LESSONS FROM APPROACHES TO INCREASE WOMEN'S PARTICIPATION IN DEVELOPMENT: WORKSHOP SUMMARY

Community/Rural/Urban Development, Labor and Human Capital,

Modeling human response errors in synthetic flight simulator domain

This paper presents a control theoretic approach to modeling human response errors (HRE) in the flight simulation domain. The human pilot is modeled as a supervisor of a highly automated system. The synthesis uses the theory of optimal control pilot modeling for integrating the pilot's observation error and the error due to the simulation model (experimental error). Methods for solving the HRE problem are suggested. Experimental verification of the models will be tested in a flight quality handling simulation

Scalable and interpretable product recommendations via overlapping co-clustering

We consider the problem of generating interpretable recommendations by identifying overlapping co-clusters of clients and products, based only on positive or implicit feedback. Our approach is applicable on very large datasets because it exhibits almost linear complexity in the input examples and the number of co-clusters. We show, both on real industrial data and on publicly available datasets, that the recommendation accuracy of our algorithm is competitive to that of state-of-art matrix factorization techniques. In addition, our technique has the advantage of offering recommendations that are textually and visually interpretable. Finally, we examine how to implement our technique efficiently on Graphical Processing Units (GPUs).Comment: In IEEE International Conference on Data Engineering (ICDE) 201

Modeling the performance of the human (pilot) interaction in a synthetic flight domain: Information theoretic approach

Current advances in computing technology are devoid of formal methods that describe the theories of how information is shared between humans and machines. Specifically, in the domain of human-machine interaction, a common mathematical foundation is lacking. The aim of this paper is to propose a formal method of human-machine (H-M) interaction paradigm from the information view point. The methods presented are interpretation- and context-free and can be used both in experimental analysis as well as in modeling problems

University Invention, Entrepreneurship, and Start-Ups

This paper develops a game-theoretic model that predicts when a university invention is commercialized in a start-up firm rather than an established firm. The model predicts that university inventions are more likely to occur in start-ups when the technology transfer officers (TTOs) search cost is high, the cost of development or commercialization is lower for a start-up, or the inventor's effort cost in development is lower in a start-up. We test the theory using data from the Association of University Technology Managers, the National Research Council, and the National Venture Capital Association. Licensing is more likely in general, and especially so in start-ups, by universities with higher quality engineering faculty and older TTOs. Start-ups are more likely by universities in states with larger levels of venture capital. TTO size has no effect on start-ups, but does increase licenses. Conversely, universities that earn greater licensing royalties have fewer start-ups but more licenses. The number of start-ups is decreasing in the interest rate, increasing in the S&P 500, and unaffected by levels of industrial research funding and the presence of a medical school. All of these results are consistent with the predictions of our theory.