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Accelerating Face Mask Detection Training Model Based on Multi-GPUs and Multi-core CPU
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Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform with large batch size and learning rate involvement to optimize resource use across storage, configuration and scaling using large datasets. the proposed model contains two parts, the first one is used for specifying and extracting the faces using the Haar Cascade classifier, and the second one considers the core part that extracts features from facial images for classification. As a result, the average speed of a multi-GPU is about 2.7 times faster than the GPU and about 3.2 times faster than the CPU. Also, according to our evaluation results, the training time obtained using multiple GPUs and multiple processes is much smaller than that obtained using a single GPU single process. Parallel training on multiple GPUs improves GPU resource utilization and training throughput. This model reflects significant accuracy compared to the other commonly used methods from relevant articles by achieving an Accuracy score of 99.5%.

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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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Publication Date
Sat Jan 01 2022
Journal Name
Revista Iberoamericana De PsicologÍa Del Ejercicio Y El Deporte
THE EFFECT OF TRAINING NETWORK TRAINING IN TWO WAYS, HIGH INTERVAL TRAINING AND REPETITION TO DEVELOP SPEED ENDURANCE ADAPT HEART RATE AND ACHIEVE 5000 METERS YOUTH
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Publication Date
Tue Nov 24 2020
Journal Name
Experimental Heat Transfer
Thermal performance of a flat-plate solar collector using aqueous colloidal dispersions of multi-walled carbon nanotubes with different outside diameters
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The thermal performance of a flat-plate solar collector (FPSC) using novel heat transfer fluids of aqueous colloidal dispersions of covalently functionalized multi-walled carbon nanotubes with β-Alanine (Ala-MWCNTs) has been studied. Multi-walled carbon nanotubes (MWCNTs) with outside diameters of (< 8 nm) and (20–30 nm) having specific surface areas (SSAs) of (500 m2/g) and (110 m2/g), respectively, were utilized. For each Ala-MWCNTs, waterbased nanofluids were synthesized using weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1%. A MATLAB code was built and a test rig was designed and developed. Heat flux intensities of 600, 800, and 1000 W/m2; mass flow rates of 0.6, 1.0, and 1.4 kg/min; and inlet fluid temperatures of 30, 40, an

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Publication Date
Mon Aug 25 2025
Journal Name
مجلة كلية التربية
A Multi-modal Critical Discourse Analysis of Selected English Political Cartoons تحليل خطاب نقدي متعدد الوسائط لرسوم كاريكاتورية سياسية إنجليزية مختارة
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This study analyses six political cartoons selected based on their relevance to current Iraqi political issues, specifically the period between 2005 and 2015, from American online newspapers (calgecartooms.com). The selection criteria included the cartoons' satirical elements, visual rhetoric, and their ability to engage with themes such as power dynamics, social issues, and public opinion. It sheds light on how these cartoons can function as mediators of meanings between the cartoonists and the readers. The data is examined using multimodal discourse analysis (MDA), which combines language study with the analysis of other visual elements, like colors, gestures, and images, to understand meaning (O’Halloran et al., 2011). The Visual Socia

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Investigation of Nonlinear Optical Characteristics of the Multi-Wall Carbon Nanotubes (MWCNT's) Suspensions using Nonlinear Self-Diffraction of a Laser Beam
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Nonlinear diffraction patterns can be obtained by focusing a laser beam through a thin slice of the material. Here, we investigated experimentally the formation of the far field nonlinear diffraction patterns of cw laser beam at 532 nm passing through a quartz cuvette containing multi-wall carbon nanotubes (MWCNT's) suspended in acetone and in DI water at concentrations of 0.030.wt.%, 0.045 wt.%, 0.060 wt.%, and 0.075 wt.%. Our results show that increasing the concentration of both types of suspensions (MWCNTs in acetone and MWCNTs DI water) led to increase in the number of pattern rings which indicates an increase in their nonlinear refractive indices. Moreover, MWCNTs DI water suspension at a concentration of 0.075 wt. % was more effic

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Publication Date
Sat Aug 31 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Credit Card Fraud Detection Using an Autoencoder Model with New Loss Function
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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Bayesian and non-Bayesian estimation of the lomax model based on upper record values under weighted LINEX loss function
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In this article, we developed a new loss function, as the simplification of linear exponential loss function (LINEX) by weighting LINEX function. We derive a scale parameter, reliability and the hazard functions in accordance with upper record values of the Lomax distribution (LD). To study a small sample behavior performance of the proposed loss function using a Monte Carlo simulation, we make a comparison among maximum likelihood estimator, Bayesian estimator by means of LINEX loss function and Bayesian estimator using square error loss (SE) function. The consequences have shown that a modified method is the finest for valuing a scale parameter, reliability and hazard functions.

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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
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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Publication Date
Sat Nov 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
Assessing the Bearing Capacity of the Strip Footing Resting on the Slope Face
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Abstract<p> Infrastructure projects, including buildings, bridges, and towers, in hilly or mountainous areas are frequently constructed on inclined landscapes. This work utilizes finite element limit analysis (FELA) to examine the effect of critical parameters on the ultimate bearing capacity (B.C.) of strip footings (S.F.) situated on slope faces. The analysis examines the impacts of Inclination of the Slope (β), Internal Friction Angle (ϕ), and embedment depth of footing (Df). As the slope angle (β) increased from 10° to 20°, the footing’s ultimate bearing capacity decreased by 55%. Furthermore, the embedded depth shows an important effect on the bearing capacity;</p> ... Show More
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