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You searched for +publisher:"Virginia Tech" +contributor:("Ramakrishnan, Narendran"). Showing records 1 – 30 of 85 total matches.

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Virginia Tech

1. Lokegaonkar, Sanket Avinash. Continual Learning for Deep Dense Prediction.

Degree: MS, Computer Science, 2018, Virginia Tech

 Transferring a deep learning model from old tasks to a new one is known to suffer from the catastrophic forgetting effects. Such forgetting mechanism is… (more)

Subjects/Keywords: Computer Vision; Continual Learning; Image Segmentation; Dense Prediction

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APA (6th Edition):

Lokegaonkar, S. A. (2018). Continual Learning for Deep Dense Prediction. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83513

Chicago Manual of Style (16th Edition):

Lokegaonkar, Sanket Avinash. “Continual Learning for Deep Dense Prediction.” 2018. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/83513.

MLA Handbook (7th Edition):

Lokegaonkar, Sanket Avinash. “Continual Learning for Deep Dense Prediction.” 2018. Web. 17 Oct 2019.

Vancouver:

Lokegaonkar SA. Continual Learning for Deep Dense Prediction. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/83513.

Council of Science Editors:

Lokegaonkar SA. Continual Learning for Deep Dense Prediction. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83513


Virginia Tech

2. Maxwell, Evan Kyle. Graph Mining Algorithms for Memory Leak Diagnosis and Biological Database Clustering.

Degree: MS, Computer Science, 2010, Virginia Tech

 Large graph-based datasets are common to many applications because of the additional structure provided to data by graphs. Patterns extracted from graphs must adhere to… (more)

Subjects/Keywords: graph mining; graph clustering; multipartite cliques; memory leak detection; bioinformatics

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APA (6th Edition):

Maxwell, E. K. (2010). Graph Mining Algorithms for Memory Leak Diagnosis and Biological Database Clustering. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/34008

Chicago Manual of Style (16th Edition):

Maxwell, Evan Kyle. “Graph Mining Algorithms for Memory Leak Diagnosis and Biological Database Clustering.” 2010. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/34008.

MLA Handbook (7th Edition):

Maxwell, Evan Kyle. “Graph Mining Algorithms for Memory Leak Diagnosis and Biological Database Clustering.” 2010. Web. 17 Oct 2019.

Vancouver:

Maxwell EK. Graph Mining Algorithms for Memory Leak Diagnosis and Biological Database Clustering. [Internet] [Masters thesis]. Virginia Tech; 2010. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/34008.

Council of Science Editors:

Maxwell EK. Graph Mining Algorithms for Memory Leak Diagnosis and Biological Database Clustering. [Masters Thesis]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/34008


Virginia Tech

3. Muthiah, Sathappan. Forecasting Protests by Detecting Future Time Mentions in News and Social Media.

Degree: MS, Computer Science, 2014, Virginia Tech

 Civil unrest (protests, strikes, and ``occupy'' events) is a common occurrence in both democracies and authoritarian regimes. The study of civil unrest is a key… (more)

Subjects/Keywords: Textmining; Information Retrieval; Social Media

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APA (6th Edition):

Muthiah, S. (2014). Forecasting Protests by Detecting Future Time Mentions in News and Social Media. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/49535

Chicago Manual of Style (16th Edition):

Muthiah, Sathappan. “Forecasting Protests by Detecting Future Time Mentions in News and Social Media.” 2014. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/49535.

MLA Handbook (7th Edition):

Muthiah, Sathappan. “Forecasting Protests by Detecting Future Time Mentions in News and Social Media.” 2014. Web. 17 Oct 2019.

Vancouver:

Muthiah S. Forecasting Protests by Detecting Future Time Mentions in News and Social Media. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/49535.

Council of Science Editors:

Muthiah S. Forecasting Protests by Detecting Future Time Mentions in News and Social Media. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/49535


Virginia Tech

4. Sundareisan, Shashidhar. Making diffusion work for you: Classification sans text, finding culprits and filling missing values.

