This research is concerned with documenting and chronicling the art of NFTs art in the Saudi artistic cultural scene, the importance of which stems from the lack of scientific sources that document this field until the preparation of this research and aims to trace historically the emergence of the field of NFTs art in the Kingdom of Saudi Arabia in the arts sector through the experiences of Saudi artists. The most prominent events for the culture, arts and technology sector, and other Saudi sectors. The research dealt with the history of the emergence of the field of NFTs art, which extends from the history of digital arts, and reviewed the most famous works of NFTs art.
As a result of the technical revolution and the artistic move

Purpose: studying and analyzing the nature of uncertainty as part of strategy formulation, through analyzing the uncertainty faced by managers in the modern business environment characterized by high complexity and dynamism, though developing of an idea about the uncertainty cases and how enable the mind to understand these cases.

Methodology: It was the use of inductive and analytical approach, in order to study the accumulation of knowledge towards development areas that could contribute to strengthening the strategy formulation.

Findings: Mentoring the future will not make the success for business organization but thought business organization ability to developing share mental

The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of

The BEK family of flows have many important practical applications such as centrifugal pumps, steam turbines, turbo-machinery and rotor-stator devices. The Bödewadt, Ekman and von Kármán flows are particular cases within this family. The convective instability of the BEK family of rotating boundary-layer flows has been considered for generalised Newtonian fluids, power-law and Carreau fluids. A linear stability analysis is conducted using a Chebyshev collocation method in order to investigate the effect of shear-thinning and shear-thickening fluids for generalised Newtonian fluids on the convective Type I (inviscid crossflow) and Type II (viscous streamline curvature) modes of instability. The results reveal that shear-thinning power-law

The principle of citizenship has international dimensions that affect the application of the principle, such as the structure of the international system, and the control of the concepts of globalization, international organizations which played an important role in the consolidation of this principle.

The problem of the study revolves around the effects of international variables on the principle of citizenship in Kuwait during the period 1991-2018.

The study used several indicators, such as: the rule of law, achieving the principle of separation of powers, the right to form parties, the application of the law of nationality, and racial discrimination, women's rights, and freedom of expression.

In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to