Home / Journals / CMES / Vol.136, No.1, 2023
Table of Content
  • Open AccessOpen Access

    EDITORIAL

    Introduction to the Special Issue on Mathematical Aspects of Computational Biology and Bioinformatics

    Dumitru Baleanu1,2,*, Carla M. A. Pinto3, Sunil Kumar4
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 1-3, 2023, DOI:10.32604/cmes.2023.026471
    (This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
    Abstract This article has no abstract. More >

  • Open AccessOpen Access

    REVIEW

    Edge Intelligence with Distributed Processing of DNNs: A Survey

    Sizhe Tang1, Mengmeng Cui1,*, Lianyong Qi2, Xiaolong Xu1
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 5-42, 2023, DOI:10.32604/cmes.2023.023684
    (This article belongs to this Special Issue: Artificial Intelligence for Mobile Edge Computing in IoT)
    Abstract With the rapid development of deep learning, the size of data sets and deep neural networks (DNNs) models are also booming. As a result, the intolerable long time for models’ training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually. Moreover, devices stay idle in the scenario of edge computing (EC), which presents a waste of resources since they can share the pressure of the busy devices but they do not. To address the problem, the strategy leveraging distributed processing has been applied to load computation tasks from a single processor to a group of… More >

  • Open AccessOpen Access

    ARTICLE

    Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

    W. M. Faizal1,*, C. Y. Khor1, Muhammad Nooramin Che Yaakob1, N. N. N. Ghazali2, M. Z. Zainon2, Norliza Binti Ibrahim3, Roziana Mohd Razi4
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 43-61, 2023, DOI:10.32604/cmes.2023.022716
    (This article belongs to this Special Issue: Computer Methods in Bio-mechanics and Biomedical Engineering)
    Abstract This paper aims to investigate and present the numerical investigation of airflow characteristics using Turbulent Kinetic Energy (TKE) to characterize the upper airway with obstructive sleep apnea (OSA) under inhale and exhale breathing conditions. The importance of TKE under both breathing conditions is that it show an accurate method in expressing the severity of flow in sleep disorder. Computational fluid dynamics simulate the upper airway’s airflow via steady-state Reynolds-averaged Navier-Stokes (RANS) with k–ω shear stress transport (SST) turbulence model. The three-dimensional (3D) airway model is created based on the CT scan images of an actual patient, meshed with 1.29 million… More >

    Graphic Abstract

    Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

  • Open AccessOpen Access

    ARTICLE

    The Effects of the Particle Size Ratio on the Behaviors of Binary Granular Materials

    Deze Yang, Xihua Chu*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 63-85, 2023, DOI:10.32604/cmes.2023.025062
    Abstract The particle size ratio (PSR) is an important parameter for binary granular materials, which may affect the microstructure and macro behaviors of granular materials. However, the effect of particle ratio on granular assemblies with different arrangements is still unclear. To explore and further clarify the effect of PSR in different packing structures, three types of numerical samples with regular, layered, and random packing are designed. Numerical results show that PSR has significant effects on binary granular samples with regular packing. The larger the PSR, the stronger the strength, the larger the modulus, and the smaller the angle between the shear… More >

  • Open AccessOpen Access

    ARTICLE

    A Novel Light Weight CNN Framework Integrated with Marine Predator Optimization for the Assessment of Tear Film-Lipid Layer Patterns

    Bejoy Abraham1, Jesna Mohan2, Linu Shine3, Sivakumar Ramachandran3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 87-106, 2023, DOI:10.32604/cmes.2023.023384
    Abstract Tear film, the outermost layer of the eye, is a complex and dynamic structure responsible for tear production. The tear film lipid layer is a vital component of the tear film that provides a smooth optical surface for the cornea and wetting the ocular surface. Dry eye syndrome (DES) is a symptomatic disease caused by reduced tear production, poor tear quality, or excessive evaporation. Its diagnosis is a difficult task due to its multifactorial etiology. Out of several clinical tests available, the evaluation of the interference patterns of the tear film lipid layer forms a potential tool for DES diagnosis.… More >

  • Open AccessOpen Access

    ARTICLE

    Implementation of Rapid Code Transformation Process Using Deep Learning Approaches

