The information spreading of awareness can prompt the manners of human to ease the infectious possibility and assist to recover swiftly. A dynamic system of Susceptible-Infected-Recovered (SIR) with Unaware-Aware (UA) process (SIR-UA) is newly developed by using compartment model through analytical approach with assumption of an infinite and well-mixed population. Moreover, individuals in a population can be classified into six states as unaware susceptible(SU), aware susceptible(SA), unaware infected(IU), aware infected(IA), unaware recovered(RU), and aware recovered(RA). Compared with previous models, the new dynamic set of equations described the more widespread situation and incorporated all possible states of Unaware-Aware (UA) with SIR process. The effect of awareness is explored carefully to show the significance on epidemic model with time steps. Consequently, the properties of parameters on the epidemic awareness model are studied to deliberate different physical situations. Finally, full phase diagrams are explored to show the epidemic sizes of susceptible and recovered individuals for various parameters.
The information awareness about contagious diseases have an influential effect on an individual's decision to suppress the diffusion of infections. In this work, a new mathematical framework for a vaccination game combined with susceptible-infected-recovered (SIR) and unaware-aware (UA) situation is considered. Altering wearing mask or taking protection against diseases, we consider the information spreading effect that might be represented the situation of self-protection. The information spreading is supposed only for local situation for a season, but has a very significant effect to reduce the infection through a generation. Within this concept, unaware and aware states are taken for susceptible, infected and vaccinated individuals for an infinite and well mixed population. Moreover, three different strategy updating rules concerning whether an individual committing or not vaccination: individual based, strategy based and direct selection are studied to show the comparison by depicting as full phase diagram. Finally, it can be seen that information spreading can subdue the spreading of epidemic within a population.
The two layer SIR/V-UA epidemic diffusion model is incorporated in metapopulation migration model for random walkers to study the impact of awareness (rumor) for evolutionary vaccination game approach. In metapopulation, each node denoted a sub-population where the individuals migrate from one node to another by random walk following different graphs; star, cycle, wheel and complete. The framework of epidemic migration model in vaccination game with information spreading effect is observed in one single season as well as generation by some strategy update rules for an individual either taking vaccination or not. Furthermore, individuals in each node are divided into seven situations as; unaware susceptible, aware susceptible, unaware vaccinated, aware vaccinated, unaware infected, aware infected and recovered in a single season. Two strategy updating rules: individual based risk assessment (IB-RA) and strategy based risk assessment (SB-RA) are discussed for game theoretical approach for four new states; healthy vaccinated, infected vaccinated, successfully free rider and failed free rider at the end of each season to explore how different graphs of an underlying social network giving impact on the final epidemic size through the effect of information spreading in the complex population network with various number of nodes. Accordingly, the information spreading with migration in metapopulation model can enhance the epidemic threshold effectiveness and help to overcome on controlling disease diffusion.
A two-layer susceptible-infected-recovered/unaware-aware (SIR-UA) epidemic model is presented to analyze the effect of different heterogeneous networks in a population. Random, scale-free, and small-world network topologies are tested to investigate the impact of awareness on the spread of epidemics in a two-layer network with diverse combinations of degree and structure. Susceptible and infected (both unaware and aware) individuals are associated with their neighboring nodes in a social network structure with various degree distributions. In the two-layer SIR-UA epidemic model, a virtual network represents the connections that spread information, while a physical network represents the physical social interactions that spread diseases. We test various combinations of network structures in virtual or physical networks, to understand the impact of information diffusion on the spread of epidemics in a heterogeneous network structure. Then, the effects of awareness on the spread of a disease are discussed. Finally, phase diagrams are illustrated to reveal the final regions covered by an epidemic with various network parameters. We find that a disease spreads less if the virtual social network is more connected than the network of physical connections.
Many recent studies on evolutionary spatial Prisoner’s Dilemma (SPD) games have provided insights into the mechanisms and frameworks that bolster the effect of network reciprocity. In this article, we provide a concise and comprehensive review of previous studies on evolutionary games and network reciprocity. Subsequently, we evaluate and compare the results from such studies in a unified manner to answer an open question in evolutionary SPD games: What are the factors underlying network reciprocity and what effect do these factors have on the emergence and promotion of cooperation? As a first step, we introduce a novel indicator to quantitatively evaluate the effectiveness (contribution) of a final fraction of cooperators via the introduction of the associated mechanisms into a simple evolutionary SPD game. In this game, the players are located on a two-dimensional square lattice with the Moore neighborhood and update their strategies by imitating the strategy of the best performing player among their neighbors, and the dynamics are separated into two periods: the enduring (END) period and the expanding (EXP) period. The initial fraction of cooperators is decreased transiently via the invasion and exploitation of defectors in the END period, and over the period, the fraction of cooperators is increased to expand cooperative clusters in the EXP period. Moreover, we also evaluate the statistical validity of our indicator by performing regression analyses. Our results indicate that two factors bolster the effect of network reciprocity: (1) the shape of the cooperative cluster (C-cluster) formed in the END period and (2) the ability to expand a single “perfect C-cluster,” which is the smallest patch, to increase the opportunity for interactions between cooperators and defectors and reduce exploitation by defectors in the EXP period.
