Stick- slip is the continuous stopping& release of the Bit/BHA due to the irregular down-hole rotation prompted by the existing relationship between the friction torque and the torque applied from the surface to free the bit.

   Friction coefficient between BHA and wellbore is the main player of stick slip amount, which can be mitigated by support a good lubricators as additives in drilling mud.

   Mathematical (or empirical) solves should be done through adjusting all parameters which supposed to reduce stick- slip as low as possible using different models, one of the main parameters is drilling mud. As per Nanoparticles drilling fluid is a new technology that offers high performance

A steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.

The current study aims to investigate the effect of strategic knowledge management practices on an excellent performance at the Institution of Industrial Development and Research- the Ministry of Iraqi Industry (IDRMII). The present research is designed according to the descriptive method. To achieve the mentioned research objective, the researchers used the questionnaire as the main data collection tool. The research sample was 150 managers who are working at the top and middle management levels. To analyses the data gathered and reaching the results, several statistical techniques were used within AMOS.V25, SPSS.V21Software, This study reached a set of results, the most important of which is the existence of a positive correlat

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

In this paper, an approximate solution of nonlinear two points boundary variational problem is presented. Boubaker polynomials have been utilized to reduce these problems into quadratic programming problem. The convergence of this polynomial has been verified; also different numerical examples were given to show the applicability and validity of this method.

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A