Yeshwantrao Chavan College of Engineering

About: Yeshwantrao Chavan College of Engineering is a based out in . It is known for research contribution in the topics: Inverter & Microstrip antenna. The organization has 632 authors who have published 586 publications receiving 4037 citations.

Wavelet-based tolerance near set approach in classifying hand images: A review

Abstract: A wavelet-based tolerance Nearness Measure (tNM) makes possible to measure fine-grained changes in shapes in pairs of images. The image correspondence utilizes image matching tactics to establish closeness between two or more images. This is one of the central tasks in computer vision. The problem considered that how can we measure the nearness or apartness of digital images. In case when it is important to detect conversion in the contour, position, and approximal orientation of bounded regions. However, the solution of this problem is that results from an application of anisotropic (direction dependent) a tolerance and wavelets near set approach to detecting affinities in pairs of images. It has been shown that tolerance near sets can be used in a concept-based approach to discovering correspondences between images. In this paper we are showing detail survey on near set approach. By near set approach an effective means of images is nothing but grouping together that correspond to each other relative to diminutive similarities in the features of bounded regions in the images.

Detection of DOM-Based XSS Attack on Web Application

Abstract: Cross-Site Scripting (XSS) is one of the huge issues of any Web-based or Online applications. In this attack, the attacker uses malicious code to intercept the information through users web application and sends it to the corresponding web server. This is possible because web browsers are capable of executing the instructions stored in Web pages. This enables the attackers to make use of this feature, so as to execute the malicious code in a user’s Web browsing application. This attack if happened, may result in very slow and poor web surfing. It is also capable of stealing the cookies, passwords and other personal information of the user. These kind of attacks are very easy in terms of implementation but the prevention or detection of this attack is a challenging task. In this paper firstly the existing research on the prevention of XSS is presented. Then a framework is proposed to detect the XSS, which can provide a legitimate solution for the mitigation of the attack.

FPGA implementation of modular architecture for packet classification using field split algorithm

Abstract: Packet classification has proved to be an important challenge in network processing. It requires comparing each packet with rules and forwarding the packet according to the highest priority matching rule. The criteria are comprised of a set of rules that specify the content of specific packet header fields to either software or hardware. Packet classification is widely used as a core function for various applications in networking. So increase demands in throughput and reduce latency. Also the performance of today's packet classification solutions depends on the rule sets. In this paper, we propose a modular Bit-Vector (BV) based architecture to perform high-speed packet classification on Field Programmable Gate Array (FPGA) Matching packets with some predefined rules using XillinxISE13.2 software.

Evolution of Ultra Wide-Band Swastik Shaped Monopole Antenna for Cognitive Radio Applications

Abstract: The proposed antenna designed specifically for Cognitive radio applications consists of a circular monopole which is evolved into the Swastika shaped dotted monopole by incorporating slots into the plane circular monopole which enhances the band width as well as gain. This ultra-wideband sensing antenna covers the spectrum from 3.425 GHz - 14.99 GHz [11.53GHz] with a gain of 6.18dBi as against 10.56GHz bandwidth of plane circular monopole with a gain of 2.17dBi. Simulated results are presented and find in good agreement with the expected results.

Wavelet based fast fractal image compression

Abstract: Image compression is a significant technology in the transmission and storage of digital images The importance of image compression is that to preserve the visual feature of the image One of the finest image compression techniques is using wavelet transform which have comparatively had several benefits over other Basically wavelets are confined in both time and frequency Wavelet transformations perform multilevel decomposition of image that is diving image into sub parts of image at different measures Discrete wavelet transform examined the signal at a different frequency bandwidth that is approximate band and detail band Using wavelet with balance resolution at any time and frequency gives a better signal illustration using multilevel analysis Therefore, at very low bit rate the suggested method improves the visual feature of decoded image