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Aiming to reduce noise pollution level, this work proposes a novel method of rationalizing the layout design of sound-absorption materials adhered to structural surfaces. The isogeometric boundary element method is applied to perform acoustic analysis directly from the Computer-Aided Design models which are built by Catmull-Clark subdivision surfaces. Based on the acoustic simulation and sensitivity analysis results, we employ the density-based topology optimization method to optimize the distribution of sound-absorption materials. A car model is used in the numerical example to demonstrate the effectiveness of the present method.
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  • Open Access

    ARTICLE

    Noise Pollution Reduction through a Novel Optimization Procedure in Passive Control Methods

    Haojie Lian1,2, Leilei Chen2,3, Xiao Lin4, Wenchang Zhao5,*, Stephane P. A. Bordas6,7, Mingdong Zhou8,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 1-18, 2022, DOI:10.32604/cmes.2022.019705
    (This article belongs to this Special Issue: Recent Advance of the Isogeometric Boundary Element Method and its Applications)
    Abstract This paper proposes a novel optimization framework in passive control techniques to reduce noise pollution. The geometries of the structures are represented by Catmull-Clark subdivision surfaces, which are able to build gap-free Computer-Aided Design models and meanwhile tackle the extraordinary points that are commonly encountered in geometric modelling. The acoustic fields are simulated using the isogeometric boundary element method, and a density-based topology optimization is conducted to optimize distribution of sound-absorbing materials adhered to structural surfaces. The approach enables one to perform acoustic optimization from Computer-Aided Design models directly without needing meshing and volume parameterization, thereby avoiding the geometric errors… More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on “Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce”

    Honghao Gao1,2, Jung Yoon Kim2,*, Yuyu Yin3
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 19-21, 2022, DOI:10.32604/cmes.2022.019665
    (This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
    Abstract This article has no abstract. More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Intelligent Models for Security and Resilience in Cyber Physical Systems

    Qi Liu1,*, Xiaodong Liu2, Radu Grosu3, Ching-Nung Yang4
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 23-26, 2022, DOI:10.32604/cmes.2022.020646
    (This article belongs to this Special Issue: Intelligent Models for Security and Resilience in Cyber Physical Systems)
    Abstract This article has no abstract. More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Novel Methods of Topology Optimization and Engineering Applications

    Kai Long1,*, Xiaodong Huang2, Zunyi Duan3, Xuan Wang4, Quhao Li5
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 27-29, 2022, DOI:10.32604/cmes.2022.020822
    (This article belongs to this Special Issue: Novel Methods of Topology Optimization and Engineering Applications)
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Study of Effect of Boundary Conditions on Patient-Specific Aortic Hemodynamics

    Qingzhuo Chi1, Huimin Chen1, Shiqi Yang1, Lizhong Mu1,*, Changjin Ji2, Ying He1, Yong Luan3
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 31-47, 2022, DOI:10.32604/cmes.2022.018286
    (This article belongs to this Special Issue: Recent Advances in Biomechanics and Biomimetic Mechanics)
    Abstract Cardiovascular computational fluid dynamics (CFD) based on patient-specific modeling is increasingly used to predict changes in hemodynamic parameters before or after surgery/interventional treatment for aortic dissection (AD). This study investigated the effects of flow boundary conditions (BCs) on patient-specific aortic hemodynamics. We compared the changes in hemodynamic parameters in a type A dissection model and normal aortic model under different BCs: inflow from the auxiliary and truncated structures at aortic valve, pressure control and Windkessel model outflow conditions, and steady and unsteady inflow conditions. The auxiliary entrance remarkably enhanced the physiological authenticity of numerical simulations of flow in the ascending… More >

  • Open Access

    ARTICLE

    Comparative Study on Deformation Prediction Models of Wuqiangxi Concrete Gravity Dam Based on Monitoring Data

    Songlin Yang1,2, Xingjin Han1,2, Chufeng Kuang1,2, Weihua Fang3, Jianfei Zhang4, Tiantang Yu4,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 49-72, 2022, DOI:10.32604/cmes.2022.018325
    (This article belongs to this Special Issue: Hybrid Intelligent Methods for Forecasting in Resources and Energy Field)
    Abstract The deformation prediction models of Wuqiangxi concrete gravity dam are developed, including two statistical models and a deep learning model. In the statistical models, the reliable monitoring data are firstly determined with Lahitte criterion; then, the stepwise regression and partial least squares regression models for deformation prediction of concrete gravity dam are constructed in terms of the reliable monitoring data, and the factors of water pressure, temperature and time effect are considered in the models; finally, according to the monitoring data from 2006 to 2020 of five typical measuring points including J23 (on dam section ), J33 (on dam section… More >

