Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.

This research studies the possibility of producing Bone China with available local and geological substitutes and other manufactured ones since it’s traditionally produced by Bone ash, Cornish stone, and China clay, while the substitutes are Kaolin instead of China clay and Feldspar potash instead of Cornish stone. Because of the unavailability of Feldspar in Iraq, it was substituted with the manufactured alternative Feldspar. Bone ash was prepared from cow bones with heating treatments, grinding and sifting. The alternative Feldspar was prepared by chemical analysis of the natural Feldspar potash with local materials that include Dwaikhla Kaolin, Urdhuma Silica sand, Potassium Carbonate, and Sodium Carbonate. The mixture was burned at

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

A bolted–welded hybrid demountable shear connector for use in deconstructable steel–concrete composite buildings and bridges was proposed. The hybrid connector consisted of a partially threaded stud, which was welded on the flange of a steel section, and a machined steel tube with compatible geometry, which was bolted on the stud. Four standard pushout tests according to Eurocode 4 were carried out to assess the shear performance of the hybrid connector. The experimental results show that the initial stiffness, shear resistance, and slip capacity of the proposed connector were higher than those of traditional welded studs. The hybrid connector was a ductile connector, according to Eurocode 4, with slip capacity higher than 6 mm. A nonli

Background: Eucalyptus extracts and derivatives are natural substances with potent antimicrobial properties. This study investigated the in- vitro effects of non-nutritive sweeteners on the antifungal activity of alcoholic and aqueous Eucalyptus extracts against Candida albicans, a common oral pathogen. Materials and Method: Ten isolates of Candida albicans were isolated from dental students’ salivary samples. The alcoholic and aqueous extracts were prepared from fresh Eucalyptus leaves using maceration. The sensitivity of Candida albicans isolates to various concentrations of Eucalyptus extracts ranging from 50 to 250 (mg/mL) was evaluated via agar well diffusion method, while the agar streaking method  was used to assess the minimum

Background: Enterococcus faecalis is emerging as an important endodontic pathogen, which can persist in the environment for extended periods after treatment and may cause endodontic failure. It is known to produce biofilms, a community of bacteria enclosed within a protective polymeric matrix. This study aimed to establish whether the biofilm formation by Enterococcus faecalis can be inhibited with steralium, co+steralium, and 5% sodium hypochlorite in the root surface environment. Materials and Methods: Extracted human teeth were biomechanically prepared, vertically sectioned, placed in the tissue culture wells exposing the root canal surface to E. faecalis to form a biofilm. At the end of the 3rd and 6th weeks, all groups were treated fo

Background: Depression in elderly aged (60 year and above )is a widespread mental health problem . The current primary healthcare systeminadequately recognize and treat elderly  patients with depression..

Objectives:To determine the prevalence of depression among elderly patientsin Mosul city, its correlation with some sociodemographic variablesand to assess severity of depression in relation to past history of depression.

Type of the study: This is a cross-sectional study.

Methods: This study assess the  prevalence of depression in a randomly selected sample 150 elderly patients aged 60 years and above (89 female &

 The integration of AI technologies is revolutionizing various aspects of the apparel and textile industry, from design and manufacturing to customer experience and sustainability. Through the use of artificial intelligence algorithms, workers in the apparel and textile industry can take advantage of a wealth of opportunities for innovation, efficiency and creativity.
The research aims to display the enormous potential of artificial intelligence in the clothing and textile industry through published articles related to the title of the research using the Google Scholar search engine. The research contributes to the development of the cultural thought of researchers, designers, merchants and the consumer with the importance of integ

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables