380,881 research outputs found

    Ergodicity and entropy in sequence spaces

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    The infinite permutations of possible moves in a game, or positions on a game board, form a one-sided sequence space. We are working with a probability measure on the space of measurable subsets of the sequence space. We are studying a shift transformation on this space, which is measure preserving. We explore conditions under which the shift transformation is ergodic and calculate the entropy of the shift that is associated with the steady state of the game where applicable. These concepts are exemplified by the games Rock, Paper, Scissors and Monopoly. We then create new games and study how the properties of ergodicity and entropy change with respect to different aspects of the games

    Critical behavior and magnetocaloric effect in Tsai-type 2/1 and 1/1 quasicrystal approximants

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    Stable Tsai-type quinary 1/1 and 2/1 approximant crystals (ACs) with chemical compositions Au56.25Al10Cu7In13Tb13.75 and Au55.5Al10Cu7In13Tb14.5, respectively, exhibiting ferromagnetic (FM) long-range orders were successfully synthesized and studied for their magnetic properties and magnetocaloric effect. The 1/1 and 2/1 ACs primarily differ in their long-range atomic arrangement and rare earth (RE) distribution, with the latter approaching quasiperiodic order while still preserving periodicity. Analyses based on the scaling principle and Kouvel-Fisher (KF) relations suggested mean-field-like behavior near Curie temperatures in both compounds. From magnetization measurements and the Maxwell equation, a magnetic entropy change of -4.3 and -4.1 J/K mol Tb were derived under a magnetic field change of 7 T for the 1/1 and 2/1 ACs, respectively. The results indicated a prominent role of intra-cluster magnetic interactions on critical behavior and magnetic entropy of the Tsai-type compounds

    Runtime Verification of Self-Adaptive Systems with Changing Requirements

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    To accurately make adaptation decisions, a self-adaptive system needs precise means to analyze itself at runtime. To this end, runtime verification can be used in the feedback loop to check that the managed system satisfies its requirements formalized as temporal-logic properties. These requirements, however, may change due to system evolution or uncertainty in the environment, managed system, and requirements themselves. Thus, the properties under investigation by the runtime verification have to be dynamically adapted to represent the changing requirements while preserving the knowledge about requirements satisfaction gathered thus far, all with minimal latency. To address this need, we present a runtime verification approach for self-adaptive systems with changing requirements. Our approach uses property specification patterns to automatically obtain automata with precise semantics that are the basis for runtime verification. The automata can be safely adapted during runtime verification while preserving intermediate verification results to seamlessly reflect requirement changes and enable continuous verification. We evaluate our approach on an Arduino prototype of the Body Sensor Network and the Timescales benchmark. Results show that our approach is over five times faster than the typical approach of redeploying and restarting runtime monitors to reflect requirements changes, while improving the system's trustworthiness by avoiding interruptions of verification.Comment: 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2023
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