Home / Journals / CMES / Vol.132, No.3, 2022
Table of Content
  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph

    Shuihua Wang1,*, Zheng Zhang2, Yuankai Huo3
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 707-709, 2022, DOI:10.32604/cmes.2022.023806
    (This article belongs to this Special Issue: Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph)
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Disease Recognition of Apple Leaf Using Lightweight Multi-Scale Network with ECANet

    Helong Yu, Xianhe Cheng, Ziqing Li, Qi Cai, Chunguang Bi*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 711-738, 2022, DOI:10.32604/cmes.2022.020263
    (This article belongs to this Special Issue: Swarm Intelligence and Applications in Combinatorial Optimization)
    Abstract To solve the problem of difficulty in identifying apple diseases in the natural environment and the low application rate of deep learning recognition networks, a lightweight ResNet (LW-ResNet) model for apple disease recognition is proposed. Based on the deep residual network (ResNet18), the multi-scale feature extraction layer is constructed by group convolution to realize the compression model and improve the extraction ability of different sizes of lesion features. By improving the identity mapping structure to reduce information loss. By introducing the efficient channel attention module (ECANet) to suppress noise from a complex background. The experimental results show that the average… More >

  • Open Access

    ARTICLE

    Effect Evaluation and Intelligent Prediction of Power Substation Project Considering New Energy

    Huiying Wu*, Meihua Zou, Ye Ke, Wenqi Ou, Yonghong Li, Minquan Ye
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 739-761, 2022, DOI:10.32604/cmes.2022.019714
    (This article belongs to this Special Issue: Hybrid Intelligent Methods for Forecasting in Resources and Energy Field)
    Abstract The evaluation of the implementation effect of the power substation project can find out the problems of the project more comprehensively, which has important practical significance for the further development of the power substation project. To ensure accuracy and real-time evaluation, this paper proposes a novel hybrid intelligent evaluation and prediction model based on improved TOPSIS and Long Short-Term Memory (LSTM) optimized by a Sperm Whale Algorithm (SWA). Firstly, under the background of considering the development of new energy, the influencing factors of power substation project implementation effect are analyzed from three aspects of technology, economy and society. Moreover, an… More >

  • Open Access

    ARTICLE

    Some Identities of the Degenerate Poly-Cauchy and Unipoly Cauchy Polynomials of the Second Kind

    Ghulam Muhiuddin1,*, Waseem A. Khan2, Deena Al-Kadi3
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 763-779, 2022, DOI:10.32604/cmes.2022.017272
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract In this paper, we introduce modied degenerate polyexponential Cauchy (or poly-Cauchy) polynomials and numbers of the second kind and investigate some identities of these polynomials. We derive recurrence relations and the relationship between special polynomials and numbers. Also, we introduce modied degenerate unipolyCauchy polynomials of the second kind and derive some fruitful properties of these polynomials. In addition, positive associated beautiful zeros and graphical representations are displayed with the help of Mathematica. More >

  • Open Access

    ARTICLE

    Partial Bell Polynomials, Falling and Rising Factorials, Stirling Numbers, and Combinatorial Identities

    Siqintuya Jin1, Bai-Ni Guo2,*, Feng Qi3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 781-799, 2022, DOI:10.32604/cmes.2022.019941
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract In the paper, the authors collect, discuss, and find out several connections, equivalences, closed-form formulas, and combinatorial identities concerning partial Bell polynomials, falling factorials, rising factorials, extended binomial coefficients, and the Stirling numbers of the first and second kinds. These results are new, interesting, important, useful, and applicable in combinatorial number theory. More >

  • Open Access

    ARTICLE

    gscaLCA in R: Fitting Fuzzy Clustering Analysis Incorporated with Generalized Structured Component Analysis

    Ji Hoon Ryoo1,*, Seohee Park2, Seongeun Kim3, Heungsun Hwang4
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 801-822, 2022, DOI:10.32604/cmes.2022.019708
    (This article belongs to this Special Issue: Algebra, Number Theory, Combinatorics and Their Applications: Mathematical Theory and Computational Modelling)
    Abstract Clustering analysis identifying unknown heterogenous subgroups of a population (or a sample) has become increasingly popular along with the popularity of machine learning techniques. Although there are many software packages running clustering analysis, there is a lack of packages conducting clustering analysis within a structural equation modeling framework. The package, gscaLCA which is implemented in the R statistical computing environment, was developed for conducting clustering analysis and has been extended to a latent variable modeling. More specifically, by applying both fuzzy clustering (FC) algorithm and generalized structured component analysis (GSCA), the package gscaLCA computes membership prevalence and item response probabilities… More >

  • Open Access

    ARTICLE

    Modeling and Prediction of Inter-System Bias for GPS/BDS-2/BDS-3 Combined Precision Point Positioning

