Home / Journals / CMES / Vol.129, No.1, 2021
Table of Content
  • Open Access

    ARTICLE

    Data-Driven Determinant-Based Greedy Under/Oversampling Vector Sensor Placement

    Yuji Saito*, Keigo Yamada, Naoki Kanda, Kumi Nakai, Takayuki Nagata, Taku Nonomura, Keisuke Asai
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 1-30, 2021, DOI:10.32604/cmes.2021.016603
    Abstract A vector-measurement-sensor-selection problem in the undersampled and oversampled cases is considered by extending the previous novel approaches: a greedy method based on D-optimality and a noise-robust greedy method in this paper. Extensions of the vector-measurement-sensor selection of the greedy algorithms are proposed and applied to randomly generated systems and practical datasets of flowfields around the airfoil and global climates to reconstruct the full state given by the vector-sensor measurement. More >

  • Open Access

    ARTICLE

    Predicting Genotype Information Related to COVID-19 for Molecular Mechanism Based on Computational Methods

    Lejun Gong1,2,*, Xingxing Zhang1, Li Zhang3, Zhihong Gao4
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 31-45, 2021, DOI:10.32604/cmes.2021.016622
    (This article belongs to this Special Issue: Computer Methods in Bio-mechanics and Biomedical Engineering)
    Abstract Novel coronavirus disease 2019 (COVID-19) is an ongoing health emergency. Several studies are related to COVID-19. However, its molecular mechanism remains unclear. The rapid publication of COVID-19 provides a new way to elucidate its mechanism through computational methods. This paper proposes a prediction method for mining genotype information related to COVID-19 from the perspective of molecular mechanisms based on machine learning. The method obtains seed genes based on prior knowledge. Candidate genes are mined from biomedical literature. The candidate genes are scored by machine learning based on the similarities measured between the seed and candidate genes. Furthermore, the results of… More >

  • Open Access

    ARTICLE

    A Novel Named Entity Recognition Scheme for Steel E-Commerce Platforms Using a Lite BERT

    Maojian Chen1,2,3, Xiong Luo1,2,3,*, Hailun Shen4, Ziyang Huang4, Qiaojuan Peng1,2,3
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 47-63, 2021, DOI:10.32604/cmes.2021.017491
    (This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
    Abstract In the era of big data, E-commerce plays an increasingly important role, and steel E-commerce certainly occupies a positive position. However, it is very difficult to choose satisfactory steel raw materials from diverse steel commodities online on steel E-commerce platforms in the purchase of staffs. In order to improve the efficiency of purchasers searching for commodities on the steel E-commerce platforms, we propose a novel deep learning-based loss function for named entity recognition (NER). Considering the impacts of small sample and imbalanced data, in our NER scheme, the focal loss, the label smoothing, and the cross entropy are incorporated into… More >

  • Open Access

    REVIEW

    Deep Learning Applications for COVID-19 Analysis: A State-of-the-Art Survey

    Wenqian Li1, Xing Deng1,2,*, Haijian Shao1, Xia Wang3
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 65-98, 2021, DOI:10.32604/cmes.2021.016981
    Abstract The COVID-19 has resulted in catastrophic situation and the deaths of millions of people all over the world. In this paper, the predictions of epidemiological propagation models, such as SIR and SEIR, are introduced to analyze the earlier COVID-19 propagation. The deep learning methods combined with transfer learning are familiar with classification-detection approaches based on chest X-ray and CT images are presented in detail. Besides, deep learning approaches have also been applied to lung ultrasound (LUS), which has been shown to be more sensitive than chest X-ray and CT images in detecting COVID-19. In the absence of a vaccine, the… More >

    Graphic Abstract

    Deep Learning Applications for COVID-19 Analysis: A <i>State-of-the-Art</i> Survey

  • Open Access

    ARTICLE

    Simulating the Effect of Temperature Gradient on Grain Growth of 6061-T6 Aluminum Alloy via Monte Carlo Potts Algorithm

    Qi Wu*, Jianan Li, Lianchun Long, Linao Liu
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 99-116, 2021, DOI:10.32604/cmes.2021.015669
    Abstract During heat treatment or mechanical processing, most polycrystalline materials experience grain growth, which significantly affects their mechanical properties. Microstructure simulation on a mesoscopic scale is an important way of studying grain growth. A key research focus of this type of method has long been how to efficiently and accurately simulate the grain growth caused by a non-uniform temperature field with temperature gradients. In this work, we propose an improved 3D Monte Carlo Potts (MCP) method to quantitatively study the relationship between non-uniform temperature fields and final grain morphologies. Properties of the aluminum alloy AA6061-T6 are used to establish a trial… More >