  • Open Access

    ARTICLE

    Mu-Net: Multi-Path Upsampling Convolution Network for Medical Image Segmentation

    Jia Chen1, Zhiqiang He1, Dayong Zhu1, Bei Hui1,*, Rita Yi Man Li2, Xiao-Guang Yue3,4,5
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 73-95, 2022, DOI:10.32604/cmes.2022.018565
    Abstract Medical image segmentation plays an important role in clinical diagnosis, quantitative analysis, and treatment process. Since 2015, U-Net-based approaches have been widely used for medical image segmentation. The purpose of the U-Net expansive path is to map low-resolution encoder feature maps to full input resolution feature maps. However, the consecutive deconvolution and convolutional operations in the expansive path lead to the loss of some high-level information. More high-level information can make the segmentation more accurate. In this paper, we propose MU-Net, a novel, multi-path upsampling convolution network to retain more high-level information. The MU-Net mainly consists of three parts: contracting… More >

  • Open Access

    ARTICLE

    An Approach for Quantifying the Influence of Seepage Dissolution on Seismic Performance of Concrete Dams

    Shaowei Wang1,2, Cong Xu1, Hao Gu3,*, Pinghua Zhu1, Hui Liu1, Bo Xu4
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 97-117, 2022, DOI:10.32604/cmes.2022.018721
    Abstract Many concrete dams seriously suffer from long-term seepage dissolution, and the induced mechanical property deterioration of concrete may significantly affect the structural performance, especially the seismic safety. An approach is presented in this paper to quantify the influence of seepage dissolution on seismic performance of concrete dams. To connect laboratory test with numerical simulation, dissolution tests are conducted for concrete specimens and using the cumulative relative leached calcium as an aging index, a deterioration model is established to predict the mechanical property of leached concrete in the first step. A coupled seepage-calcium dissolution-migration model containing two calculation modes is proposed… More >

  • Open Access

    ARTICLE

    Influence of Soil Heterogeneity on the Behavior of Frozen Soil Slope under Freeze-Thaw Cycles

    Kang Liu, Yanqiao Wang*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 119-135, 2022, DOI:10.32604/cmes.2022.018134
    Abstract Soil slope stability in seasonally frozen regions is a challenging problem for geotechnical engineers. The freeze-thaw process of soil slope caused by the temperature fluctuation increases the difficulty in predicting the slope stability because the soil property is influenced by the freeze-thaw cycle. In addition, the frozen soil, which has ice crystal, ice lens and experienced freeze-thaw process, could present stronger heterogeneity. Previous research has not investigated the combined effect of soil heterogeneity and freeze-thaw cycle. This paper studies the influence of soil heterogeneity on the stability of frozen soil slope under freeze-thaw cycles. The local average subdivision (LAS) is… More >

  • Open Access

    ARTICLE

    Remote Sensing Image Retrieval Based on 3D-Local Ternary Pattern (LTP) Features and Non-subsampled Shearlet Transform (NSST) Domain Statistical Features

    Hilly Gohain Baruah*, Vijay Kumar Nath, Deepika Hazarika
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 137-164, 2022, DOI:10.32604/cmes.2022.018339
    Abstract With the increasing popularity of high-resolution remote sensing images, the remote sensing image retrieval (RSIR) has always been a topic of major issue. A combined, global non-subsampled shearlet transform (NSST)-domain statistical features (NSSTds) and local three dimensional local ternary pattern (3D-LTP) features, is proposed for high-resolution remote sensing images. We model the NSST image coefficients of detail subbands using 2-state laplacian mixture (LM) distribution and its three parameters are estimated using Expectation-Maximization (EM) algorithm. We also calculate the statistical parameters such as subband kurtosis and skewness from detail subbands along with mean and standard deviation calculated from approximation subband, and… More >

  • Open Access

    ARTICLE

    An Experimental and Numerical Study on the Ballistic Performance of Multi-Layered Moderately-Thick Metallic Targets against 12.7-mm Projectiles