The study investigates the effect of mass recovery process on the performance of a conventional two bed solar adsorption cooling system with direct solar coupling mathematically. In an adsorption refrigeration system, the pressure in adsorber and desorber are different. The mass recovery scheme utilizes this pressure difference to enhance the refrigerant mass circulation. Average Cooling Capacity (ACC) and Coefficient of Performance (COP) were calculated by computer simulation to analyze the influences of operating conditions. The results show that the average cooling capacity of mass recovery system is superior to that of conventional system. It is also seen that mass recovery process enhances the overall performances of solar driven chiller and there is an optimum mass recovery time for an adsorption cooling system with direct solar coupling
K M Ariful Kabir, Jun Tanimoto:Analysis of epidemic outbreaks in two-layer networks with different structures for information spreading and disease diffusion. Communications in Nonlinear Science and Numerical Simulation 72. DOI: 10.1016/j.cnsns.2019.01.020
K M Ariful Kabir, Jun Tanimoto: Dynamical Behaviors for Vaccination can Suppress Infectious Disease -A Game Theoretical Approach. Chaos Solitons & Fractals 06/2019; 123:229-239., DOI:10.1016/j.chaos.2019.04.010
K.M. Ariful Kabir, Jun Tanimoto: Vaccination strategies in a two-layer SIR/V-UA epidemic model with costly information and buzz effect. Communications in Nonlinear Science and Numerical Simulation 04/2019; 76., DOI:10.1016/j.cnsns.2019.04.007
K. M. Ariful Kabir, Jun Tanimoto: Evolutionary vaccination game approach in metapopulation migration model with information spreading on different graphs. Chaos Solitons & Fractals 03/2019; 120:41-55., DOI:10.1016/j.chaos.2019.01.013
K M Ariful Kabir, Kazuki Kuga, Jun Tanimoto: Effect of information spreading to suppress the disease contagion on the epidemic vaccination game. Chaos Solitons & Fractals 02/2019; 119:180-187., DOI:10.1016/j.chaos.2018.12.023
K M Ariful Kabir, Kazuki Kuga, Jun Tanimoto: Analysis of SIR epidemic model with information spreading of awareness. Chaos Solitons & Fractals 02/2019; 119:118-125., DOI:10.1016/j.chaos.2018.12.017
K M Ariful Kabir, Jun Tanimoto: Analysis of epidemic outbreaks in two-layer networks with different structures for information spreading and disease diffusion. Communications in Nonlinear Science and Numerical Simulation 01/2019; 72., DOI:10.1016/j.cnsns.2019.01.020
K. M. Ariful Kabir, Jun Tanimoto, Zhen Wang: Influence of bolstering network reciprocity in the evolutionary spatial Prisoner’s Dilemma game: a perspective. Physics of Condensed Matter 12/2018; 91(12)., DOI:10.1140/epjb/e2018-90214-6
K. M. Ariful kabir, Rifat A. Rouf, M. M. A. Sarker, K. C. Amanul Alam, Bidyut B. Saha: Improvement of COP with Heat Recovery Scheme for Solar Adsorption Cooling System. 04/2018;, DOI:10.1142/S2010132518500165
Rifat Ara Rouf, K. C. Amanul Alam, Bidyut Baran Saha, K. M. Ariful Kabir: Utilizing Accessible Heat Enhancing Cooling Effect with Three Bed Solar Adsorption Chiller. Heat Transfer Engineering 03/2018;, DOI:10.1080/01457632.2018.1451244
Md Rakibul Hasan, K M Ariful Kabir: Numerical Investigation of Three-Dimensional Interaction Turbulent Flow.
K M Ariful Kabir, Rakibul Hasan, Amal Krishna Halder: Monte Carlo Simulation for Ground State Energies of Atoms.
Rifat Ara Rouf, M. A. Hakim Khan, Bidyut Baran Saha, K.M Ariful kabir: Energy Management and Heat Storage for Solar Adsorption Cooling. 09/2016; 3(2)., DOI:10.5109/1800866
K.M Ariful kabir, K.C. Amanul Alam, M.M.A. Sarker, Rifat A. Rouf, Bidyut B. Saha: Effect of Mass Recovery on the Performance of Solar Adsorption Cooling System. Energy Procedia 11/2015; 79:67-72., DOI:10.1016/j.egypro.2015.11.479
K M Ariful Kabir, Amal Halder: Estimation of beryllium ground state energy by Monte Carlo simulation. AIP Conference Proceedings 07/2015; 1660(090044)., DOI:10.1063/1.4926633
K. M. Ariful Kabir: Estimation of Boron Ground State Energy by Monte Carlo Simulation. 05/2015; 3(3):106., DOI:10.11648/j.ajam.20150303.15
Rifat Ara Rouf, K.C. Amanul Alam, M.A. Hakim Khan, Bidyut Baran Saha, F. Meunier, M. Abdul Alim, K.M. Ariful Kabir: Advancement of Solar Adsorption Cooling by Means of Heat Storage. Procedia Engineering 12/2014; 90., DOI:10.1016/j.proeng.2014.11.786
K.C.A. Alam, R.A. Rouf, M.A.H. Khan, K.M.A. Kabir: Performance analysis of solar adsorption cooling system - Effect of position of heat storage tank.
K. M. Ariful Kabir, Amal Halder: Estimation of Energies for Singlet and Triplet States of Helium. 09/2013; 1557(1):152-157., DOI:10.1063/1.4823894