  • Open Access

    ARTICLE

    Medical Waste Treatment Station Selection Based on Linguistic q-Rung Orthopair Fuzzy Numbers

    Jie Ling1,2, Xinmei Li1,2, Mingwei Lin1,2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 117-148, 2021, DOI:10.32604/cmes.2021.016356
    Abstract During the COVID-19 outbreak, the use of single-use medical supplies increased significantly. It is essential to select suitable sites for establishing medical waste treatment stations. It is a big challenge to solve the medical waste treatment station selection problem due to some conflicting factors. This paper proposes a multi-attribute decision-making (MADM) method based on the partitioned Maclaurin symmetric mean (PMSM) operator. For the medical waste treatment station selection problem, the factors or attributes (these two terms can be interchanged.) in the same clusters are closely related, and the attributes in different clusters have no relationships. The partitioned Maclaurin symmetric mean… More >

  • Open Access

    ARTICLE

    A Reliability Evaluation Method for Intermittent Jointed Rock Slope Based on Evolutionary Support Vector Machine

    Shuai Zheng, An-Nan Jiang*, Kai-Shuai Feng
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 149-166, 2021, DOI:10.32604/cmes.2021.016761
    Abstract The randomness of rock joint development is an important factor in the uncertainty of geotechnical engineering stability. In this study, a method is proposed to evaluate the reliability of intermittent jointed rock slope. The least squares support vector machine (LSSVM) evolved by a bacterial foraging optimization algorithm (BFOA) is used to establish a response surface model to express the mapping relationship between the intermittent joint parameters and the slope safety factor. The training samples are obtained from the numerical calculation based on the joint finite element method during this process. Considering the randomness of the intermittent joint parameters in the… More >

  • Open Access

    ARTICLE

    Moving Least Squares Interpolation Based A-Posteriori Error Technique in Finite Element Elastic Analysis

    Mohd Ahmed1,*, Devender Singh2, Saeed Al Qadhi1, Nguyen Viet Thanh3
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 167-189, 2021, DOI:10.32604/cmes.2021.014672
    (This article belongs to this Special Issue: Modeling Real World Problems with Mathematics)
    Abstract The performance of a-posteriori error methodology based on moving least squares (MLS) interpolation is explored in this paper by varying the finite element error recovery parameters, namely recovery points and field variable derivatives recovery. The MLS interpolation based recovery technique uses the weighted least squares method on top of the finite element method's field variable derivatives solution to build a continuous field variable derivatives approximation. The boundary of the node support (mesh free patch of influenced nodes within a determined distance) is taken as circular, i.e., circular support domain constructed using radial weights is considered. The field variable derivatives (stress… More >

  • Open Access

    ARTICLE

    Adaptive Object Tracking Discriminate Model for Multi-Camera Panorama Surveillance in Airport Apron

    Dequan Guo1, Qingshuai Yang2, Yu-Dong Zhang3, Gexiang Zhang1, Ming Zhu1, Jianying Yuan1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 191-205, 2021, DOI:10.32604/cmes.2021.016347
    (This article belongs to this Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract Autonomous intelligence plays a significant role in aviation security. Since most aviation accidents occur in the take-off and landing stage, accurate tracking of moving object in airport apron will be a vital approach to ensure the operation of the aircraft safely. In this study, an adaptive object tracking method based on a discriminant is proposed in multi-camera panorama surveillance of large-scale airport apron. Firstly, based on channels of color histogram, the pre-estimated object probability map is employed to reduce searching computation, and the optimization of the disturbance suppression options can make good resistance to similar areas around the object. Then… More >

  • Open Access

    ARTICLE

    Methodology for Road Defect Detection and Administration Based on Mobile Mapping Data

    Marina Davidović1,*, Tatjana Kuzmić1, Dejan Vasić1, Valentin Wich2, Ansgar Brunn2, Vladimir Bulatović1
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 207-226, 2021, DOI:10.32604/cmes.2021.016071
    (This article belongs to this Special Issue: Intelligent Computing for Engineering Applications)
    Abstract A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects visually. This paper presents a novel method for the detection of road defects. The input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping technology. The defects were categorized in three major groups with the following geometric primitives: points, lines and polygons. The method suggests the detection of point objects from matched point clouds, panoramic images and ortho photos. Defects were mapped as point, line or polygon geometries, directly derived from orthomosaics… More >

  • Open Access

    ARTICLE

    Numerical Solutions of a Novel Designed Prevention Class in the HIV Nonlinear Model

