This study presents determination of the paleostress magnitudes and orientation of Bekhme Structure in Shaqlawa area northeastern Iraq. Paleostress Analysis of slip-fault measurements is performed using Right dihedral, Lisle diagram and Mohr Circles methods. Depending on Mohr Circles, Bott law and vertical thickness, the magnitudes of the paleostress at the time of the tectonic activity were determined. Firstly, Georient Software was used to estimate the orientation of the paleostresses (σ1, σ2 and σ3). Secondly, using the rupture –friction law, taking into account depth of the overburden and the vertical stress (σv) was calculated to determine the magnitude of the paleostresses (σ1=4500 bars, σ2=1900 bars and σ3=700 bars). The high magnitudes of the principal stress axes may be referred to the active tectonic events which led to the deformation of the area during Cretaceous and Tertiary periods. The study area shows that the poles of the measured faults lie in the reactivated area of Mohr circles. This indicates the unstability of the study area. The study area is important, due to possibility of exiting of the hydrocarbon is deposited. Fold- Thrust belt mark the deformation fronts of the major orogeny that form from the collision of Arabian Plate with Turkish and Iranian Plates.
Photodetector based on Rutile and Anatase TiO2 nanostructures/n-Si Heterojunction
Abstract Background: Timely diagnosis of periodontal disease is crucial for restoring healthy periodontal tissue and improving patients’ prognosis. There is a growing interest in using salivary biomarkers as a noninvasive screening tool for periodontal disease. This study aimed to investigate the diagnostic efficacy of two salivary biomarkers, lactate dehydrogenase (LDH) and total protein, for periodontal disease by assessing their sensitivity in relation to clinical periodontal parameters. Furthermore, the study aimed to explore the impact of systemic disease, age, and sex on the accuracy of these biomarkers in the diagnosis of periodontal health. Materials and methods: A total of 145 participants were categorized into three groups based
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RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
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In this paper a new method is proposed to perform the N-Radon orthogonal frequency division multiplexing (OFDM), which are equivalent to 4-quadrature amplitude modulation (QAM), 16-QAM, 64-QAM, 256-QAM, ... etc. in spectral efficiency. This non conventional method is proposed in order to reduce the constellation energy and increase spectral efficiency. The proposed method gives a significant improvement in Bit Error Rate performance, and keeps bandwidth efficiency and spectrum shape as good as conventional Fast Fourier Transform based OFDM. The new structure was tested and compared with conventional OFDM for Additive White Gaussian Noise, flat, and multi-path selective fading channels. Simulation tests were generated for different channels
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Objective of this work is the mixing between human biometric characteristics and unique attributes of the computer in order to protect computer networks and resources environments through the development of authentication and authorization techniques. In human biometric side has been studying the best methods and algorithms used, and the conclusion is that the fingerprint is the best, but it has some flaws. Fingerprint algorithm has been improved so that their performance can be adapted to enhance the clarity of the edge of the gully structures of pictures fingerprint, taking into account the evaluation of the direction of the nearby edges and repeat. In the side of the computer features, computer and its components like human have uniqu
... Show MoreNowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor
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