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Our nation's security as well as the quality of life of its citizenry depends on the continuous reliable operation of a collection of complicated interdependent infrastructures including transportation, electric power, oil, gas, telecommunications and emergency services. A disruption in one infrastructure can quickly and significantly impact another, causing ripples across the nation. Our infrastructures are increasingly reliant on new information technologies and the Internet to operate, often being connected to one another via electronic, informational links. While these technologies allow for enormous gains in efficiency, they also create new vulnerabilities. The focus of this paper is the development of a unifying mathematical framework to represent these "mega infrastructures" and a collection of algorithms that can be used to estimate performance and optimize investment. We include a small computational example that focuses on the delivery of gas and electric services, including the underlying SCADA system that supports the gas network, to illustrate the operation of the algorithms.

Robots are being used in a host of different work environments currently. However, to date there has been very little broad exploration into the designs of systems and how that affects users’ perception of fit for the robots in different job categories. In the present experiment we showed participants images of 252 robots and asked them to make assignments of the robots into 16 potential job categories taken from the U.S. Department of Labor. The robots’ overall human likeness, as well as four contributory components of anthropomorphism were used to predict job category assignment. Results indicate that participants expect higher levels of anthropomorphism in jobs with more direct human interactions (such as education and hospitality), whereas they expect minimal levels in jobs with less human interaction (e.g. agriculture and architecture). Results also indicate that there is more nuance required for these judgments than general human likeness.

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