iLux is equipped with the most advance EEG monitoring and eye-tracking technology as well as the highly trained personnel to operate it. The difference with iLux is that there are no limits to your testing needs. We are capable of running equipment in all conditions whether it be in a lab a controlled lab setting, on a mobile device, or even with our mobile equipment for use out in everyday life. Our portable equipment allows us to conduct research in a variety of environments
There are four programming assignments in this course: a Lexical Analyzer, a Parser, a Semantics Analyzer and an Intermediate Code Generator. The four assignments bundled together result in a compiler for a custom programming language. An example the statements supported in the programming language designed in this course is shown in the picture. A GUI is provided to visualize the result of each stage: a token table, a parse tree, a symbol table, and intermediate code; as well as a console (in black background) to display alerts and error messages.
Aditionally, a VM with a GUI is provided to test the intermediate code generated by the compiler.
A student (Rajesh Surana) creates a GitHub repository with the source code for the complete project. Take a look at his repository here.
A compilation of the notes of the course (113-pages) are available on Scribd
I feel honored to have been granted the ACM Senior Member Award
Association for Computing Machinery (ACM)
August 24, 2014
The Senior Member Grade recognizes those ACM members with at least 10 years of professional experience and 5 years of continuous Professional Membership who have demonstrated performance that sets them apart from their peers.
2014 Award winners:
Eduardo Almeida; Michael Atighetchi; Brian P. Bailey; Punam Bedi; Nikhil Bhargava; Manish Bhide; Frederick J. Bourgeois; Travis D. Breaux; Carlos A. Castillo; Maria Elena Chavez-Echeagaray; Yun Chi; Wei Ding; John P Dougherty; Jane Fedorowicz; James W. Gabberty; G R Gangadharan; James Garnett; Jeffrey Gennari; Christos K. Georgiadis; Don Goelman; Javier Gonzalez-Sanchez; Mihir Gore; Anil Kumar Gupta; Winston H. Hsu; Jun Hu; Matt Huenerfauth; Jhilmil Jain; Mihai Jalobeanu; Natalie Jerger; James Anthony Junco; Hemangee K. Kapoor; Arun Kejariwal; Jong-Kook Kim; Jan H Kroeze; Sebastien Lahaie; John Lee; Jian Li; Li-Pin Liu; Diego R. Llanos; Alessio Malizia; Manoel Gomes Mendonca; Stuart Edward Middleton; Antonija Mitrovic; Mihai Nadin; Juan Arturo Nolazco-Flores; Takeshi Ogasawara; Deepak Padmanabhan; Lynne E Parker; Rajeev R Raje; Rajveer Singh Shekhawat; Heng Tao Shen; Bernhard Suhm; Jian-Tao Sun; Chin Ngai Sze; Thiab Taha; Aakash Taneja; Asser N Tantawi; Carlo Tarantola; Michela Taufer; Basant Tiwari; Balakrushna Tripathy; Jaideep Vaidya; Miroslav N. Velev; Paul J Whitbread; Alec Yasinsac; Dalu Zhang; Gottfried Zimmermann.
The 18th International Symposium on Wearable Computers
Sponsored by ACM’s special interest groups on computer-human interaction (SIGCHI) and mobility (SIGMOBILE)
Seattle, WA, US. September 2014
Building affect-driven adaptive environments is a task geared towards creating environments able to change based on the affective state of a target user. In our project, the environment is the well-known game, Pac-Man. To provide affect-driven adaptive capabilities, diverse sensors are utilized to gather user’s physiological states and an emotion recognition framework is used to fuse the sensed data and infer the user’s affective state. The game change driven by those affective states aiming to improve the user experience increasing engagement
Harris, A., Hoch, A., Kral, R., Teposte, M., Villa, A., Chavez-Echeagaray, M.E., Gonzalez-Sanchez, J., and Atkinson, R. (2014). Including Affect-driven Adaptation to the Pac-Man Video Game. In Extended Abstracts Proceedings of the 18th International Symposium on Wearable Computers (ISCW). Seattle, WA, USA. September 2014. ACM. ISBN: 978-1-4503-3048-0 doi: 10.1145/2641248.2641360.
12th International Conference on Intelligent Tutoring Systems
Hosted by the University of Hawaii at Manoa
Honolulu, Hawaii, US. Jun 2014
Intelligent Tutoring Systems (ITSs) constitute an alternative to expert human tutors, providing direct customized instruction and feedback to students. ITSs could positively impact education if adopted on a large scale, but doing that requires tools to enable their mass production. This circumstance is the key motivation for this work. We present a component-based approach for a system architecture for ITSs equipped with meta-tutoring and affective capabilities. We elicited the requirements that those systems might address and created a system architecture that models their structure and behavior to drive development efforts. Our experience applying the architecture in the incremental implementation of a four-year project is discussed.
These are the slides of the paper presentation, comments are more than welcome.
Gonzalez-Sanchez, J., Chavez-Echeagaray, M.E., VanLehn, K., Burleson, W., Girard, S., Hidalgo-Pontet, Y., and Zhang, L. (2014). A System Architecture for Affective Meta Intelligent Tutoring Systems. In Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS). Honolulu, HI, US. 5-9 June. Pp. 529–534. Springer. LNCS 8474, pp. 529–534. doi:10.1007/978-3-319-07221-0_67