Degree: MS, Computer Science, 2014, Virginia Tech

 Can we find people infected with the flu virus even though they did not visit a doctor? Can the temporal features of a trending hashtag… (more)

Subjects/Keywords: Data Mining; Social Networks; Epidemiology; Culprits; Missing nodes; Diffusion; Protests; Classification

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APA (6th Edition):

Sundareisan, S. (2014). Making diffusion work for you: Classification sans text, finding culprits and filling missing values. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/49678

Chicago Manual of Style (16th Edition):

Sundareisan, Shashidhar. “Making diffusion work for you: Classification sans text, finding culprits and filling missing values.” 2014. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/49678.

MLA Handbook (7th Edition):

Sundareisan, Shashidhar. “Making diffusion work for you: Classification sans text, finding culprits and filling missing values.” 2014. Web. 17 Oct 2019.

Vancouver:

Sundareisan S. Making diffusion work for you: Classification sans text, finding culprits and filling missing values. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/49678.

Council of Science Editors:

Sundareisan S. Making diffusion work for you: Classification sans text, finding culprits and filling missing values. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/49678


Virginia Tech

5. Self, Nathan William. User Interfaces for an Open Source Indicators Forecasting System.

Degree: MS, Computer Science, 2015, Virginia Tech

 Intelligence analysts today are faced with many challenges, chief among them being the need to fuse disparate streams of data and rapidly arrive at analytical… (more)

Subjects/Keywords: Visualization; Forecasting; Intelligence Analysis; Open Source Indicators

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APA (6th Edition):

Self, N. W. (2015). User Interfaces for an Open Source Indicators Forecasting System. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/56696

Chicago Manual of Style (16th Edition):

Self, Nathan William. “User Interfaces for an Open Source Indicators Forecasting System.” 2015. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/56696.

MLA Handbook (7th Edition):

Self, Nathan William. “User Interfaces for an Open Source Indicators Forecasting System.” 2015. Web. 17 Oct 2019.

Vancouver:

Self NW. User Interfaces for an Open Source Indicators Forecasting System. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/56696.

Council of Science Editors:

Self NW. User Interfaces for an Open Source Indicators Forecasting System. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/56696


Virginia Tech

6. Wang, Ji. Clustered Layout Word Cloud for User Generated Online Reviews.

Degree: MS, Computer Science, 2012, Virginia Tech

 User generated reviews, like those found on Yelp and Amazon, have become important refer- ence material in casual decision making, like dining, shopping and entertainment.… (more)

Subjects/Keywords: Word Cloud; Text Visualization; User Study

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APA (6th Edition):

Wang, J. (2012). Clustered Layout Word Cloud for User Generated Online Reviews. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19193

Chicago Manual of Style (16th Edition):

Wang, Ji. “Clustered Layout Word Cloud for User Generated Online Reviews.” 2012. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/19193.

MLA Handbook (7th Edition):

Wang, Ji. “Clustered Layout Word Cloud for User Generated Online Reviews.” 2012. Web. 17 Oct 2019.

Vancouver:

Wang J. Clustered Layout Word Cloud for User Generated Online Reviews. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/19193.

Council of Science Editors:

Wang J. Clustered Layout Word Cloud for User Generated Online Reviews. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/19193


Virginia Tech

7. Mahendiran, Aravindan. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.

Degree: MS, Computer Science, 2014, Virginia Tech

 Twitter has become a popular data source in the recent decade and garnered a significant amount of attention as a surrogate data source for many… (more)

Subjects/Keywords: Election Forecasting; Twitter; Query Expansion; Social Group Modeling; Probabilistic Soft Logic

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APA (6th Edition):

Mahendiran, A. (2014). Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/25430

Chicago Manual of Style (16th Edition):

Mahendiran, Aravindan. “Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.” 2014. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/25430.

MLA Handbook (7th Edition):

Mahendiran, Aravindan. “Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.” 2014. Web. 17 Oct 2019.

Vancouver:

Mahendiran A. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/25430.

