Keeping Radiation Exposure as Low as Reasonably Achievable (ALARA)
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SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Overview of the computational ontological model for the Nuclear Fuel Cycle.
Abstract not provided.
A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.
A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.
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A method for securing an IT (information technology) system using a set of methods for knowledge extraction, event detection, risk estimation and explanation for ranking cyber-alerts which includes a method to explain the relationship (or an attack pathway) from an entity (user or host) and an event context to another entity (a high-value resource) and an event context (attack or service failure).
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Presentation for DICE conference
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This paper has presented an approach to dealing with the complexity of explanation-based learning plans in complex domains. This approach uses a simplified algorithm to construct plans, and employs later refinements to repair bugs in constructed plans. This algorithm has the theoretical properties of completeness and convergence upon soundness. This incremental reasoning planning and learning algorithm has been implemented using a partial-order constraint posting planner and empirically compared to a conventional exhaustive reasoning partial-order constraint-posting planner and learning algorithm. This comparison showed that 1) incremental reasoning significantly reduced learning costs compared to exhaustive reasoning, 2) Explanation-based Learning (EBL) reduced failures from incremental reasoning, 3) EBL with incremental reasoning required less search to solve problems than EBL with exhaustive reasoning.
As our society becomes technologically more complex, computers are being used in greater and greater numbers of high consequence systems. Giving a machine control over the lives of humans can be disturbing, especially if the software that is run on such a machine has bugs. Formal reasoning is one of the most powerful techniques available to demonstrate the correctness of a piece of software. When reasoning about software and its development, one frequently encounters expressions that contain partial functions. As might be expected, the presence of partial functions introduces an additional dimension of difficulty to the reasoning framework. This difficulty produces an especially strong impact in the case of high consequence systems. An ability to use formal methods for constructing software is essential if we want to obtain greater confidence in such systems through formal reasoning. This is only reasonable under automation of software development and verification. However, the ubiquitous presence of partial functions prevents a uniform application to software of any tools not specifically accounting for partial functions. In this paper we will describe a framework for reasoning about software, based on the nonstrict explicit domain approach, that is applicable to a large class of software/hardware systems. In this framework the Hoare triples containing partial functions can be reasoned about automatically in a well-defined and uniform manner.