Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identifies a user based on the analysis of his/her typing rhythm. This paper utilizes keystroke features including dwell time (DT), flight time (FT), up-up time (UUT), and a mixture of theses features as keystroke representation. The back propagation neural network is trained with the mean of keystroke timing information for each character of password. These times are used to discriminate between the authentic users and impostors. Results of the experiments demonstrate that the backpropagation network with UUT features comparable to combination of DT and FT. Also, the results of backpropagation with combination of DT, FT and UUT provide low False Alarm Rate (FAR) and False Reject Rate (FRR) and high accuracy.
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Two dimensional meso-scale concrete modeling was used in finite element analysis of plain concrete beam subjected to bending. The plane stress 4-noded quadrilateral elements were utilized to model coarse aggregate, cement mortar. The effect of aggregate fraction distribution, and pores percent of the total area – resulting from air voids entrapped in concrete during placement on the behavior of plain concrete beam in flexural was detected. Aggregate size fractions were randomly distributed across the profile area of the beam. Extended Finite Element Method (XFEM) was employed to treat the discontinuities problems result from double phases of concrete and cracking that faced during the finite element analysis of concrete beam. Crac
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Poly (3-hydroxybutyrate) (PHB) is a typical microbial bio-polyester reserve material; known as “green plastics”, which produced under controlled conditions as intracellular products of the secondary metabolism of diverse gram-negative/positive bacteria and various extremophiles archaea. Although PHB has properties allowing being very attractive, it is too expensive to compete with conventional and non-biodegradable plastics. Feasibility of this research to evaluate the suitability of using a watermelon-derived media as an alternative substrate for PHB synthesis under stress conditions was examined. Results, include the most nutrients extraction, indicated that the watermelon seeds contain a high content of nutrients makes them a promisi
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In the present work, a kinetic study was performed to the extraction of phosphate from Iraqi Akashat phosphate ore using organic acid. Leaching was studied using lactic acid for the separation of calcareous materials (mainly calcite). Reaction conditions were 2% by weight acid concentration and 5ml/gm of acid volume to ore weight ratio. Reaction time was taken in the range 2 to 30 minutes (step 2 minutes) to determine the reaction rate constant k based on the change in calcite concentration. To determine value of activation energy when reaction temperature is varied from 25 to 65 , another investigation was accomplished. Through the kinetic data, it was found that selective leaching was controlled by surface chemical reactio
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
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The transportation model is a well-recognized and applied algorithm in the distribution of products of logistics operations in enterprises. Multiple forms of solution are algorithmic and technological, which are applied to determine the optimal allocation of one type of product. In this research, the general formulation of the transport model by means of linear programming, where the optimal solution is integrated for different types of related products, and through a digital, dynamic, easy illustration Develops understanding of the Computer in Excel QM program. When choosing, the implementation of the form in the organization is provided.