-This paper describes the development and implementation of feature selection for content based image retrieval. We are working on CBIR system with new efficient technique. In this system, we use multi feature extraction such as colour, texture and shape. The three techniques are used for feature extraction such as colour moment, gray level cooccurrence matrix and edge histogram descriptor. To reduce curse of dimensionality and find best optimal features from feature set using feature selection based on genetic algorithm. These features are divided into similar image classes using clustering for fast retrieval and improve the execution time. Clustering technique is done by k-means algorithm. The experimental result shows feature selection using GA reduces the time for retrieval and also increases the retrieval precision, thus it gives better and faster results as compared to normal image retrieval system. The result also shows precision and recall of proposed approach compared to previous approach for each image class. The CBIR system is more efficient and better performs using feature selection based on Genetic Algorithm.

Image segmentation algorithms and techniques find its applications in a wide number of domains. Segmentation of brain tumor and overall internal structure of the brain is one of the main applications in the field of medical imaging. Magnetic resonance imaging (MRI) technique is one of the many imaging modalities that are available to scan and capture the internal soft tissue structures of the body. In this paper, proposed technique has been given to extract the tumor portion, successfully demarcate the tumor boundary, locate the tumor with a bounding circle and to diagnose whether the tumor is present or absent. A fuzzy clustering-based technique is proposed which helps to study & analyze the intricate structure of the brain, hence can be used as a visual analysis and a study tool. General TermsImage Processing, Pattern Recognition Keywords MRI, Magnetic resonance imaging, image segmentation, fuzzy clustering, thresholding INTRODUCTIONMagnetic resonance imaging (MRI) technique is one of the many available imaging modalities like CT-Scan, Mammography, and X-Ray. It provides visual details about the anatomy and the overall structure of the brain. An MRI scan can be used to study the supply of blood inside the brain. Hence MRI technology becomes an important tool for detecting abnormality, tracking the progress or growth of the disease and for diagnosis too. Processing digital images by means of a digital computer comprises digital image processing domain [1].Brain tumors are caused due to abnormal, uncontrolled growth of cells. Primary tumors are those that originate in the brain. Secondary tumors are those that originate in some other part of the body, finally reaching the brain through the process of metastasis.The symptoms of brain tumors include headache, nausea, vomiting, personality and behavioral changes, memory loss, sensory disturbance, weakness, numbness [2]. MRI ScanMRI is a fairly new technique that has been used since the beginning of the 1980s. The MRI scanner uses magnetic and radio waves to create pictures of tissues, organs and other structures within the body, which can then be viewed on a computer. There is no exposure to X-rays or any other damaging forms of radiation in MRI.The pictures produced by an MRI scan are better in displaying fine details and therefore are of higher diagnostic quality when compared to more frequently used X-ray scanners for example. Utility of MRI ImagesUsing an MRI scanner, it is possible to make pictures of almost all the tissue in the body. The tissue that has the least hydrogen atoms (such as bones) turns out dark, while the tissue that has many hydrogen atoms (such as fatty tissue) looks much brighter.By changing the timing of the radio wave pulses, it is possible to gain information about the different types of tissues that are present.An MRI of the brain and spinal cord can be performed to look at different abnormalities, as it can provide clear images of these structures in spite of being surrounded by bone tissue. Changes within the tissues of brain, ...

-In intelligent transportation systems, the collaboration between vehicles and the road side units is essential to bring these systems to realization. The emerging Vehicular Ad Hoc Network (VANET) is becoming more and more important as it provides intelligent transportation application, comfort, safety, entertainment for people in vehicles. In order to provide stable routes and to get good performance in VANET, there is a need of proper routing protocols must be designed. In this paper, we are working with the very well-known ad-hoc on-demand distance vector (AODV) routing protocol. The existing Routing protocol AODV-L which is based on the Link expiration time is extended to propose a more reliable AODV-AD which is based on multichannel MAC protocol. For the performance evaluation of routing protocols, a simulation tool 'NS2' has been used. Simulation results show that the proposed AODV-AD protocol can achieves better performances in forms of high Route stability, Packet Delivery ratio and packet loss rate than traditional AODV-L and traditional AODV.

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Abstract--Wireless ad-hoc sensor networks has become crucial for everyday functioning of people and organizations. Due to their adhoc organization they are vulnerable to denial-of-service attacks. The most permanent DoS attack is to entirely exhaust nodes' batteries, called "Vampire" Attacks. These vampire attacks are not impacting any specific kind of protocols. Detection of vampire attacks in the network is not easy. A single Vampire may even increase network energy usage by a factor of O(N),where N is the number of network nodes. We discuss existing routing protocols to mitigate resource draining attacks.