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DeepFake Detection Improvement for Images Based on a Proposed Method for Local Binary Pattern of the Multiple-Channel Color Space
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DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detection in all previous studies was less than what this paper achieved, especially with the benchmark Flickr faces high-quality dataset (FFHQ). This study proposed, a new, simple, but powerful method called image Re-representation by combining the local binary pattern of multiple-channel (IR-CLBP-MC) color space as an image re-representation technique improved DeepFake detection accuracy. The IRCLBP- MC is produced using the fundamental concept of the multiple-channel of the local binary pattern (MCLBP), an extension of the original LBP. The primary distinction is that in our method, the LBP decimal value is calculated in each local patch channel, merging them to re-represent the image and producing a new image with three color channels. A pretrained convolutional neural network (CNN) was utilized to extract the deep textural features from twelve sets of a dataset of IR-CLBP-MC images made from different color spaces: RGB, XYZ, HLS, HSV, YCbCr, and LAB. Other than that, the experimental results by applying the overlap and non-overlap techniques showed that the first technique was better with the IR-CLBP-MC, and the YCbCr image color space is the most accurate when used with the model and for both datasets. Extensive experimentation is done, and the high accuracy obtained are 99.4% in the FFHQ and 99.8% in the CelebFaces Attributes dataset (Celeb-A).

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Publication Date
Sat Mar 04 2023
Journal Name
Baghdad Science Journal
Generalised Henstock - Kurzweil Integral with Multiple Point
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This paper deals with a new Henstock-Kurzweil integral in Banach Space with Bilinear triple n-tuple and integrator function Ψ which depends on multiple points in partition. Finally, exhibit standard results of Generalized Henstock - Kurzweil integral in the theory of integration.

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Investigating Iraqi EFL College Students’ Multiple Intelligences
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Various theories on learning have been developed with increasing frequency in the last
few decades. In tandem with this, Multiple Intelligence theory appeared as a new approach to
education as well as an important theory in the field of language learning. Gardner explains
that all human beings have different intelligence fields and a potential to develop them. These
intelligences are (verbal-linguistic, logical-mathematical, visual-spatial, musical, bodilykinesthetic,
interpersonal, intrapersonal, naturalistic, and Existential).
This study aims at investigating Multiple Intelligences of Iraqi college EFL students. To
achieve the aims of the study, a questionnaire is adopted according to Birmingham model
which incl

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Publication Date
Sun Dec 20 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The use of Auditors the Islamic Financial Engineering tool for Assessing Funding Risk Management in Islamic Banks: Applied research on a sample of Islamic banks
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Experience the Islamic financial industry faces many challenges, most notably the lack of proper risk management tools that meet the requirements of legality and economic efficiency advantage from another side, so it requires the search for innovative ways to manage the risk of Islamic banking, Islamic finance industry is manufacture up-to-date, if compared with the financial industry (traditional), which increases the problematic of risk management in the Islamic financial industry nature of treatment which should be compatible with Islamic law, as well as economic efficiency, thereby Progress came the importance of research to highlight the entrance to Islamic financial engineering and the goals sought to be achieved through the use of

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Publication Date
Thu Jan 14 2021
Journal Name
Iraqi Journal Of Science
Identifying Digital Forensic Frameworks Based on Processes Models
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Digital forensic is part of forensic science that implicitly covers crime related to computer and other digital devices. It‟s being for a while that academic studies are interested in digital forensics. The researchers aim to find out a discipline based on scientific structures that defines a model reflecting their observations. This paper suggests a model to improve the whole investigation process and obtaining an accurate and complete evidence and adopts securing the digital evidence by cryptography algorithms presenting a reliable evidence in a court of law. This paper presents the main and basic concepts of the frameworks and models used in digital forensics investigation.

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
A Stochastic Differential Equations Model for the Spread of Coronavirus COVID-19): The Case of Iraq
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In this paper, we model the spread of coronavirus (COVID -19) by introducing stochasticity into the deterministic differential equation susceptible  -infected-recovered (SIR model). The stochastic SIR dynamics are expressed using Itô's formula. We then prove that this stochastic SIR has a unique global positive solution I(t).The main aim of this article is to study the spread of coronavirus COVID-19 in Iraq from 13/8/2020 to 13/9/2020. Our results provide a new insight into this issue, showing that the introduction of stochastic noise into the  deterministic model for the spread of COVID-19 can cause the disease to die out, in scenarios where deterministic models predict disease persistence. These results were also clearly ill

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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Clinical and Doppler Study of Restrictive Filling Pattern in Patients with Dilated Cardiomyopathy
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Background: Dilated cardiomyopathy (DCM) is a well-recognized cause of cardiovascular morbidity and mortality.Objectives: To evaluate the prognostic implications of the restrictive left ventricular filling pattern (RFP) in dilated cardiomyopathy.Methods: Patients with DCM admitted to Ibn AL-Bitar Hospital for Cardiac Surgery, Baghdad-Iraq, from May 2006 to August 2008, underwent a full clinical evaluation and Doppler echocardiography study. Patients were classified into three groups: Group I had persistent restrictive filling pattern; Group II had reversible restrictive filling pattern; and Group III had nonrestrictive filling pattern. Results: The current study was conducted on a total number of 80 patients with DCM, fifty (62.5 %) were

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Publication Date
Thu Jan 30 2020
Journal Name
Al-kindy College Medical Journal
Pattern of Congenital Heart Disease In Children Attending Central Teaching Pediatric Hospital, Baghdad
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Background: Congenital cardiac defects have a wide spectrum of severity in infants. About 30-40% of patients with congenital cardiac defects will be symptomatic in the 1st year of life, while the diagnosis was established in 60% of patients by the 1st month of age.

Objectives: To identify the occurrence of specific types of CHD among hospitalized patients and to evaluate of growth of patients by different congenital heart lesions.

Methods: A retrospective study, done on ninety-six patients (51 male and 45 female) with congenital heart disease (CHD) admitted to central teaching hospital of pediatrics, Baghdad from 1st September 2009 to 30

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Secure Smart Contract Based on Blockchain to Prevent the Non-Repudiation Phenomenon
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Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Sun Jan 01 2023
Journal Name
Ieee Access
Fuzzy-Based Ensemble Feature Selection for Automated Estimation of Speaker Height and Age Using Vocal Characteristics
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