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The Civil Infrastructure Systems (CIS) program supports fundamental and innovative research necessary for designing, constructing, managing, maintaining, operating and protecting efficient, resilient and sustainable civil infrastructure systems. Research that recognizes the role that these systems play in societal functioning and accounts for how human behavior and social organizations contribute to and affect the performance of these systems is encouraged. While component-level, subject-matter knowledge may be crucial in many research efforts, this program focuses on the civil infrastructure as a system in which interactions between spatially-distributed components and intersystem connections exist. Thus, intra- and inter-physical, information and behavioral dependencies of these systems are also of particular interest. Topics pertaining to transportation systems, construction engineering, infrastructure systems and infrastructure management are a focus of this program. Research that considers either or both ordinary and disrupted operating environments is relevant. Methodological contributions pertaining to systems engineering and design, network analysis and optimization, performance management, vulnerability and risk analysis, mathematical and simulation modeling, exact and approximate algorithm development, control theory, statistical forecasting, dynamic and stochastic systems approaches, multi-attribute decision theory, and incorporation of behavioral and social considerations, not excluding other methodological areas or the integration of methods, specific to this application are encouraged. Additional research of interest exploits data/information, and takes advantage of relevant technological advances, such as social media. In general, research that has the promise of long-lasting, cascading (hopefully escalating) impact on the wider research community through its theoretical, scientific, mathematical or computational contributions is valued. The program d

The Energy, Power, Control, and Networks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN's goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

The following programs have due dates that fall between October 1 - 25, 2013, and these dates are being revised due to the Federal  government shutdown. These revised dates apply whether the proposal is being submitted via the NSF FastLane System or  Grants.gov. Due to compressed proposal deadlines resulting from the shutdown, proposers are advised that they may experience a  delay when contacting IT Help Central with technical support questions. Frequently asked questions regarding these date changes  are available on the Resumption of Operations page on the NSF website at: http://www.nsf.gov/bfa/dias/policy/postshutdown.jsp.