In our world, technological development has become inherent in all walks of life and is characterized by its speed in performance and uses. This development required the emergence of new technologies that represent a future revolution for a fourth industrial revolution in various fields, which contributed to finding many alternatives and innovative technical solutions that shortened time and space in terms of making Machines are smarter, more accurate, and faster in accomplishing the tasks intended for them, and we find the emergence of what is called artificial intelligence (artificial intelligence), which is the technology of the future, which is one of the most important outputs of the fourth industrial revolution, and artificial inte

Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

Abstract

This study aims to identify the degree to which the first cycle teachers use different feedback patterns in the e-learning system in addition to the differences in the degree of use according to specialization, teaching experience, and in-service training in the field of classroom assessment, as well as the interaction between them. The study sample consisted of (350) female teachers of the first cycle in government schools in Muscat Governorate for the academic year 2020/2021. The study used a questionnaire that contained four different patterns of feedback, which are reinforcement, informative, corrective, and interpretive feedback. The psychometric properties of the que

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

Proxy-based sliding mode control PSMC is an improved version of PID control that combines the features of PID and sliding mode control SMC with continuously dynamic behaviour. However, the stability of the control architecture maybe not well addressed. Consequently, this work is focused on modification of the original version of the proxy-based sliding mode control PSMC by adding an adaptive approximation compensator AAC term for vibration control of an Euler-Bernoulli beam. The role of the AAC term is to compensate for unmodelled dynamics and make the stability proof more easily. The stability of the proposed control algorithm is systematically proved using Lyapunov theory. Multi-modal equation of motion is derived using the Galerkin metho

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.

In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.

The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi