4,674 research outputs found

    Rule groupings: An approach towards verification of expert systems

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    Knowledge-based expert systems are playing an increasingly important role in NASA space and aircraft systems. However, many of NASA's software applications are life- or mission-critical and knowledge-based systems do not lend themselves to the traditional verification and validation techniques for highly reliable software. Rule-based systems lack the control abstractions found in procedural languages. Hence, it is difficult to verify or maintain such systems. Our goal is to automatically structure a rule-based system into a set of rule-groups having a well-defined interface to other rule-groups. Once a rule base is decomposed into such 'firewalled' units, studying the interactions between rules would become more tractable. Verification-aid tools can then be developed to test the behavior of each such rule-group. Furthermore, the interactions between rule-groups can be studied in a manner similar to integration testing. Such efforts will go a long way towards increasing our confidence in the expert-system software. Our research efforts address the feasibility of automating the identification of rule groups, in order to decompose the rule base into a number of meaningful units

    Terrorists Are Always Muslim but Never White: At the Intersection of Critical Race Theory and Propaganda

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    When you hear the word “terrorist,” who do you picture? Chances are, it is not a white person. In the United States, two common though false narratives about terrorists who attack America abound. We see them on television, in the movies, on the news, and, currently, in the Trump administration. The first is that “terrorists are always (brown) Muslims.” The second is that “white people are never terrorists.” Different strands of critical race theory can help us understand these two narratives. One strand examines the role of unconscious cognitive biases in the production of stereotypes, such as the stereotype of the “Muslim terrorist.” Another strand focuses on white privilege, such as the privilege of avoiding the terrorist label. These false narratives play a crucial role in Trump’s propaganda. As the critical race analysis uncovers, these two narratives dovetail with two constituent parts of propaganda: flawed ideologies and aspirational myths. Propaganda relies on preexisting false ideologies, which is another way to describe racist stereotyping. Propaganda also relies on certain ideals and myths, in this case, the myth of white innocence and white superiority. Thus, the Trump administration’s intentional invocation of both narratives amounts to propaganda in more than just the colloquial sense. Part I illustrates each of the two narratives. Part II then analyzes them through a critical race lens, showing how they map onto two strands of critical race theory. Next, Part III examines how these narratives simultaneously enable and constitute propaganda. Finally, Part IV argues that the propagation of these false narratives hurts the nation’s security

    Mapping diasporic subjectivities

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    Hospital and home teachers' views about teaching students who have medically defined mental health needs

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    Rising numbers of students with medically defined mental health needs are being referred to some hospital and home teaching services (HHTS). In July 2006 hospital and home teachers were surveyed about how this affects their work, in order to share ideas and help to promote good practice. A definition of mental health needs was not included in order to avoid limiting responses. In this challenging area, with no easy answers and this report, a small contribution to complex discussions, is intended to raise as well as to answer questions. ‘Students’ will refer to students with medically defined mental health needs

    Multi-viewpoint clustering analysis

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    In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems
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