    Kailei Wang, Mingjing Li*, Peng Yan, Leiting Dong*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 165-197, 2022, DOI:10.32604/cmes.2022.019188
    Abstract The main goal of this work is to study the ballistic performance of multi-layered moderately-thick metallic targets. Several target configurations have been considered in this work, with various types of interlayer connection (spaced, contacted and adhesive) and the number of layers (four and eight), and the influence of target configurations on ballistic performance has been studied experimentally and numerically. In the experiments, the targets were impacted by 12.7-mm projectiles at a velocity around 820 m/s. The experimental results show that, with similar total thickness, the contacted and adhesive targets exhibit better ballistic performance than the monolithic targets, and the four-layered targets… More >

  • Open Access

    ARTICLE

    Seismic Performance of Assembled Shear Wall with Defective Sleeve Connection

    Hua Yan1,2,3, Bo Song1,3,*, Dongsheng Xu2, Guodong Zhang2
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 199-217, 2022, DOI:10.32604/cmes.2022.016312
    (This article belongs to this Special Issue: Soft Computing Techniques in Materials Science and Engineering)
    Abstract In this paper, three kinds of shear walls with full sleeve grouting, fully defective sleeve and partially defective are designed for finite element analysis to analyze the influence of defects on the seismic performance of shear walls. The research shows that at the beginning of loading (5 s), the three models begin to appear compressive damage at the bottom of the wall in all three models. The damage of the defect-free model develops rapidly, and the damage of the fully defective model is basically the same as that of the partially defective model. With the gradual increase of displacement control (15 s),… More >

  • Open Access

    ARTICLE

    Game Outlier Behavior Detection System Based on Dynamic Time Warp Algorithm

    Shinjin Kang1, Soo Kyun Kim2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 219-237, 2022, DOI:10.32604/cmes.2022.018413
    (This article belongs to this Special Issue: HPC with Artificial Intelligence based Deep Video Data Analytics: Models, Applications and Approaches)
    Abstract This paper proposes a methodology for using multi-modal data in gameplay to detect outlier behavior. The proposed methodology collects, synchronizes, and quantifies time-series data from webcams, mouses, and keyboards. Facial expressions are varied on a one-dimensional pleasure axis, and changes in expression in the mouth and eye areas are detected separately. Furthermore, the keyboard and mouse input frequencies are tracked to determine the interaction intensity of users. Then, we apply a dynamic time warp algorithm to detect outlier behavior. The detected outlier behavior graph patterns were the play patterns that the game designer did not intend or play patterns that… More >

  • Open Access

    ARTICLE

    A Novel Feature Aggregation Approach for Image Retrieval Using Local and Global Features

    Yuhua Li1, Zhiqiang He1,2, Junxia Ma1,*, Zhifeng Zhang1,*, Wangwei Zhang1, Prasenjit Chatterjee3, Dragan Pamucar4
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 239-262, 2022, DOI:10.32604/cmes.2022.016287
    (This article belongs to this Special Issue: Intelligent Computing for Engineering Applications)
    Abstract The current deep convolution features based on retrieval methods cannot fully use the characteristics of the salient image regions. Also, they cannot effectively suppress the background noises, so it is a challenging task to retrieve objects in cluttered scenarios. To solve the problem, we propose a new image retrieval method that employs a novel feature aggregation approach with an attention mechanism and utilizes a combination of local and global features. The method first extracts global and local features of the input image and then selects keypoints from local features by using the attention mechanism. After that, the feature aggregation mechanism… More >

  • Open Access

    ARTICLE

    Complete Monotonicity of Functions Related to Trigamma and Tetragamma Functions

    Mona Anis1, Hanan Almuashi2, Mansour Mahmoud3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 263-275, 2022, DOI:10.32604/cmes.2022.016927
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract In this paper, we study the completely monotonic property of two functions involving the function △(x) = and deduce the double inequality , x > 0
    which improve some recent results, where ψ(x) is the logarithmic derivative of the Gamma function. Also, we deduce the completely monotonic degree of a function involving ψ'(x). More >

