in wireless sensor networks, optimal consumptionof energy and having maximum life time are important factors. in this article attempt has been made to send the data packets with particular reliability from the beginning based on aodv protocol. in this way two new fields add to the routing packets and during routing and discovering of new routes, the lowest remained energy of nodes and route tra...

premature ventricular contraction (pvc) is one of the common cardiac arrhythmias. the occurrence of pvc is dangerous in people who have recently undergone heart. a pvc beat can easily be diagnosed by a doctor based on the shape of the electrocardiogram signal. but in automatic detection, extracting several important features from each beat is required. in this paper, a method for automatic dete...

community detection is a task of fundamental importance in social network analysis. community structures enable us to discover the hidden interactions among the network entities and summarize the network information that can be applied in many applied domains such as bioinformatics, finance, e-commerce and forensic science. there exist a variety of methods for community detection based on diffe...

a novel algorithm for the fast detection of hubs in chemical networks is presented. thealgorithm identifies a set of nodes in the network as most significant, aimed to be the mosteffective points of distribution for fast, widespread coverage throughout the system. we showthat our hubs have in general greater closeness centrality and betweenness centrality thanvertices with maximal degree, while...

the proposed iafc neural networks have both stability and plasticity because theyuse a control structure similar to that of the art-1(adaptive resonance theory) neural network.the unsupervised iafc neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. this fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. the supervised iafc ...

in recent years, researches on reinforcement learning (rl) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. neural network reinforcement learning (nnrl) is among the most popular algorithms in the rl framework. the advantage of using neural networks enables the rl to search for optimal policies more efficiently in several real-life applicat...