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  • Open Access

    ARTICLE

    SepFE: Separable Fusion Enhanced Network for Retinal Vessel Segmentation

    Yun Wu1, Ge Jiao1,2,*, 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 >

  • Open Access

    ARTICLE

    AWSD: An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

    Xiang Su1, Nan Li1,*, 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

    AWSD: An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

  • Open Access

    ARTICLE

    Refined Aerodynamic Test of Wide-Bodied Aircraft and Its Application

    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 >

  • Open Access

    ARTICLE

    A New Kind of Generalized Pythagorean Fuzzy Soft Set and Its Application in Decision-Making

    Xiaoyan Wang1, Ahmed Mostafa Khalil2,*

    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 >

  • Open Access

    ARTICLE

    A Study on the Nonlinear Caputo-Type Snakebite Envenoming Model with Memory

    Pushpendra Kumar1,*, Vedat Suat Erturk2, V. Govindaraj1, Dumitru Baleanu3,4,5

    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 >

  • Open Access

    ARTICLE

    Interactive Restoration of Three-Dimensional Implicit Surface with Irregular Parts

    Jiayu Ren1,*, 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 >

  • Open Access

    ARTICLE

    COVID-19 Detection Based on 6-Layered Explainable Customized Convolutional Neural Network

    Jiaji Wang1,#, Shuwen Chen1,2,3,#,*, Yu Cao1,#, Huisheng Zhu1, Dimas Lima4,*

    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 >

  • Open Access

    ARTICLE

    Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

    Hao Zhu1, Chao Sun2,*, Qunfeng Zheng2, Qinghai Zhao1,3,*

    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

    Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

  • Open Access

    ARTICLE

    Behavioral Decision-Making of Key Stakeholders in Public-Private Partnerships: A Hybrid Method and Benefit Distribution Study

    Guoshuai Sun1,2,3, Wanyi Zhang1, Jiuying Dong4,*, 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 >

  • Open Access

    ARTICLE

    Reliability-Based Topology Optimization of Fail-Safe Structures Using Moving Morphable Bars

    Xuan Wang1,2, Yuankun Shi2, Van-Nam Hoang3, Zeng Meng2,*, Kai Long4,*, 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

    Reliability-Based Topology Optimization of Fail-Safe Structures Using Moving Morphable Bars

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