Earticle

In this paper, we proposed novel continuous tone representational method based reaction-diffusion model. We extended previous related research of hedcut-style rendering by adding controllability to reaction-diffusion based texture generation method. These controls includes pattern size and pattern direction for various style rendering. Our method is comparable with stipping method which can generate artistic style rendering with continuous tone representation of input images. While stippling can show stable tonal results for low density points area, high density region which stipples redundant is suffer from non-linear brightness. On the contrary, our method shows stable tonal results for all brightness spans. We also present anisotropic diffusion for directional pattern generation which can applied to more various style rendering. In this contribution includes mathematical model and results of various style.

This paper presents non-photorealistic rendering methods of hedcut-style effects by using reaction-diffusion model. Reaction-diffusion model is a mathematical model proposed by Turing to describe the biological formation of natural patterns but we adapted this model as a tonal depiction method of stipples and curve patterns. According to the input image brightness, this model generates stipple patterns of black or white dots for near-black or near-white image area while it produces curve patterns for middle gray image area. Our method uses simple pre-processing step to compensate brightness and contrast of input image. We compare previous method and hand-made hedcut artwork with our results. Our works can be applied in game application and stylized rendering area.

GGAC is an improvement based on geodesic active contour model (GAC). GGAC model is a widely used method for image segmentation. But, it will be difficult to achieve satisfactory segmentation results to the texture, uneven structure, edge particles, weak edge and other features of the wood surface image. Therefore, the author proposes a segmentation method that integrates the improved Canny edge detection result integrated into the improved GGAC model redrawing boundary stop function, and uses the improved variational level set method to achieve the numerical solution. The algorithm has reduced the choice sensitivity to the initial contour and enhanced the scalability, which can make the profile curve converge to defect edges more rapidly, avoid the local optimum, and improve segmentation effects of weak edges and uneven image. The results are clearer, more consistent and real-time. It has provided a more effective way to segment the wood surface defects, and broadened the application scope of Canny operator and an improved geodesic active contour model.

This paper is concerned with the optimal control problem for some reaction diusion model. That is, we show the existence of the global weak solution for the Field-Noyes model. We also show the existence of the optimal control.

A reaction-diffusion model with spatiotemporal delay modeling the dynamical behavior of a single species is investigated. The parameter regions for the local stability, global stability and instability of the unique positive constant steady state solution are derived. The conditions of the occurrence of Turing (diffusion-driven) instability are obtained. The existence of time-periodic solutions, the existence and nonexistence of nonconstant positive steady state solutions are proved by bifurcation method and energy method. Numerical simulations are presented to verify and illustrate the theoretical results.

본 연구는 비임상 집단을 대상으로 정서 자극에 대한 주의 편향을 탐색하고, 정서 자극의 유형과 제시 시간(SOA: 100, 300, 500 밀리초)에 따른 편향 양상의 차이를 확인하고자 하였다. 이를 위해 두 가지 정서 자극(실험 1: 정서 얼굴, 실험 2: 정서 단어)을 사용한 탐침 탐사 과제를 실시하고, 반응시간 및 정확률 분석과 함께 표류 확산 모델(Drift Diffusion Model, DDM)을 적용하였다. 실험 1에서는 정서 얼굴 자극이 500 밀리초 동안 제시될 때 부정 정서 자극에 대한 회피 경향이 나타났으며, DDM 분석에서는 정서 자극과 자극-목표의 공간적 일치 여부에 따라 표류율이 달라지는 양상이 관찰되었다. 반면, 실험 2에서는 정서 단어 자극에 대해 유의한 정서 편향 효과가 나타나지 않았다. 본 연구는 비임상 집단에서도 특정 조건에서 정서 편향이 나타날 수 있음을 확인하였으며, DDM을 활용해 정서 자극이 정보처리 과정의 구체적 단계에 미치는 영향을 보다 정밀하게 설명할 수 있음을 시사한다.

This study investigated attentional biases toward emotional stimuli in a non-clinical population and examined how these biases differ depending on the type of emotional stimulus and its presentation duration (SOA: 100, 300, and 500 ms). To this end, participants completed a dot-probe task using two types of emotional stimuli (Experiment 1: emotional faces; Experiment 2: emotional words), and analyses were conducted on both reaction times and accuracy, alongside the application of the Drift Diffusion Model (DDM). In Experiment 1, attentional avoidance of negative facial expressions was observed only when emotional faces were presented for 500 ms. DDM analyses revealed that drift rates varied depending on the spatial congruency between the emotional stimulus and the target, indicating different patterns of evidence accumulation based on emotional valence. In contrast, Experiment 2 showed no significant attentional bias effects for emotional word stimuli. These findings demonstrate that emotional biases can emerge under specific conditions even in non-clinical populations and suggest that the DDM provides a more detailed explanation of how emotional stimuli influence distinct stages of cognitive processing.