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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
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for Facial Image Detection System
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HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Mon Sep 30 2024
Journal Name
Al-mustansiriyah Journal Of Science
A Transfer Learning Approach for Arabic Image Captions
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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
The adsorption-desorption process as a method for separation of nitrogen-carbon dioxide gas mixture using activated carbon
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Gas adsorption phenomenon on solid surface has been used as a mean in separation and purification of gas mixture depending on the difference in tendencies of each component in the gas mixture to be adsorbed on the solid surface according to its behaviour. This work concerns to study the possibilities to separate the gas mixture using adsorption-desorption phenomenon on activated carbon. The experimental results exhibit good separation factor at temperature of -40 .

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Publication Date
Tue Mar 31 2026
Journal Name
Polymers For Advanced Technologies
Utilizing the Potential of Polyvinylidene Fluoride in Developing Durable Superhydrophobic and Antibacterial Nanocomposite Coatings for Oil/Water Separation
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ABSTRACT<p> The increasing demand for durable and multifunctional separation materials necessitates polymer‐based coatings that combine mechanical robustness with high selectivity. This study aims to develop antibacterial oil/water separation systems that effectively address challenges posed by microorganisms, which can decrease filter effectiveness and impact overall separation efficiency. Metal meshes were coated with titanium dioxide (TiO <sub>2</sub> ), octadecanethiol (ODT), and polyvinylidene fluoride (PVDF) via spray coating using four formulations: TiO <sub>2</sub> </p> ... Show More
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Publication Date
Wed Jul 05 2017
Journal Name
Neural Computing And Applications
Hybrid soft computing approach for determining water quality indicator: Euphrates River
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Publication Date
Tue Nov 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Implementation of new Secure Mechanism for Data Deduplication in Hybrid Cloud
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Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Dynamic Routing Method over Hybrid SDN for Flying Ad Hoc Networks
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Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

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