Yun Wu¹, Ge Jiao^1,2,*, Jiahao Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2465-2485, 2023, DOI:10.32604/cmes.2023.026189

Abstract The accurate and automatic segmentation of retinal vessels from fundus images is critical for the early diagnosis and prevention of many eye diseases, such as diabetic retinopathy (DR). Existing retinal vessel segmentation approaches based on convolutional neural networks (CNNs) have achieved remarkable effectiveness. Here, we extend a retinal vessel segmentation model with low complexity and high performance based on U-Net, which is one of the most popular architectures. In view of the excellent work of depth-wise separable convolution, we introduce it to replace the standard convolutional layer. The complexity of the proposed model is reduced by decreasing the number of… More >

Xiang Su¹, Nan Li^1,*, Yuedi Hu¹, Haisheng Li²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2935-2956, 2023, DOI:10.32604/cmes.2023.026083

Abstract This paper introduces an aircraft wing simulation data set (AWSD) created by an automatic workflow based on creating models, meshing, simulating the wing flight flow field solution, and parameterizing solution results. AWSD is a flexible, independent wing collection of simulations with specific engineering requirements. The data set is applicable to handle computer geometry processing tasks. In contrast to the existing 3D model data set, there are some advantages the scale of this data set is not limited by the collection source, the data files have high quality, no defects, redundancy, and other problems, and the models and simulation are all… More > Graphic Abstract

Dawei Liu, Zhiwei Jin, Xin Peng^*, Gang Liu, Yue Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2691-2713, 2023, DOI:10.32604/cmes.2023.026048

Abstract The large dual-channel wide-bodied aircraft has a long range and a high cruise Mach number. Therefore, its aerodynamic design requires a high level of wind tunnel test refinement. Based on the requirements of aerodynamic design for the future wide-bodied aircraft and the characteristics of high-speed wind tunnel tests, the error theory is introduced to analyze the factors affecting the accuracy of the test data. This study carries out a series of research on the improvement of refined aerodynamic test technology in an FL-26 wind tunnel, including design and optimization of the support system of wide-bodied aircraft, model attitude angle measurement,… More >

Xiaoyan Wang¹, Ahmed Mostafa Khalil^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2861-2871, 2023, DOI:10.32604/cmes.2023.026021

Abstract The aim of this paper is to introduce the concept of a generalized Pythagorean fuzzy soft set (GPFSS), which is a combination of the generalized fuzzy soft sets and Pythagorean fuzzy sets. Several of important operations of GPFSS including complement, restricted union, and extended intersection are discussed. The basic properties of GPFSS are presented. Further, an algorithm of GPFSSs is given to solve the fuzzy soft decision-making. Finally, a comparative analysis between the GPFSS approach and some existing approaches is provided to show their reliability over them. More >

Pushpendra Kumar^1,*, Vedat Suat Erturk², V. Govindaraj¹, Dumitru Baleanu^3,4,5

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2487-2506, 2023, DOI:10.32604/cmes.2023.026009

Abstract In this article, we introduce a nonlinear Caputo-type snakebite envenoming model with memory. The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractional-order sense. The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector (L1-PC) scheme with error estimation and stability analysis. The proof of the existence and positivity of the solution is given by using the fixed point theory. From the necessary simulations, we justify that the first-time implementation of the proposed method on an epidemic model shows that the scheme is fully suitable and time-efficient… More >

Jiayu Ren^1,*, Yoshihisa Fujita², Susumu Nakata²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2111-2125, 2023, DOI:10.32604/cmes.2023.025970

Abstract Implicit surface generation based on the interpolation of surface points is one of the well-known modeling methods in the area of computer graphics. Several methods for the implicit surface reconstruction from surface points have been proposed on the basis of radial basis functions, a weighted sum of local functions, splines, wavelets, and combinations of them. However, if the surface points contain errors or are sparsely distributed, irregular components, such as curvature-shaped redundant bulges and unexpectedly generated high-frequency components, are commonly seen. This paper presents a framework for restoring irregular components generated on and around surfaces. Users are assumed to specify… More >

Jiaji Wang^1,#, Shuwen Chen^1,2,3,#,*, Yu Cao^1,#, Huisheng Zhu¹, Dimas Lima^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2595-2616, 2023, DOI:10.32604/cmes.2023.025804

Abstract This paper presents a 6-layer customized convolutional neural network model (6L-CNN) to rapidly screen out patients with COVID-19 infection in chest CT images. This model can effectively detect whether the target CT image contains images of pneumonia lesions. In this method, 6L-CNN was trained as a binary classifier using the dataset containing CT images of the lung with and without pneumonia as a sample. The results show that the model improves the accuracy of screening out COVID-19 patients. Compared to other methods, the performance is better. In addition, the method can be extended to other similar clinical conditions. More >

Hao Zhu¹, Chao Sun^2,*, Qunfeng Zheng², Qinghai Zhao^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3265-3283, 2023, DOI:10.32604/cmes.2023.025777

Abstract Electric vehicle charging identification and positioning is critically important to achieving automatic charging. In terms of the problem of automatic charging for electric vehicles, a dual recognition and positioning method based on deep learning is proposed. The method is divided into two parts: global recognition and localization and local recognition and localization. In the specific implementation process, the collected pictures of electric vehicle charging attitude are classified and labeled. It is trained with the improved YOLOv4 network model and the corresponding detection model is obtained. The contour of the electric vehicle is extracted by the BiSeNet semantic segmentation algorithm. The… More > Graphic Abstract

Guoshuai Sun^1,2,3, Wanyi Zhang¹, Jiuying Dong^4,*, Shuping Wan², Jiao Feng⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2895-2934, 2023, DOI:10.32604/cmes.2023.025652

Abstract Public-private partnerships (PPPs) have been used by governments around the world to procure and construct infrastructural amenities. It relies on private sector expertise and funding to achieve this lofty objective. However, given the uncertainties of project management, transparency, accountability, and expropriation, this phenomenon has gained tremendous attention in recent years due to the important role it plays in curbing infrastructural deficits globally. Interestingly, the reasonable benefit distribution scheme in a PPP project is related to the behavior decision-making of the government and social capital, as well as the performance of the project. In this paper, the government and social capital… More >

Xuan Wang^1,2, Yuankun Shi², Van-Nam Hoang³, Zeng Meng^2,*, Kai Long^4,*, Yuesheng Wang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3173-3195, 2023, DOI:10.32604/cmes.2023.025501

Abstract This paper proposes an effective reliability design optimization method for fail-safe topology optimization (FSTO) considering uncertainty based on the moving morphable bars method to establish the ideal balance between cost and robustness, reliability and structural safety. To this end, a performance measure approach (PMA)-based double-loop optimization algorithm is developed to minimize the relative volume percentage while achieving the reliability criterion. To ensure the compliance value of the worst failure case can better approximate the quantified design requirement, a p-norm constraint approach with correction parameter is introduced. Finally, the significance of accounting for uncertainty in the fail-safe design is illustrated by… More > Graphic Abstract