3,262 research outputs found

    Pluggable AOP: Designing Aspect Mechanisms for Third-party Composition

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    Studies of Aspect-Oriented Programming (AOP) usually focus on a language in which a specific aspect extension is integrated with a base language. Languages specified in this manner have a fixed, non-extensible AOP functionality. In this paper we consider the more general case of integrating a base language with a set of domain specific third-party aspect extensions for that language. We present a general mixin-based method for implementing aspect extensions in such a way that multiple, independently developed, dynamic aspect extensions can be subject to third-party composition and work collaboratively

    How Opinion Leaders Affect Others on Seeking Truth in a Bounded Confidence Model

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    Seeking truth is an important objective of agents in social groups. Opinion leaders in social groups may help or hinder the other agents on seeking the truth by symmetric nature. This paper studies the impact of opinion leaders by considering four characteristics of opinion leaders—reputation, stubbornness, appeal, and extremeness—on the truth-seeking behavior of agents based on a bounded confidence model. Simulations show that increasing the appeal of the leader whose opinion is opposite to the truth has a straightforward impact, i.e., it normally prevents the agents from finding the truth. On the other hand, it also makes the agents who start out close to the truth move away from the truth by increasing the group bound of confidence, if there is an opinion leader opposite to the truth. The results demonstrate that the opinion of the leader is important in affecting the normal agents to reach the truth. Furthermore, for some cases, small variations of the parameters defining the agents’ characteristics can lead to large scale changes in the social group

    Stochastic to deterministic crossover of fractal dimension for a Langevin equation

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    Using algorithms of Higuchi and of Grassberger and Procaccia, we study numerically how fractal dimensions cross over from finite-dimensional Brownian noise at short time scales to finite values of deterministic chaos at longer time scales for data generated from a Langevin equation that has a strange attractor in the limit of zero noise. Our results suggest that the crossover occurs at such short time scales that there is little chance of finite-dimensional Brownian noise being incorrectly identified as deterministic chaos.Comment: 12 pages including 3 figures, RevTex and epsf. To appear Phys. Rev. E, April, 199
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