The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

The catalytic cracking of three feeds of extract lubricating oil, that produced as a by-product from the process of furfural extraction of lubricating oil base stock in AL-Dura refinery at different operating condition, were carried out at a fixed bed laboratory reactor. The initial boiling point for these feeds was 140 ºC for sample (1), 86 ºC for sample (2) and 80 ºC for sample (3). The catalytic cracking processes were carried out at temperature range 325-400 ºC and initially at atmospheric pressure after 30 minutes over 9.88 % HY-zeolite catalyst load. The comparison between the conversion at different operating conditions of catalytic cracking processes indicates that a high yield was obtained at 375°C, according to gasoline pr

ABSTRACT
                  The research aims to analyze the value chain of dairy products in Iraq (Abu Ghraib/Study Case) factories for the year 2022, where value chain rings are identified to discuss and track the most important determinants and problems in the value chain rings of dairy products and their basic and secondary activities, as well as calculate the value added of the products by subtracting the total revenues of products from their variable costs. Research data were collected for the period 2022. Preliminary information and data from its field sources and personal interviews were collected through a questionnaire prepa

Objectives: The study aims to assess some of the contributing factors to abdominal postoperative wound infection and
to find out the relationship between postoperative wound infections and some socio-demographic characteristics such as
age, gender, level of education, occupation and residential area.
Methodology: A descriptive study was carried out in Sulaimani Teaching Hospital (Kurdistan Region). The study has
started from January 15th up to October 31th, 2009. To achieve the study objectives, a purposive "non probability"
sample of (100) patients who have abdominal postoperative wound infection, Adult female and male patients who were
admitted to Sulaimani Teaching Hospital was selected.
The data were collected th

Present study was carried out to find prevalence of MRSA in healthy individual of second stage students, college of pharmacy/Baghdad University. A total of 74 student selected between age 18-23 years old were included in this study, nasal swabs collected and subjected to many diagnostic standard bacteriological identification methods. Culture, colonial morphology, Gram stain,  mannitol fermentation, coagulase ,gelatinasetest, DNAase, MR/VP and antimicrobial susceptibility test was performed on tryptic soy agar by modified Kirby-Bauer muller hinton disc diffusion method and the result show that out of 74 nasal swabs,67(90.5%) were MRSA positive isolates, 21(31.4%) of them were mannitol ferment and 46(68.6%) non mannitol fermenter, am

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat