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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
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Tue Jun 01 2010
Journal Name
Journal Of The College Of Languages (jcl)
Multiple Voice narrative
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With the shift of narration and the revolution against the traditional methods which were dominated by the authorial intrusion and the single narrative voice, there appeared new forms that go along with the change in methods of narration. Form becomes the representation which equips us to understand more fully aspects of existence outside of art. Form is the objectifying of idea, and its excellence depends upon its appropriateness to the idea.1 One of the most important approaches to writing fiction is the power of point of view.

In the strategy of 'point of view' lies the secret of art and, as Norman Friedman indicates, it provides a method for distinguishing the possible degrees of authorial extinction in the narrati

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sat Apr 01 2023
Journal Name
The Ocular Surface
Detecting dry eye from ocular surface videos based on deep learning
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Mon Sep 30 2019
Journal Name
College Of Islamic Sciences
Voice occasion in the hadith (Sahih Azkar) for example
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Voice studies are one of the sensory studies of their first association with auditory taste, which broadcasts its connection to the most sensory point contained in the physical corners, and in order to satisfy our conscience from these fundamental voices, we searched for in modern contexts, high proportions related to the words of Muhammadiyah, so we are looking for (events In the hadiths of the Prophet (peace be upon him), to settle our journey when the true adhkaar received from the Prophet, peace be upon him, and to control us start a journey through which we repeat between the cities of audio repetitions, sometimes we find ourselves have stood at the entrance of what corresponds to the sounds between the title of the Hadith and its t

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Publication Date
Mon Sep 03 2018
Journal Name
Al-academy
The Use of Light Text in Arab TV Shows (The Voice TV Program) -A Model
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The research tackles an important subject, namely, the light text and how it works well in the Arab television programs. The methodological framework of the research     presents the research problem stated in the following question: How can the text be used and what is its impact in the Arab TV programs? The importance of this research is that it deals with the subject of light text and its impact on Arab television programs.

This study is useful to the workers and scholars in the field of lighting as well as the goal of the research in (studying of the employment of light text in Arab television programs).

The limits of research were manifested in the study of the light text and how to make use of it

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Publication Date
Mon Oct 04 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Perforation location optimization through 1-D mechanical earth model for high-pressure deep formations
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Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms
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    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

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Publication Date
Mon Aug 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A survey of deepfakes in terms of deep learning and multimedia forensics
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Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

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