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Reverberant signal separation using optimized complex sparse nonnegative tensor deconvolution on spectral covariance matrix
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Publication Date
Fri Mar 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Complex of Lascoux in Partition (3,3,2)
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In this paper, the complex of Lascoux in the case of partition (3,3,2) has been studied by using diagrams ,divided power of the place polarization ) (k ijï‚¶ ,Capelli identites and the idea of mapping Cone .

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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Design and Study of Fractal Optical Modulator for Infrared Transmitted Signal
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The optical modulator was designed by using iterated function

systems (IFSs) by IFS Construction Kit program. The modulator was inserted into the optical system using ZEMAX optical design program. In this program, it is assumed that the modulator is made from one of Ø¢ the infrared transmitting materials. Eight materials at room temperature were used in this study; these are IRTRAN materials, Si, and Ge for the range of 3-9 l-lm.

Systems were evaluated and analyzed by using different criteria,

including spot diagram, modulation transfer function, and point spread function. The effect of optical modulator change with the chang of Ø¢ its material results in focusing of functions and frequencies as requ

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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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Publication Date
Sun Mar 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Ethanol-Water Separation by Pressure Swing Adsorption (PSA)
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Single long spiral tube column pressure swing adsorption (PSA) unit, 25 mm diameter, and 6 m length was constructed to study the separation of water from ethanol at azeotropic concentration of 95 wt%. The first three meters of the column length acted as a vaporizer and the remaining length acted as an adsorber filled by commercial 3A zeolite. The effect of pressure, temperature and feed flow rate on the product ethanol purity, process recovery and productivity were studied. The results showed that ethanol purity increased with temperature and pressure and decreased with feed flow rate. The purity decreased with increasing productivity. The purity range was 98.9 % to 99.6 %, the recovery range was 0.82 to 0.92 and the productivity range w

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Some Game via Ἷ-Semi-g-Separation Axioms
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The research demonstrates new species of the games by applying separation axioms via  sets, where the relationships between the various species that were specified and the strategy of winning and losing to any one of the players, and their relationship with the concepts of separation axioms via  sets have been studied.

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Publication Date
Tue Jan 01 2019
Journal Name
Open Access Journal Of Chemistry
Gas Storage and Separation in Metal Organic Frameworks
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Publication Date
Tue Jan 01 2019
Journal Name
Open Access Journal Of Chemistry
Gas Storage and Separation in Metal Organic Frameworks
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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Sun Aug 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Some Games in ẛ- PRE- g- separation axioms
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     The primary purpose of this subject is to define new games in ideal spaces via set. The relationships between games that provided and the winning and losing strategy for any player were elucidated.

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