    Zulqurnain Sabir1, Muhammad Umar1, Muhammad Asif Zahoor Raja2,*, Dumitru Baleanu3,4
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 227-251, 2021, DOI:10.32604/cmes.2021.016611
    (This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
    Abstract The presented research aims to design a new prevention class (P) in the HIV nonlinear system, i.e., the HIPV model. Then numerical treatment of the newly formulated HIPV model is portrayed handled by using the strength of stochastic procedure based numerical computing schemes exploiting the artificial neural networks (ANNs) modeling legacy together with the optimization competence of the hybrid of global and local search schemes via genetic algorithms (GAs) and active-set approach (ASA), i.e., GA-ASA. The optimization performances through GA-ASA are accessed by presenting an error-based fitness function designed for all the classes of the HIPV model and its corresponding… More >

  • Open Access

    ARTICLE

    Code Transform Model Producing High-Performance Program

    Bao Rong Chang1,*, Hsiu-Fen Tsai2, Po-Wen Su1
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 253-277, 2021, DOI:10.32604/cmes.2021.015673
    (This article belongs to this Special Issue: Hybrid Intelligent Methods for Forecasting in Resources and Energy Field)
    Abstract This paper introduces a novel transform method to produce the newly generated programs through code transform model called the second generation of Generative Pre-trained Transformer (GPT-2) reasonably, improving the program execution performance significantly. Besides, a theoretical estimation in statistics has given the minimum number of generated programs as required, which guarantees to find the best one within them. The proposed approach can help the voice assistant machine resolve the problem of inefficient execution of application code. In addition to GPT-2, this study develops the variational Simhash algorithm to check the code similarity between sample program and newly generated program, and… More >

  • Open Access

    ARTICLE

    Uncertainty Analysis of Seepage-Induced Consolidation in a Fractured Porous Medium

    Lingai Guo1, Marwan Fahs2, Hussein Hoteit3, Rui Gao1,*, Qian Shao1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 279-297, 2021, DOI:10.32604/cmes.2021.016619
    (This article belongs to this Special Issue: Modeling of Heterogeneous Materials)
    Abstract Numerical modeling of seepage-induced consolidation process usually encounters significant uncertainty in the properties of geotechnical materials. Assessing the effect of uncertain parameters on the performance variability of the seepage consolidation model is of critical importance to the simulation and tests of this process. To this end, the uncertainty and sensitivity analyses are performed on a seepage consolidation model in a fractured porous medium using the Bayesian sparse polynomial chaos expansion (SPCE) method. Five uncertain parameters including Young’s modulus, Poisson’s ratio, and the permeability of the porous matrix, the permeability within the fracture, and Biot’s constant are studied. Bayesian SPCE models… More >

  • Open Access

    ARTICLE

    IDV: Internet Domain Name Verification Based on Blockchain

    Ning Hu1, Yu Teng2, Yan Zhao1, Shi Yin1, Yue Zhao3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 299-322, 2021, DOI:10.32604/cmes.2021.016839
    (This article belongs to this Special Issue: Blockchain Security)
    Abstract The rapid development of blockchain technology has provided new ideas for network security research. Blockchain-based network security enhancement solutions are attracting widespread attention. This paper proposes an Internet domain name verification method based on blockchain. The authenticity of DNS (Domain Name System) resolution results is crucial for ensuring the accessibility of Internet services. Due to the lack of adequate security mechanisms, it has always been a challenge to verify the authenticity of Internet domain name resolution results. Although the solution represented by DNSSEC (Domain Name System Security Extensions) can theoretically solve the domain name verification problem, it has not been… More >

  • Open Access

    ARTICLE

    Subdivision Surface-Based Isogeometric Boundary Element Method for Steady Heat Conduction Problems with Variable Coefficient

    Xiuyun Chen1, Xiaomeng Yin2, Kunpeng Li3, Ruhui Cheng1, Yanming Xu1,4,*, Wei Zhang1
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 323-339, 2021, DOI:10.32604/cmes.2021.016794
    (This article belongs to this Special Issue: Recent Advance of the Isogeometric Boundary Element Method and its Applications)
    Abstract The present work couples isogeometric analysis (IGA) and boundary element methods (BEM) for three dimensional steady heat conduction problems with variable coefficients. The Computer-Aided Design (CAD) geometries are built by subdivision surfaces, and meantime the basis functions of subdivision surfaces are employed to discretize the boundary integral equations for heat conduction analysis. Moreover, the radial integration method is adopted to transform the additional domain integrals caused by variable coefficients to the boundary integrals. Several numerical examples are provided to demonstrate the correctness and advantages of the proposed algorithm in the integration of CAD and numerical analysis. More >

