COMPARATIVE RESULTS FROM APPLYING A MULTILAYERED NETWORK FRAMEWORK TO ENGINEER NUCLEAR SECURITY SYSTEMS.
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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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This report provides information on the commercialization potential of the NASA Activity Monitor. Data on current commercially available products, market size, and growth are combined with information on the NASA technology and the projected impact of this technology on the market.
An optically responsive electronic lock is disclosed comprising an optical fiber serving as a key and having Bragg gratings placed therein. Further, an identification system is disclosed which has the optical fiber serving as means for tagging and identifying an object. The key or tagged object is inserted into a respective receptacle and the Bragg gratings cause the optical fiber to reflect a predetermined frequency spectra pattern of incident light which is detected by a decoder and compared against a predetermined spectrum to determine if an electrical signal is generated to either operate the lock or light a display of an authentication panel.
This tutorial presents an overview of the application of artificial neural network (ANN) to power.
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Information Technology (IT) Security Risk Management is a critical task in the organization, which must protect its resources and data against the loss of confidentiality, integrity, and availability. As systems become more complex and diverse, and more vulnerabilities are discovered while attacks from intrusions and malicious content increase, it is becoming increasingly difficult to manage IT security. This paper describes an approach to address IT security risk through risk management and mitigation in both the institution and in the project life cycle.
A security code system for controlling access to computer and computer-controlled entry situations comprises a plurality of subsets of alpha-numeric characters disposed in random order in matrices of at least two dimensions forming theoretical rectangles, cubes, etc., such that when access is desired, at least one pair of previously unused character subsets not found in the same row or column of the matrix is chosen at random and transmitted by the computer. The proper response to gain access is transmittal of subsets which complete the rectangle, and/or a parallelepiped whose opposite corners were defined by first groups of code. Once used, subsets are not used again to absolutely defeat unauthorized access by eavesdropping, and the like.
Modernization of energy systems has led to in- creased interactions among multiple critical infrastructures and diverse stakeholders making the challenge of operational decision making more complex and at times beyond cognitive capabilities of human operators. The state-of-the-art machine learning and deep learning approaches show promise of supporting users with complex decision-making challenges, such as those occurring in our rapidly transforming cyber-physical energy systems. However, successful adoption of data-driven decision support technology for critical infrastructure will be dependent on the ability of these technologies to be trustworthy and contextually interpretable. In this paper, we investigate the feasibility of implementing XAI for interpretable detection of cyberattacks in the energy system. Leveraging a proof-of-concept simulation use case of detection of a data falsification attack on a photovoltaic system using XGBoost algorithm, we demonstrate how Local Interpretable Model-Agnostic Explanations (LIME), a flavor XAI approach, can help provide contextual and actionable interpretation of cyberattack detection.