Andrew Omame^1,2,*, Mujahid Abbas^3,6, Dumitru Baleanu^4,5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2973-3012, 2024, DOI:10.32604/cmes.2023.029681

Abstract A patient co-infected with COVID-19 and viral hepatitis B can be at more risk of severe complications than the one infected with a single infection. This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19. The model is fitted to real COVID-19 data from Pakistan. The proposed model incorporates logistic growth and saturated incidence functions. Rigorous analyses using the tools of stochastic calculus, are performed to study appropriate conditions for the existence of unique global solutions, stationary distribution in the sense of ergodicity and disease… More >

Borja Bordel Sánchez^1,*, Ramón Alcarria², Tomás Robles¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3189-3218, 2023, DOI:10.32604/cmc.2023.039466

Abstract Cyber-Physical Systems are very vulnerable to sparse sensor attacks. But current protection mechanisms employ linear and deterministic models which cannot detect attacks precisely. Therefore, in this paper, we propose a new non-linear generalized model to describe Cyber-Physical Systems. This model includes unknown multivariable discrete and continuous-time functions and different multiplicative noises to represent the evolution of physical processes and random effects in the physical and computational worlds. Besides, the digitalization stage in hardware devices is represented too. Attackers and most critical sparse sensor attacks are described through a stochastic process. The reconstruction and protection mechanisms are based on a weighted… More >

Kazem Nouri^1,*, Milad Fahimi¹, Leila Torkzadeh¹, Dumitru Baleanu^2,3

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1495-1514, 2022, DOI:10.32604/cmc.2022.024406

Abstract The novel Coronavirus COVID-19 emerged in Wuhan, China in December 2019. COVID-19 has rapidly spread among human populations and other mammals. The outbreak of COVID-19 has become a global challenge. Mathematical models of epidemiological systems enable studying and predicting the potential spread of disease. Modeling and predicting the evolution of COVID-19 epidemics in near real-time is a scientific challenge, this requires a deep understanding of the dynamics of pandemics and the possibility that the diffusion process can be completely random. In this paper, we develop and analyze a model to simulate the Coronavirus transmission dynamics based on Reservoir-People transmission network.… More >

Karpagam Sundararajan¹, Lalit Garg^2,*, Kathiravan Srinivasan^4,*, Ali Kashif Bashir³, Jayakumar Kaliappan⁴, Ganapathy Pattukandan Ganapathy⁵, Senthil Kumaran Selvaraj⁶, T. Meena⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 447-487, 2021, DOI:10.32604/cmes.2021.015528

Abstract Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Its beginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughts in the last few decades. Predicting future droughts is vital for framing drought management plans to sustain natural resources. The data-driven modelling for forecasting the metrological time series prediction is becoming more powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques have demonstrated success in the drought prediction process and are becoming popular to predict the weather, especially the… More >

Muhammad Rafiq¹, Ali Ahmadian^{2, *}, Ali Raza³, Dumitru Baleanu⁴, Muhammad Sarwar Ahsan¹, Mohammad Hasan Abdul Sathar⁵

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 33-51, 2020, DOI:10.32604/cmc.2020.010893

Abstract Nonlinear stochastic modeling has significant role in the all discipline of sciences. The essential control measuring features of modeling are positivity, boundedness and dynamical consistency. Unfortunately, the existing stochastic methods in literature do not restore aforesaid control measuring features, particularly for the stochastic models. Therefore, these gaps should be occupied up in literature, by constructing the control measuring features numerical method. We shall present a numerical control measures for stochastic malaria model in this manuscript. The results of the stochastic model are discussed in contrast of its equivalent deterministic model. If the basic reproduction number is less than one, then… More >

Muhammad Shoaib Arif^{1, *}, Ali Raza¹, Muhammad Rafiq², Mairaj Bibi³, Javeria Nawaz Abbasi³, Amna Nazeer³, Umer Javed⁴

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 61-77, 2020, DOI:10.32604/cmc.2020.08595

Abstract We are presenting the numerical simulations for the stochastic computer virus propagation model in this manuscript. We are comparing the solutions of stochastic and deterministic computer virus models. Outcomes of a threshold number R₀ hold in stochastic computer virus model. If R₀ < 1 then in such a condition virus controlled in the computer population while R₀ > 1 shows virus rapidly spread in the computer population. Unfortunately, stochastic numerical techniques fail to cope with large step sizes of time. The suggested structure of the stochastic non-standard finite difference technique can never violate the dynamical properties. On this basis, we… More >

Muhammad Shoaib Arif¹, Ali Raza¹, Wasfi Shatanawi^{2, 3, *}, Muhammad Rafiq⁴, Mairaj Bibi⁵

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1025-1043, 2019, DOI:10.32604/cmc.2019.08405

Abstract We are presenting the numerical analysis for stochastic SLBR model of computer virus over the internet in this manuscript. We are going to present the results of stochastic and deterministic computer virus model. Outcomes of the threshold number C* hold in stochastic computer virus model. If C*<1 then in such a condition virus controlled in the computer population while C*>1 shows virus spread in the computer population. Unfortunately, stochastic numerical techniques fail to cope with large step sizes of time. The suggested structure of the stochastic non-standard finite difference scheme (SNSFD) maintains all diverse characteristics such as dynamical consistency, bounded-ness… More >

Hong Qian^*

Molecular & Cellular Biomechanics, Vol.5, No.2, pp. 107-118, 2008, DOI:10.3970/mcb.2008.005.107

Abstract At the molecular and cellular level, mechanics and chemistry are two aspects of the same macromolecular system. We present a bottom-up approach to such systems based on Kramers' diffusion theory of chemical reactions, the theory of polymer dynamics, and the recently developed models for molecular motors. Using muscle as an example, we develop a viscoelastic theory of muscle in terms of an simple equation for single motor protein movement. Both A.V. Hill's contractile component and A.F. Huxley's equation of sliding-filament motion are shown to be special cases of the general viscoelastic theory of the active material. Some disparity between the… More >

Leiting Dong^1,2, Salah H. Gamal³, Satya N. Atluri^2,4

CMC-Computers, Materials & Continua, Vol.37, No.1, pp. 1-21, 2013, DOI:10.3970/cmc.2013.037.001

Abstract In this paper, a simple and reliable procedure of stochastic computation is combined with the highly accurate and efficient Trefftz Computational Grains (TCG), for a direct numerical simulation (DNS) of heterogeneous materials with microscopic randomness. Material properties of each material phase, and geometrical properties such as particles sizes and distribution, are considered to be stochastic with either a uniform or normal probabilistic distributions. The objective here is to determine how this microscopic randomness propagates to the macroscopic scale, and affects the stochastic characteristics of macroscopic material properties. Four steps are included in this procedure: (1) using the Latin hypercube sampling,… More >