    Zejie Wang1, Qianxin Wang1,*, Sanxi Li2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 823-843, 2022, DOI:10.32604/cmes.2022.020106
    (This article belongs to this Special Issue: Data Acquisition and Electromagnetic Interference Detection by Internet of Things)
    Abstract The combination of Precision Point Positioning (PPP) with Multi-Global Navigation Satellite System (MultiGNSS), called MGPPP, can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System (BDS). However, the Inter-System Bias (ISB) measurement of Multi-GNSS, including the time system offset, the coordinate system difference, and the inter-system hardware delay bias, must be considered for Multi-GNSS data fusion processing. The detected ISB can be well modeled and predicted by using a quadratic model (QM), an autoregressive integrated moving average model (ARIMA), as well as the sliding window strategy… More >

  • Open Access

    ARTICLE

    An Automated Detection Approach of Protective Equipment Donning for Medical Staff under COVID-19 Using Deep Learning

    Qiang Zhang1, Ziyu Pei1, Rong Guo1, Haojun Zhang2, Wanru Kong2, Jie Lu3, Xueyan Liu1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 845-863, 2022, DOI:10.32604/cmes.2022.019085
    (This article belongs to this Special Issue: Paradigms of Deep Learning, Big Data Analytics, Artificial Intelligence and Mathematical Statistics in Medical Applications for Combating Epidemics)
    Abstract Personal protective equipment (PPE) donning detection for medical staff is a key link of medical operation safety guarantee and is of great significance to combat COVID-19. However, the lack of dedicated datasets makes the scarce research on intelligence monitoring of workers’ PPE use in the field of healthcare. In this paper, we construct a dress codes dataset for medical staff under the epidemic. And based on this, we propose a PPE donning automatic detection approach using deep learning. With the participation of health care personnel, we organize 6 volunteers dressed in different combinations of PPE to simulate more dress situations… More >

  • Open Access

    ARTICLE

    On Soft Pre-Rough Approximation Space with Applications in Decision Making

    M. El Sayed1,*, Wadia Faid Hassan Al-shameri1, M. A. El Safty2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 865-879, 2022, DOI:10.32604/cmes.2022.020066
    (This article belongs to this Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)
    Abstract A soft, rough set model is a distinctive mathematical model that can be used to relate a variety of real-life data. In the present work, we introduce new concepts of rough set based on soft pre-lower and soft pre-upper approximation space. These concepts are soft pre-rough equality, soft pre-rough inclusion, soft pre-rough belonging, soft predefinability, soft pre-internal lower, and soft pre-external lower. We study the properties of these concepts. Finally, we use the soft pre-rough approximation to illustrate the importance of our method in decision-making for Chikungunya medical illnesses. In reality, the impact factors of Chikungunya’s medical infection were determined.… More >

  • Open Access

    ARTICLE

    Group Decision-Making Method with Incomplete Intuitionistic Fuzzy Preference Relations Based on a Generalized Multiplicative Consistent Concept

    Xiaoyun Lu1, Jiuying Dong2,3,*, Hecheng Li1, Shuping Wan4
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 881-907, 2022, DOI:10.32604/cmes.2022.020598
    (This article belongs to this Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)
    Abstract Based on the analyses of existing preference group decision-making (PGDM) methods with intuitionistic fuzzy preference relations (IFPRs), we present a new PGDM framework with incomplete IFPRs. A generalized multiplicative consistent for IFPRs is defined, and a mathematical programming model is constructed to supplement the missing values in incomplete IFPRs. Moreover, in this study, another mathematical programming model is constructed to improve the consistency level of unacceptably multiplicative consistent IFPRs. For group decisionmaking (GDM) with incomplete IFPRs, three reliable sources inuencing the weights of experts are identified. Subsequently, a method for determining the weights of experts is developed by simultaneously considering… More >

  • Open Access

    ARTICLE

    Visual Object Tracking via Cascaded RPN Fusion and Coordinate Attention

    Jianming Zhang1,2,*, Kai Wang1,2, Yaoqi He1,2, Lidan Kuang1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 909-927, 2022, DOI:10.32604/cmes.2022.020471
    (This article belongs to this Special Issue: Enabled and Human-centric Computational Intelligence Solutions for Visual Understanding and Application)
    Abstract Recently, Siamese-based trackers have achieved excellent performance in object tracking. However, the high speed and deformation of objects in the movement process make tracking difficult. Therefore, we have incorporated cascaded region-proposal-network (RPN) fusion and coordinate attention into Siamese trackers. The proposed network framework consists of three parts: a feature-extraction sub-network, coordinate attention block, and cascaded RPN block.We exploit the coordinate attention block, which can embed location information into channel attention, to establish long-term spatial location dependence while maintaining channel associations. Thus, the features of different layers are enhanced by the coordinate attention block. We then send these features separately into… More >

  • Open Access

    ARTICLE

    A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm

    Qidai Lin1, Ying Gong2,*, Yizhi Shi1, Changsen Feng2, Youbing Zhang2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 929-944, 2022, DOI:10.32604/cmes.2022.020752
    (This article belongs to this Special Issue: Artificial Intelligence in Renewable Energy and Storage Systems)
    Abstract The integrated energy systems, usually including electric energy, natural gas and thermal energy, play a pivotal role in the energy Internet project, which could improve the accommodation of renewable energy through multi-energy complementary ways. Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network, a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper. The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm, and thereby achieved a hierarchical and non-repeated sampling. Then, the improved RelieF… More >

