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A grand challenge in computing is the creation of machines that can proactively interpret and learn from data in real time, solve unfamiliar problems using what they have learned, and operate with the energy efficiency of the human brain. While complex machine-learning algorithms and advanced electronic hardware (henceforth referred to as 'hardware') that can support large-scale learning have been realized in recent years and support applications such as speech recognition and computer vision, emerging computing challenges require real-time learning, prediction, and automated decision-making in diverse domains such as autonomous vehicles, military applications,healthcare informatics and business analytics. A salient feature of these emerging domains is the large and continuously streaming data sets that these applications generate, which must be processed efficiently enough to support real-time learning and decision making based on these data. This challenge requires novel hardware techniques and machine-learning architectures.This solicitation seeks to lay the foundation for next-generation co-design of RTML algorithms and hardware, with the principal focus on developing novel hardware architectures and learning algorithms in which all stages of training (including incremental training, hyperparameter estimation, and deployment) can be performed in real time. The National Science Foundation (NSF) and the Defense Advanced Research Projects Agency (DARPA) are teaming up through this Real-Time Machine Learning (RTML) program to explore high-performance, energy-efficient hardware and machine-learning architectures that can learn from a continuous stream of new data in real time, through opportunities for post-award collaboration between researchers supported by DARPA and NSF.

All of comparative biology depends on knowledge of the evolutionary relationships (phylogeny) of living and extinct organisms. In addition, understanding biodiversity and how it changes over time is only possible when Earth's diversity is organized into a phylogenetic framework. The goals of the Genealogy of Life (GoLife) program are to resolve the phylogenetic history of life and to integrate this genealogical architecture with underlying organismal data. The ultimate vision of this program is an open access, universal Genealogy of Life that will provide the comparative framework necessary for testing questions in systematics, evolutionary biology, ecology, and other fields. A further strategic integration of this genealogy of life with data layers from genomic, phenotypic, spatial, ecological and temporal data will produce a grand synthesis of biodiversity and evolutionary sciences. The resulting knowledge infrastructure will enable synthetic research on biological dynamics throughout the history of life on Earth, within current ecosystems, and for predictive modeling of the future evolution of life.Projects submitted to this program should emphasize increased efficiency in contributing to a complete Genealogy of Life and integration of various types of organismal data with phylogenies.This program also seeks to broadly train next generation, integrative phylogenetic biologists, creating the human resource infrastructure and workforce needed to tackle emerging research questions in comparative biology. Projects should train students for diverse careers by exposing them to the multidisciplinary areas of research within the proposal.

The objective of the Cybersecurity Innovation for Cyberinfrastructure (CICI) program is to develop, deploy and integrate security solutions that benefit the scientific community by ensuring the integrity, resilience and reliability of the end-to-end scientific workflow. CICI seeks three categories of projects: 1.Secure Scientific Cyberinfrastructure (SSC):These awards seek to secure the scientific workflow by encouraging novel and trustworthy architectural and design approaches, models and frameworks for the creation of a holistic, integrated security environment that spans the entire scientific CI ecosystem. 2.Research Data Protection (RDP):These awards provide solutions that both ensure the provenance of research data and reduce the complexity of protecting research data sets regardless of funding source. 3.Cybersecurity Center of Excellence (CCoE):This award seeks to provide the NSF community with a centralized resource of expertise and leadership in trustworthy cyberinfrastructure.

As NASA moves forward with plans to support human exploration of the solar system, a critical need arises to supply basic materials such as oxygen (O2) and water (H2O), food, propellants, and other materials (radiation shielding, clothing, etc.). As mankind ventures farther from Earth and for greater periods of time, it becomes imperative to develop technologies and mission architectures that utilize local resources, such as those found in lunar regolith, to provide supplies needed for human exploration.  The objective of SRC Phase 2 is to find solutions to allow a heterogeneous, multi-robot team to autonomously complete tasks envisioned for a lunar in-situ resource utilization (ISRU) mission. This challenge will require competitors to develop software that allows a virtual team of robotic systems (i.e. virtual robotic team) to operate autonomously to successfully achieve these tasks.

Naval Surface Warfare Center (NSWC) Crane and the Office of the Undersecretary of Defense for Research and Engineering (OUSD(R&E))'s Joint Hypersonic Transition Office (JHTO) are interested in receiving research proposals in the following areas. Each will have a Period of Performance (PoP) of 12 months. a. Systems-level design of high-temperature composite materials and structures research utilization of fiber architectures and matrix compositions b. Novel position, navigation, and timing and adaptive flight controls c. Design-oriented models to optimize scramjet and multi-mode engines d. Simulation Methods for the Rapid Prediction of Hypersonic Environments e. Addressing the flow path processes that occur in rectangular or curved inlets and isolators including the destabilization that may occur due to junction flows or off-nominal flight conditions f. The development of methods and models including validation experiments and instrumentation to provide high quality data on multiphase blast properties and structural responses to structures g. Improving the understanding of rotating detonation rocket engine (RDRE) physics and developing design solutions for their inherent technical challenges h. Hypersonic Workforce Curricula Development

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.