CMES-Computer Modeling in Engineering & Sciences

ISSN: 1526-1492 (print) Impact Factor: 1.593
ISSN: 1526-1506 (online) Publication Frequency: Monthly

About the Journal

This journal publishes original research papers of reasonable permanent value, in the areas of computational mechanics, computational physics, computational chemistry, and computational biology, pertinent to solids, fluids, gases, biomaterials, and other continua. Various length scales (quantum, nano, micro, meso, and macro), and various time scales (picoseconds to hours) are of interest. Papers which deal with multi-physics problems, as well as those which deal with the interfaces of mechanics, chemistry, and biology, are particularly encouraged. New computational approaches, and more efficient algorithms, which eventually make near-real-time computations possible, are welcome. Original papers dealing with new methods such as meshless methods, and mesh-reduction methods are sought.

Indexing and Abstracting

Science Citation Index (Web of Science): 2020 Impact Factor 1.593; Current Contents: Engineering, Computing & Technology; Scopus Citescore (Impact per Publication 2020): 1.6; SNIP (Source Normalized Impact per Paper 2020): 0.59; RG Journal Impact (average over last three years); Engineering Index (Compendex); Applied Mechanics Reviews; Cambridge Scientific Abstracts: Aerospace and High Technology, Materials Sciences & Engineering, and Computer & Information Systems Abstracts Database; CompuMath Citation Index; INSPEC Databases; Mathematical Reviews; MathSci Net; Mechanics; Science Alert; Science Navigator; Zentralblatt fur Mathematik; Portico, etc...

Current Issue - Vol.129, No.1, 2021 Most Viewed

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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
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ARTICLE
Predicting Genotype Information Related to COVID-19 for Molecular Mechanism Based on Computational Methods
Lejun Gong^1,2,*, 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
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ARTICLE
A Novel Named Entity Recognition Scheme for Steel E-Commerce Platforms Using a Lite BERT
Maojian Chen^1,2,3, Xiong Luo^1,2,3,*, Hailun Shen⁴, Ziyang Huang⁴, Qiaojuan Peng^1,2,3
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
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REVIEW
Deep Learning Applications for COVID-19 Analysis: A State-of-the-Art Survey
Wenqian Li¹, Xing Deng^1,2,*, 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
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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
Views:591 Downloads:393 Download PDF

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ARTICLE
Medical Waste Treatment Station Selection Based on Linguistic q-Rung Orthopair Fuzzy Numbers
Jie Ling^1,2, Xinmei Li^1,2, Mingwei Lin^1,2,*
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
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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
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ARTICLE
Moving Least Squares Interpolation Based A-Posteriori Error Technique in Finite Element Elastic Analysis
Mohd Ahmed^1,*, 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
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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 Yuan^1,*
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
Views:281 Downloads:208 Download PDF

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ARTICLE
Methodology for Road Defect Detection and Administration Based on Mobile Mapping Data
Marina Davidović^1,*, 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
Views:284 Downloads:222 Download PDF

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ARTICLE
Numerical Solutions of a Novel Designed Prevention Class in the HIV Nonlinear Model
Zulqurnain Sabir¹, Muhammad Umar¹, Muhammad Asif Zahoor Raja^2,*, Dumitru Baleanu^3,4
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
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ARTICLE
Code Transform Model Producing High-Performance Program
Bao Rong Chang^1,*, 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
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ARTICLE
Uncertainty Analysis of Seepage-Induced Consolidation in a Fractured Porous Medium
Lingai Guo¹, Marwan Fahs², Hussein Hoteit³, Rui Gao^1,*, Qian Shao^1,*
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
Views:255 Downloads:214 Download PDF

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ARTICLE
IDV: Internet Domain Name Verification Based on Blockchain
Ning Hu¹, Yu Teng², Yan Zhao¹, Shi Yin¹, Yue Zhao^3,*
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
Views:243 Downloads:229 Download PDF

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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 Xu^1,4,*, 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
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ARTICLE
Weighted Parameterized Correlation Coefficients of Indeterminacy Fuzzy Multisets and Their Multicriteria Group Decision Making Method with Different Decision Risks
Cheng Du¹, Jun Ye^2,*
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
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ARTICLE
Neutrosophic N-Structures Applied to Sheffer Stroke BL-Algebras
Tugce Katican¹, Tahsin Oner¹, Akbar Rezaei^2,*, 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
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ARTICLE
The New Neutrosophic Double and Triple Exponentially Weighted Moving Average Control Charts
Ambreen Shafqat^1,2, Muhammad Aslam^3,*, 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
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ARTICLE
Study of Degenerate Poly-Bernoulli Polynomials by λ-Umbral Calculus
Lee-Chae Jang¹, Dae San Kim², Hanyoung Kim³, Taekyun Kim^3,*, 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
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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 Guo^2,*, 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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ARTICLE
Validating the Correct Wearing of Protection Mask by Taking a Selfie: Design of a Mobile Application “CheckYourMask” to Limit the Spread of COVID-19
Karim Hammoudi^1,2,*, Adnane Cabani³, Halim Benhabiles⁴, Mahmoud Melkemi^1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1049-1059, 2020, DOI:10.32604/cmes.2020.011663
（This article belongs to this Special Issue: Computer Modelling of Transmission, Spread, Control and Diagnosis of COVID-19)
Abstract In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019–2020 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. The symptom of COVID-19 was reported first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting everyone having a smartphone and… More
Views:19645 Downloads:9347 Download PDF