  • Open Access

    ARTICLE

    The Improved Element-Free Galerkin Method for Anisotropic Steady-State Heat Conduction Problems

    Heng Cheng1, Zebin Xing1, Miaojuan Peng2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 945-964, 2022, DOI:10.32604/cmes.2022.020755
    (This article belongs to this Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)
    Abstract In this paper, we considered the improved element-free Galerkin (IEFG) method for solving 2D anisotropic steady-state heat conduction problems. The improved moving least-squares (IMLS) approximation is used to establish the trial function, and the penalty method is applied to enforce the boundary conditions, thus the final discretized equations of the IEFG method for anisotropic steady-state heat conduction problems can be obtained by combining with the corresponding Galerkin weak form. The influences of node distribution, weight functions, scale parameters and penalty factors on the computational accuracy of the IEFG method are analyzed respectively, and these numerical solutions show that less computational… More >

  • Open Access

    ARTICLE

    A Parallel Computing Schema Based on IGA

    Jinggang Deng1,2, Bingquan Zuo1,2,*, Huixin Luo1,2, Weikang Xie1,2, Jiashu Yang1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 965-990, 2022, DOI:10.32604/cmes.2022.020631
    (This article belongs to this Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)
    Abstract In this paper, a new computation scheme based on parallelization is proposed for Isogeometric analysis. The parallel computing is introduced to the whole progress of Isogeometric analysis. Firstly, with the help of the “tensorproduct” and “iso-parametric” feature, all the Gaussian integral points in particular element can be mapped to a global matrix using a transformation matrix that varies from element. Then the derivatives of Gauss integral points are computed in parallel, the results of which can be stored in a global matrix. And a middle layer is constructed to assemble the final stiffness matrices in parallel. The numerical example results… More >

  • Open Access

    ARTICLE

    Numerical Simulation Research on Static Aeroelastic Effect of the Transonic Aileron of a High Aspect Ratio Aircraf

    Hongtao Guo, Changrong Zhang, Binbin Lv, Li Yu*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 991-1010, 2022, DOI:10.32604/cmes.2022.020638
    (This article belongs to this Special Issue: Vibration Control and Utilization)
    Abstract The static aeroelastic effect of aircraft ailerons with high aspect ratio at transonic velocity is investigated in this paper by the CFD/CSD fluid-structure coupling numerical simulation. The influences of wing static aeroelasticity and the ‘scissor opening’ gap width between aileron control surface and the main wing surface on aileron efficiency are mainly explored. The main purpose of this paper is to provide technical support for the wind tunnel experimental model of aileron static aeroelasticity. The results indicate that the flight dynamic pressure has a great influence on the static aeroelastic effect of ailerons, and the greater the dynamic pressure, the… More >

  • Open Access

    ARTICLE

    Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features

    Wen Yee Wong1, Ayman Khallel Ibrahim Al-Ani1, Khairunnisa Hasikin1,*, Anis Salwa Mohd Khairuddin2, Sarah Abdul Razak3, Hanee Farzana Hizaddin4, Mohd Istajib Mokhtar5, Muhammad Mokhzaini Azizan6
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 1011-1038, 2022, DOI:10.32604/cmes.2022.019244
    (This article belongs to this Special Issue: Computer Modeling for Smart Cities Applications)
    Abstract Water quality analysis is essential to understand the ecological status of aquatic life. Conventional water quality index (WQI) assessment methods are limited to features such as water acidic or basicity (pH), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N), and suspended solids (SS). These features are often insufficient to represent the water quality of a heavy metal–polluted river. Therefore, this paper aims to explore and analyze novel input features in order to formulate an improved WQI. In this work, prospective insights on the feasibility of alternative water quality input variables as new discriminant features… More >

  • Open Access

    ARTICLE

    B-PesNet: Smoothly Propagating Semantics for Robust and Reliable Multi-Scale Object Detection for Secure Systems

    Yunbo Rao1,2, Hongyu Mu1, Zeyu Yang1, Weibin Zheng1, Faxin Wang1, Jiansu Pu1, Shaoning Zeng2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 1039-1054, 2022, DOI:10.32604/cmes.2022.020331
    (This article belongs to this Special Issue: Internet of Things in Healthcare and Health: Security and Privacy)
    Abstract Multi-scale object detection is a research hotspot, and it has critical applications in many secure systems. Although the object detection algorithms have constantly been progressing recently, how to perform highly accurate and reliable multi-class object detection is still a challenging task due to the influence of many factors, such as the deformation and occlusion of the object in the actual scene. The more interference factors, the more complicated the semantic information, so we need a deeper network to extract deep information. However, deep neural networks often suffer from network degradation. To prevent the occurrence of degradation on deep neural networks,… More >

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