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
The 3-aminoacetophenone and 4-aminoantipyrine were used as precursors to prepare new six ligands. The three new ligands (L1,L2 and L3) were synthesis by reacting one mole of 3-aminoacetophenone with one mole of (Acetyl chloride), (benzoyl chloride), (4-methoxybenzoyl chloride) and ammonium thiocyanat in acetone as a solvent, they are:- L1 (AAA) =[N-(3-acetylphenylcarbamothioyl)acetamide] L2 (BAA) =[N-(3-acetylphenylcarbamothioyl)benzamide] L3 (MAA) =[N-(3-acetylphenylcarbamothioyl)-4-methoxy benzamide] Also three new derivatives of 4-aminoantipyrine were synthesis by reacting one mole of 4-aminoantipyrine with one mole of (Acetyl chloride), (benzoyl chloride), (4-methoxybenzoyl chloride) and ammonium thio
... Show MoreBackground: Diabetic is a chronic systemic disorder of glucose metabolism. That could be diagnosed using fasting and/or random plasma glucose and Glycated Haemoglobin (HbA1c). Several biochemical and microbial alterations of saliva could affect dental caries occurrence and severity among diabetic patients. The aim of the present study was to assess the relation of salivary glucose with severity of dental caries and Mutans Streptococci, among uncontrolled and controlled diabetic groups in comparison with non-diabetic control group. Materials and Methods: The total sample composed of adults aged (18-22) years. Divided into 25 uncontrolled diabetic patients (HbA1c > 7), 25 controlled diabetic patients (HbA1c ≤ 7), in addition to 25 no
... Show MoreSilver selenide telluride Semiconducting (Ag2Se0.8Te0.2) thin films were by thermal evaporation at RT with thickness350 nm at annealing temperatures (300, 348, 398, and 448) °K for 1 hour on glass substrates .using X-ray diffraction, the structural characteristics were calculated as a function of annealing temperatures with no preferential orientation along any plane. Atomic force microscopy (AFM) and X-ray techniques are used to analyze the Ag2SeTe thin films' physical makeup and properties. AFM techniques were used to analyze the surface morphology of the Ag2SeTe films, and the results showed that the values for average diameter, surface roughness, and grain size mutation increased with annealing temperature (116.36-171.02) nm The transm
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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