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Applications of Artificial Intelligence in Graphic Design
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If the Industrial Revolution has enabled the replacement of humans with machines, the digital revolution is moving towards replacing our brains with artificial intelligence, so it is necessary to consider how this radical transformation affects the graphic design ecosystem. Hence, the research problem emerged (what are the effects of artificial intelligence on graphic design) and the research aimed to know the capabilities and effects of artificial intelligence applications in graphic design, and the study dealt in its theoretical framework with two main axes, the first is the concept of artificial intelligence, and the second is artificial intelligence applications in graphic design. The descriptive approach adopted a method of content analysis to analyze three research samples to reach a number of results and conclusions, including:
1- Due to the employment of artificial intelligence in graphic design, it has facilitated the designer's work in some routine design aspects and made him focus on the creative aspects of design more broadly.
2- 2- As a result of the rapid scientific progress, the issue of creative awareness when applying artificial intelligence will be a temporary problem that can be overcome in the future and will accelerate the creative competition between it and the graphic designer

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Publication Date
Wed Aug 26 2020
Journal Name
Iraqi Journal Of Agricultural Sciences
COMPARISON THE ACCURACY OF COMPUTING POINT COORDINATS BETWEEN DIFFERENT INSTRUMENTS AND APPLICATIONS OF GPS
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The study was aimed to determine the coordinates of  the points were measured by different ways and different instruments, the most precise way using the differential global positioning system (DGPS) that will be the reference measurements in comparison, less precise way using navigator GPS. Google earth (pro.), and the other applications of GPS mobile ( Samsung and I-phone). In this research (8 points) were chosen that are occasional in location. The comparison of the different observations can give us an idea of ​​the extent to which the accuracy of the observations differs from the different devices used in the observing, as well as through the knowledge of the best device and the best way to measure coordinates accurately t

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Publication Date
Tue Apr 19 2022
Journal Name
Chemical Methodologies
Biosynthesis, Characterization, and Applications of Bismuth Oxide Nanoparticles Using Aqueous Extract of Beta Vulgaris
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Bismuth oxide nanoparticle Bi2O3NPs has a wide range of applications and less adverse effects than conventional radio sensitizers. In this work, Bi2O3NPs (D1, D2) were successfully synthesized by using the biosynthesis method with varying bismuth salts, bismuth sulfate Bi2(SO4)3 (D1) or bismuth nitrate. Penta hydrate Bi(NO3)3.5H2O (D2) with NaOH with beta-vulgaris extract. The Bi2O3NPs properties were characterized by different spectroscopic methods to determine Bi2O3NPs structure, nature of bonds, size of nanoparticle, element phase, presence, crystallinity and morphology. The existence of the Bi2O3 band was verified by the FT-IR. The Bi2O3 NPs revealed an absorption peak in the UV-visible spectrum, with energy gap Eg = 3.80eV. The X-ray p

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Publication Date
Sat Jan 01 2022
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees21gr
Study and preparation of optoelectronic properties of AgAl1-xInxSe2/Si heterojunction solar cell applications
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Publication Date
Fri Jan 11 2019
Journal Name
Iraqi Journal Of Physics
Study of starch, sugar blending effect on the biodegradability of (PVA) for packaging applications
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PVA, Starch/PVA, and Starch/PVA/sugar samples of different
concentrations (10, 20, 30 and 40 % wt/wt) were prepared by casting
method. DSC analysis was carried; the results showed only one glass
transition temperature (Tg) for the samples involved, which suggest
that starch/PVA and starch/PVA/sugar blends are miscible. The
miscibility is attributed to the hydrogen bonds between PVA and
starch. This is in a good agreement with (FTIR) results. Tg and Tm
decrease with starch and sugar content compared with that for
(PVA). Systematic decrease in ultimate strength, due to starch and
sugar ratio increase, is attributed to (PVA), which has more hydroxyl
groups that made its ultimate strength higher than that for

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Publication Date
Wed Dec 25 2024
Journal Name
Jurnal Kimia Valensi
Green Synthesis, Characterization, and Applications of Aluminum Oxide Nanoparticles Using Aqueous Extract of Clove
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In this work, γ-Al2O3NPs were successfully biosynthesized, mediated aluminum nitrate nona hydrate Al(NO3)3.9H2O, sodium hydroxide, and aqueous clove extract in alkali media. The γ-Al2O3NPs were characterized by different techniques like Fourier transform infrared spectroscopy (FT-IR), UV-Vis spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy–dispersive x-ray spectroscopy, transmission electron microscope (TEM), Energy-dispersive X-ray spectroscopy (EDX), and atomic force microscopy (AFM). The final results indicated the γ-Al2O3NPs nanoparticle size, bonds nature, element phase, crystallinity, morphology, surface image, particle analysis – threshold detection, and the topography parameter. The id

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Publication Date
Mon May 01 2023
Journal Name
Environmental Nanotechnology, Monitoring & Management
A review study summarizes the main characterization techniques of nano-composite photocatalysts and their applications in photodegradation of organic pollutants
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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Sat Dec 31 2022
Journal Name
Mathematical Modelling Of Engineering Problems
Experimental and Numerical Study of Open Channel Flow with T-Section Artificial Bed Roughness
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Experimental and numerical studies have been conducted on the effects of bed roughness elements such as cubic and T-section elements that are regularly half-channel arrayed on one side of the river on turbulent flow characteristics and bed erosion downstream of the roughness elements. The experimental study has been done for two types of bed roughness elements (cubic and T-section shape) to study the effect of these elements on the velocity profile downstream the elements with respect to different water flow discharges and water depths. A comparison between the cubic and T-section artificial bed roughness showed that the velocity profile downstream the T-section increased in smooth side from the river and decrease in the rough side

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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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