The present study focused mainly on the analysis of stiffened and unstiffened composite laminated plates subjected to buckling load. Analytical, numerical and experimental analysis for different cases has been considered. The experimental investigation is to manufacture the laminates and to find mechanical properties of glass-polyester such as longitudinal, transverse young modulus, shear modulus. The compressive test was carried to find the critical buckling load of plate. The design parameters of the laminates such as aspect ratio, thickness ratio, boundary conditions and number of stiffeners were investigated using high order shear deformation theory (HOST) and Finite element coded by ANSYS .The main conclusion was the buckling load c

Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydropho

This paper includes the application of Queuing theory with of Particle swarm algorithm or is called (Intelligence swarm) to solve the problem of The queues and developed for General commission for taxes /branch Karkh center in the service stage of the Department of calculators composed of six  employees , and it was chosen queuing model is a single-service channel  M / M / 1 according to the nature of the circuit work mentioned above and it will be divided according to the letters system for each employee, and  it was composed of data collection times (arrival time , service time, departure time)

This study was established to investigate the correlation between the expression of matrix metalloproteinases (MMP-1) and the pathogenesis of osteoarthritis (OA). Blood samples were collected from 55 female patients with inflammatory OA and controls for estimation of serum (MMP-1) levels. In the current study, there is significant increase (p<0.001) in the mean of serum MMP-1 levels in osteoarthritis females (4027.73 ± 1345.28 pg/ml) than that in control females (798.76 ± 136.79 pg/ml). It was concluded that MMP-1 may be associated with the pathogenesis of osteoarthritis.

Human health was and still the most important problem and objective of all most researches. Finding out what causes in the decadence of healthiness of Iraqi population is our tendency in the present work, Uranium causing cancer that is affected by a correlation between age and gender of bladder cancer patients is studied in the present work. Mean of Uranium concentration (Uc) decreased with increasing age for all age group without dependency on gender. While, there is a wide dispersion in Mean Uc excretion between males and females, due to the effect of correlated gender with age, where female Mean Uc is maximum at age 50-69 year (2.355 µg/L), and it's higher than male Mean Uc (2.022 µg/L) in this age stage because of menopause, a

The objective of this study is to determine levels of some pro-inflammatory cytokines (IL-12 and SIL-2R) in pregnant women with polycystic ovary syndrome (PCOS) and also to determine incidence of spontaneous abortion during first trimester in pregnant women with PCOS compared with non-PCOS pregnant women. This Study was performed on (93) women, consisted of: 1- (63) pregnant women during the first trimester, which included:A- (33)PCOS pregnant women and subdivided into the following groups: (20) successful pregnant PCOS, (7) blighted Ovum PCOS and (6) missed abortion PCOS. B- (30) non-PCOS pregnant women, which included: (27) successful pregnant control and (3) non-PCOS pregnant women were withdrawn from this study because of their abortion

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class