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REVIEW
Review on Application of Artificial Intelligence in Civil Engineering
Youqin Huang¹, Jiayong Li¹, Jiyang Fu^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.3, pp. 845-875, 2019, DOI:10.32604/cmes.2019.07653
Abstract In last few years, big data and deep learning technologies have been successfully applied in various fields of civil engineering with the great progress of machine learning techniques. However, until now, there has been no comprehensive review on its applications in civil engineering. To fill this gap, this paper reviews the application and development of artificial intelligence in civil engineering in recent years, including intelligent algorithms, big data and deep learning. Through the work of this paper, the research direction and difficulties of artificial intelligence in civil engineering for the past few years can be known. It is shown that… More
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ARTICLE
Data Augmentation Technology Driven By Image Style Transfer in Self-Driving Car Based on End-to-End Learning
Dongjie Liu¹, Jin Zhao^{1, *}, Axin Xi², Chao Wang¹, Xinnian Huang¹, Kuncheng Lai¹, Chang Liu¹
CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 593-617, 2020, DOI:10.32604/cmes.2020.08641
Abstract With the advent of deep learning, self-driving schemes based on deep learning are becoming more and more popular. Robust perception-action models should learn from data with different scenarios and real behaviors, while current end-to-end model learning is generally limited to training of massive data, innovation of deep network architecture, and learning in-situ model in a simulation environment. Therefore, we introduce a new image style transfer method into data augmentation, and improve the diversity of limited data by changing the texture, contrast ratio and color of the image, and then it is extended to the scenarios that the model has been… More
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ARTICLE
Conceptual Modular Design of Auto Body Frame Based on Hybrid Optimization Method
Yonghong Zhao¹, Changsheng Wang², Huanquan Yuan¹, Yongcheng Li¹, Chunlai Shan², Wenbin Hou^{2, *}
CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 351-376, 2020, DOI:10.32604/cmes.2020.08058
Abstract This article presents a systematic research methodology of modular design for conceptual auto body frame by hybrid optimization method. A modified graph-based decomposition optimization algorithm is utilized to generate an optimal BIW assembly topo model composed of “potential modules”. The consistency constraint function in collaborative optimization is extended to maximize the commonality of modules and minimize the performance loss of all car types in the same product family simultaneously. A novel screening method is employed to select both “basic structures” and “reinforcement” modules based on the dimension optimization of the manufacturing elements and the optimal assembly mode; this allows for… More
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ARTICLE
ALCencryption: A Secure and Efficient Algorithm for Medical Image Encryption
Jiao Ge^1,2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1083-1100, 2020, DOI:10.32604/cmes.2021.013039
（This article belongs to this Special Issue: Computer Methods in Bio-mechanics and Biomedical Engineering)
Abstract With the rapid development of medical informatization and the popularization of digital imaging equipment, DICOM images contain the personal privacy of patients, and there are security risks in the process of storage and transmission, so it needs to be encrypted. In order to solve the security problem of medical images on mobile devices, a safe and efficient medical image encryption algorithm called ALCencryption is designed. The algorithm first analyzes the medical image and distinguishes the color image from the gray image. For gray images, the improved Arnold map is used to scramble them according to the optimal number of iterations,… More
Views:4928 Downloads:1207 Download PDF

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ARTICLE
Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm
Tinghuai Ma^1,*, Honghao Zhou¹, Dongdong Jia¹, Abdullah Al-Dhelaan², Mohammed Al-Dhelaan², Yuan Tian³
CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 569-592, 2019, DOI:10.32604/cmes.2019.07758
Abstract Feature selection has been widely used in data mining and machine learning. Its objective is to select a minimal subset of features according to some reasonable criteria so as to solve the original task more quickly. In this article, a feature selection algorithm with local search strategy based on the forest optimization algorithm, namely FSLSFOA, is proposed. The novel local search strategy in local seeding process guarantees the quality of the feature subset in the forest. Next, the fitness function is improved, which not only considers the classification accuracy, but also considers the size of the feature subset. To avoid… More
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