In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and   then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g

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

(28)Bacterial local isolates of Bacillus sp. were obtained from soil samples. Isolates were tested for thermostable alpha- amylase production on solid media; fifteen isolates were able to develop clear zone around the bacterial growth after floating the plates with iodine reagent (Lugol's solution). There were further tested in submerged culture which led to selection of Bacillus sp. H14since it was the most efficient .Microbial and biochemical tests showed that the local isolate Bacillus sp.H14was refered to the species B.licheniformis that signed as H14 was refered to the species B.licheniformis H14 .,To get ahigher yield of alpha – amylase(48.70unit/mg protein) production from the local isolate B.licheniformis H14 . This study used

BACKGROUND: Hepatocyte growth factor (HGF) is a proangiogenic factor that exerts different effects over stem cell survival growth, apoptosis, and adhesion. Its impact on leukemogenesis has been established by many studies. AIM: This study aimed to determine the effect of plasma HGF activity on acute myeloid leukemia (AML) patients at presentation and after remission. PATIENTS AND METHODS: This was a cross-sectional prospective study of 30 newly-diagnosed, adult, and AML patients. All patients received the 7+3 treatment protocol. Patients’ clinical data were taken at presentation, and patients were followed up for 6 months to evaluate the clinical status. Plasma HGF levels were estimated by ELISA based methods in the pa

Two field experiments were conducted during the season 2021-2022 in central Iraq represented by the Al-Muthanna governorate - Al-Majd District and Al-Qadisiyah governorate / Al-Nouriah Research Station to determine the productivity of the Baghdad 3 cultivar from spray foliar fertilization of Macro and Micro elements with alcoholic sugars and half the fertilizer recommendation for addition floor, three treatments were used for fertilization: T1 as the control treatment and T2 with alcoholic sugar fertilization at a concentration of 20 g.L-1 + the fertilizer combination of Macro and Micro elements, and T3 with alcoholic sugar fertilization at a concentration of 40 g.L-1 + the fertilizer combination of Macro and Microelements, at irrigation 55

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

Objectives: The purpose of this in vitro study was to compare the effect of adding poloxamer surfactant to irrigant solutions on the penetration de..