7th Edition):

Lu, Yingzhou. “Multi-omics Data Integration for Identifying Disease Specific Biological Pathways.” 2018. Web. 11 Apr 2021.

Vancouver:

Lu Y. Multi-omics Data Integration for Identifying Disease Specific Biological Pathways. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/83467.

Council of Science Editors:

Lu Y. Multi-omics Data Integration for Identifying Disease Specific Biological Pathways. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83467

24. Lin, Jason. Analysis of Blockchain-based Smart Contracts for Peer-to-Peer Solar Electricity Transactive Markets.

Degree: MS, Electrical Engineering, 2019, Virginia Tech

 The emergence of blockchain technology and increasing penetration of distributed energy resources (DERs) have created a new opportunity for peer-to-peer (P2P) energy trading. However, challenges… (more)

Subjects/Keywords: auction mechanism; blockchain; game theory; smart contract; transactive energy

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APA (6th Edition):

Lin, J. (2019). Analysis of Blockchain-based Smart Contracts for Peer-to-Peer Solar Electricity Transactive Markets. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87563

Chicago Manual of Style (16th Edition):

Lin, Jason. “Analysis of Blockchain-based Smart Contracts for Peer-to-Peer Solar Electricity Transactive Markets.” 2019. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/87563.

MLA Handbook (7th Edition):

Lin, Jason. “Analysis of Blockchain-based Smart Contracts for Peer-to-Peer Solar Electricity Transactive Markets.” 2019. Web. 11 Apr 2021.

Vancouver:

Lin J. Analysis of Blockchain-based Smart Contracts for Peer-to-Peer Solar Electricity Transactive Markets. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/87563.

Council of Science Editors:

Lin J. Analysis of Blockchain-based Smart Contracts for Peer-to-Peer Solar Electricity Transactive Markets. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87563

25. Bijinemula, Sandeep Kumar. An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks.

Degree: MS, Computer Engineering, 2019, Virginia Tech

 Real-time systems require temporal correctness along with accuracy. This notion of temporal correctness is achieved by specifying deadlines to each of the tasks. In order… (more)

Subjects/Keywords: Adaptive variable rate task; demand bound function; worst-case demand; knapsack problem

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APA (6th Edition):

Bijinemula, S. K. (2019). An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87403

Chicago Manual of Style (16th Edition):

Bijinemula, Sandeep Kumar. “An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks.” 2019. Masters Thesis, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/87403.

MLA Handbook (7th Edition):

Bijinemula, Sandeep Kumar. “An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks.” 2019. Web. 11 Apr 2021.

Vancouver:

Bijinemula SK. An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/87403.

Council of Science Editors:

Bijinemula SK. An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87403


Virginia Tech

26. Zheng, Yao. Privacy Preservation for Cloud-Based Data Sharing and Data Analytics.

Degree: PhD, Computer Science and Applications, 2016, Virginia Tech

 Data privacy is a globally recognized human right for individuals to control the access to their personal information, and bar the negative consequences from the… (more)

Subjects/Keywords: information privacy; cryptography; machine learning

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APA (6th Edition):

Zheng, Y. (2016). Privacy Preservation for Cloud-Based Data Sharing and Data Analytics. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73796

Chicago Manual of Style (16th Edition):

Zheng, Yao. “Privacy Preservation for Cloud-Based Data Sharing and Data Analytics.” 2016. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/73796.

MLA Handbook (7th Edition):

Zheng, Yao. “Privacy Preservation for Cloud-Based Data Sharing and Data Analytics.” 2016. Web. 11 Apr 2021.

Vancouver:

Zheng Y. Privacy Preservation for Cloud-Based Data Sharing and Data Analytics. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/73796.

Council of Science Editors:

Zheng Y. Privacy Preservation for Cloud-Based Data Sharing and Data Analytics. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/73796

27. Tsai, Tsung-Heng. Bayesian Alignment Model for Analysis of LC-MS-based Omic Data.

Degree: PhD, Electrical Engineering, 2014, Virginia Tech

 Liquid chromatography coupled with mass spectrometry (LC-MS) has been widely used in various omic studies for biomarker discovery. Appropriate LC-MS data preprocessing steps are needed… (more)

Subjects/Keywords: alignment; Bayesian inference; biomarker discovery; liquid chromatography-mass spectrometry (LC-MS); Markov chain Monte Carlo (MCMC)

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APA (6th Edition):

Tsai, T. (2014). Bayesian Alignment Model for Analysis of LC-MS-based Omic Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64151

Chicago Manual of Style (16th Edition):

Tsai, Tsung-Heng. “Bayesian Alignment Model for Analysis of LC-MS-based Omic Data.” 2014. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/64151.

