Accurate Intrusion Detection Based On Feature Optimization Using Plant Grow Algorithm

The process of features reduction enhanced the performance of the intrusion detection system. Nowadays used various features reduction algorithms are used for static as well as dynamic features reduction. The feature reduction technique behaves in dual mode. The reduction of features cannot have fixed how many features are reducing for the better detection process of intrusion. The process of features reduction used plant grow optimization algorithm and classification using support vector machine algorithm

Control of vortex shedding behind circular cylinder for flows at low reynolds numbers

It has been observed by researchers in the past that vortex shedding behind circular cylinders can be altered, and in some cases suppressed, over a limited range of Reynolds numbers by proper placement of a second, much smaller, 'control' cylinder in the near wake of the main cylinder. Results are presented for numerical computations of some such situations. A stabilized finite element method is employed to solve the incompressible Navier-Stokes equations in the primitive variables formulation. At low Reynolds numbers, for certain relative positions of the main and control cylinder, the vortex shedding from the main cylinder is completely suppressed. Excellent agreement is observed between the present computations and experimental findings of other researchers. In an effort to explain the mechanism of control of vortex shedding, the streamwise variation of the pressure coefficient close to the shear layer of the main cylinder is compared for various cases, with and without the control cylinder. In the cases where the vortex shedding is suppressed, it is observed that the control cylinder provides a local favorable pressure gradient in the wake region, thereby stabilizing the shear layer locally

Study about Power Filters in Power System Quality and Stability Enhancement

The excessive power electronics devices in the distribution systems have evolved the problem of power quality. Arc Furnaces, Variable Frequency Drives (VFD), Computer power supplies play a major role in the deterioration in the quality power by injecting harmonics in the utility supply source. Extensive use of non-linear loads leads to a multitude of unwanted harmonics in the operation of the electrical system. Of these, the harmonics of current and voltage are the most significant. in this paper presented is the power quality and the Shunt Active Power Filter and the description of the Harmonics and Its Effects

A Survey on Performance Improvement of Data Analysis Using Unsupervised K-Means Clustering

The algorithms clustering implemented on the machines and made intelligent machines are called unsupervised machine learning algorithms. They can perform essential tasks by k-means clustering algorithm based on improved quantum particle swarm optimization algorithm is often more error in data analysis. As more data becomes available, more complex problems can be tackled and solved. The analysis of patient's data is becoming more critical to evaluate the patient's medical condition and prevent and take precautions for the future. With the help of technology and computerized automation of machines, data can be analyzed more efficiently. Managing the massive volume of data has many problems interrelated to data security. Experiments on actual datasets show that our technique will get similar results with standard ways with fewer computation tasks. Process mining and data mining techniques have opened new access for the diagnosis of disease. Similarly, data mining can provide effective treatment for a disease's triennial prevention; finally, an effective clustering result is obtained. The algorithm is tested with the UCI data set. The results show that the improved algorithm ensures the global convergence of the algorithm and brings more accurate clustering results