Sabina Rakhmetulayeva^1,*, Zhandos Zhanabekov², Aigerim Bolshibayeva³

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4503-4523, 2024, DOI:10.32604/cmc.2024.057974 - 19 December 2024

Abstract The applications of machine learning (ML) in the medical domain are often hindered by the limited availability of high-quality data. To address this challenge, we explore the synthetic generation of echocardiography images (echoCG) using state-of-the-art generative models. We conduct a comprehensive evaluation of three prominent methods: Cycle-consistent generative adversarial network (CycleGAN), Contrastive Unpaired Translation (CUT), and Stable Diffusion 1.5 with Low-Rank Adaptation (LoRA). Our research presents the data generation methodology, image samples, and evaluation strategy, followed by an extensive user study involving licensed cardiologists and surgeons who assess the perceived quality and medical soundness of More > Graphic Abstract

Yoshitaka Umeno^1,*, Atsushi Kubo², Emi Kawai¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-2, 2024, DOI:10.32604/icces.2024.012708

Abstract Fatigue fracture accounts for a substantial fraction of failure cases in industrial products, especially in metal materials. While the mechanism of fatigue crack propagation can be understood in the mechanical point of view considering the effect of microstructures and crystal orientations on crack growth, there is still much room for investigations of the mechanism of fatigue crack formation under cyclic loading. It is widely understood that the fatigue crack formation in macroscopic metal materials originates in the persistent slip band (PSB) formed as a result of self-organization of dislocation structures [1]. Nevertheless, the PSB formation… More >

Yaoyao Wang¹, Mansheng Xiao^1,*, Yuqing Hu², Jin Yan¹, Zeyu Zhu¹

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4433-4449, 2024, DOI:10.32604/cmc.2024.053232 - 12 September 2024

Abstract Due to the limitations of a priori knowledge and convolution operation, the existing image restoration techniques cannot be directly applied to the cultural relics mural restoration, in order to more accurately restore the original appearance of the cultural relics mural images, an image restoration based on the denoising diffusion probability model (Denoising Diffusion Probability Model (DDPM)) and the Transformer method. The process involves two steps: in the first step, the damaged mural image is firstly utilized as the condition to generate the noise image, using the time, condition and noise image patch as the inputs… More >

Dinh Phu Cuong Le^1,2, Dong Wang¹, Viet-Tuan Le^3,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 37-60, 2024, DOI:10.32604/cmc.2024.050790 - 18 July 2024

Abstract Transformer models have emerged as dominant networks for various tasks in computer vision compared to Convolutional Neural Networks (CNNs). The transformers demonstrate the ability to model long-range dependencies by utilizing a self-attention mechanism. This study aims to provide a comprehensive survey of recent transformer-based approaches in image and video applications, as well as diffusion models. We begin by discussing existing surveys of vision transformers and comparing them to this work. Then, we review the main components of a vanilla transformer network, including the self-attention mechanism, feed-forward network, position encoding, etc. In the main part of More >

C. Suganthini^*, R. Baskaran

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1715-1731, 2023, DOI:10.32604/iasc.2023.034019 - 05 January 2023

Abstract In online social networks (OSN), they generate several specific user activities daily, corresponding to the billions of data points shared. However, although users exhibit significant interest in social media, they are uninterested in the content, discussions, or opinions available on certain sites. Therefore, this study aims to identify influential communities and understand user behavior across networks in the information diffusion process. Social media platforms, such as Facebook and Twitter, extract data to analyze the information diffusion process, based on which they cascade information among the individuals in the network. Therefore, this study proposes an influential… More >

Yi Yang^*, Robert A. Nawrocki, Richard M. Voyles, Haiyan H. Zhang

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 237-266, 2021, DOI:10.32604/cmc.2021.017439 - 04 June 2021

Abstract Because charge carriers of many organic semiconductors (OSCs) exhibit fractional drift diffusion (Fr-DD) transport properties, the need to develop a Fr-DD model solver becomes more apparent. However, the current research on solving the governing equations of the Fr-DD model is practically nonexistent. In this paper, an iterative solver with high precision is developed to solve both the transient and steady-state Fr-DD model for organic semiconductor devices. The Fr-DD model is composed of two fractional-order carriers (i.e., electrons and holes) continuity equations coupled with Poisson’s equation. By treating the current density as constants within each pair… More >

Shengyang Feng^1,2,3,*, Dongbo Xiong⁴, Guojie Chen⁵, Yu Cui¹, Puxin Chen¹

FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.3, pp. 651-663, 2020, DOI:10.32604/fdmp.2020.07981 - 25 May 2020

Abstract Convection and diffusion are the main factors affecting radon migration. In this paper, a coupled diffusion-convection radon migration model is presented taking into account turbulence effects. In particular, the migration of radon is simulated in the framework of the k-ε turbulence model. The model equations are solved in a complex 3D domain by the finite element method (FEM). Special attention is paid to the case study about radon migration in an abandoned air defense shelter (AADS). The results show that air convection in a confined space has a great influence on the radon migration and the More >

Senbo Chen^{1, 3, *}, Wenan Tan^{1, 2}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 345-358, 2020, DOI:10.32604/cmc.2020.09807 - 20 May 2020

Abstract The problem of influence maximizing in social networks refers to obtaining a set of nodes of a specified size under a specific propagation model so that the aggregation of the node-set in the network has the greatest influence. Up to now, most of the research has tended to focus on monolayer network rather than on multiplex networks. But in the real world, most individuals usually exist in multiplex networks. Multiplex networks are substantially different as compared with those of a monolayer network. In this paper, we integrate the multi-relationship of agents in multiplex networks by… More >

Yanlong Zhang¹, Baoli Yin¹, Yue Cao¹, Yang Liu^{1 , *}, Hong Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.3, pp. 1081-1098, 2020, DOI:10.32604/cmes.2020.07822 - 01 March 2020

Abstract In this article, a high-order scheme, which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme, is developed for looking for the numerical solution of a two-dimensional nonlinear time fractional thermal diffusion model. The time Caputo fractional derivative is approximated by using the L2 -1 _σ formula, the first-order derivative and nonlinear term are discretized by some second-order approximation formulas, and the quadratic finite element is used to approximate the spatial direction. The error accuracy O(h ³ + ∆t ² ) is obtained, which is verified by the numerical More >

Marco A.A. Kappel¹, Diego C. Knupp¹, Roberto P. Domingos¹, IvanN. Bastos¹

CMC-Computers, Materials & Continua, Vol.49-50, No.1, pp. 13-29, 2015, DOI:10.3970/cmc.2015.049.013

Abstract This work is aimed at the direct and inverse analysis of hydrogen permeation in steels employing a novel anomalous diffusion model. For the inverse analysis, experimental data for hydrogen permeation in a 13% chromium martensitic stainless steel, available in the literature [Turnbull, Carroll and Ferriss (1989)], was employed within the Bayesian framework for inverse problems. The comparison between the predicted values and the available experimental data demonstrates the feasibility of the new model in adequately describing the physical phenomena occurring in this particular problem. More >