SRL MS Thesis Defense of Nahum Villanueva Luna. Monday, March 6. Title: ARCaching: Using Augmented Reality on Mobile Devices to Improve Geocacher Experience

Thesis Defense
Monday, March 6

Title: ARCaching: Using Augmented Reality on Mobile Devices to Improve Geocacher Experience

Nahum Villanueva Luna

10 AM Monday, March 6, 2017

516 H.R. Bright Building

Abstract

ARCaching is an augmented reality application designed to help Geocachers on their quest to find hidden containers around the world. Geocaching is a popular treasure hunting game that uses GPS

coordinates and mobile devices to guide players to hidden object. ARCaching is trying to test the effects that using augmented reality on this kind of tasks could have and if it helps to improve the user's experience while Geocaching. 

Biography

  Born on Mérida Yucatán Mexico on April 29 in 1991. I got my bachelor's degree as a Software Engineer on 2013 at "Universidad Autónoma De Yucatán" in Mexico. I'm currently finishing my master's degree on computer engineering at Texas A&M at the Sketch Recognition Lab.

Advisor: Dr. Tracy Hammond

 

SRL MS Thesis Defense of Jorge I. Herrera-Camara. Friday, March 3. Title: Flow2code - From Hand-drawn Flowchart to Code Execution

Thesis Defense

Friday, March 3

Title:   Flow2code - From Hand-drawn Flowchart to Code Execution

Jorge I. Herrera-Camara

10:00 AM, March 3, 2017

Location: 516 H.R. Bright Building

Abstract

Flowcharts play an important role when learning programming by conveying algorithms graphically and making them easy to read and understand. When learning how to code with flowcharts and the transition between the two, people often use computer based software to design and execute the algorithm conveyed by the flowchart. This require the users to learn how to use the computer based software which often leads to a steep learning curve. Using off- line sketch recognition and computer vision algorithms on a mobile device the learning curve can decrement, by drawing the flowchart on a piece of paper and using a mobile device with a camera to be able to capture it. Flow2Code is a code flowchart recognizer that allows the users to code simple scripts on a piece of paper by drawing flowcharts. This approach attempts to be more intuitive since the user does not need to learn how to use a system to design the flowchart. Only a pencil, a notebook with white pages and a mobile device is needed to achieve the same result. The main contribution of this thesis would be to provide a more intuitive and easy to use tool for people to translate and execute flowcharts into code. 

 Biography

Born in Yucatan, Mexico, studied software engineering as undergraduate back home. I have worked in Software Engineering roles for two years after graduating from undergrad. Then decided to start my MS in Computer Science here at A&M in 2015.

Advisor: Dr. Tracy Hammond 

 

 

SRL MS Thesis Defense of Aqib Bhat. Thursday, March 2. Title: Sketchography - Automatic Grading of Map Sketches for Geography Education

Thesis Defense

Thursday, March 2

 

Title: Sketchography - Automatic Grading of Map Sketches for Geography Education

Aqib Bhat

10 am, Thursday, March 2, 2017

Room 326 Teague Building

Abstract

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. 

Biography

Aqib Niaz Bhat obtained his Bachelor of Technology degree in Electronics and Communication engineering from National Institute of Technology, Srinagar, India. He is currently a Computer Science Master's thesis student in the department of Computer Science & Engineering at Texas A&M University, College Station. He has worked as a software engineer with Wipro Technologies and interned with Amazon.com. Aqib is a member of the Sketch Recognition Lab.

Advisor: Dr. Tracy Hammond