Council of Science Editors:

Mahendiran A. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/25430


Virginia Tech

8. Arefiyan Khalilabad, Seyyed Mostafa. Deep Learning Models for Context-Aware Object Detection.

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

 In this thesis, we present ContextNet, a novel general object detection framework for incorporating context cues into a detection pipeline. Current deep learning methods for… (more)

Subjects/Keywords: Context-aware Detection; Object Detection; Context Modeling; Context Extraction; Convolutional Neural Network; Computer Vision; Deep Learning; Machine Learning

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APA (6th Edition):

Arefiyan Khalilabad, S. M. (2017). Deep Learning Models for Context-Aware Object Detection. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/88387

Chicago Manual of Style (16th Edition):

Arefiyan Khalilabad, Seyyed Mostafa. “Deep Learning Models for Context-Aware Object Detection.” 2017. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/88387.

MLA Handbook (7th Edition):

Arefiyan Khalilabad, Seyyed Mostafa. “Deep Learning Models for Context-Aware Object Detection.” 2017. Web. 17 Oct 2019.

Vancouver:

Arefiyan Khalilabad SM. Deep Learning Models for Context-Aware Object Detection. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/88387.

Council of Science Editors:

Arefiyan Khalilabad SM. Deep Learning Models for Context-Aware Object Detection. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/88387


Virginia Tech

9. Zhao, Liang. Spatio-temporal Event Detection and Forecasting in Social Media.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Nowadays, knowledge discovery on social media is attracting growing interest. Social media has become more than a communication tool, effectively functioning as a social sensor… (more)

Subjects/Keywords: event detection; event forecasting; social media

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APA (6th Edition):

Zhao, L. (2016). Spatio-temporal Event Detection and Forecasting in Social Media. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81904

Chicago Manual of Style (16th Edition):

Zhao, Liang. “Spatio-temporal Event Detection and Forecasting in Social Media.” 2016. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/81904.

MLA Handbook (7th Edition):

Zhao, Liang. “Spatio-temporal Event Detection and Forecasting in Social Media.” 2016. Web. 17 Oct 2019.

Vancouver:

Zhao L. Spatio-temporal Event Detection and Forecasting in Social Media. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/81904.

Council of Science Editors:

Zhao L. Spatio-temporal Event Detection and Forecasting in Social Media. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/81904


Virginia Tech

10. Cadena, Jose Eduardo. Finding Interesting Subgraphs with Guarantees.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Networks are a mathematical abstraction of the interactions between a set of entities, with extensive applications in social science, epidemiology, bioinformatics, and cybersecurity, among others.… (more)

Subjects/Keywords: Graph Mining; Data Mining; Graph Algorithms; Anomaly Detection; Finding Subgraphs; Parameterized Complexity; Distributed Algorithms

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APA (6th Edition):

Cadena, J. E. (2018). Finding Interesting Subgraphs with Guarantees. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81960

Chicago Manual of Style (16th Edition):

Cadena, Jose Eduardo. “Finding Interesting Subgraphs with Guarantees.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/81960.

MLA Handbook (7th Edition):

Cadena, Jose Eduardo. “Finding Interesting Subgraphs with Guarantees.” 2018. Web. 17 Oct 2019.

Vancouver:

Cadena JE. Finding Interesting Subgraphs with Guarantees. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/81960.

Council of Science Editors:

Cadena JE. Finding Interesting Subgraphs with Guarantees. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/81960


Virginia Tech

11. Hua, Ting. Topics, Events, Stories in Social Media.

Degree: PhD, Computer Science, 2018, Virginia Tech

 The rise of big data, especially social media data (e.g., Twitter, Facebook, Youtube), gives new opportunities to the understanding of human behavior. Consequently, novel computing… (more)

Subjects/Keywords: Social media; Topic modeling; Event Detection

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APA (6th Edition):

Hua, T. (2018). Topics, Events, Stories in Social Media. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82029

Chicago Manual of Style (16th Edition):

Hua, Ting. “Topics, Events, Stories in Social Media.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/82029.

MLA Handbook (7th Edition):

Hua, Ting. “Topics, Events, Stories in Social Media.” 2018. Web. 17 Oct 2019.

Vancouver:

Hua T. Topics, Events, Stories in Social Media. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/82029.

