High-order rogue waves of a long wave-short wave model

The long wave-short wave model describes the interaction between the long wave and the short wave. Exact higher-order rational solution expressed by determinants is calculated via the Hirota's bilinear method and the KP hierarchy reduction. It is found that the fundamental rogue wave for the short wave can be classified into three different patterns: bright, intermediate and dark ones, whereas the rogue wave for the long wave is always bright type. The higher-order rogue waves correspond to the superposition of fundamental rogue waves. The modulation instability analysis show that the condition of the baseband modulation instability where an unstable continuous-wave background corresponds to perturbations with infinitesimally small frequencies, coincides with the condition for the existence of rogue-wave solutions.Comment: 14 pages, 5 figure

Crossing the ‘Uncanny Valley’: Adaptation to Cartoon Faces Can Influence Perception of Human Faces

In this study we assessed whether there is a single face space common to both human and cartoon faces by testing whether adaptation to cartoon faces can affect perception of human faces. Participants were shown Japanese animation cartoon videos containing faces with abnormally large eyes. The use of animated videos eliminated the possibility of position-dependent retinotopic adaptation (because the faces appear at many different locations) and more closely simulated naturalistic exposure. Adaptation to cartoon faces with large eyes significantly shifted preferences for human faces toward larger eyes, consistent with a common, non-retinotopic representation for both cartoon and human faces. This supports the possibility that there are representations that are specific to faces yet common to all kinds of faces

An Adaptable IoT Rule Engine Framework for Dataflow Monitoring and Control Strategies

The monitoring of data generated by a large number of devices in Internet of Things (IoT) systems is an important and complex issue. Several studies have explored the use of generic rule engine, primarily based on the RETE algorithm, for monitoring the flow of device data. In order to solve the performance problem of the RETE algorithm in IoT scenarios, some studies have also proposed improved RETE algorithms. However, implementing modifications to the general rule engine remains challenges in practical applications. The Thingsboard open-source platform introduces an IoT-specific rule engine that does not rely on the RETE algorithm. Its interactive mode attracted attention from developers and researchers. However, the close integration between its rule module and the platform, as well as the difficulty in formulating rules for multiple devices, limits its flexibility. This paper presents an adaptable and user-friendly rule engine framework for monitoring and control IoT device data flows. The framework is easily extensible and allows for the formulation of rules contain multiple devices. We designed a Domain-Specific Language (DSL) for rule description. A prototype system of this framework was implemented to verify the validity of theoretical method. The framework has potential to be adaptable to a wide range of IoT scenarios and is especially effective in where real-time control demands are not as strict.Comment: 15 pages,10 figure