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You searched for +publisher:"Texas A&M University" +contributor:("Huang, Jeff"). Showing records 1 – 7 of 7 total matches.

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Texas A&M University

1. Singh, Pawan Kumar. Programming Web Applications Declaratively A Qualitative Study.

Degree: MS, Computer Science, 2016, Texas A&M University

 In the declarative programming approach of property models, a dataflow constraint system manages the behavior of a user interface. The dataflow constraint system captures the… (more)

Subjects/Keywords: Property Models; HotDrink; JavaScript

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APA (6th Edition):

Singh, P. K. (2016). Programming Web Applications Declaratively A Qualitative Study. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/158078

Chicago Manual of Style (16th Edition):

Singh, Pawan Kumar. “Programming Web Applications Declaratively A Qualitative Study.” 2016. Masters Thesis, Texas A&M University. Accessed March 05, 2021. http://hdl.handle.net/1969.1/158078.

MLA Handbook (7th Edition):

Singh, Pawan Kumar. “Programming Web Applications Declaratively A Qualitative Study.” 2016. Web. 05 Mar 2021.

Vancouver:

Singh PK. Programming Web Applications Declaratively A Qualitative Study. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1969.1/158078.

Council of Science Editors:

Singh PK. Programming Web Applications Declaratively A Qualitative Study. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/158078


Texas A&M University

2. Sahoo, Akash. Efficient and Secured Framework for Internet of Things Based on Motifs.

Degree: MS, Computer Engineering, 2016, Texas A&M University

 Internet of Things (IoT) has allowed embedded devices to connect to the vast internet network worldwide. The amount of data produced and exchanged between them… (more)

Subjects/Keywords: IoT; Homomorphic Encryption; Embedded Systems; motifs

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APA (6th Edition):

Sahoo, A. (2016). Efficient and Secured Framework for Internet of Things Based on Motifs. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/159067

Chicago Manual of Style (16th Edition):

Sahoo, Akash. “Efficient and Secured Framework for Internet of Things Based on Motifs.” 2016. Masters Thesis, Texas A&M University. Accessed March 05, 2021. http://hdl.handle.net/1969.1/159067.

MLA Handbook (7th Edition):

Sahoo, Akash. “Efficient and Secured Framework for Internet of Things Based on Motifs.” 2016. Web. 05 Mar 2021.

Vancouver:

Sahoo A. Efficient and Secured Framework for Internet of Things Based on Motifs. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1969.1/159067.

Council of Science Editors:

Sahoo A. Efficient and Secured Framework for Internet of Things Based on Motifs. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/159067


Texas A&M University

3. Rajagopalan, Arun Krishnakumar. Fast and Precise On-The-Fly Data Race Detection.

Degree: MS, Computer Science, 2016, Texas A&M University

 While concurrent programming is quickly gaining popularity lately, developing bug-free programs is still challenging. Although developers have a wide choice of race detection tools available,… (more)

Subjects/Keywords: bug detection; concurrency; debugging; dynamic analysis; parallelism; performance analysis; runtime monitoring; software engineering; redundancy; data race; missing events; precise detection; happens-before; maximal thread causality

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APA (6th Edition):

Rajagopalan, A. K. (2016). Fast and Precise On-The-Fly Data Race Detection. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157131

Chicago Manual of Style (16th Edition):

Rajagopalan, Arun Krishnakumar. “Fast and Precise On-The-Fly Data Race Detection.” 2016. Masters Thesis, Texas A&M University. Accessed March 05, 2021. http://hdl.handle.net/1969.1/157131.

MLA Handbook (7th Edition):

Rajagopalan, Arun Krishnakumar. “Fast and Precise On-The-Fly Data Race Detection.” 2016. Web. 05 Mar 2021.

Vancouver:

Rajagopalan AK. Fast and Precise On-The-Fly Data Race Detection. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1969.1/157131.

Council of Science Editors:

Rajagopalan AK. Fast and Precise On-The-Fly Data Race Detection. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157131


Texas A&M University

4. Bhat, Aqib Niaz. Sketchography - Automatic Grading of Map Sketches for Geography Education.

Degree: MS, Computer Science, 2017, Texas A&M University

 Geography is a vital classroom subject that teaches students about the physical features of the planet we live on. Despite the importance of geographic knowledge,… (more)

Subjects/Keywords: Sketch Recognition; Geography

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APA (6th Edition):

Bhat, A. N. (2017). Sketchography - Automatic Grading of Map Sketches for Geography Education. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161656

Chicago Manual of Style (16th Edition):

Bhat, Aqib Niaz. “Sketchography - Automatic Grading of Map Sketches for Geography Education.” 2017. Masters Thesis, Texas A&M University. Accessed March 05, 2021. http://hdl.handle.net/1969.1/161656.

MLA Handbook (7th Edition):

Bhat, Aqib Niaz. “Sketchography - Automatic Grading of Map Sketches for Geography Education.” 2017. Web. 05 Mar 2021.

Vancouver:

Bhat AN. Sketchography - Automatic Grading of Map Sketches for Geography Education. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1969.1/161656.

Council of Science Editors:

Bhat AN. Sketchography - Automatic Grading of Map Sketches for Geography Education. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161656


Texas A&M University

5. Dhulipala, Pranav Vaidik. Using Landmark Based Susceptibility Weighted Imaging for Interventional Device Localization in MRI.

Degree: MS, Electrical Engineering, 2018, Texas A&M University

 MRI is a widely studied imaging modality due to its superior resolution and soft-tissue contrast. However, the application of MRI is limited in cases when… (more)

Subjects/Keywords: Susceptibility Weighted Imaging; MRI; Qualitative Susceptibility Mapping

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APA (6th Edition):

Dhulipala, P. V. (2018). Using Landmark Based Susceptibility Weighted Imaging for Interventional Device Localization in MRI. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173694

Chicago Manual of Style (16th Edition):

Dhulipala, Pranav Vaidik. “Using Landmark Based Susceptibility Weighted Imaging for Interventional Device Localization in MRI.” 2018. Masters Thesis, Texas A&M University. Accessed March 05, 2021. http://hdl.handle.net/1969.1/173694.

MLA Handbook (7th Edition):

Dhulipala, Pranav Vaidik. “Using Landmark Based Susceptibility Weighted Imaging for Interventional Device Localization in MRI.” 2018. Web. 05 Mar 2021.

Vancouver:

Dhulipala PV. Using Landmark Based Susceptibility Weighted Imaging for Interventional Device Localization in MRI. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1969.1/173694.

Council of Science Editors:

Dhulipala PV. Using Landmark Based Susceptibility Weighted Imaging for Interventional Device Localization in MRI. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173694

6. Rachala, Abhijith Reddy. Evaluation of Hardware-based Data Flow Integrity.

Degree: MS, Computer Engineering, 2019, Texas A&M University

 Computer security is a very critical problem these days, as it has widespread consequences in case of a failure of computer systems security, like desktop… (more)

Subjects/Keywords: Data Flow Integrity; gem5; Security; Computer architecture

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APA (6th Edition):

Rachala, A. R. (2019). Evaluation of Hardware-based Data Flow Integrity. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/186252

Chicago Manual of Style (16th Edition):

Rachala, Abhijith Reddy. “Evaluation of Hardware-based Data Flow Integrity.” 2019. Masters Thesis, Texas A&M University. Accessed March 05, 2021. http://hdl.handle.net/1969.1/186252.

MLA Handbook (7th Edition):

Rachala, Abhijith Reddy. “Evaluation of Hardware-based Data Flow Integrity.” 2019. Web. 05 Mar 2021.

Vancouver:

Rachala AR. Evaluation of Hardware-based Data Flow Integrity. [Internet] [Masters thesis]. Texas A&M University; 2019. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1969.1/186252.

Council of Science Editors:

Rachala AR. Evaluation of Hardware-based Data Flow Integrity. [Masters Thesis]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/186252

7. Basavaraju, Akanksh. Machine Learning Approaches to Road Surface Anomaly Assessment Using Smartphone Sensors.

Degree: MS, Electrical Engineering, 2018, Texas A&M University

 Road surface quality is an essential component of roadway infrastructure that leads to better driving standards and reduces risk of traffic accident. Traditional road condition… (more)

Subjects/Keywords: Support Vector Machines; Neural Network; Multi-layer Perceptron; Decision Tree; Road Condition; Pavement Condition; Pothole; Crack; Smartphone Sensors; Accelerometer

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

APA (6th Edition):

Basavaraju, A. (2018). Machine Learning Approaches to Road Surface Anomaly Assessment Using Smartphone Sensors. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174107

Chicago Manual of Style (16th Edition):

Basavaraju, Akanksh. “Machine Learning Approaches to Road Surface Anomaly Assessment Using Smartphone Sensors.” 2018. Masters Thesis, Texas A&M University. Accessed March 05, 2021. http://hdl.handle.net/1969.1/174107.

MLA Handbook (7th Edition):

Basavaraju, Akanksh. “Machine Learning Approaches to Road Surface Anomaly Assessment Using Smartphone Sensors.” 2018. Web. 05 Mar 2021.

Vancouver:

Basavaraju A. Machine Learning Approaches to Road Surface Anomaly Assessment Using Smartphone Sensors. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1969.1/174107.

Council of Science Editors:

Basavaraju A. Machine Learning Approaches to Road Surface Anomaly Assessment Using Smartphone Sensors. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174107

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