Council of Science Editors:

Hua T. Topics, Events, Stories in Social Media. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82029


Virginia Tech

12. Wang, Wei. Event Detection and Extraction from News Articles.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Event extraction is a type of information extraction(IE) that works on extracting the specific knowledge of certain incidents from texts. Nowadays the amount of available… (more)

Subjects/Keywords: Event Detection; Event Encoding; Deep Learning; Convolutional Neural Network; Recurrent Neural Network; Multi Instance Learning; Multi Task Learning

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APA (6th Edition):

Wang, W. (2018). Event Detection and Extraction from News Articles. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82238

Chicago Manual of Style (16th Edition):

Wang, Wei. “Event Detection and Extraction from News Articles.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/82238.

MLA Handbook (7th Edition):

Wang, Wei. “Event Detection and Extraction from News Articles.” 2018. Web. 17 Oct 2019.

Vancouver:

Wang W. Event Detection and Extraction from News Articles. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/82238.

Council of Science Editors:

Wang W. Event Detection and Extraction from News Articles. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82238


Virginia Tech

13. Guo, Jia. Trust-based Service Management of Internet of Things Systems and Its Applications.

Degree: PhD, Computer Science, 2018, Virginia Tech

 A future Internet of Things (IoT) system will consist of a huge quantity of heterogeneous IoT devices, each capable of providing services upon request. It… (more)

Subjects/Keywords: Trust management; Internet of Things (IoT) systems; mobile cloud computing; service management; security; scalability; performance analysis

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APA (6th Edition):

Guo, J. (2018). Trust-based Service Management of Internet of Things Systems and Its Applications. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82854

Chicago Manual of Style (16th Edition):

Guo, Jia. “Trust-based Service Management of Internet of Things Systems and Its Applications.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/82854.

MLA Handbook (7th Edition):

Guo, Jia. “Trust-based Service Management of Internet of Things Systems and Its Applications.” 2018. Web. 17 Oct 2019.

Vancouver:

Guo J. Trust-based Service Management of Internet of Things Systems and Its Applications. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/82854.

Council of Science Editors:

Guo J. Trust-based Service Management of Internet of Things Systems and Its Applications. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82854


Virginia Tech

14. Saraf, Parang. A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Automated event extraction from free text remains an open problem, particularly when the goal is to identify all relevant events. Manual extraction is currently the… (more)

Subjects/Keywords: Event Extraction; Visual Analytics; News Analytics; Civil Unrest

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APA (6th Edition):

Saraf, P. (2018). A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82926

Chicago Manual of Style (16th Edition):

Saraf, Parang. “A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/82926.

MLA Handbook (7th Edition):

Saraf, Parang. “A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction.” 2018. Web. 17 Oct 2019.

Vancouver:

Saraf P. A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/82926.

Council of Science Editors:

Saraf P. A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82926


Virginia Tech

15. Chen, Liangzhe. Segmenting, Summarizing and Predicting Data Sequences.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Temporal data is ubiquitous nowadays and can be easily found in many applications. Consider the extensively studied social media website Twitter. All the information can… (more)

Subjects/Keywords: Sequence Mining; Segmentation; Topic Modeling

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APA (6th Edition):

Chen, L. (2018). Segmenting, Summarizing and Predicting Data Sequences. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83573

Chicago Manual of Style (16th Edition):

Chen, Liangzhe. “Segmenting, Summarizing and Predicting Data Sequences.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/83573.

MLA Handbook (7th Edition):

Chen, Liangzhe. “Segmenting, Summarizing and Predicting Data Sequences.” 2018. Web. 17 Oct 2019.

Vancouver:

Chen L. Segmenting, Summarizing and Predicting Data Sequences. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/83573.

Council of Science Editors:

Chen L. Segmenting, Summarizing and Predicting Data Sequences. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83573


Virginia Tech

16. Shao, Huijuan. Temporal Mining Approaches for Smart Buildings Research.

Degree: PhD, Computer Science, 2017, Virginia Tech

 With the advent of modern sensor technologies, significant opportunities have opened up to help conserve energy in residential and commercial buildings. Moreover, the rapid urbanization… (more)

Subjects/Keywords: Data mining; Sustainability; Energy disaggregation; Occupancy prediction

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APA (6th Edition):

Shao, H. (2017). Temporal Mining Approaches for Smart Buildings Research. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84349

Chicago Manual of Style (16th Edition):

Shao, Huijuan. “Temporal Mining Approaches for Smart Buildings Research.” 2017. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/84349.

