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  • Open Access

    ARTICLE

    A Study on the Transmission Dynamics of the Omicron Variant of COVID-19 Using Nonlinear Mathematical Models

    S. Dickson1, S. Padmasekaran1, Pushpendra Kumar2,*, Kottakkaran Sooppy Nisar3, Hamidreza Marasi4

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2265-2287, 2024, DOI:10.32604/cmes.2023.030286 - 11 March 2024

    Abstract This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models, considering the delay in converting susceptible individuals into infected ones. The significant delays eventually resulted in the pandemic’s containment. To ensure the safety of the host population, this concept integrates quarantine and the COVID-19 vaccine. We investigate the stability of the proposed models. The fundamental reproduction number influences stability conditions. According to our findings, asymptomatic cases considerably impact the prevalence of Omicron infection in the community. The real data of the Omicron variant from Chennai, Tamil Nadu, India, is More >

  • Open Access

    ARTICLE

    Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

    Li Zheng, Gang Xu*, Wenbin Chen

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 935-957, 2024, DOI:10.32604/cmc.2023.046006 - 30 January 2024

    Abstract Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company’s transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty… More >

  • Open Access

    ARTICLE

    Fractal Fractional Order Operators in Computational Techniques for Mathematical Models in Epidemiology

    Muhammad Farman1,2,4, Ali Akgül3,9,*, Mir Sajjad Hashemi5, Liliana Guran6,7, Amelia Bucur8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1385-1403, 2024, DOI:10.32604/cmes.2023.028803 - 17 November 2023

    Abstract New fractional operators, the COVID-19 model has been studied in this paper. By using different numerical techniques and the time fractional parameters, the mechanical characteristics of the fractional order model are identified. The uniqueness and existence have been established. The model’s Ulam-Hyers stability analysis has been found. In order to justify the theoretical results, numerical simulations are carried out for the presented method in the range of fractional order to show the implications of fractional and fractal orders. We applied very effective numerical techniques to obtain the solutions of the model and simulations. Also, we… More >

  • Open Access

    ARTICLE

    Mathematical Modelling and Simulations of Active Direct Methanol Fuel Cell

    RABIRANJAN MURMUa,b, DEBASHIS ROYa, HAREKRUSHNA SUTARb

    Journal of Polymer Materials, Vol.40, No.3-4, pp. 125-139, 2023, DOI:10.32381/JPM.2023.40.3-4.1

    Abstract A one dimensional isothermal model is proposed by modelling the kinetics of methanol transport at anode flow channel (AFC), membrane and cathode catalyst layer of direct methanol fuel cell (DMFC). Analytical model is proposed to predict methanol cross-over rate through the electrolyte membrane and cell performance. The model presented in this paper considered methanol diffusion and electrochemical oxidation at the anode and cathode channels. The analytical solution of the proposed model was simulated in a MATLAB environment to obtain the polarization curve and leakage current. The effect of methanol concentration on cell voltage and leakage More >

  • Open Access

    ARTICLE

    Simulation Analysis of New Energy Vehicle Engine Cooling System Based on K-E Turbulent Flow Mathematical Model

    Hongyu Mu1,2,*, Yinyan Wang1, Chuanlei Yang1, Hong Teng2, Xingtian Zhao2, Hongquan Lu2, Dechun Wang2, Shiyang Hao2, Xiaolong Zhang2, Yan Jin2

    Energy Engineering, Vol.120, No.10, pp. 2325-2342, 2023, DOI:10.32604/ee.2023.029360 - 28 September 2023

    Abstract New energy vehicles have better clean and environmental protection characteristics than traditional fuel vehicles. The new energy engine cooling technology is critical in the design of new energy vehicles. This paper used one-and three-way joint simulation methods to simulate the refrigeration system of new energy vehicles. Firstly, a k-ε turbulent flow model for the cooling pump flow field is established based on the principle of computational fluid dynamics. Then, the CFD commercial fluid analysis software FLUENT is used to simulate the flow field of the cooling pump under different inlet flow conditions. This paper proposes More > Graphic Abstract

    Simulation Analysis of New Energy Vehicle Engine Cooling System Based on K-E Turbulent Flow Mathematical Model

