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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 achieves (4.81) dB GNSDR gain, (7.28) dB GSIR gain, and (3.39) dB GSAR gain in comparison to current approaches

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Publication Date
Wed Mar 13 2019
Journal Name
Al-khwarizmi Engineering Journal
Transient Behavior Analysis for Solar Energy Storage in PCM-CFM Material Using Equivalent Heat Capacity Method as Storage Model
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A paraffin wax and copper foam matrix were used as a thermal energy storage material in the double passes air solar chimney (SC) collector to get ventilation effect through daytime and after sunset. Air SC collector was installed in the south wall of an insulated test room and tested with different working angles (30o, 45o and 60o). Different SC types were used; single pass, double passes flat plate collector and double pass thermal energy storage box collector (TESB). A computational model based on the finite volume method for transient tw dimensional domains was carried out to describe the heat transfer and storage in the thermal energy storage material of collector. Also, equivalent specific heat metho

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Publication Date
Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Design and Development of Powerful Neuroevolution Based Optimized GNNBiLSTM Model for Consumer Behaviour and Effective Recommendation in Social Networks
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Publication Date
Tue Jan 01 2019
Journal Name
Australian Journal Of Mathematical Analysis And Applications
Formulation of approximate mathematical model for incoming water to some dams on Tigris and Euphrates Rivers using spline function
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n this paper, we formulate three mathematical models using spline functions, such as linear, quadratic and cubic functions to approximate the mathematical model for incoming water to some dams. We will implement this model on dams of both rivers; dams on the Tigris are Mosul and Amara while dams on the Euphrates are Hadetha and Al-Hindya.

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Publication Date
Wed Jan 01 2014
Journal Name
Scienceasia
A combined compact genetic algorithm and local search method for optimizing the ARMA(1,1) model of a likelihood estimator
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In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

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Publication Date
Fri Jun 30 2017
Journal Name
Journal Of Engineering
Performance Evaluation of a PID and a Fuzzy PID Controllers Designed for Controlling a Simulated Quadcopter Rotational Dynamics Model
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This work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers m

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Teaching Using Adey- Shire Model and its Effect in Achievement and Critical Thinking for first intermediate students in Mathematics
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The aim of this research is to measure the effect of Adey- Shire model in the achievement and critical thinking of first intermediate female students in mathematics. The researcher adopted the experimental method with a post-test, the research of sample consists of (60) female students, divided into two groups with (30) students in the experimental group, that studied with Adey- Shire model, and (30) students in the control group who studied in the usual way. The two groups are equivalent in many variables. The researcher makes two tests of multiple choices, the first one is an achievement test consists (30) items and another test was for a critical thinking test with (25) items. The statistical analysis make to both tests is made with s

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Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Educational Program Based on the (Guttmann) Model for Developing Awareness and Emotional Experience among University Students
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Abstract

The aim of the research is to identify the level of awareness and emotional experience among university students and to identify the effect of the educational program based on (Guttmann) model for developing awareness and emotional experience among university students by verifying the validity of the following zero hypotheses: 1) There are no statistically significant differences in the development of awareness and emotional experience among university students at the level of (0.05) between the mean scores of the experimental group in the pre and post-tests. 2) There are no statistically significant differences in the development of awareness and emotional experience among university students at the lev

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
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Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy

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Publication Date
Sun Oct 01 2023
Journal Name
Applied Sciences
Multiobjective Optimization of Stereolithography for Dental Bridge Based on a Simple Shape Model Using Taguchi and Response Surface Methods
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Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

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