40389264
Application of Efficient Numerical Methods in Solution of Ordinary Differential Equations for Modeling Electrical Activity in Cardiac Cells
There is a large number of ordinary differential equations (ODEs) characterize the electrical behavior generated by ionic movements in human myocardial cell. In this paper, several approaches were investigated in order to improve the efficiency of solving the ODE systems for ten Tusscher et al.’s ionic model of human ventricular tissue. By using non-standard finite difference (NSFD) scheme, the stiffness of the ODEs system will be successfully reduced, so a larger step-size can be used. A popular multi-step method called backward differentiation formulation (BDF) was also incorporated into the computational model for testing the largest possible time steps. The results show that NSFD can be as much as 10 times more efficient than standard forward Euler in single cell model simulation while maintaining an acceptable level of accuracy. The investigation of BDF method shows that a large step size is not recommended for the single cell simulation application. All solvers were coupled to the partial differential equations for the complete simulation of heart tissue, and such computation scheme may be a good calculation technique in heart modeling and simulation.
36668943
Parallel Solution in Simulation of Cardiac Excitation Anisotropic Propagation
Solution in simulation of cardiac excitation anisotropic propagation throughout the ventricular myocardium is computationally very expensive that demands the introduction of a high performance computing techniques. In this study, a canine ventricle model was constructed features a realistic anatomical structure, including intramural fiber rotation and a conduction system. By using operator-splitting scheme, adaptive time step and backward differentiation formulation techniques in a parallel implement, we solved mondomain equation successfully. The stimulation produced isochrone's map is close to the clinical record that obtained from the non-contact mapping system of Ensite 3000. The results show that the proposed methods can successfully be used to simulate heart excitation anisotropic propagation in three-dimensional anatomical large tissue size.
40155382
Efficient Solution of Bidomain Equations in Simulation of Cardiac Excitation Anisotropic Propagation
Bidomain equations are used to characterize myocardial physiological activation and propagation. Their numerical solution is costly computation because of the higher temporal and spatial discretization requirements, especially in three dimensions. In most previous studies, the heart was supposed to be homogeneous isotropic medium, and thus can use the mondomain equation in stead of the bidomain equations to simulate the heart excitation propagation. Simulation of heart excitation anisotropic propagation in three-dimensional large tissue size by solving bidomain equations has not been implemented yet. In this paper, we present an efficient solution of bidomain equations in simulation of heart excitation anisotropic propagation by combining some numerical techniques such as non-standard finite difference (NSFD), domain decomposition and multigrid methods. The results show that the proposed method can successfully be used to simulate heart excitation anisotropic propagation in three-dimensional large tissue size, and it suggests that such method may provide a good basis for heart simulation research in a more physiologically way.
15870104
Homomorphism Resolving of XPath Trees Based on Automata
As a query language for navigating XML trees and selecting a set of element nodes, XPath is ubiquitous in XML applications. One important issue of XPath queries is containment checking, which is known as a co-NP complete. The homomorphism relationship between two XPath trees, which is a PTIME problem, is a sufficient but not necessary condition for the containment relationship. We propose a new tree structure to depict XPath based on the level of the tree node and adopt a method of sharing the prefixes of multi-trees to construct incrementally the most effective automata, named XTHC (XPath Trees Homomorphism Checker). XTHC takes an XPath tree and produces the result of checking homomorphism relationship between an arbitrary tree in multi-trees and the input tree, thereinto the input tree is transformed into events which force the automata to run. Moreover, we consider and narrow the discrepancy between homomorphism relationship and containment relationship as possible as we can.
10873376
Efficient Modeling of An Anatomy-Based Face and Fast 3D Facial Expression Synthesis
This paper presents new methods for efficient modeling and animation of an hierarchical facial model that conforms to the human face anatomy for realistic and fast 3D facial expression synthesis. The facial model has a skin–muscle–skull structure. The deformable skin model directly simulates the nonlinear visco-elastic behavior of soft tissue and effectively prevents model collapse. The construction of facial muscles is achieved by using an efficient muscle mapping approach. Based on a cylindrical projection of the texture-mapped facial surface and wire-frame skin and skull meshes, this approach ensures different muscles to be located at the anatomically correct positions between the skin and skull layers. For computational efficiency, we devise an adaptive simulation algorithm which uses either a semi-implicit integration scheme or a quasi-static solver to compute the relaxation by traversing the designed data structures in a breadth-first order. The algorithm runs in real-time and has successfully synthesized realistic facial expressions. 
 
 
 
ACM CSS: I.3.5 Computer Graphics: Computational Geometry and Object Modelling—physically based modelling; I.3.7 Computer Graphics: Three-Dimensional Graphics and Realism—animation;
10896727
Firefly: illuminating future network-on-chip with nanophotonics
Future many-core processors will require high-performance yet energy-efficient on-chip networks to provide a communication substrate for the increasing number of cores. Recent advances in silicon nanophotonics create new opportunities for on-chip networks. To efficiently exploit the benefits of nanophotonics, we propose Firefly - a hybrid, hierarchical network architecture. Firefly consists of clusters of nodes that are connected using conventional, electrical signaling while the inter-cluster communication is done using nanophotonics - exploiting the benefits of electrical signaling for short, local communication while nanophotonics is used only for global communication to realize an efficient on-chip network. Crossbar architecture is used for inter-cluster communication. However, to avoid global arbitration, the crossbar is partitioned into multiple, logical crossbars and their arbitration is localized. Our evaluations show that Firefly improves the performance by up to 57% compared to an all-electrical concentrated mesh (CMESH) topology on adversarial traffic patterns and up to 54% compared to an all-optical crossbar (OP XBAR) on traffic patterns with locality. If the energy-delay-product is compared, Firefly improves the efficiency of the on-chip network by up to 51% and 38% compared to CMESH and OP XBAR, respectively.
16356479
A multi-agent simulation for social agents
Agent-based modeling of human social behavior is an increasingly important research area. Many fully functional multi-agent systems have been developed and have been put to use over the years. But efficient scalable and robust social systems are difficult to engineer, both from the modeling perspective and the implementation perspective. There exist three important difficulties. First, the system needs to have an adaptable agent framework that can successfully make intuitive and deliberative decisions much like a real social participant would. Secondly, the system must have a robust architecture that not only ensures its functioning no matter the simulation, but also provides an easily understood interface that researchers can interact with while running their simulations. Finally, the system must be effectively distributed to handle the necessary number of agents that social research requires to obtain meaningful results. This paper presents our work on creating a multi-agent simulation for social agents that would overcome these three difficulties. Lastly, we present a simulation to test the system and provide the results of that simulation.
52849739
Inverse System Decoupling Control for Induction Motor Based on Neural Network On-Line Learning
The induction motor is a MIMO, nonlinear and high coupling system. The reversibility of the induction motor is testified. Consequently, a pseudo-linear system is completed by constructing a neural network inverse (NNI) system and combining it with the motor system. The inverse can transform the MIMO nonlinear system into two SISO linear subsystems (i.e., rotor speed and flux subsystems). In order to approach the inversion exactly in operation of the motor, the control method online learning based on NNI system is proposed, in which connection value can be amended continuously on-line to make the NN adapt to the changes of environment to strengthen its robustness. Simulation and experiment results have shown that NN can be adjusted in the control process. The good applicability of NN along with the strong stability and robustness of the system can be achieved by using the proposed method.