  • Open Access

    ARTICLE

    Statistical Time Series Forecasting Models for Pandemic Prediction

    Ahmed ElShafee1, Walid El-Shafai2,3, Abeer D. Algarni4,*, Naglaa F. Soliman4, Moustafa H. Aly5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 349-374, 2023, DOI:10.32604/csse.2023.037408 - 26 May 2023

    Abstract COVID-19 has significantly impacted the growth prediction of a pandemic, and it is critical in determining how to battle and track the disease progression. In this case, COVID-19 data is a time-series dataset that can be projected using different methodologies. Thus, this work aims to gauge the spread of the outbreak severity over time. Furthermore, data analytics and Machine Learning (ML) techniques are employed to gain a broader understanding of virus infections. We have simulated, adjusted, and fitted several statistical time-series forecasting models, linear ML models, and nonlinear ML models. Examples of these models are… More >

  • Open Access

    ARTICLE

    Kinetic Modeling of Light Naphtha Hydroisomerization in an Industrial Universal Oil Products Penex™ Unit

    Ramzy S. Hamied1, Zaidoon M. Shakor2,*, Anfal H. Sadeiq1, Adnan A. Abdul Razak2, Ammar T. Khadim3

    Energy Engineering, Vol.120, No.6, pp. 1371-1386, 2023, DOI:10.32604/ee.2023.028441 - 03 April 2023

    Abstract Recently, the isomerization of light naphtha has been increasingly significant in assisting refiners in meeting sternness specifications for gasoline. Isomerization process provides refiners with the advantage of reducing sulfur, olefin, and benzene in the gasoline basin without significantly victimizing the octane. The mathematical modeling of a chemical reaction is a critical tool due to it can used to optimize the experimental data to estimate the optimum operating conditions for industrial reactors. This paper describes light naphtha isomerization reactions over a Pt/Al2O3-Cl catalyst at the Al-Dura Oil Refinery (Baghdad, Iraq) using a newly developed universal mathematical model.… More >

  • Open Access

    ARTICLE

    A Study on the Nonlinear Caputo-Type Snakebite Envenoming Model with Memory

    Pushpendra Kumar1,*, Vedat Suat Erturk2, V. Govindaraj1, Dumitru Baleanu3,4,5

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2487-2506, 2023, DOI:10.32604/cmes.2023.026009 - 09 March 2023

    Abstract In this article, we introduce a nonlinear Caputo-type snakebite envenoming model with memory. The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractional-order sense. The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector (L1-PC) scheme with error estimation and stability analysis. The proof of the existence and positivity of the solution is given by using the fixed point theory. From the necessary simulations, we justify that the first-time implementation of the proposed method on an epidemic model shows that the scheme More >

  • Open Access

    ARTICLE

    A New Generative Mathematical Model for Coverless Steganography System Based on Image Generation

    Al-Hussien Seddik1, Mohammed Salah2, Gamal Behery2, Ahmed El-harby2, Ahmed Ismail Ebada2, Sokea Teng3, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5087-5103, 2023, DOI:10.32604/cmc.2023.035364 - 28 December 2022

    Abstract The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its efficiency. Recently, researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it; this is called the stego image. This paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response (QR) code and maze game image generation. This system consists of two components. The first component contains two processes, encryption process,… More >

  • Open Access

    ARTICLE

    A Stochastic Framework for Solving the Prey-Predator Delay Differential Model of Holling Type-III

    Naret Ruttanaprommarin1, Zulqurnain Sabir2,3, Rafaél Artidoro Sandoval Núñez4, Emad Az-Zo’bi5, Wajaree Weera6, Thongchai Botmart6,*, Chantapish Zamart6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5915-5930, 2023, DOI:10.32604/cmc.2023.034362 - 28 December 2022

    Abstract The current research aims to implement the numerical results for the Holling third kind of functional response delay differential model utilizing a stochastic framework based on Levenberg-Marquardt backpropagation neural networks (LVMBPNNs). The nonlinear model depends upon three dynamics, prey, predator, and the impact of the recent past. Three different cases based on the delay differential system with the Holling 3rd type of the functional response have been used to solve through the proposed LVMBPNNs solver. The statistic computing framework is provided by selecting 12%, 11%, and 77% for training, testing, and verification. Thirteen numbers of neurons More >

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