Dilli Raj Neupane
Numerical Accuracy of Secant Method has been calculated by finding the value of square roots of natural numbers from 1 to 25 with two initial guesses, x0 = 0.9 and x1=6.0. Lowest percentage error has been obtained in the calculation of square roots of 9, 16 and 25. Highest percentage error has been obtained in the calculation of square root of 17 and is equal to 0.000025546811. Average percentage error in secant method in the calculation of square roots of natural numbers from 1 to 25 has been found to be 0.000005455409.
Mohamed Al kilani and Volodymyr Kobziev
Today, with the revolution of technology the Information and Communication technology ICT become one of the active technologies that provide government services through websites and smart phones, to its citizen. Transfer to e-government depends on a number of issues must be clarified. In this paper Libyan e-government factors (needed) has been discussed. According to Libyan environment, TOE (technology–organization– environment) has been assigned to support propositions that can affect adoption of egovernment in Libya. TOE model helps to figure out the relationship between factors that needed to adoption e-government, these factors are: Technological Factors, Organizational Factors, and Environmental Factors.
B. Ben Sujitha and V. Kavitha
The growing importance of network security is shifting security concerns towards the network itself rather than being just host-based. Security services must be evolving into network-based and distributed approaches to deal with heterogeneous open platforms and support scalable solutions. Intrusion detection based upon computational intelligence is currently attracting considerable interest from the research community. Evolutionary computation systems provides adaptation, fault tolerance, high computational speed and error resilience in the face of noisy information fit the requirements of building a good intrusion detection model. In this review paper, the new intended IDS is prescribed as Agent which can automate the process of detection as well as new type of attack can be detected. The newly proposed system can be build using Genetic algorithm which is integrated with PCA for fast transformation of data and reduced set of data.
Sanjay Gaur and Mukta Agarwal
Data preparation is a fundamental stage of data mining. Completeness, quality and real world data preparation is a pre- requirement for efficiency in data mining. Analysis and the application of a solution to new data, is difficult in the data with missing value. It also affects loss of accuracy of mediatory result and calculation. To overcome this situation some statistical techniques are applied for the data preparation .In present study we introduce one sequential method by which missing values are replaced through estimated value. This method is based on motile middling method, which is very much suitable for numerical variables of the time series data.