The problem caused by fake news continues to worsen in today's online social networks. Intuitively, it seems effective to issue corrections as a countermeasure. However, corrections can, ironically, strengthen attention to fake news, which worsens the situation. This paper proposes a model for describing the interaction between fake news and the corrections as a reaction-diffusion system; this yields the mechanism by which corrections increase attention to fake news. In this model, the emergence of groups of users who believe in fake news is understood as a Turing pattern that appears in the activator-inhibitor model. Numerical calculations show that even if the network structure has no spatial bias, the interaction between fake news and the corrections creates groups that are strongly interested in discussing fake news. Also, we propose and evaluate a basic strategy to counter fake news.

This paper presents a shortest path search algorithm using a model of excitable reaction-diffusion dynamics. In our previous work, we have proposed a framework of Digital Reaction-Diffusion System (DRDS)--a model of a discrete-time discrete-space reaction-diffusion system useful for nonlinear signal processing tasks. In this paper, we design a special DRDS, called an "excitable DRDS," which emulates excitable reaction-diffusion dynamics and produces traveling waves. We also demonstrate an application of the excitable DRDS to the shortest path search problem defined on two-dimensional (2-D) space with arbitrary boundary conditions.

This paper presents an algorithm for fingerprint image restoration using Digital Reaction-Diffusion System (DRDS). The DRDS is a model of a discrete-time discrete-space nonlinear reaction-diffusion dynamical system, which is useful for generating biological textures, patterns and structures. This paper focuses on the design of a fingerprint restoration algorithm that combines (i) a ridge orientation estimation technique using an iterative coarse-to-fine processing strategy and (ii) an adaptive DRDS having a capability of enhancing low-quality fingerprint images using the estimated ridge orientation. The phase-only image matching technique is employed for evaluating the similarity between an original fingerprint image and a restored image. The proposed algorithm may be useful for person identification applications using fingerprint images.

The Belousov-Zhabotinsky (BZ) reaction provides us important clues in controlling 2D phase-lagged stable synchronous patterns in an excitable medium. Because of the difficulty in computing reaction-diffusion systems in large systems using conventional digital processors, we here propose a cellular-automaton (CA) circuit that emulates the BZ reaction. In the circuit, a two-dimensional array of parallel processing cells is responsible for fast emulation, and its operation rate is independent of the system size. The operations of the proposed CA circuit were demonstrated by using a simulation program with integrated circuit emphasis (SPICE).

This paper presents a digital reaction-diffusion system (DRDS)--a model of a discrete-time discrete-space reaction-diffusion dynamical system--for designing new image processing algorithms inspired by biological pattern formation phenomena. The original idea is based on the Turing's model of pattern formation which is widely known in mathematical biology. We first show that the Turing's morphogenesis can be understood by analyzing the pattern forming property of the DRDS within the framework of multidimensional digital signal processing theory. This paper also describes the design of an adaptive DRDS for image processing tasks, such as enhancement and restoration of fingerprint images.

We predict that chemical waves can propagate as a guided mode in a reaction-diffusion system that consists of two regions with different wave speeds. In comparison with electromagnetic waveguides, unique features of the guided chemical waves can be seen in their dispersion characteristics. Conditions for supporting lowest-loss guided waves are discussed.