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Software Framework for Control and Observation in Distributed Environments (CODE)

Ames Research Center, Moffett Field, California CODE is a framework for control and observation in distributed environments. The framework enables the observation of resources (computer systems, storage systems, networks, and so on), services (database servers, application execution, servers, file transfer servers, and so on), and applications. Further, the framework provides support for the secure and scalable transmission of this observed information to programs that are interested in it. The framework also supports the secure execution of actions on remote computer systems so that a management program can respond to the observed data that it receives. To assist in writing management programs, the framework interfaces to an existing expert system so that a user can define a set of rules for the expert system to reason on, instead of writing a large amount of code. The framework is modular and can be easily extended to incorporate new sensors to make observations, new actuators to perform actions, new communication protocols, and new security mechanisms. The software also includes several applications that show how the framework can be used.

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Simple RunTime eXecutive (SRTX)

Marshall Space Flight Center, Alabama Simple RunTime eXecutive (SRTX) software provides scheduling and publish/subscribe data transfer services. The scheduler allows dynamic allocation of real-time periodic and asynchronous tasks across homogeneous multi core/multiprocessor systems. Most real-time systems assign tasks to specific cores on an a priori basis. Allowing the operating system scheduler to determine the best allocation of threads is not a unique innovation. However, it is coupled with a deterministic publish/subscribe data transfer system that guarantees the tasks process data deterministically, regardless of the number of processor cores in the system.

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v-Anomica: A Fast Support Vector-Based Novelty Detection Technique

Ames Research Center, Moffett Field, California Outlier or anomaly detection refers to the task of identifying abnormal or inconsistent patterns from a dataset. While they may seem to be undesirable entities, identifying them has many potential applications in fraud and intrusion detection, medical research, and safety-critical vehicle health management. Outliers can be detected using supervised, semi-supervised, or unsupervised techniques. Unsupervised techniques do not require labeled instances for detecting outliers. Supervised techniques require labeled instances of both normal and abnormal operation data for first building a model (e.g., a classifier), and then testing if an unknown data point is a normal one or an outlier. The model can be probabilistic such as Bayesian inference or deterministic such as decision trees, Support Vector Machines (SVMs), and neural networks. Semi-supervised techniques only require labeled instances of normal data. Hence, they are more widely applicable than the fully supervised ones. These techniques build models of normal data and then flag outliers that do not fit the model.

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Self-Stabilizing Distributed Clock Synch ronization Protocol for Arbitrary Digraphs

Langley Research Center, Hampton, Virginia A report describes a self-stabilizing distributed clock synchronization protocol in the absence of faults in the system. It is focused on the distributed clock synchronization of an arbitrary, non-partitioned digraph ranging from fully connected to 1-connected networks of nodes, while allowing for differences in the network elements. The protocol does not rely on assumptions about the initial state of the system, other than the presence of at least one node, and no central clock or a centrally generated signal, pulse, or message is used.

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Precision Navigation Strategies for Primitive Solar-System-Body Sample Return Missions

Goddard Space Flight Center, Greenbelt, Maryland This project investigated advanced navigation strategies required to approach, perform proximity operations, and return a sample from an asteroid or comet. An optimized navigation strategy for a notional mission to a near-Earth asteroid was developed to serve as a baseline for future missions and mission proposals. Essential simulation and analysis software enhancements were developed and implemented in the Orbit De ter mination Toolbox (ODTBX), an open-source, early mission navigation analysis tool suite built on a flexible architecture. The development efforts of this project resulted in the first fully open-source tool suite with the capabilities of performing primitive body navigation simulation and analyses.

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Orbit Determination Toolbox 2012a (v5.0)

Goddard Space Flight Center, Greenbelt, Maryland The Orbit Determination Toolbox (ODTBX) 2012a (v5.0) is an advanced mission simulation and analysis tool used for concept exploration, proposal, early design phase, or rapid design center environments: the emphasis is on flexibility, but it has enough fidelity to produce credible results. ODTBX v5.0 includes multiple feature additions, enhancements, and bug fixes from the prior release (v4.5). The primary user interface and supporting functions are written in Matlab and Java.

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Design and Construction of Protograph-Based LDPC Codes

This innovation can be used in magnetic tape recording and other channels with finite-state representation. NASA’s Jet Propulsion Laboratory, Pasadena, California Writing (recording) to a storage device and reading from it can be considered as a noisy channel. A storage device such as magnetic recoding and optical recording can be modeled as a partial response channel. Partial-response techniques are a special case of precoding technique where the intersymbol interference is forced to some known pattern. Thus, read-back data from storage devices may have intersymbol interference.

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