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Reverberant signal separation using optimized complex sparse nonnegative tensor deconvolution on spectral covariance matrix
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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Spectral fluctuations in <sup>24</sup>Mg nucleus using the framework of the nuclear shell model
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Abstract<p>Random matrix theory is used to study the chaotic properties in nuclear energy spectrum of the <sup>24</sup>Mg nucleus. The excitation energies (which are the main object of this study) are obtained via performing shell model calculations using the OXBASH computer code together with an effective interaction of Wildenthal (W) in the isospin formalism. The <sup>24</sup>Mg nucleus is assumed to have an inert <sup>16</sup>O core with 8 nucleons (4protons and 4neutrons) move in the 1d<sub>5/2</sub>, 2s<sub>1/2</sub> and 1d<sub>3/2</sub> orbitals. The spectral fluctuations are studied by two statistical measures: the nearest neighb</p> ... Show More
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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Controlled Release Floating Matrix Tablet of Captopril
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The present study was done to prepare a gastroretentive floating tablet of captopril (CAP) which is an angiotensin converting enzyme inhibitor (ACE-inhibitor) used in the treatment of hypertension and heart failure. CAP is mainly absorbed from the proximal intestine and to a lesser extent from the stomach, also CAP stability decreases as the pH raised above 1.2 and this makes it a suitable candidate for floating dosage form.Effervescent floating tablets of CAP were prepared in order to prolong the gastric residence time and increase the bioavailability of the drug. The floating tablets of CAP were prepared by direct compression and wet granulation technique, using the polymer hydroxypropylmethylcellulose (HPMC) as the primary retarding p

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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
Effect of electrode separation in magnetron DC plasma sputtering on grain size of gold coated samples
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In this work, an experimental research on a low voltage DC magnetron plasma sputtering (0-650) volt is used for coating gold on a glass substrate at a constant pressure of argon gas 0.2 mbar and deposition time of 30 seconds. We focused on the effects of operating conditions for the system such as, electrode separation and sputtering current on coated samples under the influence of magnetic flux. Electron temperature and electrons and ions densities are determined by a cylindrical single Langmuir probe. The results show the sensitivity of electrode separation lead to change the plasma parameters. Furthermore, the surface morphology of gold coated samples at different electrode separation and sputtering current were studied by atomic forc

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Publication Date
Tue Dec 10 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Development of Robust and Efficient Symmetric Random Keys Model based on the Latin Square Matrix
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Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Influence of fly ash on the volumetric and physical properties of Stone Matrix Asphalt Concrete
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Stone Matrix Asphalt (SMA) is a gap-graded asphalt concrete hot blend combining high-quality coarse aggregate with a rich asphalt cement content. This blend generates a stable paving combination with a powerful stone-on-stone skeleton that offers excellent durability and routing strength. The objectives of this work are: Studying the durability performance of stone matrix asphalt (SMA) mixture in terms of moisture damage and temperature susceptibility and Discovering the effect of stabilized additive (Fly Ash ) on the performance of stone matrix asphalt (SMA) mixture. In this investigation, the durability of stone matrix asphalt concrete was assessed in terms of temperature susceptibility, resistance to moisture damage, and sensitivity t

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Publication Date
Tue May 31 2022
Journal Name
Iraqi Geological Journal
The Impact of Matrix Acidizing on the Petrophysical Properties of the Mishrif Formation: Experimental Investigation
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Matrix acidizing is a good stimulation process in which acid is introduced into the reservoir near the wellbore area via the wellbore or coil tubing. In the oil industry, formation damage is a prevalent problem. Bypassing wellbore damage by producing wormholes in carbonate reservoirs is the main purpose of acidizing the matrix of the formation. When doing lab tests, scientists are looking for a wormhole-inducing injection rate that can be used in the field. Meantime the ongoing works on the Ahdeb oil field's Mishrif reservoir, several reports have documented the difficulties encountered during stimulation operations, including high injection pressures that make it difficult to inject acid into the reservoir formation; and only a few

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Study the Effect of Different Reinforcements on the Damping Properties of the Polymer Matrix Composite
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In this research, damping properties for composite materials were evaluated using logarithmic decrement method to study the effect of reinforcements on the damping ratio of the epoxy matrix. Three stages of composites were prepared in this research. The first stage included preparing binary blends of epoxy (EP) and different weight percentages of polysulfide rubber (PSR) (0%, 2.5%, 5%, 7.5% and 10%). It was found that the weight percentage 5% of polysulfide was the best percentage, which gives the best mechanical properties for the blend matrix. The advantage of this blend matrix is that; it mediates between the brittle properties of epoxy and the flexible properties of a blend matrix with the highest percentage of PSR. The second stage

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Spectral Technique for Baud Time Estimation
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A new approach for baud time (or baud rate) estimation of a random binary signal is presented. This approach utilizes the spectrum of the signal after nonlinear processing in a way that the estimation error can be reduced by simply increasing the number of the processed samples instead of increasing the sampling rate. The spectrum of the new signal is shown to give an accurate estimate about the baud time when there is no apriory information or any restricting preassumptions. The performance of the estimator for random binary square waves perturbed by white Gaussian noise and ISI is evaluated and compared with that of the conventional estimator of the zero crossing detector.

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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