Incorporating situationally qualified human observations into a fusion process for intelligence analysis

Since my second year at UB my research assistantship has been funded by a 3 year multi-university research initiative (MURI) grant focused on network based hard/soft information fusion.  The first year of this research (for me at least) was focused on learning about how accurate people are at observing different phenomena in the world given specific contextual factors.  For example, how accurately can people judge distances?  What if it’s nighttime?  What if it’s snowing? etc.

This work was developed to allow human observations to be appropriately characterized in terms of their error/bias so that they could be integrated into a data fusion process along with hard data (which comes from things like radar sensors that are highly calibrated).  The poster below, which was created for a UB School of Engineering and Applied Sciences poster competition, describes the results of these research efforts at a high level.

Evaluating and Interpreting the Creation of Causal Influence Models

Below (flash required for viewing)  is a poster submission that highlights some of the research I helped to conduct in my first year at UB.  The research objective was to investigate users’ abilities to create Causal Influence Networks, a class of Bayesian networks, with varying complexity and types of relationships, using a causal influence model.  Funding for this research was generously provided by Charles River Analytics.

Abstract: Bayesian networks (BNs) are probabilistic models used to reason under uncertainty by graphically expressing domain knowledge in order to reason about states, causes, and effects. While BNs have many advantages, their complexity can hamper the process of knowledge elicitation and encoding. For example, BNs require the definition of a priori, conditional probabilities: as complex models increase in size, this requires eliciting exponential numbers of complex probabilities. Multiple “canonical modeling” approaches, such as Causal Influence Models (CIMs), have been developed to address these complexities. However, little progress has been made towards human-in-the-loop evaluation of such approaches – specifically, their accessibility and usability, their related user interfaces, and how they enable a user to correctly create and interpret variables and probabilistic relationships. In this study, we evaluated the CIM approach (implemented in a software application) to determine the effect on user task performance. Results indicate that the model complexity has an adverse effect on performance when users are interpreting an existing model; that semantics of a model may impact performance; and that users were generally successful in creating new models of different situations.

NextGen Gaming

http://emotiv.com

A friend of mine directed me to this site as we were talking about research topics in HF/Gaming that will be big in the future.  Emotiv (Sydney, AU) is the first company to produce a commercially available, mainstream consumer targeted EEG/EKG monitoring headset ($299, not available quite yet).   The purpose?  Play video games with your mind…

That’s right, the Emotiv headset is designed for playing video games with one’s thoughts and facial movements.  Of course the humanitarian would apply said technology to assist the disabled (they do have a demo where it controls a wheelchair and car), but the Emotiv monitor was developed for games and what they’ve shown so far looks promising so check it out.

Really the applications are endless, and of course other research on EEG based interfaces exist, but the fact that in a few months i’ll be essentially in charge of the virtual world “force” has got me giddy with anticipation….  so many future articles/reviews to come… until then check out these:

CNN – The Future of Gaming
USA Today – Let Video Games read your mind
Business Week – New Mind-Control Headset

(on a side note, i know i’ve been away for a while, but with a nice break coming up i’ll be trying to catch up on all the great things i’ve wanted to share with the world….)