MLA Handbook (7th Edition):

Shao, Huijuan. “Temporal Mining Approaches for Smart Buildings Research.” 2017. Web. 17 Oct 2019.

Vancouver:

Shao H. Temporal Mining Approaches for Smart Buildings Research. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/84349.

Council of Science Editors:

Shao H. Temporal Mining Approaches for Smart Buildings Research. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/84349

17. Ning, Yue. Modeling Information Precursors for Event Forecasting.

Degree: PhD, Computer Science, 2018, Virginia Tech

 This dissertation is focused on the design and evaluation of machine learning algorithms for modeling information precursors for use in event modeling and forecasting. Given… (more)

Subjects/Keywords: Information Reciprocity; Precursor Learning; Event Modeling; Event Forecasting

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APA (6th Edition):

Ning, Y. (2018). Modeling Information Precursors for Event Forecasting. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84486

Chicago Manual of Style (16th Edition):

Ning, Yue. “Modeling Information Precursors for Event Forecasting.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/84486.

MLA Handbook (7th Edition):

Ning, Yue. “Modeling Information Precursors for Event Forecasting.” 2018. Web. 17 Oct 2019.

Vancouver:

Ning Y. Modeling Information Precursors for Event Forecasting. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/84486.

Council of Science Editors:

Ning Y. Modeling Information Precursors for Event Forecasting. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/84486


Virginia Tech

18. Khandpur, Rupinder Paul. Augmenting Dynamic Query Expansion in Microblog Texts.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Dynamic query expansion is a method of automatically identifying terms relevant to a target domain based on an incomplete query input. With the explosive growth… (more)

Subjects/Keywords: Dynamic Query Expansion; Microblog Event Retrieval; Social Media Analytics; Visual Knowledge Discovery

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APA (6th Edition):

Khandpur, R. P. (2018). Augmenting Dynamic Query Expansion in Microblog Texts. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84852

Chicago Manual of Style (16th Edition):

Khandpur, Rupinder Paul. “Augmenting Dynamic Query Expansion in Microblog Texts.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/84852.

MLA Handbook (7th Edition):

Khandpur, Rupinder Paul. “Augmenting Dynamic Query Expansion in Microblog Texts.” 2018. Web. 17 Oct 2019.

Vancouver:

Khandpur RP. Augmenting Dynamic Query Expansion in Microblog Texts. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/84852.

Council of Science Editors:

Khandpur RP. Augmenting Dynamic Query Expansion in Microblog Texts. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/84852


Virginia Tech

19. Zhang, Hao. Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection.

Degree: PhD, Computer Science, 2015, Virginia Tech

 An increasing variety of malware, including spyware, worms, and bots, threatens data confidentiality and system integrity on computing devices ranging from backend servers to mobile… (more)

Subjects/Keywords: Network Security; Stealthy Malware; Anomaly Detection

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APA (6th Edition):

Zhang, H. (2015). Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64246

Chicago Manual of Style (16th Edition):

Zhang, Hao. “Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection.” 2015. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/64246.

MLA Handbook (7th Edition):

Zhang, Hao. “Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection.” 2015. Web. 17 Oct 2019.

Vancouver:

Zhang H. Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/64246.

Council of Science Editors:

Zhang H. Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/64246


Virginia Tech

20. Tuli, Gaurav. Modeling and Twitter-based Surveillance of Smoking Contagion.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Nicotine, in the form of cigarette smoking, chewing tobacco, and most recently as vapor smoking, is one of the most heavily used addictive drugs in… (more)

Subjects/Keywords: Tobacco Epidemic; Twitter-based Surveillance; Smoking-related Messaging; Electronic-cigarette; Networks; Control of Contagion Pro cesses; Modeling and Simulation

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APA (6th Edition):

Tuli, G. (2016). Modeling and Twitter-based Surveillance of Smoking Contagion. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64426

Chicago Manual of Style (16th Edition):

Tuli, Gaurav. “Modeling and Twitter-based Surveillance of Smoking Contagion.” 2016. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/64426.

