Information collection from remote location is very important for several tasks such as temperate monitoring, air quality investigation, and wartime surveillance. Wireless sensor network is the first choice to complet...Information collection from remote location is very important for several tasks such as temperate monitoring, air quality investigation, and wartime surveillance. Wireless sensor network is the first choice to complete these types of tasks. Basically, information prediction scheme is an important feature in any sensor nodes. The efficiency of the sensor network can be improved to large extent with a suitable information prediction scheme. Previously, there were several efforts to resolve this problem, but their accuracy is decreased as the prediction threshold reduces to a small value. Our proposed Adams-Bashforth-Moulton algorithm to overcome this drawback was compared with the Milne Simpson scheme. The proposed algorithm is simulated on distributed sensor nodes where information is gathered from the Intel Berkeley Research Laboratory. To maximize the power saving in wireless sensor network, our adopted method achieves the accuracy of 60.28 and 59.2238 for prediction threshold of 0.01 for Milne Simpson and Adams-Bashforth-Moulton algorithms, respectively.展开更多
This paper presents an alternative representation of a system of differential equations qualitatively showing the behavior of the biological rhythm of a crayfish during their transition from juvenile to adult stages. ...This paper presents an alternative representation of a system of differential equations qualitatively showing the behavior of the biological rhythm of a crayfish during their transition from juvenile to adult stages. The model focuses on the interaction of four cellular oscillators coupled by diffusion of a hormone, a parameter μ is used to simu- late the quality of communication among the oscillators, in biological terms, it mea- sures developmental maturity of the crayfish. Since some quorum-sensing mechanism is assumed to be responsible for the synchronization of the biological oscillators, it is nat- ural to investigate the possibility that the underlying diffusion process is not standard, i.e. it may be a so-called anomalous diffusion. In this case, it is well understood that diffusion equations with fractional derivatives describe these processes in a more realis- tic way. The alternative formulation of these equations contains fractional operators of Liouville-Caputo and Caputo-Fabrizio type. The numerical simulations of the equations reflect synchronization of ultradian rhythms leading to a circadian rhythm. The classical behavior is recovered when the order of the fractional derivative is V = 1. We discuss possible biological implications.展开更多
This paper proposes fractional-order systems for Hopfield Neural Network(HNN).The so-called Predictor Corrector Adams Bashforth Moulton Method(PCABMM)has been implemented for solving such systems.Graphical comparisons...This paper proposes fractional-order systems for Hopfield Neural Network(HNN).The so-called Predictor Corrector Adams Bashforth Moulton Method(PCABMM)has been implemented for solving such systems.Graphical comparisons between the PCABMM and the Runge-Kutla Method(RKM)solutions for the classical HNN reveal that the proposed technique is one of the powerful tools for handling these systems.To determine all Lyapunov exponents for them,the Benettin-Wolf algorithm has been involved in the PCABMM.leased on such algorithm,the Lyapunov exponents as a function of a given parameter and as another function of the fractional-order have been described,the intermittent chaos for these systems has been explored.A new result related to the Mittag-Leffler stability of some nonlinear Fractional-order Hopfield Neural Network(FoHNN)systems has been shown.Besides,the description and the dynamic analysis of those phenomena have been discussed and verified theoretically and numerically via illustrating the phase portraits and the Lyapunov exponents'diagrams.展开更多
文摘Information collection from remote location is very important for several tasks such as temperate monitoring, air quality investigation, and wartime surveillance. Wireless sensor network is the first choice to complete these types of tasks. Basically, information prediction scheme is an important feature in any sensor nodes. The efficiency of the sensor network can be improved to large extent with a suitable information prediction scheme. Previously, there were several efforts to resolve this problem, but their accuracy is decreased as the prediction threshold reduces to a small value. Our proposed Adams-Bashforth-Moulton algorithm to overcome this drawback was compared with the Milne Simpson scheme. The proposed algorithm is simulated on distributed sensor nodes where information is gathered from the Intel Berkeley Research Laboratory. To maximize the power saving in wireless sensor network, our adopted method achieves the accuracy of 60.28 and 59.2238 for prediction threshold of 0.01 for Milne Simpson and Adams-Bashforth-Moulton algorithms, respectively.
文摘This paper presents an alternative representation of a system of differential equations qualitatively showing the behavior of the biological rhythm of a crayfish during their transition from juvenile to adult stages. The model focuses on the interaction of four cellular oscillators coupled by diffusion of a hormone, a parameter μ is used to simu- late the quality of communication among the oscillators, in biological terms, it mea- sures developmental maturity of the crayfish. Since some quorum-sensing mechanism is assumed to be responsible for the synchronization of the biological oscillators, it is nat- ural to investigate the possibility that the underlying diffusion process is not standard, i.e. it may be a so-called anomalous diffusion. In this case, it is well understood that diffusion equations with fractional derivatives describe these processes in a more realis- tic way. The alternative formulation of these equations contains fractional operators of Liouville-Caputo and Caputo-Fabrizio type. The numerical simulations of the equations reflect synchronization of ultradian rhythms leading to a circadian rhythm. The classical behavior is recovered when the order of the fractional derivative is V = 1. We discuss possible biological implications.
基金supporting this work by the University Ajman Grant:2Q20-COVID-19-08.
文摘This paper proposes fractional-order systems for Hopfield Neural Network(HNN).The so-called Predictor Corrector Adams Bashforth Moulton Method(PCABMM)has been implemented for solving such systems.Graphical comparisons between the PCABMM and the Runge-Kutla Method(RKM)solutions for the classical HNN reveal that the proposed technique is one of the powerful tools for handling these systems.To determine all Lyapunov exponents for them,the Benettin-Wolf algorithm has been involved in the PCABMM.leased on such algorithm,the Lyapunov exponents as a function of a given parameter and as another function of the fractional-order have been described,the intermittent chaos for these systems has been explored.A new result related to the Mittag-Leffler stability of some nonlinear Fractional-order Hopfield Neural Network(FoHNN)systems has been shown.Besides,the description and the dynamic analysis of those phenomena have been discussed and verified theoretically and numerically via illustrating the phase portraits and the Lyapunov exponents'diagrams.
