The research aims to identify the future teachers' attitudes toward cloud computing in the Kingdom of Saudi Arabia from their point of view. The research adopted the descriptive approach, and a questionnaire was applied to a random sample of (370) male and female teachers in governmental and private general education schools in the Al-Jouf region, Saudi Arabia. The results of the research concluded that the reality of future teachers' attitudes towards cloud computing in the Kingdom of Saudi Arabia from their point of view is very high and that most areas of using computing are in the field of assessment, then teaching, and activities. The challenges of future teachers' attitudes toward cloud computing are recorded at a high level, parti

The importance of this study stems from the importance of preserving the environment and creating a clean sustainable environment from waste and emissions and all the operations of industrial companies in general and cement companies in particular by activating sustainability accounting standards. The research aims to identify and diagnose deviations in violation of sustainability standards by employing the non-renewable resources standard (NR0401) For the construction industries to create a sustainable audit environment, the deductive approach was followed in the theoretical side and the inductive and descriptive approach to the practical side. The most important results of the research were the possibility of applying sustainab

In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

     Ontology is a system for classifying human knowledge according to its objective characteristics and hierarchical relations through building clusters or that bear common characteristics. In digital environments, it is a mechanism that helps regulate a vast amount of information by achieving a complete link between sub-thematic concepts and their main assets. The purpose of this study is to survey the previously conducted studies that use ontology in organizing digital data on social networking sites, such as the search engines Yahoo, Google, and social networks as Facebook and their findings. Results have shown that all these studies invest ontology for the purpose of organizing digital content data, especially on

Background: The access cavity is a critical stage in root canal therapy and it may influence the subsequent steps of the treatment. The new minimally invasive endodontic access cavity preparation concept aims to preserve sound tooth structure by conserving as much intact dentine as possible including the pulp chamber's roof, to keep the teeth from fracturing during and after endodontic treatment. While there is great interest in such access opening designs in numerous publications, still there is a lack of scientific evidence to support the application of such modern access cavity designs in clinical practice. This review aims to critically examine the literature on minimal access cavity preparations, explain the effect of minimally inva

One of the most popular and legally recognized behavioral biometrics is the individual's signature, which is used for verification and identification in many different industries, including business, law, and finance. The purpose of the signature verification method is to distinguish genuine from forged signatures, a task complicated by cultural and personal variances. Analysis, comparison, and evaluation of handwriting features are performed in forensic handwriting analysis to establish whether or not the writing was produced by a known writer. In contrast to other languages, Arabic makes use of diacritics, ligatures, and overlaps that are unique to it. Due to the absence of dynamic information in the writing of Arabic signatures,

This paper describes the digital chaotic signal with ship map design. The robust digital implementation eliminates the variation tolerance and electronics noise problems common in analog chaotic circuits. Generation of good non-repeatable and nonpredictable random sequences is of increasing importance in security applications. The use of 1-D chaotic signal to mask useful information and to mask it unrecognizable by the receiver is a field of research in full expansion. The piece-wise 1-D map such as ship map is used for this paper. The main advantages of chaos are the increased security of the transmission and ease of generation of a great number of distinct sequences. As consequence, the number of users in the systems can be increased. Rec