Xin Tong¹, Changlin Zhang^2,*, Jingya Wang¹, Zhiyan Zhao¹, Zhuoxian Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 561-581, 2023, DOI:10.32604/cmes.2022.022495

Abstract The dark web is a shadow area hidden in the depths of the Internet, which is difficult to access through common search engines. Because of its anonymity, the dark web has gradually become a hotbed for a variety of cyber-crimes. Although some research based on machine learning or deep learning has been shown to be effective in the task of analyzing dark web traffic in recent years, there are still pain points such as low accuracy, insufficient real-time performance, and limited application scenarios. Aiming at the difficulties faced by the existing automated dark web traffic analysis methods, a novel method… More >

Yeol Woo Sung, Dae Seung Park, Cheong Ghil Kim^*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 795-808, 2023, DOI:10.32604/cmes.2022.022465

Abstract The entry into a hyper-connected society increases the generalization of communication using SNS. Therefore, research to analyze big data accumulated in SNS and extract meaningful information is being conducted in various fields. In particular, with the recent development of Deep Learning, the performance is rapidly improving by applying it to the field of Natural Language Processing, which is a language understanding technology to obtain accurate contextual information. In this paper, when a chatbot system is applied to the healthcare domain for counseling about diseases, the performance of NLP integrated with machine learning for the accurate classification of medical subjects from… More >

Jie Ren^1,2, Chuqiao Xu³, Junliang Wang^2,4, Jie Zhang^2,*, Xinhua Mao⁴, Wei Shen⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 599-618, 2023, DOI:10.32604/cmes.2022.022415

Abstract The prognostics health management (PHM) from the systematic view is critical to the healthy continuous operation of process manufacturing systems (PMS), with different kinds of dynamic interference events. This paper proposes a three leveled digital twin model for the systematic PHM of PMSs. The unit-leveled digital twin model of each basic device unit of PMSs is constructed based on edge computing, which can provide real-time monitoring and analysis of the device status. The station-leveled digital twin models in the PMSs are designed to optimize and control the process parameters, which are deployed for the manufacturing execution on the fog server.… More >

Hong’an Li¹, Min Zhang^1,*, Dufeng Chen², Jing Zhang¹, Meng Yang³, Zhanli Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 779-794, 2023, DOI:10.32604/cmes.2022.022369

Abstract Computer-aided diagnosis based on image color rendering promotes medical image analysis and doctor-patient communication by highlighting important information of medical diagnosis. To overcome the limitations of the color rendering method based on deep learning, such as poor model stability, poor rendering quality, fuzzy boundaries and crossed color boundaries, we propose a novel hinge-cross-entropy generative adversarial network (HCEGAN). The self-attention mechanism was added and improved to focus on the important information of the image. And the hinge-cross-entropy loss function was used to stabilize the training process of GAN models. In this study, we implement the HCEGAN model for image color rendering… More > Graphic Abstract

Tongping Shen^1,2,*, Huanqing Xu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 539-560, 2023, DOI:10.32604/cmes.2022.022312

Abstract For the problems of complex model structure and too many training parameters in facial expression recognition algorithms, we proposed a residual network structure with a multi-headed channel attention (MCA) module. The migration learning algorithm is used to pre-train the convolutional layer parameters and mitigate the overfitting caused by the insufficient number of training samples. The designed MCA module is integrated into the ResNet18 backbone network. The attention mechanism highlights important information and suppresses irrelevant information by assigning different coefficients or weights, and the multi-head structure focuses more on the local features of the pictures, which improves the efficiency of facial… More >

Binghui Cui^1,*, Liaojun Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 357-376, 2023, DOI:10.32604/cmes.2022.022309

Abstract Flow-type landslide is one type of landslide that generally exhibits characteristics of high flow velocities, long jump distances, and poor predictability. Simulation of its propagation process can provide solutions for risk assessment and mitigation design. The smoothed particle hydrodynamics (SPH) method has been successfully applied to the simulation of two-dimensional (2D) and three-dimensional (3D) flow-like landslides. However, the influence of boundary resistance on the whole process of landslide failure is rarely discussed. In this study, a boundary condition considering friction is proposed and integrated into the SPH method, and its accuracy is verified. Moreover, the Navier-Stokes equation combined with the… More > Graphic Abstract

Nima Pirhadi¹, Xusheng Wan¹, Jianguo Lu¹, Jilei Hu^2,3,*, Mahmood Ahmad^4,5, Farzaneh Tahmoorian⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 733-754, 2023, DOI:10.32604/cmes.2022.022207

Abstract Liquefaction is one of the most destructive phenomena caused by earthquakes, which has been studied in the issues of potential, triggering and hazard analysis. The strain energy approach is a common method to investigate liquefaction potential. In this study, two Artificial Neural Network (ANN) models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept (W) by using laboratory test data. A large database was collected from the literature. One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model. To investigate the complex influence… More >

Ramya Arumugam¹, Ramamoorthy Kumar^1,*, Samiappan Dhanalakshmi¹, Khin Wee Lai², Lei Jiao^3,*, Xiang Wu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 301-323, 2023, DOI:10.32604/cmes.2022.022144

Abstract Sensors play an important role in shaping and monitoring human health. Exploration of methods to use Fiber Bragg Grating (FBG) with enhanced sensitivity has attracted great interest in the field of medical research. In this paper, a novel apodization function is proposed and performance evaluation and optimization of the same have been made. A comparison was conducted between various existing apodization functions and the proposed one based on optical characteristics and sensor parameters. The results evince the implementation of the proposed apodization function for vital sign measurement. The optical characteristics considered for evaluation are Peak Resonance Reflectivity level, Side Lobes… More > Graphic Abstract

Long Chen^1,*, Shuxun Liang², Nan Yan², Xiangqian Yang², Baotong Li³

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 687-709, 2023, DOI:10.32604/cmes.2022.021986

Abstract Lattice structures with excellent physical properties have attracted great research interest. In this paper, a novel volume parametric modeling method based on the skeleton model is proposed for the construction of three-dimensional lattice structures. The skeleton model is divided into three types of nodes. And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes. The unit-cell is assembled with distinct nodes according to the geometric features. The final lattice structure is created by the periodic arrangement of unit-cells. Several different types of volume parametric lattice structures are constructed to prove the stability and applicability of the… More > Graphic Abstract

Nives Brajčić Kurbaša^*, Blaž Gotovac, Vedrana Kozulić

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 65-90, 2023, DOI:10.32604/cmes.2022.021940

Abstract The purpose of this paper is to present the class of atomic basis functions (ABFs) which are of exponential type and are denoted by . While ABFs of the algebraic type are already represented in the numerical modeling of various problems in mathematical physics and computational mechanics, ABFs of the exponential type have not yet been sufficiently researched. These functions, unlike the ABFs of the algebraic type , contain the tension parameter , which gives them additional approximation properties. Exponential monomials up to the th degree can be described exactly by the linear combination of the functions . The function… More >