MLA Handbook (7th Edition):

Tuli, Gaurav. “Modeling and Twitter-based Surveillance of Smoking Contagion.” 2016. Web. 17 Oct 2019.

Vancouver:

Tuli G. Modeling and Twitter-based Surveillance of Smoking Contagion. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/64426.

Council of Science Editors:

Tuli G. Modeling and Twitter-based Surveillance of Smoking Contagion. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/64426


Virginia Tech

21. Gad, Samah Hossam Aldin. Expressive Forms of Topic Modeling to Support Digital Humanities.

Degree: PhD, Computer Science, 2014, Virginia Tech

 Unstructured textual data is rapidly growing and practitioners from diverse disciplines are expe- riencing a need to structure this massive amount of data. Topic modeling… (more)

Subjects/Keywords: Topic Modeling; LDA; Segmentation

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APA (6th Edition):

Gad, S. H. A. (2014). Expressive Forms of Topic Modeling to Support Digital Humanities. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/65145

Chicago Manual of Style (16th Edition):

Gad, Samah Hossam Aldin. “Expressive Forms of Topic Modeling to Support Digital Humanities.” 2014. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/65145.

MLA Handbook (7th Edition):

Gad, Samah Hossam Aldin. “Expressive Forms of Topic Modeling to Support Digital Humanities.” 2014. Web. 17 Oct 2019.

Vancouver:

Gad SHA. Expressive Forms of Topic Modeling to Support Digital Humanities. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/65145.

Council of Science Editors:

Gad SHA. Expressive Forms of Topic Modeling to Support Digital Humanities. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/65145


Virginia Tech

22. Momtazpour, Marjan. Knowledge Discovery for Sustainable Urban Mobility.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Due to the rapid growth of urban areas, sustainable urbanization is an inevitable task for city planners to address major challenges in resource management across… (more)

Subjects/Keywords: Data mining; Urban computing; Smart grids; Electric vehicles.

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APA (6th Edition):

Momtazpour, M. (2016). Knowledge Discovery for Sustainable Urban Mobility. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/65157

Chicago Manual of Style (16th Edition):

Momtazpour, Marjan. “Knowledge Discovery for Sustainable Urban Mobility.” 2016. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/65157.

MLA Handbook (7th Edition):

Momtazpour, Marjan. “Knowledge Discovery for Sustainable Urban Mobility.” 2016. Web. 17 Oct 2019.

Vancouver:

Momtazpour M. Knowledge Discovery for Sustainable Urban Mobility. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/65157.

Council of Science Editors:

Momtazpour M. Knowledge Discovery for Sustainable Urban Mobility. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/65157


Virginia Tech

23. Liu, Xiaomo. Online Knowledge Community Mining and Modeling for  Effective Knowledge Management.

Degree: PhD, Computer Science, 2013, Virginia Tech

 More and more in recent years, activities that people once did in the real world they now do in virtual space. In particular, online communities… (more)

Subjects/Keywords: Online Communities; Knowledge Management; Expertise Profiling; Knowledge Helpfulness Prediction; Knowledge Sharing & Diffusion

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APA (6th Edition):

Liu, X. (2013). Online Knowledge Community Mining and Modeling for  Effective Knowledge Management. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/50646

Chicago Manual of Style (16th Edition):

Liu, Xiaomo. “Online Knowledge Community Mining and Modeling for  Effective Knowledge Management.” 2013. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/50646.

MLA Handbook (7th Edition):

Liu, Xiaomo. “Online Knowledge Community Mining and Modeling for  Effective Knowledge Management.” 2013. Web. 17 Oct 2019.

Vancouver:

Liu X. Online Knowledge Community Mining and Modeling for  Effective Knowledge Management. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/50646.

