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<p><span>Wireless Ad Hoc Network is a dynamically organized network on emergency situations, in which a group of wireless devices send data among themselves without requiring any base stations for forwarding data. Here the nodes itself perform the functions of routing. This important characteristic of mobile ad hoc networks allows the hassle free set up of the network for communications in different crisis such as battlefield and natural disaster zones. Multi hop communication in MANET is achieved by the cooperation of nodes in forwarding data packets. This feature of MANET is largely exploited to launch a security attack called black hole attack. A light weight solution called SEC-DSR is proposed to defend the network from black hole attack and enables communication among nodes even in the presence of attackers. In this scheme, by analyzing only the control packets used for routing in the network, the compromised nodes launching the attack are identified. From the collective judgment by the participating nodes in the routing path, a secure route free of black hole nodes is selected for communication by the host. Simulation results validate and ensure the effectiveness of the proposed solution tested on an ad hoc network with compromised black hole nodes.</span></p>

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ABSTRACT:The main purpose of this paper should be to show that the outer frame of a leaf and with the help of Back propagation Network is enough to give a reasonable statement about the species category is identified. Leaves Recognition is a neuronal network based java application/applet to recognize images of leaves using Back propagation Network. The intention is to give the user the ability to administrate a hierarchical list of images, where they can perform some sort of image using edge detection to identify the individual tokens of every image. The Thinning algorithm here is used to process the image recursively and minimizes the found lines to a one-pixel wide one by comparing the actual pixel situation with specific patterns can be identified and then minimizes it. The urgent situation is that due to environmental degradation and lack of awareness, many rare plant species are at the risk of extinction so it is necessary to keep record for plant protection. It focuses on using digital image processing for the purpose of automate classification and recognition of plants based on the images of the leaves. It help to protect the plant and mainly it is used for highly production of rare plant or herbal plant used for medical purpose. Efficacy of the proposed methods is studied by using two neural classifiers. These are neuro-fuzzy controller and a feed-forward back-propagation multi-layered perception to discriminate between 28 classes of leaves. The features have been applied individually as well as in combination to investigate how recognition accuracies can be improved with the help of B&T algorithm.

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