Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of the user for user authentication. Back Propagation Neural Network (BPNN) and the Probabilistic Neural Network (PNN) are used as a classifier to discriminate between the authentic and impostor users. Furthermore, four keystroke dynamics features namely: Dwell Time (DT), Flight Time (FT), Up-Up Time (UUT), and a mixture of (DT) and (FT) are extracted to verify whether the users could be properly authenticated. Two datasets (keystroke-1) and (keystroke-2) are used to show the applicability of the proposed Keystroke dynamics user authentication system. The best results obtained with lowest false rates and highest accuracy when using UUT compared with DT and FT features and comparable to combination of DT and FT, because of UUT as one direct feature that implicitly contained the two other features DT, and FT; that lead to build a new feature from the previous two features making the last feature having more capability to discriminate the authentic users from the impostors. In addition, authentication with UUT alone instead of the combination of DT and FT reduce the complexity and computational time of the neural network when compared with combination of DT and FT features.
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Two field experiments were carried out for cultivating yellow maize crop Zea mays L. during the autumn planting season 2019 in two sites with soils of different textures. The first site is a loamy texture in one of the fields of the Medhatia Agriculture Division, Babylon Governorate. The second was silty loam by an alluvial mixture in one of the fields of Al-Nouriah Research Station, Ministry of Agriculture located in Al-Nouriah sub-district, Al-Qadisiyah governorate. It was found through the results that the uniformity, efficiency, and adequacy of the irrigation efficiency of the sprinkler irrigation method is better than that of the sprinkler irrigation method, and it ranged between (88.6-88.7) for uniformity and (84-86)% of the irrigatio
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Roller-Compacted Concrete is a no-slump concrete, with no reinforcing steel, no forms, no finishing and wet enough to support compaction by vibratory rollers. Due to the effect of curing on properties and durability of concrete, the main purpose of this research is to study the effect of various curing methods (air curing, 7 days water curing, and permanent water curing) and porcelanite (local material used as an Internal Curing agent) with different replacement percentages of fine aggregate (volumetric replacement) on some properties of Roller-Compacted Concrete and to explore the possibility of introducing practical Roller-Compacted Concrete for road pavement with minimum requirement of curing. Specimens were sawed fro
... Show MoreThis study aimed at evaluating the torsional capacity of reinforced concrete (RC) beams externally wrapped with fiber reinforced polymer (FRP) materials. An analytical model was described and used as a new computational procedure based on the softened truss model (STM) to predict the torsional behavior of RC beams strengthened with FRP. The proposed analytical model was validated with the existing experimental data for rectangular sections strengthened with FRP materials and considering torque-twist relationship and crack pattern at failure. The confined concrete behavior, in the case of FRP wrapping, was considered in the constitutive laws of concrete in the model. Then, an efficient algorithm was developed in MATLAB environment t
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