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James Llinas [4]James L. Llinas [1]
  1. Ontology and Cognitive Outcomes.David Limbaugh, Jobst Landgrebe, David Kasmier, Ronald Rudnicki, James Llinas & Barry Smith - 2020 - Journal of Knowledge Structures and Systems 1 (1): 3-22.
    The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors (...)
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  2. Conceptual Space Modeling for Space Event Characterization.Jeremy R. Chapman, David Kasmier, David Limbaugh, Stephen R. Gagnon, John L. Crassidis, James Llinas, Barry Smith & Alexander P. Cox - 2020 - IEEE 23rd International Conference on Information Fusion (FUSION).
    This paper provides a method for characterizing space events using the framework of conceptual spaces. We focus specifically on estimating and ranking the likelihood of collisions between space objects. The objective is to design an approach for anticipatory decision support for space operators who can take preventive actions on the basis of assessments of relative risk. To make this possible our approach draws on the fusion of both hard and soft data within a single decision support framework. Contextual data is (...)
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  3.  44
    An Introduction to Hard and Soft Data Fusion Via Conceptual Spaces Modeling for Space Event Characterization.Jeremy Chapman, David Kasmier, John L. Crassidis, James L. Llinas, Barry Smith & Alex P. Cox - 2021 - In National Symposium on Sensor & Data Fusion (NSSDF), Military Sensing Symposia (MSS).
    This paper describes an AFOSR-supported basic research program that focuses on developing a new framework for combining hard with soft data in order to improve space situational awareness. The goal is to provide, in an automatic and near real-time fashion, a ranking of possible threats to blue assets (assets trying to be protected) from red assets (assets with hostile intentions). The approach is based on Conceptual Spaces models, which combine features from traditional associative and symbolic cognitive models. While Conceptual Spaces (...)
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  4.  60
    Implementing Dempster-Shafer Theory for Property Similarity in Conceptual Spaces Modeling.Jeremy R. Chapman, John L. Crassidis, James Llinas, Barry Smith & David Kasmier - 2022 - Sensor Systems and Information Systems IV, American Institute of Aeronautics and Astronautics (AIAA) SCITECH Forum 2022.
    Previous work has shown that the Complex Conceptual Spaces − Single Observation Mathematical framework is a useful tool for event characterization. This mathematical framework is developed on the basis of Conceptual Spaces and uses integer linear programming to find the needed similarity values. The work of this paper is focused primarily on space event characterization. In particular, the focus is on the ranking of threats for malicious space events such as a kinetic kill. To make the Conceptual Spaces framework work, (...)
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  5. Conceptual Spaces for Space Event Characterization Via Hard and Soft Data Fusion.Jeremy R. Chapman, David Kasmier, David Limbaugh, Stephen R. Gagnon, John Crassidis, James Llinas, Barry Smith & Alexander P. Cox - 2021 - AIAA (American Institute of Aeronautics and Astronautics) Scitech 2021 Forum.
    The overall goal of the approach developed in this paper is to estimate the likelihood of a given kinetic kill scenario between hostile spacebased adversaries using the mathematical framework of Complex Conceptual Spaces Single Observation. Conceptual spaces are a cognitive model that provide a method for systematically and automatically mimicking human decision making. For accurate decisions to be made, the fusion of both hard and soft data into a single decision framework is required. This presents several challenges to this data (...)
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