27 research outputs found

    Construction of Self-Dual Integral Normal Bases in Abelian Extensions of Finite and Local Fields

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    Let F/EF/E be a finite Galois extension of fields with abelian Galois group Γ\Gamma. A self-dual normal basis for F/EF/E is a normal basis with the additional property that TrF/E(g(x),h(x))=ήg,hTr_{F/E}(g(x),h(x))=\delta_{g,h} for g,h∈Γg,h\in\Gamma. Bayer-Fluckiger and Lenstra have shown that when char(E)≠2char(E)\neq 2, then FF admits a self-dual normal basis if and only if [F:E][F:E] is odd. If F/EF/E is an extension of finite fields and char(E)=2char(E)=2, then FF admits a self-dual normal basis if and only if the exponent of Γ\Gamma is not divisible by 44. In this paper we construct self-dual normal basis generators for finite extensions of finite fields whenever they exist. Now let KK be a finite extension of \Q_p, let L/KL/K be a finite abelian Galois extension of odd degree and let \bo_L be the valuation ring of LL. We define AL/KA_{L/K} to be the unique fractional \bo_L-ideal with square equal to the inverse different of L/KL/K. It is known that a self-dual integral normal basis exists for AL/KA_{L/K} if and only if L/KL/K is weakly ramified. Assuming p≠2p\neq 2, we construct such bases whenever they exist

    Non-unimodular hermitian forms

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    Context-sensitive affect sensing and metaphor identification in virtual drama

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    Affect interpretation from story/dialogue context and metaphorical expressions is challenging but essential for the development of emotion inspired intelligent user interfaces. In order to achieve this research goal, we previously developed an AI actor with the integration of an affect detection component on detecting 25 emotions from literal text-based improvisational input. In this paper, we report updated development on metaphorical affect interpretation especially for sensory & cooking metaphors. Contextual affect detection with the integration of emotion modeling is also explored. Evaluation results for the new developments are provided. Our work benefits systems with intention to employ emotions embedded in the scenarios/characters and open-ended input for visual representation without detracting users from learning situations
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