Simulation Practice and Theory最新文献

Calcium plays an essential role as a messenger and as a factor in cardiac contraction. In the present study, a model for Ca²⁺ handling in cardiac cells is presented. After the identification of the sarcoplasmic reticulum (SR) parameters, the SERCA pump and ryanodine channels activities, a comparison is made between experimental and calculated responses. The model's parameters were identified using optimization methods. This identification is based on the response of the digitonin permeabilized cells. The model deals with the dynamics of the calcium exchange between the different compartments of the cell. Cell compartments involved are the SR, the cytosol and the extra-cellular medium. The different components of the mathematical models are discussed and compared. The modeling and simulation are run within Ψlab,¹ a freeware for modeling and simulation of dynamic systems.

Cochlear implants are used to restore hearing in the profoundly deaf [Th.J. Balkany, Otolaryngol. Clin. North. Am. 19 (2) (1986) 215–449] by direct electrical stimulation of the auditory nerve. To study the working mechanism of cochlear implants and to provide a tool to develop better ones, a Boundary Element electrical volume conduction model of the cochlea (the auditory part of the inner ear) has been constructed. In this paper first a short comparison of the available numerical methods is given, then an algorithm is presented with which different cochlear geometries can be constructed and fitted with different types of cochlear implants. With the resulting model the potential distributions induced by the implant can be calculated, and a prediction of the effect of the implant can be made. The use of the meshing algorithm is not restricted to cochlear implants, but is also applicable in other fields.

Interstitial fluid pressure (IFP) is one of the main obstacles for macromolecular agents uptake and distribution in solid tumors. It has been demonstrated to reduce effectiveness of different macromolecular agents used in in vivo anti-tumor therapies, which on the other hand showed very good anti-tumor properties in in vitro conditions [L.T. Baxter, R.K. Jain, Microvascular Research 37 (1989) 77–104]. With an appropriate model we demonstrated the correlation between different physiological properties of solid tumor and IFP. The model which we present showed high correlation with results from literature and thus represents a good simulation of physiological processes that govern fluid dynamics in solid tumors. One of the potential uses of presented model is drafting of future experiments which would lead to more effective chemo- or immuno-therapy of solid tumors. This model could also serve as an aid to the interpretation of different experimental results concerning IFP.

This paper deals with simulation experiments on the model-based adaptive control of the distributed parameter bioreactor in the presence of the measurement noise. Since in such cases the adaptive controller itself is not able to ensure good control performance, there is a need to propose more sophisticated application. It is based on the first-order digital low-pass filters and allows us to decrease the influence of the measurement noise on the control performance. In order to decrease this influence it is possible to adjust three parameters of the application: controller tuning parameter, forgetting factor for the estimation of the substrate consumption rate and time constant of the low-pass filters. Simulation results, presented in this paper, have been obtained for different values of these parameters and, based on these results, it is possible to propose a robust application for the adaptive control of the bioreactor with optimally chosen values of the adjustable parameters. This application can be suggested to be applied in the adaptive control of a real industrial distributed parameter bioreactor with noisy measurement data.

In this paper, the methodology for normal gait recognition and estimation is described. Normal gait recognition is derived on the basis of kinematics data of the human locomotion system. Measurements were carried out and the data were processed and statistically analyzed.

The procedure was done on a group of 20 students. Kinematics data have been presented in phase plane. Sets of data in phase plane for the specific discrete moments in time were statistically processed using the Gaussian and Bootstrap methods. Discrete moments are chosen according to specific gait phases of a gait cycle. Finally, as a result of statistical analysis, the gait quality index (GQI) is obtained for each gait phase.

Human behaviour in manual control especially in transport systems has some non-linearities such as saturation, delay dead band and so on. In this paper, the standard model of human operator is analysed from the viewpoint of system identification. Therefore, some procedures for the identification of the human behaviour model are developed from available data. These procedures are validated by application according to experimental data from laboratory experiments with human tracking of the various stimuli for a step, sinusoidal and pseudo-random target movement. The simulation experiment results had shown that the simple linear model of human behaviour describes it for a wide area of behaviour. Used linear model of the operator is suitable only for a step response type of target movement. To track a time-varying input signal, a non-linear model needs to be used. The paper concludes with a recommendation for further identification methods for a non-linear model of the human operator.

This paper introduces a graph-oriented representation of metabolism, and shows how to apply the shortest path algorithm to reconstruct metabolic pathways. Our metabolic model is constructed from molecular structures of compounds and reaction formulas of enzymes, and its output is all the logically possible pathways consisting of input reactions. We also show how to integrate putative reactions in the model.

Synchronous VLSI design is approaching a critical point, with clock distribution becoming an increasingly costly and complicated issue and power consumption rapidly emerging as a major concern. Hence, recently, there has been a resurgence of interest in asynchronous digital design techniques as they promise to liberate VLSI systems from clock skew problems, offer the potential for low power and high performance and encourage a modular design philosophy which makes incremental technological migration a much easier task. This activity has revealed a need for modelling and simulation techniques suitable for the asynchronous design style. Contributing to the quest for modelling and simulation techniques suitable for asynchronous design, and motivated by the increasing debate regarding the potential of CSP for this purpose, this paper investigates the suitability of occam, a CSP-based programming language, for the modelling and simulation of complex asynchronous systems. A generic modelling framework is introduced and issues arising from the parallel semantics of CSP/occam when the latter is employed to perform simulation are addressed.

A neural network controller is described and implemented for controlling the vibration of a rotor-bearing system. A multi-layered neural network is used to model the inverse dynamics or the rotor-bearing system on-line. It is learnt by a backpropagation algorithm, and a delta rule, in which the difference between the actual control input to the plant, which is generated from the neural controller, and the input estimated from the inverse-dynamics model by using an actual plant output, is minimized. The results show a satisfactory diminished response of the rotor-bearing system when the controller is applied to the system.