  • Open Access

    ARTICLE

    Weighted Parameterized Correlation Coefficients of Indeterminacy Fuzzy Multisets and Their Multicriteria Group Decision Making Method with Different Decision Risks

    Cheng Du1, Jun Ye2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 341-354, 2021, DOI:10.32604/cmes.2021.016758
    (This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
    Abstract

    Real-life data introduce noise, uncertainty, and imprecision to statistical projects; it is advantageous to consider strategies to overcome these information expressions and processing problems. Neutrosophic (indeterminate) numbers can flexibly and conveniently represent the hybrid information of the partial determinacy and partial indeterminacy in an indeterminate setting, while a fuzzy multiset is a vital mathematical tool in the expression and processing of multi-valued fuzzy information with different and/or same fuzzy values. If neutrosophic numbers are introduced into fuzzy sequences in a fuzzy multiset, the introduced neutrosophic number sequences can be constructed as the neutrosophic number multiset or indeterminate fuzzy multiset. Motivated… More >

  • Open Access

    ARTICLE

    Neutrosophic N-Structures Applied to Sheffer Stroke BL-Algebras

    Tugce Katican1, Tahsin Oner1, Akbar Rezaei2,*, Florentin Smarandache3
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 355-372, 2021, DOI:10.32604/cmes.2021.016996
    (This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
    Abstract In this paper, we introduce a neutrosophic N-subalgebra, a (ultra) neutrosophic N-filter, level sets of these neutrosophic N-structures and their properties on a Sheffer stroke BL-algebra. By defining a quasi-subalgebra of a Sheffer stroke BL-algebra, it is proved that the level set of neutrosophic N-subalgebras on the algebraic structure is its quasi-subalgebra and vice versa. Then we show that the family of all neutrosophic N-subalgebras of a Sheffer stroke BL-algebra forms a complete distributive lattice. After that a (ultra) neutrosophic N-filter of a Sheffer stroke BL-algebra is described, we demonstrate that every neutrosophic N-filter of a Sheffer stroke BL-algebra is… More >

  • Open Access

    ARTICLE

    The New Neutrosophic Double and Triple Exponentially Weighted Moving Average Control Charts

    Ambreen Shafqat1,2, Muhammad Aslam3,*, Muhammad Saleem4, Zameer Abbas5
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 373-391, 2021, DOI:10.32604/cmes.2021.016772
    (This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
    Abstract The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average (NEWMA) chart. In this study, two control charts are designed under the uncertain environment or neutrosophic statistical interval system, when all observations are undermined, imprecise or fuzzy. These are termed neutrosophic double and triple exponentially weighted moving average (NDEWMA and NTEWMA) control charts. For the proficiency of the proposed chart, Monte Carlo simulations are used to calculate the run-length characteristics (such as average run length (ARL), standard deviation of the run length (SDRL), percentiles (P25, P50, P75))… More >

  • Open Access

    ARTICLE

    Study of Degenerate Poly-Bernoulli Polynomials by λ-Umbral Calculus

    Lee-Chae Jang1, Dae San Kim2, Hanyoung Kim3, Taekyun Kim3,*, Hyunseok Lee3
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 393-408, 2021, DOI:10.32604/cmes.2021.016917
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract Recently, degenerate poly-Bernoulli polynomials are defined in terms of degenerate polyexponential functions by Kim-Kim-Kwon-Lee. The aim of this paper is to further examine some properties of the degenerate poly-Bernoulli polynomials by using three formulas from the recently developed ‘λ-umbral calculus.’ In more detail, we represent the degenerate poly-Bernoulli polynomials by Carlitz Bernoulli polynomials and degenerate Stirling numbers of the first kind, by fully degenerate Bell polynomials and degenerate Stirling numbers of the first kind, and by higherorder degenerate Bernoulli polynomials and degenerate Stirling numbers of the second kind. More >

  • Open Access

    ARTICLE

    Determinantal Expressions and Recursive Relations for the Bessel Zeta Function and for a Sequence Originating from a Series Expansion of the Power of Modified Bessel Function of the First Kind

    Yan Hong1, Bai-Ni Guo2,*, Feng Qi3
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 409-423, 2021, DOI:10.32604/cmes.2021.016431
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract In the paper, by virtue of a general formula for any derivative of the ratio of two differentiable functions, with the aid of a recursive property of the Hessenberg determinants, the authors establish determinantal expressions and recursive relations for the Bessel zeta function and for a sequence originating from a series expansion of the power of modified Bessel function of the first kind. More >

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