Authentication is the process of determining whether someone or something is,
in fact, who or what it is declared to be. As the dependence upon computers and
computer networks grows, the need for user authentication has increased. User’s
claimed identity can be verified by one of several methods. One of the most popular
of these methods is represented by (something user know), such as password or
Personal Identification Number (PIN). Biometrics is the science and technology of
authentication by identifying the living individual’s physiological or behavioral
attributes. Keystroke authentication is a new behavioral access control system to
identify legitimate users via their typing behavior. The objective of this paper is to
provide user authentication based on keystroke dynamic in order to avoid un
authorized user access to the system. Naive Bayes Classifier (NBC) is applied for
keystroke authentication using unigraph and diagraph keystroke features. The
unigraph Dwell Time (DT), diagraph Down-Down Time (DDT) features, and
combination of (DT and DDT) are used. The results show that the combination of
features (DT and DDT) produces better results with low error rate as compared
with using DT or DDT alone.
The experiences in the life are considered important for many fields, such as industry, medical and others. In literature, researchers are focused on flexible lifetime distribution.
In this paper, some Bayesian estimators for the unknown scale parameter of Inverse Rayleigh Distribution have been obtained, of different two loss functions, represented by Suggested and Generalized loss function based on Non-Informative prior using Jeffery's and informative prior represented by Exponential distribution. The performance of estimators is compared empirically with Maximum Likelihood estimator, Using Monte Carlo Simulation depending on the Mean Square Error (MSE). Generally, the preference of Bayesian method of Suggeste
... Show MoreThe reliability of hybrid systems is important in modern technology, specifically in engineering and industrial fields; it is an indicator of the machine's efficiency and ability to operate without interruption for an extended period of time. It also allows for the evaluation of machines and equipment for planning and future development. This study looked at reliability of hybrid (parallel series) systems with asymmetric components using exponential and Pareto distributions. Several simulation experiments were performed to estimate the reliability function of these systems using the Maximum Likelihood method and the Standard Bayes method with a quadratic loss (QL) function and two priors: non-informative (Jeffery) and inform
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This research is considered one of the important researches in Maysan Governorate, as it focuses on the construction of helicopter airport project in the oil fields of the Maysan Oil Company, where the oil general companies in Maysan Governorate suffer from the cost of transporting the foreign engineering experts and the governing equipment of sustaining oil industry from Iraq's international airports to oil fields and vice versa. Private international transport companies transport foreign engineering from the oil fields to Iraqi airports and vice versa, and other international security companies take action to provide protection for foreign engineering experts during transportation. Hence, this process is very costly.
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A theoretical model is developed to determine time evolution of temperature at the surface of an opaque target placed in air for cases characterized by the formation of laser supported absorption waves (LSAW) plasmas. The model takes into account the power temporal variation throughout an incident laser pulse, (i.e. pulse shape, or simply: pulse profile).
Three proposed profiles are employed and results are compared with the square pulse approximation of a constant power.
The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for
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In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes
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