    Bao Rong Chang1, Hsiu-Fen Tsai2,*, Han-Lin Chou1
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 107-134, 2023, DOI:10.32604/cmes.2023.024018
    Abstract Our previous work has introduced the newly generated program using the code transformation model GPT-2, verifying the generated programming codes through simhash (SH) and longest common subsequence (LCS) algorithms. However, the entire code transformation process has encountered a time-consuming problem. Therefore, the objective of this study is to speed up the code transformation process significantly. This paper has proposed deep learning approaches for modifying SH using a variational simhash (VSH) algorithm and replacing LCS with a piecewise longest common subsequence (PLCS) algorithm to faster the verification process in the test phase. Besides the code transformation model GPT-2, this study has… More >

    Graphic Abstract

    Implementation of Rapid Code Transformation Process Using Deep Learning Approaches

  • Open AccessOpen Access

    ARTICLE

    A New Hybrid Hierarchical Parallel Algorithm to Enhance the Performance of Large-Scale Structural Analysis Based on Heterogeneous Multicore Clusters

    Gaoyuan Yu1, Yunfeng Lou2, Hang Dong3, Junjie Li1, Xianlong Jin1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 135-155, 2023, DOI:10.32604/cmes.2023.025166
    Abstract Heterogeneous multicore clusters are becoming more popular for high-performance computing due to their great computing power and cost-to-performance effectiveness nowadays. Nevertheless, parallel efficiency degradation is still a problem in large-scale structural analysis based on heterogeneous multicore clusters. To solve it, a hybrid hierarchical parallel algorithm (HHPA) is proposed on the basis of the conventional domain decomposition algorithm (CDDA) and the parallel sparse solver. In this new algorithm, a three-layer parallelization of the computational procedure is introduced to enable the separation of the communication of inter-nodes, heterogeneous-core-groups (HCGs) and inside-heterogeneous-core-groups through mapping computing tasks to various hardware layers. This approach can… More >

  • Open AccessOpen Access

    ARTICLE

    Topic Controlled Steganography via Graph-to-Text Generation

    Bowen Sun1, Yamin Li1,2,3,*, Jun Zhang1, Honghong Xu1, Xiaoqiang Ma4, Ping Xia2,3,5
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 157-176, 2023, DOI:10.32604/cmes.2023.025082
    Abstract Generation-based linguistic steganography is a popular research area of information hiding. The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to. However, in the course of our experiment, we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text, which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases, and that the topic of generated texts is uncontrollable, so there is still room for improvement in concealment. In this paper,… More >

  • Open AccessOpen Access

    ARTICLE

    Health Monitoring of Milling Tool Inserts Using CNN Architectures Trained by Vibration Spectrograms

    Sonali S. Patil, Sujit S. Pardeshi, Abhishek D. Patange*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 177-199, 2023, DOI:10.32604/cmes.2023.025516
    Abstract In-process damage to a cutting tool degrades the surface finish of the job shaped by machining and causes a significant financial loss. This stimulates the need for Tool Condition Monitoring (TCM) to assist detection of failure before it extends to the worse phase. Machine Learning (ML) based TCM has been extensively explored in the last decade. However, most of the research is now directed toward Deep Learning (DL). The “Deep” formulation, hierarchical compositionality, distributed representation and end-to-end learning of Neural Nets need to be explored to create a generalized TCM framework to perform efficiently in a high-noise environment of cross-domain… More >

  • Open AccessOpen Access

    ARTICLE

    Design of a Computational Heuristic to Solve the Nonlinear Liénard Differential Model

    Li Yan1, Zulqurnain Sabir2, Esin Ilhan3, Muhammad Asif Zahoor Raja4, Wei Gao5, Haci Mehmet Baskonus6,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 201-221, 2023, DOI:10.32604/cmes.2023.025094
    Abstract In this study, the design of a computational heuristic based on the nonlinear Liénard model is presented using the efficiency of artificial neural networks (ANNs) along with the hybridization procedures of global and local search approaches. The global search genetic algorithm (GA) and local search sequential quadratic programming scheme (SQPS) are implemented to solve the nonlinear Liénard model. An objective function using the differential model and boundary conditions is designed and optimized by the hybrid computing strength of the GA-SQPS. The motivation of the ANN procedures along with GA-SQPS comes to present reliable, feasible and precise frameworks to tackle stiff… More >

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