In this paper an improved particle swarm optimization algorithm (IPSO) for electromagnetic applications is proposed. In order to overcome the drawbacks of standard PSO, some improved mechanisms for velocity updating, the exceeding boundary control, global best perturbation and the simplified quadratic interpolation (SQI) operator are adopted. To show the effectiveness of the proposed algorithm,...

We present a global payoff-based strategy updating model for studying cooperative behavior of a networked population. We adopt the Prisoner's Dilemma game and the snowdrift game as paradigms for characterizing the interactions among individuals. We investigate the model on regular, small-world, and scale-free networks, and find multistable cooperation states depending on the initial cooperator ...

Todays information systems are based on an architecture built up of object servers and client applications that are distributed in a network of multiple heterogeneous computing platforms. In this environment, distributed object-database systems provide eecient and reliable storing, querying, and updating of a large diversity of objects. The concern of this paper are database languages for unifo...

In the present scenario location updating is main problem in mobile applications. Mobile clients will be spread based on location hierarchy. Updating all mobile clients’ information at single database server faces overhead problem. To overcome this, in our approach we are providing server hierarchy for load balancing. Mobile clients generally send continuous information to servers. But if movem...

We propose a methodology, called multi-level local-global upscaling, for generating accurate upscaled models of permeabilities or transmissibilities for flow simulation in highly heterogeneous subsurface formations. The method generates an initial adapted grid based on the given fine scale reservoir heterogeneity and potential flow paths. It then applies local-global upscaling [1], along with a...

In this paper we present an interactive global illumination method for Direct Volume Rendering (DVR) based on the many-light approach, a class of global illumination methods which gained much interest recently. We extend these methods to handle transfer function and volume density updates efficiently in order to foster ability of interactive volume exploration. Global illumination techniques ac...

This paper introduces an ant colony search algorithm (ACSA) to solve the optimal network restoration problem. It is a population based approach that uses exploration of positive feedback as well as greedy search. The ACSA was inspired from natural behavior of the ant colonies on how they find the food source and bring them back to their nest by building the unique trail formation. By applying t...

This paper presents a new algorithm for solving large scale global optimization problems based on hybridization of simulated annealing and Nelder-Mead algorithm. The new algorithm is called simulated Nelder-Mead algorithm with random variables updating (SNMRVU). SNMRVU starts with an initial solution, which is generated randomly and then the solution is divided into partitions. The neighborhood...

To enhance the optimization ability of particle swarm algorithm, a novel quantum-inspired particle swarm optimization algorithm is proposed. In this method, the particles are encoded by the probability amplitudes of the basic states of the multi-qubits system. The rotation angles of multi-qubits are determined based on the local optimum particle and the global optimal particle, and the multi-qu...

Predicting the near future is important for survival and plays a central role in theories of perception, language processing, and learning. Prediction failures may be particularly important for initiating the updating of perceptual and memory systems and, thus, for the subjective experience of events. Here, we asked observers to make predictions about what would happen 5 sec later in a movie of...