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Deploying Facial Segmentation Landmarks for Deepfake Detection
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this aspect of the Deepfake detection task and proposes pre-processing steps to improve accuracy and close the gap between training and validation results with simple operations. Additionally, it differed from others by dealing with the positions of the face in various directions within the image, distinguishing the concerned face in an image containing multiple faces, and segmentation the face using facial landmarks points. All these were done using face detection, face box attributes, facial landmarks, and key points from the MediaPipe tool with the pre-trained model (DenseNet121). Lastly, the proposed model was evaluated using Deepfake Detection Challenge datasets, and after training for a few epochs, it achieved an accuracy of 97% in detecting the Deepfake

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
The Attitudees toward aggresive behaviore for sample of college of education and college of science for womens student: The Attitudees toward aggresive behaviore for sample of college of education and college of science for womens student
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Abstract
The purposes of this study were to identifying the (attitudes of college of
education and college of science for womens in Baghdad university students
toward aggresive behaviore) and to determine the differences of student's
attitudes due to Specialization.
The study sample consists of (460) Female students.Aquestionave of
(59) items was desiged and distributed selected sample after established it's
validity and reliablity.The results indicated that the attitude of Baghdad
University For College of education and college of science students toward
aggresive behaviore were Negative.
The findings revealed that there were statistically significant differences
in the student's attitudes due to special

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Publication Date
Fri Dec 02 2022
Journal Name
Journal Of Physical Education
The Effect of Jigsaw Strategy on Learning Spiking in Volleyball for Sophomore Students
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The research aimed at designing teaching program using jigsaw in learning spiking in volleyball as well as identifying the effect of these exercises on learning spring in volleyball. The researchers used the experimental method on (25) students as experimental group and (27) students as controlling group and (15) students as pilot study group. The researchers conducted spiking tests then the data was collected and treated using proper statistical operations to conclude that the strategy have a positive effect in experimental group. Finally, the researchers recommended using the strategy in making similar studies on other subjects and skills.

Publication Date
Sat Dec 30 2023
Journal Name
مجلة نسق
Evaluating the Students’ Performance in the College of Education for Women in Using the Digital Transformation
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This study aims at evaluating the performance of MA students in the College of Education for Women in using the digital transformation and identifying the significant difference in performance evaluation according to the variable of academic qualification (Master or PHD). In order to achieve the aim of the research the researcher prepared a questionnaire of 20 items, and this happens after the researcher's getting acquaintance of the literature of previous studies related to the variable of the research. The apparent validity of the items was examined by exposing them to 10 juries specialized in education, psychology and evaluation and measurement. The stability of the items was examined via two methods, the test-repetition and half-divisio

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Mon Mar 01 2021
Journal Name
The Saudi Dental Journal
Development of patient information leaflets for fixed, removable, and functional appliances for Arabic-speaking orthodontic patients
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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
A Proposed Artificial Intelligence Algorithm for Assessing of Risk Priority for Medical Equipment in Iraqi Hospital
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This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

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Publication Date
Sun Dec 16 2012
Journal Name
Journal Of Physical Education
Analysis study for some offensive plans for Iraqi Duhok participated in Asian club in Basketball 2011
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The tactical side in application of offensive plans in basketball did not take a large in scientific research because it always change because it related in mental ability of players and for the condition of the game and researchers notice that from their followed a lot of games for Duhok basketball club in Iraq league. There is a problem that connected in games results it clears in weakness in application of offensive plans in all kind (man to man & zone defense & side ball plans & under basketball and half court). The goal of study concentrate by designing a sheet for som offensive plans for study and analysis to Duhok club on Asian Championship 2011 at the base the sample contained (Iraq Duhok & application science Jordan & Lebanon sport

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot
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Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

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Publication Date
Thu Apr 15 2021
Journal Name
Biochem. Cell. Arch.
CYTOKINES PROFILE FOR INTESTINAL AND SPLEEN HOMOGENATE FOR IMMUNOSUPPRESSANT BALB/C MICE INFECTED WITH CRYPTOSPORIDIUM PARVUM
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Cryptosporidiosis is mainly cause a persistent diarrhea in immune compromised patients, BALB/c mice have been suppressed by dexamethasone, tissue Th1, Th2 and Th17 cytokines concentrations in the ileum were significantly diminished in both infected and immunosuppressed mice. Level of IFN-g, TNF-a, IL-12, IL-6, IL-17A was increased in level, IL-4 didn’t increases, in both ileal and spleen tissue. Levels of above cytokines were examined in spleen in order to follow the proliferation of CD4+ T-cell during C. parvum infection.

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Appraisal of intelligent notification system for smart university campus based internet of objects for social activities
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