  • Open Access

    ARTICLE

    k-Order Fibonacci Polynomials on AES-Like Cryptology

    Mustafa Asci, Suleyman Aydinyuz*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 277-293, 2022, DOI:10.32604/cmes.2022.017898
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract The Advanced Encryption Standard (AES) is the most widely used symmetric cipher today. AES has an important place in cryptology. Finite field, also known as Galois Fields, are cornerstones for understanding any cryptography. This encryption method on AES is a method that uses polynomials on Galois fields. In this paper, we generalize the AES-like cryptology on 2 × 2 matrices. We redefine the elements of k-order Fibonacci polynomials sequences using a certain irreducible polynomial in our cryptology algorithm. So, this cryptology algorithm is called AES-like cryptology on the k-order Fibonacci polynomial matrix. More >

  • Open Access

    ARTICLE

    On Degenerate Array Type Polynomials

    Lan Wu1, Xue-Yan Chen1, Muhammet Cihat Dağli2, Feng Qi3,4,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 295-305, 2022, DOI:10.32604/cmes.2022.018778
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract In the paper, with the help of the Faá di Bruno formula and an identity of the Bell polynomials of the second kind, the authors define degenerate λ-array type polynomials, establish two explicit formulas, and present several recurrence relations of degenerate λ-array type polynomials and numbers. More >

  • Open Access

    ARTICLE

    A Lightweight and Robust User Authentication Protocol with User Anonymity for IoT-Based Healthcare

    Chien-Ming Chen1,*, Shuangshuang Liu1, Shehzad Ashraf Chaudhry2, Yeh-Cheng Chen3, Muhammad Asghar khan4
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 307-329, 2022, DOI:10.32604/cmes.2022.018749
    (This article belongs to this Special Issue: Internet of Things in Healthcare and Health: Security and Privacy)
    Abstract With the rise of the Internet of Things (IoT), the word “intelligent medical care” has increasingly become a major vision. Intelligent medicine adopts the most advanced IoT technology to realize the interaction between patients and people, medical institutions, and medical equipment. However, with the openness of network transmission, the security and privacy of information transmission have become a major problem. Recently, Masud et al. proposed a lightweight anonymous user authentication protocol for IoT medical treatment, claiming that their method can resist various attacks. However, through analysis of the protocol, we observed that their protocol cannot effectively resist privileged internal attacks,… More >

  • Open Access

    ARTICLE

    Improving Date Fruit Classification Using CycleGAN-Generated Dataset

    Dina M. Ibrahim1,2,*, Nada M. Elshennawy2
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 331-348, 2022, DOI:10.32604/cmes.2022.016419
    (This article belongs to this Special Issue: New Trends in Statistical Computing and Data Science)
    Abstract Dates are an important part of human nutrition. Dates are high in essential nutrients and provide a number of health benefits. Date fruits are also known to protect against a number of diseases, including cancer and heart disease. Date fruits have several sizes, colors, tastes, and values. There are a lot of challenges facing the date producers. One of the most significant challenges is the classification and sorting of dates. But there is no public dataset for date fruits, which is a major limitation in order to improve the performance of convolutional neural networks (CNN) models and avoid the overfitting… More >

  • Open Access

    ARTICLE

    Skew t Distribution-Based Nonlinear Filter with Asymmetric Measurement Noise Using Variational Bayesian Inference

    Chen Xu1, Yawen Mao2, Hongtian Chen3,*, Hongfeng Tao1, Fei Liu1
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 349-364, 2022, DOI:10.32604/cmes.2021.019027
    (This article belongs to this Special Issue: Advances on Modeling and State Estimation for Industrial Processes)
    Abstract This paper is focused on the state estimation problem for nonlinear systems with unknown statistics of measurement noise. Based on the cubature Kalman filter, we propose a new nonlinear filtering algorithm that employs a skew t distribution to characterize the asymmetry of the measurement noise. The system states and the statistics of skew t noise distribution, including the shape matrix, the scale matrix, and the degree of freedom (DOF) are estimated jointly by employing variational Bayesian (VB) inference. The proposed method is validated in a target tracking example. Results of the simulation indicate that the proposed nonlinear filter can perform… More >

  • Open Access

    ARTICLE

    Experimental and Numerical Study on Mechanical Properties of Z-pins Reinforced Composites Adhesively Bonded Single-Lap Joints

