Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

ھدف البحث الـــــى : ١ -إعداد تدریبات القوة الارتدادیة في وسطین متباینین على بعض المؤشرات الفسیولوجیة لتطویر القوة الانفجاریة ودقة مھارتي الأرسال والضرب الساحق بالكرة الطائرة . ٢ -التعرف على تأثیر تدریبات القوة الارتدادیة في وسطین متباینین على بعض المؤشرات الفسیولوجیة لتطویر القوة الانفجاریة.. ٣ -التعرف على تأثیر تدریبات القوة الارتدادیة في وسطین متباینین على دقة مھارتي الأرسال والضرب الساحق بالكرة الطائرة

ABSTRACT

        The research aim is to determine the relation between governmental consumption expenditure (GCE) & GDP in Iraq for the period 1981-2006.

The research has determined the scale of optimization for (GCE) & try to know the extent productivity of this expenditure and using the long run &short run model to test .The results clarify the following

1-The marginal productivity for the (GCE) is positive so it is productive.

2-The (GCE) in Iraq is too high because the marginal productivity for the expenditure less than 1.

3- The (GCE) percentage to GNP is

Methicillin resistant Staphylococcus aureus (MRSA) is one of the principal nosocomial causative agents. This bacterium has the capability to resist wide range of antibiotics and it is responsible for many diseases like skin, nose and wounds infection. In this study, randomly amplified polymorphic DNA (RAPD)-PCR was applied with ten random primers to examine the molecular diversity among methicillin resistant Staphylococcus aureus (MRSA) isolates in the hospitals and to investigate the genetic distance between them. 90 Isolates were collected from clinical specimens from Iraqi hospitals for a total of 90 isolates. Only 10 strains (11.11%) were found to be MRSA. From these 10 primers, only 9 gave clear amplification products. 91 fragment l

Antibiotics present the greatest threat to soil and aquatic ecosystems among the different therapeutic groups of medicines (which include prescription drugs and treatments for cancer). The strongest drugs, antibiotics, have been utilized to stop the growth of microorganisms or eradicate them. Using high-performance liquid chromatography technology with fluorescence detection, the amounts of levofloxacin and tetracycline in the wastewater from three hospitals (Medical City, Al-Kindi, and Al-Yarmouk) were determined. Levofloxacin and tetracycline were chosen in this study because they are the most important water pollutants. These antibiotic residues were separated and measured using a gradient elution technique on a reverse-phase C18

Antibiotics present the greatest threat to soil and aquatic ecosystems among the different therapeutic groups of medicines (which include prescription drugs and treatments for cancer). The strongest drugs, antibiotics, have been utilized to stop the growth of microorganisms or eradicate them. Using high-performance liquid chromatography technology with fluorescence detection, the amounts of levofloxacin and tetracycline in the wastewater from three hospitals (Medical City, AlKindi, and Al-Yarmouk) were determined. Levofloxacin and tetracycline were chosen in this study because they are the most important water pollutants. These antibiotic residues were separated and measured using a gradient elution technique on a reverse-phase C18 co

     In this study, we investigate about the run length properties of cumulative sum (Cusum) and The exponentially weighted moving average (EWMA) control charts, to detect positive shifts in the mean of the process for the poisson distribution with unknown mean. We used markov chain approach to compute the average and the standard deviation for run length for Cusum and EWMA control charts, when the variable under control follows poisson distribution. Also, we used the Cusum and the EWMA control charts for monitoring a process mean when the observations (products are selected from Al_Mamun Factory ) are identically and independently distributed (iid) from poisson distribution i