The surface finish of the machining part is the mostly important characteristics of products quality and its indispensable customers’ requirement. Taguchi robust parameters designs for optimizing for surface finish in turning of 7025 AL-Alloy using carbide cutting tool has been utilized in this paper. Three machining variables namely; the machining speeds (1600, 1900, and 2200) rpm, depth of cut (0.25, 0.50, 0.75) mm and the feed rates (0.12, 0.18, 0.24) mm/min utilized in the experiments. The other variables were considered as constants. The mean surface finish was utilized as a measuring of surface quality. The results clarified that increasing the speeds reduce the surface roughness, while it rises with increasing the depths and fee

This research foxed on the effect of fire flame of different burning temperatures (300, 400 and 500)oC on the compressive strength of reactive powder concrete (RPC).The steady state duration of the burning test was (60)min. Local consuming material were used to mixed a RPC of compressive strength around (100) MPa. The tested specimens were reinforced by (3.0) cm hooked end steel fiber of (1100) MPa yield strength. Three steel fiber volume fraction were adopted in this study (0, 1.0and 1.5)% and two cooling process were included, gradual and sudden. It was concluding that increasing burning temperature decreases the residual compressive strength for RPC specimens of(0%) steel fiber volume fraction by (12.16, 19.46&24.49) and (18.20, 27.77 &3

An ultrasonic treatment was applied to the vacuum gas oil at intervals of 5 to 30 minutes, at 70°C.  In this work, the improvement of the important properties of Iraqi vacuum gas oil, such as carbon residue, was studied with several parameter conditions that affect vacuum efficiency, such as sonication time (5, 10, 15, 20, 25, and 30) min, power amplitude (10–50%). After ultrasonic treatment, the carbon residue of vacuum gas oil was evaluated using a Conradson carbon residue meter (ASTM D189). The experiment revealed that the oil's carbon residue had decreased by 16%. As a consequence of the experiment It was discovered that ultrasonic treatment might reduce the carbon residual and density of oil samples being studied. It also notice

Education around the world has been negatively affected by the new coronavirus disease (COVID-19) pandemic. Many institutions had to transition to distance learning in compliance with the enforced safety measures. Distance learning might work well for settings with stable internet connections, professional technical teams, and basic implementation of technology in education. In contrast, distance learning faces serious challenges in less fortunate settings with inferior infrastructure. This report aims to shed light on the immediate action steps taken at a leading pharmacy school in Iraq to accommodate for the enforced changes in pharmacy education. The University of Baghdad College of Pharmacy went from less than minimal technology impl

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

The world faced many communication challenges in 2020 after the Covid-19 pandemic, the most important of which was the continuation of schooling. Therefore, the research aimed to analyze the current reality of the studied universities in terms of strengths and weaknesses and measure the implementing level of quality requirements of e-learning. This research studies the impact of knowledge sharing in its dimensions (behavior, organizational culture, work teams, and technology) on the e-learning quality and its dimensions (e-learning management, educational content, evaluation ,and evaluation). After conducting the survey, there was a difference in the universities’ application of the quality requirements of e-learning, as the study

The aims of the research is to know the role of Organisational learning in building talent management strategies in the Ministry of Science and Technology , where we see the challenges facing organizations today dictate now and in the future activation of scientific expertise to meet these challenges and the dissemination of these concepts within the priorities and data organizational culture of these organizations despite having a lot of the importance of organizational knowledge and learning applications .Despite learning and adopting some of the organizations have to enhance their competitiveness, we find a lot of organizations, including (The ministry researched) still do not realize the importance of the role of organization

  The present study aimed at ((building an educational -learning design based on the theory of Merrill in (CDT) and measuring the effectiveness of this design in the motivation and achievement of the high school fifth grade students to art education in the subject of the history of modern art)). The research community is made of fifth grade preparatory students in the secondary school of Umm Ayman in the Directorate of Education of Baghdad / Ar-Rusafa in a simple random way. The study sample (58 students) was chosen from section (e) to study according to Merrill theory (CDT) and section (d) to study according to the traditional way.
The pilot design of the control and experimental equivalent groups that have partial control in t

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m