MLA Handbook (7th Edition):

Tsai, Tsung-Heng. “Bayesian Alignment Model for Analysis of LC-MS-based Omic Data.” 2014. Web. 11 Apr 2021.

Vancouver:

Tsai T. Bayesian Alignment Model for Analysis of LC-MS-based Omic Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/64151.

Council of Science Editors:

Tsai T. Bayesian Alignment Model for Analysis of LC-MS-based Omic Data. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64151

28. Ghosh, Shibani. A Real-time Management of Distribution Voltage Fluctuations due to High Solar Photovoltaic (PV) Penetrations.

Degree: PhD, Electrical Engineering, 2017, Virginia Tech

 Due to the rapid growth of grid-tied solar photovoltaic (PV) systems in the generation mix, the distribution grid will face complex operational challenges. High PV… (more)

Subjects/Keywords: Solar photovoltaic (PV) system; High PV penetration; Distribution voltage regulation; Solar generation forecasting; Active power curtailment

…Voltage Regulator Virginia Tech- Advanced Research Institute xii 1. Introduction 1.1… …Virginia Tech Advanced Research Institute (VT-ARI) building in Arlington, Virginia. The… 

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APA (6th Edition):

Ghosh, S. (2017). A Real-time Management of Distribution Voltage Fluctuations due to High Solar Photovoltaic (PV) Penetrations. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/74424

Chicago Manual of Style (16th Edition):

Ghosh, Shibani. “A Real-time Management of Distribution Voltage Fluctuations due to High Solar Photovoltaic (PV) Penetrations.” 2017. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/74424.

MLA Handbook (7th Edition):

Ghosh, Shibani. “A Real-time Management of Distribution Voltage Fluctuations due to High Solar Photovoltaic (PV) Penetrations.” 2017. Web. 11 Apr 2021.

Vancouver:

Ghosh S. A Real-time Management of Distribution Voltage Fluctuations due to High Solar Photovoltaic (PV) Penetrations. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/74424.

Council of Science Editors:

Ghosh S. A Real-time Management of Distribution Voltage Fluctuations due to High Solar Photovoltaic (PV) Penetrations. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/74424

29. Bitaraf, Hamideh. Mitigating Impacts of High Wind Energy Penetration through Energy Storage and Demand Response.

Degree: PhD, Electrical Engineering, 2016, Virginia Tech

 High renewable energy penetration is a goal for many countries to increase energy security and reduce carbon emissions from conventional power plants. Wind energy is… (more)

Subjects/Keywords: High wind energy penetration; Energy storage; Demand response

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APA (6th Edition):

Bitaraf, H. (2016). Mitigating Impacts of High Wind Energy Penetration through Energy Storage and Demand Response. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/70864

Chicago Manual of Style (16th Edition):

Bitaraf, Hamideh. “Mitigating Impacts of High Wind Energy Penetration through Energy Storage and Demand Response.” 2016. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/70864.

MLA Handbook (7th Edition):

Bitaraf, Hamideh. “Mitigating Impacts of High Wind Energy Penetration through Energy Storage and Demand Response.” 2016. Web. 11 Apr 2021.

Vancouver:

Bitaraf H. Mitigating Impacts of High Wind Energy Penetration through Energy Storage and Demand Response. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/70864.

Council of Science Editors:

Bitaraf H. Mitigating Impacts of High Wind Energy Penetration through Energy Storage and Demand Response. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/70864

30. Karra, Kiran. Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine Learning.

Degree: PhD, Electrical Engineering, 2018, Virginia Tech

 Many machine learning (ML) techniques rely on probability, random variables, and stochastic modeling. Although statistics pervades this field, there is a large disconnect between the… (more)

Subjects/Keywords: copula; machine learning; big data; stochastic; probability

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APA (6th Edition):

Karra, K. (2018). Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine Learning. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/85110

Chicago Manual of Style (16th Edition):

Karra, Kiran. “Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine Learning.” 2018. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/85110.

MLA Handbook (7th Edition):

Karra, Kiran. “Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine Learning.” 2018. Web. 11 Apr 2021.

Vancouver:

Karra K. Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine Learning. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/85110.

Council of Science Editors:

Karra K. Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine Learning. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/85110

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