    Yinhuan Yang1,*, Manfeng Gong1, Xiaoqun Xia1, Linzhi Wu2,3
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 365-378, 2022, DOI:10.32604/cmes.2022.018535
    (This article belongs to this Special Issue: Mechanics of Composite Materials and Structures)
    Abstract The mechanical properties of Z-pins reinforced composites adhesively bonded single-lap joints (SLJs) under un-directional tension loading are investigated by experimental and numerical methods. Three kinds of joint configurations, including SLJs with three/two rows of Z-pins and “I” array of Z-pins, are investigated by tension test. The failure modes and mechanism of reinforced joints with different Z-pins numbers and alignment are analyzed, and the comparison is performed for the failure strengths of no Z-pins and Z-pins reinforced joints. According to experimental results, failure modes of three kinds of joints are all mixed failure. It turns out that the Z-pins are pulled… More >

  • Open Access

    ARTICLE

    A Flux Based Approximation to Simulate Coupled Hydromechanical Problems for Mines with Heterogeneous Rock Types Using the Material Point Method

    Gysbert Basson1,*, Andrew P. Bassom2, Brian Salmon3
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 379-409, 2022, DOI:10.32604/cmes.2022.019112
    (This article belongs to this Special Issue: Modeling of Heterogeneous Materials)
    Abstract Advances in numerical simulation techniques play an important role in helping mining engineers understand those parts of the rock mass that cannot be readily observed. The Material Point Method (MPM) is an example of such a tool that is gaining popularity for studying geotechnical problems. In recent years, the original formulation of MPM has been extended to not only account for simulating the mechanical behaviour of rock under different loading conditions, but also to describe the coupled interaction of pore water and solid phases in materials. These methods assume that the permeability of mediums is homogeneous, and we show that… More >

  • Open Access

    ARTICLE

    A New Approach to Vague Soft Bi-Topological Spaces

    Arif Mehmood1, Saleem Abdullah2, Choonkil Park3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 411-428, 2022, DOI:10.32604/cmes.2022.016967
    (This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
    Abstract Fuzzy soft topology considers only membership value. It has nothing to do with the non-membership value. So an extension was needed in this direction. Vague soft topology addresses both membership and non-membership values simultaneously. Sometimes vague soft topology (single structure) is unable to address some complex structures. So an extension to vague soft bi-topology (double structure) was needed in this direction. To make this situation more meaningful, a new concept of vague soft bi-topological space is introduced and its structural characteristics are attempted with a new definition. In this article, new concept of vague soft bi-topological space (VSBTS) is initiated… More >

  • Open Access

    ARTICLE

    LF-CNN: Deep Learning-Guided Small Sample Target Detection for Remote Sensing Classification

    Chengfan Li1,2, Lan Liu3,*, Junjuan Zhao1, Xuefeng Liu4
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 429-444, 2022, DOI:10.32604/cmes.2022.019202
    (This article belongs to this Special Issue: Machine Learning-Guided Intelligent Modeling with Its Industrial Applications)
    Abstract Target detection of small samples with a complex background is always difficult in the classification of remote sensing images. We propose a new small sample target detection method combining local features and a convolutional neural network (LF-CNN) with the aim of detecting small numbers of unevenly distributed ground object targets in remote sensing images. The k-nearest neighbor method is used to construct the local neighborhood of each point and the local neighborhoods of the features are extracted one by one from the convolution layer. All the local features are aggregated by maximum pooling to obtain global feature representation. The classification… More >

  • Open Access

    ARTICLE

    Machine Learning Enhanced Boundary Element Method: Prediction of Gaussian Quadrature Points

    Ruhui Cheng1, Xiaomeng Yin2, Leilei Chen1,3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 445-464, 2022, DOI:10.32604/cmes.2022.018519
    (This article belongs to this Special Issue: Machine Learning-Guided Intelligent Modeling with Its Industrial Applications)
    Abstract This paper applies a machine learning technique to find a general and efficient numerical integration scheme for boundary element methods. A model based on the neural network multi-classification algorithm is constructed to find the minimum number of Gaussian quadrature points satisfying the given accuracy. The constructed model is trained by using a large amount of data calculated in the traditional boundary element method and the optimal network architecture is selected. The two-dimensional potential problem of a circular structure is tested and analyzed based on the determined model, and the accuracy of the model is about 90%. Finally, by incorporating the… More >

  • Open Access

    ARTICLE

    Visualization Detection of Solid–Liquid Two-Phase Flow in Filling Pipeline by Electrical Capacitance Tomography Technology