Council of Science Editors:

Liu X. Online Knowledge Community Mining and Modeling for  Effective Knowledge Management. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/50646


Virginia Tech

24. Guo, Sheng. Using Dependency Parses to Augment Feature Construction for Text Mining.

Degree: PhD, Computer Science, 2012, Virginia Tech

 With the prevalence of large data stored in the cloud, including unstructured information in the form of text, there is now an increased emphasis on… (more)

Subjects/Keywords: dependency parsing; text mining; linguistic cues

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APA (6th Edition):

Guo, S. (2012). Using Dependency Parses to Augment Feature Construction for Text Mining. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28046

Chicago Manual of Style (16th Edition):

Guo, Sheng. “Using Dependency Parses to Augment Feature Construction for Text Mining.” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/28046.

MLA Handbook (7th Edition):

Guo, Sheng. “Using Dependency Parses to Augment Feature Construction for Text Mining.” 2012. Web. 17 Oct 2019.

Vancouver:

Guo S. Using Dependency Parses to Augment Feature Construction for Text Mining. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/28046.

Council of Science Editors:

Guo S. Using Dependency Parses to Augment Feature Construction for Text Mining. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28046


Virginia Tech

25. Hossain, Mahmud Shahriar. Exploratory Data Analysis using Clusters and Stories.

Degree: PhD, Computer Science, 2012, Virginia Tech

 Exploratory data analysis aims to study datasets through the use of iterative, investigative, and visual analytic algorithms. Due to the difficulty in managing and accessing… (more)

Subjects/Keywords: Alternative clustering; Guided clustering; Storytelling; Connecting the dots

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APA (6th Edition):

Hossain, M. S. (2012). Exploratory Data Analysis using Clusters and Stories. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28085

Chicago Manual of Style (16th Edition):

Hossain, Mahmud Shahriar. “Exploratory Data Analysis using Clusters and Stories.” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/28085.

MLA Handbook (7th Edition):

Hossain, Mahmud Shahriar. “Exploratory Data Analysis using Clusters and Stories.” 2012. Web. 17 Oct 2019.

Vancouver:

Hossain MS. Exploratory Data Analysis using Clusters and Stories. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/28085.

Council of Science Editors:

Hossain MS. Exploratory Data Analysis using Clusters and Stories. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28085


Virginia Tech

26. Patnaik, Debprakash. Multiple Uses of Frequent Episodes in Temporal Process Modeling.

Degree: PhD, Computer Science, 2011, Virginia Tech

 This dissertation investigates algorithmic techniques for temporal process discovery in many domains. Many different formalisms have been proposed for modeling temporal processes such as motifs,… (more)

Subjects/Keywords: motifs; graphical models; frequent episodes; dynamic Bayesian networks; temporal data mining

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APA (6th Edition):

Patnaik, D. (2011). Multiple Uses of Frequent Episodes in Temporal Process Modeling. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28413

Chicago Manual of Style (16th Edition):

Patnaik, Debprakash. “Multiple Uses of Frequent Episodes in Temporal Process Modeling.” 2011. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/28413.

MLA Handbook (7th Edition):

Patnaik, Debprakash. “Multiple Uses of Frequent Episodes in Temporal Process Modeling.” 2011. Web. 17 Oct 2019.

Vancouver:

Patnaik D. Multiple Uses of Frequent Episodes in Temporal Process Modeling. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/28413.

Council of Science Editors:

Patnaik D. Multiple Uses of Frequent Episodes in Temporal Process Modeling. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/28413

27. Akupatni, Vivek Bharath. My4Sight: A Human Computation Platform for Improving Flu Predictions.

Degree: MS, Computer Science, 2015, Virginia Tech

 While many human computation (human-in-the-loop) systems exist in the field of Artificial Intelligence (AI) to solve problems that can't be solved by computers alone, comparatively… (more)

Subjects/Keywords: human computation; human-in-the-loop; crowd sourcing; my4sight; influenza forecasting

Page 1 Page 2

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APA (6th Edition):

Akupatni, V. B. (2015). My4Sight: A Human Computation Platform for Improving Flu Predictions. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/56579

Chicago Manual of Style (16th Edition):

Akupatni, Vivek Bharath. “My4Sight: A Human Computation Platform for Improving Flu Predictions.” 2015. Masters Thesis, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/56579.

