Design and evaluation of intelligent classifier based intrusion detection system

We have discovered a novel approach of intrusion detection system using an intelligent data classifier based on a self organizing map (SOM). We have surveyed all other unsupervised intrusion detection methods, different alternative SOM based techniques and KDD winner IDS methods. This paper provides a robust designed and implemented intelligent data classifier technique based on a single large size (30x30) self organizing map (SOM) having the capability to detect all types of attacks given in the DARPA Archive 1999 the lowest false positive rate being 0.04 % and higher detection rate being 99.73% tested using full KDD data sets and 89.54% comparable detection rate and 0.18% lowest false positive rate tested using corrected data sets.

The renin-angiotensin system is modulated by swimming training depending on the age of spontaneously hypertensive rats

Aim: To investigate the effects of swimming training on the renin-angiotensin system (RAS) during the development of hypertensive disease. Main methods: Male spontaneously hypertensive rats (SHR) were randomized into: sedentary young (SY), trained young (TV), sedentary adult (SA), and trained adult (TA) groups. Swimming was performed 5 times/wk/8wks. Key findings: Trained young and adult rats showed both decreased systolic and mean blood pressure, and bradycardia after the training protocol. The left ventricular hypertrophy (LVH) was observed only in the TA group (12.7%), but there was no increase on the collagen volume fraction. Regarding the components of the RAS, TV showed lower activity and gene expression of angiotensinogen (AGT) compared to SY. The TA group showed lower activity of circulatory RAS components, such as decreased serum ACE activity and plasma renin activity compared to SA. However, depending on the age, although there were marked differences in the modulation of the RAS by training, both trained groups showed a reduction in circulating angiotensin II levels which may explain the lower blood pressure in both groups after swimming training. Significance: Swimming training regulates the RAS differently in adult and young SHR rats. Decreased local cardiac RAS may have prevented the LVH exercise-induced in the TV group. Both groups decreased serum angiotensin II content, which may, at least in part, contribute to the lowering blood pressure effect of exercise training. (C) 2011 Elsevier Inc. All rights reserved.

Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.