Open Access
ARTICLE
Jie Bai, Xiaowei Zeng*
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 551-565, 2022, DOI:10.32604/cmes.2022.019376
Abstract Cell migration plays a significant role in many biological activities, yet the physical mechanisms of cell migration are still not well understood. In this study, a continuum physics-based epithelial monolayer model including the intercellular interaction was employed to study the cell migration behavior in a confluent epithelial monolayer at constant cell density. The epithelial cell was modeled as isotropic elastic material. Through finite element simulation, the results revealed that the motile cell was subjected to higher stress than the other jammed cells during the migration process. Cell stiffness was implied to play a significant role in epithelial cell migration behavior.… More >
Open Access
REVIEW
Dandan Xu1, Haijian Shao1,*, Xing Deng1,2, Xia Wang3
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 567-597, 2022, DOI:10.32604/cmes.2022.019245
Abstract As wind and photovoltaic energy become more prevalent, the optimization of power systems is becoming increasingly crucial. The current state of research in renewable generation and power forecasting technology, such as wind
and photovoltaic power (PV), is described in this paper, with a focus on the ensemble sequential LSTMs approach
with optimized hidden-layers topology for short-term multivariable wind power forecasting. The methods for
forecasting wind power and PV production. The physical model, statistical learning method, and machine learning
approaches based on historical data are all evaluated for the forecasting of wind power and PV production.
Moreover, the experiments demonstrated that… More >
Open Access
ARTICLE
Ali Salehi, Mahdi Fakoor*, Amirreza Kosari, Seyed Mohammad Navid Ghoreishi
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 599-618, 2022, DOI:10.32604/cmes.2022.018840
Abstract Satellite design process is an interdisciplinary subject in which the need for collaboration among various science and engineering disciplines is evident. Meanwhile, finding an optimal process for conceptual design of a satellite, which can optimize time and cost, is still an important issue. In this paper, based on system engineering approach, an optimal design process is proposed for LEO satellite constellations. In the proposed method, design process, design sequences, and data flow are established. In this regard, the conceptual design process is divided into two levels of mission (or constellation) and system (or satellite) as well as 15 main activities… More >
Open Access
ARTICLE
Fujia Wei1,2,*, Liyin Shen1, Yuanming Xiang2, Xingjie Zhang2, Yu Tang2, Qian Tan2
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 619-637, 2022, DOI:10.32604/cmes.2022.019082
Abstract Concrete exterior quality is one of the important metrics in evaluating construction project quality. Among the defects affecting concrete exterior quality, bughole is one of the most common imperfections, thus detecting concrete bughole accurately is significant for improving concrete exterior quality and consequently the quality of the whole project. This paper presents a deep learning-based method for detecting concrete surface bugholes in a more objective and automatic way. The bugholes are identified in concrete surface images by Mask R-CNN. An evaluation metric is developed to indicate the scale of concrete bughole. The proposed approach can detect bugholes in an instance… More >
Open Access
ARTICLE
Rohul Amin1, Şuayip Yüzbası2,*, Shah Nazir3
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 639-653, 2022, DOI:10.32604/cmes.2022.019154
Abstract In this paper, Haar collocation algorithm is developed for the solution of first-order of HIV infection CD4+ T-Cells
model. In this technique, the derivative in the nonlinear model is approximated by utilizing Haar functions. The
value of the unknown function is obtained by the process of integration. Error estimation is also discussed, which
aims to reduce the error of numerical solutions. The numerical results show that the method is simply applicable.
The results are compared with Runge-Kutta technique, Bessel collocation technique, LADM-Pade and Galerkin
technique available in the literature. The results show that the Haar technique is easy, precise and… More >
Open Access
ARTICLE
Zengchen Yu1, Ke Wang2,*, Shuxuan Xie1, Yuanfeng Zhong1, Zhihan Lv3
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 655-675, 2022, DOI: 10.32604/cmes.2022.019612
Abstract Few-shot Learning algorithms can be effectively applied to fields where certain categories have only a small amount
of data or a small amount of labeled data, such as medical images, terrorist surveillance, and so on. The Metric
Learning in the Few-shot Learning algorithm is classified by measuring the similarity between the classified samples
and the unclassified samples. This paper improves the Prototypical Network in the Metric Learning, and changes
its core metric function to Manhattan distance. The Convolutional Neural Network of the embedded module is
changed, and mechanisms such as average pooling and Dropout are added. Through comparative experiments, it… More >
Open Access
ARTICLE
Sridharan Kannan*
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 677-694, 2022, DOI:10.32604/cmes.2022.018580
Abstract With the worldwide analysis, heart disease is considered a significant threat and extensively increases the mortality rate. Thus, the investigators mitigate to predict the occurrence of heart disease in an earlier stage using the design of a better Clinical Decision Support System (CDSS). Generally, CDSS is used to predict the individuals’ heart disease and periodically update the condition of the patients. This research proposes a novel heart disease prediction system with CDSS composed of a clustering model for noise removal to predict and eliminate outliers. Here, the Synthetic Over-sampling prediction model is integrated with the cluster concept to balance the… More >
Open Access
ARTICLE
Junjian Fu1,2, Pengfei Sun1, Yixian Du1,2,*, Lei Tian1, Qihua Tian1, Xiangman Zhou1
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 695-713, 2022, DOI:10.32604/cmes.2022.017842
Abstract Cellular structures are regarded as excellent candidates for lightweight-design, load-bearing, and energy-absorbing applications. In this paper, a novel S-based TPMS hollow isotropic cellular structure is proposed with both superior load-bearing and energy-absorbing performances. The hollow cellular structure is designed with Boolean operation based on the Fischer-Koch (S) implicit triply periodic minimal surfaces (TPMS) with different level parameters. The anisotropy and effective elasticity properties of cellular structures are evaluated with the numerical homogenization method. The finite element method is further conducted to analyze the static mechanical performance of hollow cellular structure considering the size effect. The compression experiments are finally carried… More >
Open Access
ARTICLE
Sai Li1, Xin Lai2,*, Lisheng Liu3
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 715-746, 2022, DOI:10.32604/cmes.2022.018544
Abstract In this work, we modeled the brittle fracture of shell structure in the framework of Peridynamics Mindlin-Reissener shell theory, in which the shell is described by material points in the mean-plane with its drilling rotation neglected in kinematic assumption. To improve the numerical accuracy, the stress-point method is utilized to eliminate the numerical instability induced by the zero-energy mode and rank-deficiency. The crack surface is represented explicitly by stress points, and a novel general crack criterion is proposed based on that. Instead of the critical stretch used in common peridynamic solid, it is convenient to describe the material failure by… More >
Open Access
ARTICLE
Jong-In Choi1, Soo-Kyun Kim2, Shin-Jin Kang3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 747-762, 2022, DOI:10.32604/cmes.2022.018201
（This article belongs to this Special Issue: HPC with Artificial Intelligence based Deep Video Data Analytics: Models, Applications and Approaches)
Abstract Two-dimensional (2D) character animation is one of the most important visual elements on which users’ interest
is focused in the game field. However, 2D character animation works in the game field are mostly performed
manually in two dimensions, thus generating high production costs. This study proposes a generative adversarial
network based production tool that can easily and quickly generate the sprite images of 2D characters. First, we
proposed a methodology to create a synthetic dataset for training using images from the real world in the game
resource production field where machine learning datasets are insufficient. In addition, we have enabled… More >
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