MLA Handbook (7th Edition):

Akupatni, Vivek Bharath. “My4Sight: A Human Computation Platform for Improving Flu Predictions.” 2015. Web. 17 Oct 2019.

Vancouver:

Akupatni VB. My4Sight: A Human Computation Platform for Improving Flu Predictions. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/56579.

Council of Science Editors:

Akupatni VB. My4Sight: A Human Computation Platform for Improving Flu Predictions. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/56579


Virginia Tech

28. Hossain, K.S.M. Tozammel. Modeling Evolutionary Constraints and Improving Multiple Sequence Alignments using Residue Couplings.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Residue coupling in protein families has received much attention as an important indicator toward predicting protein structures and revealing functional insight into proteins. Existing coupling… (more)

Subjects/Keywords: residue coupling; multiple sequence alignment; graphical models; pattern set mining

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APA (6th Edition):

Hossain, K. S. M. T. (2016). Modeling Evolutionary Constraints and Improving Multiple Sequence Alignments using Residue Couplings. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83218

Chicago Manual of Style (16th Edition):

Hossain, K S M Tozammel. “Modeling Evolutionary Constraints and Improving Multiple Sequence Alignments using Residue Couplings.” 2016. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/83218.

MLA Handbook (7th Edition):

Hossain, K S M Tozammel. “Modeling Evolutionary Constraints and Improving Multiple Sequence Alignments using Residue Couplings.” 2016. Web. 17 Oct 2019.

Vancouver:

Hossain KSMT. Modeling Evolutionary Constraints and Improving Multiple Sequence Alignments using Residue Couplings. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/83218.

Council of Science Editors:

Hossain KSMT. Modeling Evolutionary Constraints and Improving Multiple Sequence Alignments using Residue Couplings. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/83218


Virginia Tech

29. Zhang, Xuchao. Scalable Robust Models Under Adversarial Data Corruption.

Degree: PhD, Computer Science, 2019, Virginia Tech

 The presence of noise and corruption in real-world data can be inevitably caused by accidental outliers, transmission loss, or even adversarial data attacks. Unlike traditional… (more)

Subjects/Keywords: Robust Model; Adversarial Data Corruption; Scalability

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APA (6th Edition):

Zhang, X. (2019). Scalable Robust Models Under Adversarial Data Corruption. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/88833

Chicago Manual of Style (16th Edition):

Zhang, Xuchao. “Scalable Robust Models Under Adversarial Data Corruption.” 2019. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/88833.

MLA Handbook (7th Edition):

Zhang, Xuchao. “Scalable Robust Models Under Adversarial Data Corruption.” 2019. Web. 17 Oct 2019.

Vancouver:

Zhang X. Scalable Robust Models Under Adversarial Data Corruption. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/88833.

Council of Science Editors:

Zhang X. Scalable Robust Models Under Adversarial Data Corruption. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/88833


Virginia Tech

30. Chen, Feng. Efficient Algorithms for Mining Large Spatio-Temporal Data.

Degree: PhD, Computer Science, 2013, Virginia Tech

 Knowledge discovery on spatio-temporal datasets has attracted growing interests. Recent advances on remote sensing technology mean that massive amounts of spatio-temporal data are being collected,… (more)

Subjects/Keywords: Spatio-Temporal Analysis; Outlier Detection; Robust Prediction; Energy Disaggregation

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

APA (6th Edition):

Chen, F. (2013). Efficient Algorithms for Mining Large Spatio-Temporal Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19220

Chicago Manual of Style (16th Edition):

Chen, Feng. “Efficient Algorithms for Mining Large Spatio-Temporal Data.” 2013. Doctoral Dissertation, Virginia Tech. Accessed October 17, 2019. http://hdl.handle.net/10919/19220.

MLA Handbook (7th Edition):

Chen, Feng. “Efficient Algorithms for Mining Large Spatio-Temporal Data.” 2013. Web. 17 Oct 2019.

Vancouver:

Chen F. Efficient Algorithms for Mining Large Spatio-Temporal Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/10919/19220.

Council of Science Editors:

Chen F. Efficient Algorithms for Mining Large Spatio-Temporal Data. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19220

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