A new technique presents to improve the performance of dynamic voltage restorer (DVR) for voltage sag mitigation. This control scheme is based on cuckoo search algorithm with tree fuzzy rule based classifier (CSA-TFRC). CSA is used for optimizing the output of TFRC so the classification output of the network is enhanced. While, the combination of cuckoo search algorithm, fuzzy and decision tree...

Cuckoo hashing is a highly practical dynamic dictionary: it provides amortized constant insertion time, worst case constant deletion time and lookup time, and good memory utilization. However, with a noticeable probability during the insertion of n elements some insertion requires Ω(log n) time. Whereas such an amortized guarantee may be suitable for some applications, in other applications (su...

Parasites can have dramatic effects on life-history decisions of hosts such as timing of reproduction, clutch size, and investment in individual offspring, depending on the timing of parasite effects on host fitness. Moreover, parasites may influence the optimum values of important life-history traits such as clutch size and brood size by having different fitness effects for large and for small...

Cleptoparasitic wasps and bees smuggle their eggs into the nest of a host organism. Here the larvae of the cleptoparasite feed upon the food provision intended for the offspring of the host. As cleptoparasitism incurs a loss of fitness for the host organism (offspring of the host fail to develop), hosts of cleptoparasites are expected to exploit cues that alert them to potential cleptoparasite ...

About 10,000 arthropods live as ants' social parasites and have evolved a number of mechanisms allowing them to penetrate and survive inside the ant nests. Many of them can intercept and manipulate their host communication systems. This is particularly important for butterflies of the genus Maculinea, which spend the majority of their lifecycle inside Myrmica ant nests. Once in the colony, cate...

Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. These networks can be trained with gradient descent back propagation. The algorithm is not definite in finding the global minimum of the error function since gradient descent may get stuck ...