Drilling solutions can be considered as an intricate mixture comprising of number of chemical additives which aid specific needs such as controlling the rheological properties and reducing corrosion. Inhibitors are substances that are added in small concentrations to corrosive environment to decrease the corrosion. Their applications can be found in drilling equipments. The effect of adding Zinc Sulphate and Carboxymethyl Cellulose to study their influence on the corrosion of carbon steel in Bentonite mud has been evaluated using Weight Loss Technique. This study focuses on determining rheological properties and corrosion characteristics. Results show CMC and ZnSO₄ work as inhibitors when added to the Bentonite with inhibition

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

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

The research aims to know the concept of politic behavior as one of the important behaviours in the different fields and sectors. It is considered to be part of the organizatial work to face the expected  risks. It includes two group of factors personal (self –monitors, locus of control ,expectation s of success, perceived job alternatives)and organizational(promotion ,division resources,role  ambiguity ,democratic decision)studied by the researcher  in the frame of the relationship with the variable  of display  continuous trust matain which includes two variable (build trust mantain, display  trust continuouness)through applied frame by random sample consists of (90)employee  at Farouq State

Abstract An experiment was conducted to study the effect of Glomus mosseae and two concentration (21 and 42%) of super phosphate. They used either to be separated or together with inoculation of G. mosseae on physiological characters of Horeum Vulagera . The results showed that all treatment affected significantly especially super phosphate at the above concentration together with G. mosseae. The effects appeared as an increase in plant height , leaves area , dry weight of total plant , stem dry weight , leaves dry weight , tiller’s number , flag leaf area , dry weight of flag and also increased in CGR , RGR , RGR- NAR , LAI . The yield component increased in number of spikes, number of spikelet’s / spike, number of grain / spike, weigh

 Receipt date:11/19/2020 acceptance date:10/1/2021 Publishing date:12/31/2021

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Human rights are one of the basic concepts of modern and contemporary times, and political thought as the origin of political science and its source of knowledge have impact  in this science and its branches

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra