The effect of three ionic liquids viz., 1-hexyl-3-methylimidazolium tetrafluoroborate (ILE), 1-hexyl-3-metylimidazolium hexafluorophosphate (ILF) and 1-octyl-3-methylimidazolium tetrafluoroborate (ILG) when used as surfactants on the performance of dissolved air floatation (DAF) was investigated.

   Experiments were conducted at a temperature of 30-35 ºC, 10ppm ferric chloride as coagulant, 50% recycle ratio, pH 8, and 10 minutes treatment time  to find oil and grease (OG) and turbidity removal efficiencies at saturation pressure (2-6) bar.

ILs were used at concentration of 50 µl/liter of treated water in two positions in DAF system; the saturation vessel and the treatment tank. The performance using ILs

    تعد مراجعة النظير واحدة من الأســاليب الحديثة فــي مجال الرقابة والتدقيق ونشــأة كأداة لقياس مــدى فاعليــة الرقابــة علــى الجــودة هو لبنة أساسية في إدارة الجودة الشاملة ووسيلة لتحســين أدوات الرقابــة المعمول بها، وللتحقق من مدى الانسجام بين المعايير الدولية للأجهزة العليا للرقابة المالية والمحاسبة والاجراءات المعمول بها من قبل الاجهزة العليا للرقابة وعليه فأن مراجعة النظير أداة تستخدم ف

Human resources have been regarded as the most important asset for any organization because of its essential part in achieving the sustainable competitive advantage and survival. Managing human resources is very challenging and requires an effective bundle of practices that contribute to attaining the organizational goals. This study tries to confirm the importance of HRM practices in small businesses which came to play a vital role in the economies of the world, through clarifying the influence of HRM practices on the organizational performance, using a mediating variable (employees’ outcomes). Also the study attempts to highlight the key role of governmental support from view point of small businesses, through verifying the significant

The research started from the basic objective of tracking the reality of organizational excellence in educational organizations on the basis of practical application. The research in its methodology was based on the examination of organizational excellence in the way of evaluating institutional performance. Tikrit University was selected as a case study to study the reality of application to the dimensions of organizational excellence in it, The results of the analysis for ten periods during the year and month. For the accuracy of the test and its averages, it was preferable to use the T test to determine the significance of the results compared to the basic criteria.

The research found that there is an o

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims