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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
URL: http://hdl.handle.net/1969.1/158078 
► 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…
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▼ 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 user-interface logic as a set of variables and dependencies between those variables. This thesis builds on the prior work that realizes the property models approach as a concrete library for web development called HotDrink. This thesis evaluates the effectiveness of the declarative programming approach of property models, describes the experience of implementing a medium-size web application following the approach, and compares property models with existing web frameworks. A particular focus is on how programming with property models helps programmers to avoid defects related to asynchronous execution of responses to user events.
Advisors/Committee Members: Järvi, Jaakko (advisor), Huang, Jeff (advisor), Sprintson, Alex (committee member).
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
URL: http://hdl.handle.net/1969.1/159067
► 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)
▼ 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 is growing exponentially and with the present hardware and software architecture it is difficult to support them. With billions of IoT devices waiting to be connected in the near future, it is necessary to build infrastructure for the upcoming change as the energy and cost associated with the continuous transmission, classification and storage will be huge. We need to build an efficient framework that can scale easily, follow consistent protocol, maintain security and save resources.
The thesis focuses in solving the major upcoming problems of the Internet of Things by proposing a lightweight framework which resides in both the server and the end device as server client model. The framework has the following benefits – it reduces network congestion, reduces data consumption and maintains security. The framework resides on the data and communication layer, classifying the data into known patterns - Motifs. We have used modified Hidden Markov Model to classify the sensor data into Motifs. The framework transfers only the motifs attributes information instead of complete sensor data. Thus the data can now be compressed by orders of magnitude into these classes of recurrent patterns. It not only saves on data storage but also on network transmission. It helps us to create a state based model and in anomaly detection and security.
We also optimize Partial Homomorphic Encryption based on El-Gamal Algorithm using OpenCL, OpenMP, SIMD, batch processing, Karatsuba algorithm and used to secure the framework while allowing simple computation to be performed on the encrypted data.
Advisors/Committee Members: Mahapatra, Rabi (advisor), Huang, Jeff (committee member), Hu, Jiang (committee member).
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
URL: http://hdl.handle.net/1969.1/157131
► 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,…
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▼ 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, we have found that the majority of these techniques do not scale well and developers are often forced to balance precision with speed. Additionally, various practical issues force even precise race detectors to produce spurious warnings, defeating their purpose and burdening their users. We design and implement a novel race detection technique that is both fast and precise, even in the face of missing program source information. Towards this goal, we have developed two separate tools, TREE and RDIT, that respectively improve performance and precision over existing techniques.
TREE, implemented in the RoadRunner framework, acts as a filter and sends through only those events that might add value to race detection while eliminating those events which are deemed redundant for this purpose. All the while, removing these redundant events does not affect its race detection capability. We have evaluated TREE against a whole set of standard benchmarks, including two large real-world applications. We have found that there exists a significant number of redundant events in all these applications and on an average, TREE saves somewhere between 15-25% of analysis time as compared to the state-of-the-art techniques.
Meanwhile, our next tool, RDIT, is able to precisely detect races in programs with incomplete source information, generating no false positives. RDIT is also maximal in the sense that it detects a maximal set of true races from the observed incomplete trace. It is underpinned by a sound BarrierPair model that abstracts away the missing events by capturing the invocation data of their enclosing methods. By making the least conservative assumption that a missing method introduces synchronization only when its invocation data overlaps with other missing methods, and by formulating maximal thread causality as a set of logical constraints, RDIT guarantees to precisely detect races with maximal capability. We tested RDIT against seven real-world large concurrent systems and have detected dozens of true races with zero false alarm. Comparatively, existing algorithms such as Happens-Before, Causal-Precede, and Maximal-Causality, which are all known to be precise, were observed reporting hundreds of false alarms due to trace incompleteness.
Advisors/Committee Members: Huang, Jeff (advisor), Welch, Jennifer L (committee member), Ji, Jim (committee member).
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
URL: http://hdl.handle.net/1969.1/161656
► 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,…
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▼ 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, almost 75% of 8th graders scored below proficient in geography on the 2014 National Assessment of Educational Progress. Sketchography is a pen-based intelligent tutoring system that provides real-time feedback to students learning the locations, directions, and topography of rivers around the world. Sketchography uses sketch recognition and artificial intelligence to understand the user’s sketched intentions. As sketches are inherently messy, and even the most expert geographer will draw only a close approximation of the river’s flow, data has been gathered from both novice and expert sketchers. This data, in combination with professors’ grading rubrics and statistically driving AI-algorithms, provide real-time automatic grading that is similar to a human grader’s score. Results show the system to be 94.64% accurate compared to human grading.
