Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You only look once”) neural network algorithm, which is an efficient real-time object identification algorithm, an intelligent system was developed in this thesis to distinguish which faces are wearing a mask and who is not wearing a wrong mask. The proposed system was developed based on data preparation, preprocessing, and adding a multi-layer neural network, followed by extracting the detection algorithm to improve the accuracy of the system. Two global data sets were used to train and test the proposed system and worked on it in three models, where the first contains the AIZOO data set, the second contains the MoLa RGB CovSurv data set, and the third model contains a combined data set for the two in order to provide cases that are difficult to identify and the accuracy results that were obtained. obtained from the merging datasets showed that the face mask (0.953) and the face recognition system were the most accurate in detecting them (0.916).
Field experiment was conducted to test the effect of saline water 2 and7 dSm-1 potassium fertilizer rate 150,300 and 450 kg/donum on nitrogen fixation in Pisum sativum L. nodules. The experiment included anatomy study .Results water salinity ( 2,7 dSm-1) as a main plot and fertilizer rates as a sub plot. Results indicated that irrigation with saline water 7 dSm-¹ caused a significant decrease in N contents especially in the lower parts of the plants. The percentage of the N decreased in lower leaves to (0.01%) under 7dSm-¹ and 300 kg/donum fertilizer; however the percentage increased in the upper leaves to (2.80%) under with 2dSm-¹of irrigation water and 300 kg/ donum fertilizer rate. Fresh weight decreased to 6.26g under 7 dSm
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The present research has investigated the effect of microwave energy on improving the flow properties of heavy crude oil. The fragmentation of crude oil molecules was carried out with and without using 1 and 10 wt. % concentration of various types of H-donors like tetralin, cyclohexane, and naphtha. Microwave power of 320, 385, and 540 W and radiation time 1-9 min, and temperature were studied. The kinematic viscosity and asphaltene content were measured for evaluation the improving of heavy crude oil.
Results show that viscosity of crude oil decreased with increase H-donor concentration, a maximum percentage of viscosity reduction was10.63 % for tetralin at 6 min radiation time, while 8.67%, and 7.34% for cycl
... Show MoreBackground: Psoriasis is a common inflammatory condition worldwide, with an average prevalence ranging from 2% to 3%. However, the incidence of psoriasis varies among different ethnic groups and regions. Elevated leptin levels have been associated with increased cellular proliferation, including T-cells. Additionally, high leptin levels may stimulate the synthesis of proinflammatory cytokines such as ILـ6 and TNFـα. Objectives: To evaluate the effect of Apremilast on Leptin in obese psoriatic patients. Subjects and Methods: Thirty patients with psoriasis were included in This prospective cohort study to measure the levels of serum Leptin by using the ELISA technique, before and after receiving Apremilast. Result: The present work
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Background: Mother-infant bonding is an important psychological step postpartum and disturbed relationship may carry dramatic consequences as a psychological disorder which may affect the periodontal health of the mother. The aim of the present study was to assess the effect of the postpartum Mother-infant bonding on their periodontal condition. Materials and Methods: Mothers in the postpartum period with age range 20-35 years were subjected to postpartum Bonding Questionnaire (PBQ). Periodontal health status was assessed by measuring probing pocket depth and clinical attachment level. Results: The mean values of both probing pocket depth (PPD) and clinical attachment loss (CAL) were higher among disordered mothers than mothers with normal
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The various properties of the ground and excited electronic states of coumarins 102 using density functional theory (DFT) and time-dependent density functional theory (TDDFT) was calculated by the B3LYP density functional model with 6-31G(d,p) basis set by Gaussian 09 W program. Spectral characteristics of coumarin102 have been probed into by methods of experimental UV-visible, and quantum chemistry. The UV spectrum was measured in methanol. The optimized structures, total energies, electronic states (HOMO- LUMO), energy gap, ionization potentials, electron affinities, chemical potential, global hardness, softness, global electrophilictity, and dipole moment were measured. We find good agreement between experimental data of UV spectrum and
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Due to the importance of the extraction process in many engineering and medical industries, in addition to great interest in medicinal plants, in this research, microwave-assisted extraction has been applied to extract some active compounds from Rosmarinus officinalis leaves. The optimal extraction conditions were then determined by calculating the ratio and extraction efficiency. The process has also been described through kinetic study by applying five kinetic models, the Hyperbolic diffusion model, Power low model, the First order reaction model, Elovich's model, and Fick's second law diffusion model and determining their compatibility with the studies operation, and determining the kinetic constants for each model. The result
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This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a
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