120592105
Hydrodynamic modelling and CFD simulation of ferrofluids flow in magnetic targeting drug delivery
Magnetic targeting drug delivery is a method of carrying drug-loaded magnetic nanoparticles to a tissue target in the human body under the applied magnetic field. This method increases the drug concentration in the target and reduces the adverse side-effects. In this article, a mathematical model is presented to describe the hydrodynamics of ferrofluids as drug carriers flowing in a blood vessel under the applied magnetic field. Numerical simulations are performed to obtain better insight into the theoretical analysis with computational fluid dynamics. A 3D flow field of magnetic particles in an idealised blood vessel model containing an aneurysm is analysed to further understand clinical application of magnetic targeting drug delivery. Simulation samples demonstrate the important parameters leading to adequate drug delivery to the target site depending on the applied magnetic field in coincidence with reported results from animal experiments. Results of the analysis provide the important information and can suggest strategies for improving delivery in favour of the clinical application.
38041019
Towards an Efficient Self-organizing Reconfiguration Method for Self-reconfigurable Robots
This paper deals with the essential technique for self-organizing metamorphosis of self-reconfigurable robots. A general model describing self-reconfigurable robots is proposed; the model is capable of expressing the topological structure of typical 2-D and 3-D self-reconfigurable robots. Afterwards, a self-organizing metamorphic strategy of self-reconfigurable robots, based on full-discrete local intelligence, is proposed. The modules concurrently process the local interactive information. A reasonable motion sequence for modules can be obtained by means of determining and evolving the rules of modules motion. Consequently, the global self-organizing behavior will be obtained, and the complexity of the algorithm is reduced. Simulation samples are provided to illustrate this approach and demonstrate the effectiveness of the proposed strategy.
2507502
An Analytical Performance Model of IP-SAN
In this paper we propose a component-based analytical performance model for IP-SAN. We model four key components within IP-SAN individually and they are IP network, cache, RAID and disks. We validate these component models and compose them to give an entire IP-SAN performance model. The entire IP-SAN model analyzes the performance of an IP-SAN configuration under multiple synchronous workloads by using closed queueing network model and under asynchronous workload by using open queueing network model. We also validate the entire IP-SAN performance model against a real IP-SAN system. The theoretical results are compared with the results from a real IP-SAN using a variety of synthetic workloads. These experiments prove that the component-based method is an appropriate way to build performance model for a complex storage system. To our knowledge, this is the first exploration into building analytical performance model for entire IP-SAN system and validating against a real system. We also identify areas for future research in the performance analysis of real IP-SAN.
644571
Parametric inference for progressive Type-I hybrid censored data on a simple step-stress accelerated life test model
This paper considers a simple step-stress accelerated life test model under progressive Type-I hybrid censoring scheme. The progressive Type-I hybrid censoring scheme and statistical method in synthetic accelerated stresses are provided so as to decrease the lifetime and reduce the test cost. An exponentially distributed life of test units and a cumulative exposure model are assumed. The maximum likelihood estimates of the model parameters are obtained using a pivotal quantity. Two useful lemmas and a theorem are given to construct the approximate confidence intervals for the model parameters. Finally, simulation results are provided to assess the method of inference developed in this article. The simulation results show that the method does improve for large sample size.
8176507
Research and Application of Spatio-temporal Data Mining Based on Ontology
In this paper, the spatio-temporal data mining is studied by adopting the ontology theory. The method of spatio-temporal data mining based on ontology is presented and a new spatio-temporal forecasting model based on ontology is designed. The model uses two measures of spatio-temporal autocorrelation: spatio-temporal adjacency matrix and spatio-temporal contiguity measure. We use this model in the forecast about medium and long term coarse granularity in the railway passenger flow, and the results show that using the method of spatio-temporal forecasting based on ontology can obtain a good forecasting precision
6807682
A generalization of Sperner's theorem and an application to graph orientations
A generalization of Sperner's theorem is established: For a multifamily M={Y"1,...,Y"p} of subsets of {1,...,n} in which the repetition of subsets is allowed, a sharp lower bound for the number @f(M) of ordered pairs (i,j) satisfying i j and Y"i@?Y"j is determined. As an application, the minimum average distance of orientations of complete bipartite graphs is determined.
13145807
Stochastic Hopf bifurcation and chaos of stochastic Bonhoeffer-van der Pol system via Chebyshev polynomial approximation
Abstract In this paper, we analyzed stochastic chaos and Hopf bifurcation of stochastic Bonhoeffer–van der Pol (SBVP for short) system with bounded random parameter of an arch-like probability density function. The modifier ‘stochastic’ here implies dependent on some random parameter. In order to study the dynamical behavior of the SBVP system, Chebyshev polynomial approximation is applied to transform the SBVP system into its equivalent deterministic system, whose response can be readily obtained by conventional numerical methods. Thus, we can further explore the nonlinear phenomena in SBVP system. Stochastic chaos and Hopf bifurcation analyzed here are by and large similar to those in the deterministic mean-parameter Bonhoeffer–van der Pol system (DM–BVP for short) but there are also some featuring differences between them shown by numerical results. For example, in the SBVP system the parameter interval matching chaotic responses diffuses into a wider one, which further grows wider with increasing of intensity of the random variable. The shapes of limit cycles in the SBVP system are some different from that in the DM–BVP system, and the sizes of limit cycles become smaller with the increasing of intensity of the random variable. And some biological explanations are given.