    Ningbo Jing1, Mingqiao Li1, Lang Liu2,*, Yutong Shen1, Peijiao Yang1, Xuebin Qin1
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 465-476, 2022, DOI:10.32604/cmes.2022.018965
    (This article belongs to this Special Issue: Mechanical Reliability of Advanced Materials and Structures for Harsh Applications)
    Abstract During mine filling, the caking in the pipeline and the waste rock in the filling slurry may cause serious safety accidents such as pipe blocking or explosion. Therefore, the visualization of the inner mine filling of the solid–liquid two-phase flow in the pipeline is important. This paper proposes a method based on capacitance tomography for the visualization of the solid–liquid distribution on the section of a filling pipe. A feedback network is used for electrical capacitance tomography reconstruction. This reconstruction method uses radial basis function neural network fitting to determine the relationship between the capacitance vector and medium distribution error.… More >

  • Open Access

    ARTICLE

    Research on Normal Pythagorean Neutrosophic Set Choquet Integral Operator and Its Application

    Changxing Fan1, Jihong Chen2,*, Keli Hu1,3, En Fan1, Xiuqing Wang1
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 477-491, 2022, DOI:10.32604/cmes.2022.019159
    (This article belongs to this Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)
    Abstract We first propose the normal Pythagorean neutrosophic set (NPNS) in this paper, which synthesizes the distribution of the incompleteness, indeterminacy, and inconsistency of the Pythagorean neutrosophic set (PNS) and normal fuzzy number. We also define some properties of NPNS. For solving the decision-making problem of the non-strictly independent and interacting attributes, two kinds of NPNS Choquet integral operators are proposed. First, the NPNS Choquet integral average (NPNSCIA) operator and the NPNS Choquet integral geometric (NPNSCIG) operator are proposed. Then, their calculating formulas are derived, their properties are discussed, and an approach for solving the interacting multi-attribute decision making based on… More >

  • Open Access

    ARTICLE

    N-SVRG: Stochastic Variance Reduction Gradient with Noise Reduction Ability for Small Batch Samples

    Haijie Pan, Lirong Zheng*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 493-512, 2022, DOI:10.32604/cmes.2022.019069
    (This article belongs to this Special Issue: Enabled and Human-centric Computational Intelligence Solutions for Visual Understanding and Application)
    Abstract The machine learning model converges slowly and has unstable training since large variance by random using a sample estimate gradient in SGD. To this end, we propose a noise reduction method for Stochastic Variance Reduction gradient (SVRG), called N-SVRG, which uses small batches samples instead of all samples for the average gradient calculation, while performing an incremental update of the average gradient. In each round of iteration, a small batch of samples is randomly selected for the average gradient calculation, while the average gradient is updated by rounding of the past model gradients during internal iterations. By suitably reducing the… More >

  • Open Access

    ARTICLE

    Spectral Matching Classification Method of Multi-State Similar Pigments Based on Feature Differences

    Meng Da1, Huiqin Wang1,*, Ke Wang1, Zhan Wang2
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 513-527, 2022, DOI:10.32604/cmes.2022.019040
    (This article belongs to this Special Issue: Computer Modeling for Smart Cities Applications)
    Abstract The properties of the same pigments in murals are affected by different concentrations and particle diameters, which cause the shape of the spectral reflectance data curve to vary, thus influencing the outcome of matching calculations. This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences. Fast principal component analysis (FPCA) was used to calculate the eigenvalue variance of pigment spectral reflectance, then applied to the original reflectance values for parameter characterization. We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral curve. Secondly, the… More >

  • Open Access

    ARTICLE

    Strategy for Creating AR Applications in Static and Dynamic Environments Using SLAM- and Marker Detector-Based Tracking

    Chanho Park1,2, Hyunwoo Cho1, Sangheon Park1, Sung-Uk Jung1, Suwon Lee3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 529-549, 2022, DOI:10.32604/cmes.2022.019214
    (This article belongs to this Special Issue: Algebra, Number Theory, Combinatorics and Their Applications: Mathematical Theory and Computational Modelling)
    Abstract Recently, simultaneous localization and mapping (SLAM) has received considerable attention in augmented reality (AR) libraries and applications. Although the assumption of scene rigidity is common in most visual SLAMs, this assumption limits the possibilities of AR applications in various real-world environments. In this paper, we propose a new tracking system that integrates SLAM with a marker detection module for real-time AR applications in static and dynamic environments. Because the proposed system assumes that the marker is movable, SLAM performs tracking and mapping of the static scene except for the marker, and the marker detector estimates the 3-dimensional pose of the… More >

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