Advisors/Committee Members: Hammond, Tracy (advisor), Goldberg, Daniel (committee member), Klein, Andrew (committee member), Huang, Jeff (committee member).
Subjects/Keywords: Sketch Recognition; Geography
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APA ·
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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
URL: http://hdl.handle.net/1969.1/173694
► 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)
▼ 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 metallic interventional devices are
present in the target tissues. High susceptibility of metallic objects often causes artifacts in MR
images, making them difficult to localize. SWI is a widely used clinical tool to enhance the image
contrast in MR imaging modality. SWI uses phase information of MR images to enhance contrast
in tissues with different susceptibilities. In this study, we use a novel SWI-based approach called
Metal ARtifact Based Landmark Enhanced SWI (MARBLES) to create a positive contrast image
(PCI) for localizing the metallic objects in the MR images. The approach was tested on four different
dataset and the results were observed, discussed and compared against that of a Qualitative
Susceptibility Mapping (QSM) based approach.
Advisors/Committee Members: Ji, Jim X (advisor), Wright, Steven M (committee member), Narayanan, Krishna R (committee member), Huang, Jeff (committee member).
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
URL: http://hdl.handle.net/1969.1/186252
► 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)
▼ 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 machines, mobile phones, tablets and Internet of Things (IoT) devices. Usually, attackers try to find vulnerabilities in the target systems and by exploiting these vulnerabilities, they launch an attack, thereby achieving their malicious goal.
Software data attacks modify the intended control/data flow in a program that is unprotected. Control data attacks are executed by exploiting buffer overflows or string vulnerabilities to overwrite a return address, a function pointer or some other information about control data. Non-control data attacks exploit similar vulnerabilities to overwrite security critical data without changing the intended control-flow in the program. Data flow integrity ensures that the flow of data in a program at runtime is permitted by the data flow graph. The main objective of the thesis is to implement a hardware-based data flow integrity technique and check for vulnerabilities on a target application. This implementation is achieved by referencing a data flow graph against which the runtime data flow of a program is checked. DFI checking is integrated into existing processor with most changes in hardware going to the load/store unit and the arithmetic unit. In gem5, this is realised by modifying source code of the simulator at instruction level to monitor each load/store instruction on the target application and check if there are any data flow violations and check the overhead caused by the modification of gem5 source code to integrate DFI checking with existing CPU models on gem5. From experiments results, we measured the performance overhead to be up to 14.5%. We also roughly estimate the extra hardware required for this implementation on real hardware.
Advisors/Committee Members: Hu, Jiang (advisor), Huang, Jeff (advisor), Annapareddy, Narasimha (committee member).
Subjects/Keywords: Data Flow Integrity; gem5; Security; Computer architecture
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APA ·
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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
URL: http://hdl.handle.net/1969.1/174107
► 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)
▼ 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 monitoring systems fall short of current need for quick responses to maintain road quality. Several alternative systems have been proposed that utilize sensors mounted on vehicles and with the ubiquitous use of smartphone for personal use and navigation, smartphone based road condition assessment has gained prominence.
We propose to analyze different multiclass supervised machine learning techniques to effectively classify road surface conditions using accelerometer, gyroscope and GPS data collected from smartphones. Our work focusses on classification of three main class labels- smooth road, pothole and deep transverse cracks. We investigate our conjecture that using features from all three axes of the sensors provide more accurate results as compared to using features from only one axis. We also investigate the performance of deep neural networks to classify road conditions with and without explicit manual feature extraction. Our results consistently show that models trained with features from all axes of the smartphone sensors perform better than models that use only one axis. This shows that there is information in the vibration signals along all three axis for road anomalies. We also observe that the use of neural networks provide significantly accurate data classification. The approaches discussed here can be implemented on a larger scale to monitor road for defects that present a safety risk to commuters as well as provide maintenance information to relevant authorities.
Advisors/Committee Members: Ji, Jim (advisor), Wright, Steven M (advisor), Du, Jing (committee member), Serpedin, Erchin (committee member), Huang, Jeff (committee member).
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 ·
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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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