In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

Water injection equipments such as pipelines, which are used in the second recovery of oil in the Al-Ahdeb wells, suffer from the corrosion in water during maintaining vacuum deoxygenated tower that used to decrease concentration of the dissolved oxygen gas in the water from 6.2-9.1 ppm to o.5 ppm. This study involved calculation the corrosion rates of the internal surfaces of the pipelines either during operation of the vacuum unit or when the tower out of operation.  Finally, find the solution by one of the following suggestions. In the first suggestion removal of the dissolved O₂ from water is achieved by increasing the dosage of the oxygen scavenger (sodium sulphite). The second suggestion involves re

Water injection equipments such as pipelines, which are used in the second recovery of oil in the Al-Ahdeb wells, suffer from the corrosion in water during maintaining vacuum deoxygenated tower that used to decrease concentration of the dissolved oxygen gas in the water from 6.2-9.1 ppm to o.5 ppm. This study involved calculation the corrosion rates of the internal surfaces of the
pipelines either during operation of the vacuum unit or when the tower out of operation. Finally, find the solution by one of the following suggestions. In the first suggestion removal of the dissolved O2 from water is achieved by increasing the dosage of the oxygen scavenger (sodium sulphite). The second suggestion involves removing the dissolved O2 from w

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev