Abstract: The Session Initiation Protocol (SIP) is an application-layer control protocol which is used to create, alter and cease multimedia sessions. These multimedia sessions include call and video conferences, Internet telephony and other such events. In general, SIP has centralized videoconference system, which faces the drawbacks of scalability and bandwidth. When there is a need to have a multimedia conference on a large-scale, the issue of excessive load on Conference Server (CS) must be resolved. In this paper we deal with this bottleneck issue on Conference Server by examining the shortcomings of current multimedia conference model. We propose a dynamic scalable model for SIP-based conferences DSMVC (Dynamic Scalable Model for Video Conferencing), which will help us reducing the traffic from CS. In this model, clients act as a CS rather than using a one CS for every client. As a result, when the number of clients increases, the number of CS increases accordingly. Since hosts play a role of CS in this model, they need to communicate with each other and in order to do that, a client needs to know the IP address of an appropriate networking partner. DSMVC request-routing helps a client identifying the IP address of its suitable partner. We analyze the load on the network and thus assess the scalability of the conference system. By simulation of the assessment, DSMVC conference system is found to have scalability for the number of clients.

Abstract: This paper presents a method to obtain an estimation of range for disparity mapping using curve fitting tool (cftool) in navigation of stereo vision autonomous vehicle. This tool is provided by Matlab software. The disparity mapping is produced by block matching algorithm Sum of Absolute Differences (SAD). The range determined by cftool will be used as a reference for navigation of autonomous vehicle. The process of camera calibration, image rectification, stereo correspondence and disparity mapping is also discussed in this paper.

Abstract: The convergence of various wireless access technologies has always been a difficult assignment because of the fact that they have emerged independently. Future vision of wireless world is an integrated network of different wireless access technologies with improved system resources utilization anywhere, anytime. WLANs are expected to complement cellular networks such as 2G or 3G in near future. Cellular networks facilitate users with high mobility but less data rate (2 Mbps) as compared to WLAN systems having higher data rate (54Mbps) but less mobility (100m). From the users’ standpoint, the convergence of WLAN and cellular systems together will help to have combined benefits from both technologies. It pledges for a renewed aim beyond 3G, to support at least: 1Gbps bandwidth in low-mobility coverage area, and 100 Mbps peak bandwidth in full mobility mode. The seamless and capable handoff between different access technologies also known as vertical handoff is crucial and remains a testing problem. In this paper, vertical handoff procedure in location-aware heterogeneous wireless access network is being proposed. An outline for the examination of vertical handoff algorithm sensitive to various mobility parameters including velocity, FSL and RSS threshold is simulated. Moreover, it is targeted to estimate the performance of vertical handoff in terms of RSS (received signal strength) measurement in converged wireless network with appropriate propagation model and is validated by the results of the simulations.

Abstract: This paper presents an approach for intrusion prevention and self-healing system for network security. The approach detects, prevents, and heals harmful events, which are the actual reasons for damage of any of the system’s components. The proposed approach explores the design and implementation of artificial immune systems (AISs) inspired by the human immune system, in solving the problem of network security. A novel approach for network security based on the combination of biological intrusion prevention (IP) and self-healing concepts is proposed. The system integrates an artificial immune intrusion prevention system for network security inspired by the immunology theory known as danger theory and adaptive immune system. The approach is based upon data inspired by the human immune system (HIS), which applied to the autonomous defense system. The present model looks at the danger model and its application to attack defense in order to create a fully decentralized model. The intrusion prevention system (IPS) analyzes the behavior of system processes and network traffic to detect harmful events. Abnormal behaviors are the actual reason for damage of any of the system’s components. The detection of the damage caused by different types of malicious events or attack profiles is used to trigger the self - healing (SH) mechanism. This system is autonomous and enhances the fault repair and system recovery.

Abstract: In the world test are conducted and checked computerized. This is the best method of conducting tests and checking the abilities of the people. Most systems are just for conducting tests that comprises of multiple choice questions this is not good approach because some questions need visual help and some need two to three lines description. We have proposed a system that not only conducts and checks tests but also designs tests. The system will allow the paper setter to design the paper that comprises of multiple choice questions (MCQs) but also the descriptive questions and true false. The results make it more attractive for educational application.

Abstract: The purpose of this article is to develop an automated imaging system for the classification between normal and abnormal tissues in medical images obtained by chest radiography scans. This research paper focuses on first and second order statistical texture parameters and shows the strength of these statistical texture parameters. Japanese Society of Radiological Technology built database was used. To reduce computational complexity, the chest radiographs sizes were scaled down by a factor of four with new dimensions 512 by 512 pixels and 256 numbers of gray levels (8-bits) by use of gray scale transformations. Fisher Coefficient and classification error probability with average correlation coefficients (POE + ACC) features selection methods and PCA, LDA and NDA features reduction methods were used to reduce features and artificial neural network classifier (ANN) was used. The results accuracy obtained by this research was nearly upto 98 percent.

Abstract: A novel video watermarking system operating in the three-dimensional wavelet transform is here presented. Specifically the video sequence is partitioned into spatio-temporal units and the single shots are projected onto the 3D wavelet domain. first a gray- scale watermark image is decomposed into a series of bitplanes that are preprocessed with a random location matrix. after that the preprocessed bitplanes are adaptively spread spectrum and added in 3D wavelet coefficients of the video shot. Our video watermarking algorithm is robust against the attacks of frame dropping, averaging and swapping. Furthermore, it allows blind retrieval of embedded watermark which does not need the original video and the watermark is perceptually invisible. The algorithm design, evaluation, and experimentation of the proposed scheme are described in this paper.

Abstract: In this paper, block-matching with Gaussian Filter adaptive technique is proposed to estimate the motion velocity displacement point in the ultrasound image. We apply the Hexagon-Diamond Displacement Point (HDDP) technique to estimate the motion displacement. The motion displacement is based on the hexagon and diamond displacement pattern search points. The displacement pattern search point is to determine the displacement of motion velocity point in the ultrasound image sequence. The motion velocity displacement point is then used as reference point to access the diagnose or problematic area. Furthermore, motion velocity displacement point will be used as reference point to measure the displacement distance from the original point. At the same time, Gaussian Filter will help to suppress the existing high level of noise in order to improve the point signal-to-noise ratio (PSNR) of the ultrasound image sequence. The experimental result shows that the Gaussian Filter helps to improve the PSNR points in the ultrasound images sequence.