CMES-Computer Modeling in Engineering & Sciences

ISSN: 1526-1492 (print) Impact Factor: 2.027
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): 2021 Impact Factor 2.027; Current Contents: Engineering, Computing & Technology; Scopus Citescore (Impact per Publication 2021): 2.5; SNIP (Source Normalized Impact per Paper 2021): 0.617; 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.132, No.3, 2022 Most Viewed

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EDITORIAL
Introduction to the Special Issue on Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph
Shuihua Wang^1,*, 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
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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
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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
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ARTICLE
Some Identities of the Degenerate Poly-Cauchy and Unipoly Cauchy Polynomials of the Second Kind
Ghulam Muhiuddin^1,*, 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
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ARTICLE
Partial Bell Polynomials, Falling and Rising Factorials, Stirling Numbers, and Combinatorial Identities
Siqintuya Jin¹, Bai-Ni Guo^2,*, Feng Qi^3,*
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
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ARTICLE
gscaLCA in R: Fitting Fuzzy Clustering Analysis Incorporated with Generalized Structured Component Analysis
Ji Hoon Ryoo^1,*, 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
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ARTICLE
Modeling and Prediction of Inter-System Bias for GPS/BDS-2/BDS-3 Combined Precision Point Positioning
Zejie Wang¹, Qianxin Wang^1,*, 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
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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 Liu^1,*
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
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ARTICLE
On Soft Pre-Rough Approximation Space with Applications in Decision Making
M. El Sayed^1,*, 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
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ARTICLE
Group Decision-Making Method with Incomplete Intuitionistic Fuzzy Preference Relations Based on a Generalized Multiplicative Consistent Concept
Xiaoyun Lu¹, Jiuying Dong^2,3,*, 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
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ARTICLE
Visual Object Tracking via Cascaded RPN Fusion and Coordinate Attention
Jianming Zhang^1,2,*, Kai Wang^1,2, Yaoqi He^1,2, Lidan Kuang^1,2
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
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ARTICLE
A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm
Qidai Lin¹, Ying Gong^2,*, 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
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ARTICLE
The Improved Element-Free Galerkin Method for Anisotropic Steady-State Heat Conduction Problems
Heng Cheng¹, Zebin Xing¹, Miaojuan Peng^2,*
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
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ARTICLE
A Parallel Computing Schema Based on IGA
Jinggang Deng^1,2, Bingquan Zuo^1,2,*, Huixin Luo^1,2, Weikang Xie^1,2, Jiashu Yang^1,2
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
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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
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ARTICLE
Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features
Wen Yee Wong¹, Ayman Khallel Ibrahim Al-Ani¹, Khairunnisa Hasikin^1,*, 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
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ARTICLE
B-PesNet: Smoothly Propagating Semantics for Robust and Reliable Multi-Scale Object Detection for Secure Systems
Yunbo Rao^1,2, 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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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
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ARTICLE
Multi-Feature Fusion-Guided Multiscale Bidirectional Attention Networks for Logistics Pallet Segmentation
Weiwei Cai^1,2, Yaping Song¹, Huan Duan¹, Zhenwei Xia¹, Zhanguo Wei^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1539-1555, 2022, DOI:10.32604/cmes.2022.019785
（This article belongs to this Special Issue: Computer Modeling for Smart Cities Applications)
Abstract In the smart logistics industry, unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by humans. Therefore, they play a critical role in smart warehousing, and semantics segmentation is an effective method to realize the intelligent identification of logistics pallets. However, most current recognition algorithms are ineffective due to the diverse types of pallets, their complex shapes, frequent blockades in production environments, and changing lighting conditions. This paper proposes a novel multi-feature fusion-guided multiscale bidirectional attention (MFMBA) neural network for logistics pallet segmentation. To better predict… More
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ARTICLE
Bioconvection Cross Diffusion Effects on MHD Flow of Nanofluids over Three Different Geometries with Melting
Tahir Kamran, Muhammad Imran^*, Muhammad N. Naeem, Mohsan Raza
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1023-1039, 2022, DOI:10.32604/cmes.2022.017391
（This article belongs to this Special Issue: Recent Trends in Nanofluids: Modelling and Simulations)
Abstract Currently, nanofluid is a hot area of interest for researchers. The nanofluid with bioconvection phenomenon attracted the researchers owing to its numerous applications in the field of nanotechnology, microbiology, nuclear science, heat storage devices, biosensors, biotechnology, hydrogen bomb, engine of motors, cancer treatment, the atomic reactor, cooling of devices, and in many more. This article presents the bioconvection cross-diffusion effects on the magnetohydrodynamic flow of nanofluids on three different geometries (cone, wedge, and plate) with mixed convection. The temperature-dependent thermal conductivity, thermal diffusivity, and Arrhenius activation energy applications are considered on the fluid flow with melting phenomenon. The flow is… 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
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