Xuechen Liu¹, Majid Khan², Zahid Rasheed³, Syed Masroor Anwar^4,*, Muhammad Arslan⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1171-1195, 2022, DOI:10.32604/cmes.2022.019199 - 14 March 2022

Abstract The EWMA charts are the well-known memory-type charts used for monitoring the small-to-intermediate shifts in the process parameters (location and/or dispersion). The hybrid EWMA (HEWMA) charts are enhanced version of the EWMA charts, which effectively monitor the process parameters. This paper aims to develop two new uppersided HEWMA charts for monitoring shifts in process variance, i.e., HEWMA1 and HEWMA2 charts. The design structures of the proposed HEWMA1 and HEWMA2 charts are based on the concept of integrating the features of two EWMA charts. The HEWMA1 and HEWMA2 charts plotting statistics are developed using one EWMA… More >

Yaning Xiao, Xue Sun^*, Yanling Guo, Sanping Li, Yapeng Zhang, Yangwei Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 815-850, 2022, DOI:10.32604/cmes.2022.019198 - 14 March 2022

Abstract Gorilla troops optimizer (GTO) is a newly developed meta-heuristic algorithm, which is inspired by the collective lifestyle and social intelligence of gorillas. Similar to other metaheuristics, the convergence accuracy and stability of GTO will deteriorate when the optimization problems to be solved become more complex and flexible. To overcome these defects and achieve better performance, this paper proposes an improved gorilla troops optimizer (IGTO). First, Circle chaotic mapping is introduced to initialize the positions of gorillas, which facilitates the population diversity and establishes a good foundation for global search. Then, in order to avoid getting… More >

Rohul Amin¹, Şuayip Yüzbası^2,*, Shah Nazir³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 639-653, 2022, DOI:10.32604/cmes.2022.019154 - 14 March 2022

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 More >

G. Muhiuddin^1,*, K. Porselvi², B. Elavarasan², D. Al-Kadi³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 979-999, 2022, DOI:10.32604/cmes.2022.018615 - 14 March 2022

Abstract In general, ordered algebraic structures, particularly ordered semigroups, play an important role in fuzzification in many applied areas, such as computer science, formal languages, coding theory, error correction, etc. Nowadays, the concept of ambiguity is important in dealing with a variety of issues related to engineering modeling problems, network theory, decision-making problems in real-life situations, and so on. Several theories have been developed by various researchers to overcome the difficulties that arise from uncertainty, including fuzzy sets, intuitionistic fuzzy sets, probability, soft sets, neutrosophic sets, and many more. In this paper, we focus solely on More >

Jong-In Choi¹, Soo-Kyun Kim², Shin-Jin Kang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 747-762, 2022, DOI:10.32604/cmes.2022.018201 - 14 March 2022

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. More >

Abdon Atangana^1,2, Ilknur Koca^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 787-814, 2022, DOI:10.32604/cmes.2022.019221 - 14 March 2022

Abstract Very recently, a new concept was introduced to capture crossover behaviors that exhibit changes in patterns. The aim was to model real-world problems exhibiting crossover from one process to another, for example, randomness to a power law. The concept was called piecewise calculus, as differential and integral operators are defined piece wisely. These behaviors have been observed in the spread of several infectious diseases, for example, tuberculosis. Therefore, in this paper, we aim at modeling the spread of tuberculosis using the concept of piecewise modeling. Several cases are considered, conditions under which the unique system More >

Jingchun Zhou^1,*, Taian Shi¹, Weishi Zhang^1,*, Weishen Chu²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1063-1081, 2022, DOI:10.32604/cmes.2022.019447 - 14 March 2022

Abstract The scattering and absorption of light propagating underwater cause the underwater images to present low contrast, color deviation, and loss of details, which in turn make human posture recognition challenging. To address these issues, this study introduced the dual-guided filtering technique and developed an underwater diver image improvement method. First, the color distortion of the underwater diver image was solved using white balance technology to obtain a color-corrected image. Second, dual-guided filtering was applied to the white balanced image to correct the distorted color and enhance its details. Four feature weight maps of the two More >

Naigong Yu^*, Hejie Yu

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1147-1169, 2022, DOI:10.32604/cmes.2022.019430 - 14 March 2022

Abstract The entorhinal-hippocampus structure in the mammalian brain is the core area for realizing spatial cognition. However, the visual perception and loop detection methods in the current biomimetic robot navigation model still rely on traditional visual SLAM schemes and lack the process of exploring and applying biological visual methods. Based on this, we propose a map construction method that mimics the entorhinal-hippocampal cognitive mechanism of the rat brain according to the response of entorhinal cortex neurons to eye saccades in recent related studies. That is, when mammals are free to watch the scene, the entorhinal cortex… More >

Jie Bai, Xiaowei Zeng^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 551-565, 2022, DOI:10.32604/cmes.2022.019376 - 14 March 2022

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 More >

Jie Zhang, Jiaxiang Zhao^*, Pengchang Xu

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 905-917, 2022, DOI:10.32604/cmes.2022.019097 - 14 March 2022

Abstract Accurately, reliably and rapidly identifying intrinsically disordered (IDPs) proteins is essential as they often play important roles in various human diseases; moreover, they are related to numerous important biological activities. However, current computational methods have yet to develop a network that is sufficiently deep to make predictions about IDPs and demonstrate an improvement in performance. During this study, we constructed a deep neural network that consisted of five identical variant models, ResNet18, combined with an MLP network, for classification. Resnet18 was applied for the first time as a deep model for predicting IDPs, which allowed More >