In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, with a
good degree of accuracy reaching 97.26, 95.92 and 86.43% respectively. These ANN models could be used as a support for workers in operating the filters in water treatment plants and to improve water treatment process. With the use of ANN, water systems will get more efficient, so reducing operation cost and improving the quality of the water produced.
Horizontal wells have revolutionized hydrocarbon production by enhancing recovery efficiency and reducing environmental impact. This paper presents an enhanced Black Oil Model simulator, written in Visual Basic, for three-dimensional two-phase (oil and water) flow through porous media. Unlike most existing tools, this simulator is customized for horizontal well modeling and calibrated using extensive historical data from the South Rumaila Oilfield, Iraq. The simulator first achieves a strong match with historical pressure data (1954–2004) using vertical wells, with an average deviation of less than 5% from observed pressures, and is then applied to forecast the performance of hypothetical horizontal wells (2008–2011). The result
... Show MoreObjective: Evaluate the effects of different storage periods on flexural strength (FS) and degree of conversion (DC) of Bis-Acryl composite and Urethane dimethacrylate provisional restorative materials. Material and Methods: A total of 60 specimens were prepared from four temporary crown materials commercially available and assigned to four tested groups (n = 15 for each group): Prevision Temp, B&E CROWN, Primma Art, and Charm Temp groups. The specimens were stored in artificial saliva, and the FS was tested after 24 h, 7 d, and 14 d. A standard three-point bending test was conducted using a universal testing machine. Additionally, the DC was determined using a Fourier transform infrared spectroscopy (FTIR) device. The data were analyzed st
... Show MoreMixing this strategy with a qualitative research design and an idea known as AI-supported journalism, the paper is going to approach the requirements of how AI technologies may transform journalism content and culture in a way beyond what one anticipates; therefore, enabling more of it to reach an audience. The current research used descriptive research design to investigate the potential applications of the AI tools that mediate civilizational conversation and a structured questionnaire to media professionals. AI-driven journalism can promote peaceful cohabitation and mutual respect and thus act as a bridge between cultures, the research said. The piece even goes on to mention the need for media establishments and civil soc
... Show MoreBackground: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, an
... Show MoreBackground: Neural tube defects (NTDs) are said to be inherited in a multifactorial fashion, i.e. genetic-environmental interaction. Maternal nutritional deficiencies had long been reported to cause NTDs, especially folate deficiency during early pregnancy. More attention had been paid to the exact mechanism by which this deficiency state causes these defects in the developing embryo. The most significant of all researches was that connecting reduced folate and increased homocysteine level in maternal serum on one hand and the risk of developing a NTD baby on the other hand. Objectives : to determine the significance of homocysteine level in Iraqi mothers who gave birth to babies with NTDs as compared to normal controls. Patients, Materials
... Show MoreThis study specifically contributes to the urgent need for novel methods in Training of Trainers (ToT) programs which can be more effective and efficient through incorporation of AI tools. By exploring scenarios in which AI could be used to dramatically advance trainer preparation, knowledge-sharing, and skill-building across sectors, the research aims to understand the possibility. This study uses a mixed-methods approach, it surveys 500 trainers and conducts in-depth interviews with a further 50 ToT program directors across diverse industries to evaluate the impact of AI-enhanced ToT programs. The results showcase that the use of AI has a substantial positive effect on trainer performance and program outcomes. AI-enhanced ToT programs, fo
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