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 on

In cyber security, the most crucial subject in information security is user authentication. Robust text-based password methods may offer a certain level of protection. Strong passwords are hard to remember, though, so people who use them frequently write them on paper or store them in file for computer .Numerous of computer systems, networks, and Internet-based environments have experimented with using graphical authentication techniques for user authentication in recent years. The two main characteristics of all graphical passwords are their security and usability. Regretfully, none of these methods could adequately address both of these factors concurrently. The ISO usability standards and associated characteristics for graphical

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Thiamine stimulates the production of a red pigment , which is chromatographically and spectrophotometrically identical to prodigiosin , by growing cultures of serratia marcescens mutant 9-3-3 . this mutant is blocked in the formation of 2- methyl -3- amyl pyrorol( MAP),the monopyrrole moiety of prodigiosin , but accumulates 4-methoxy-2, 2-bipyrrole -5- carboxaldehyde (MBC) and can couple this compound with( MAP) to form prodigiosin . Addition of thiamine caused production of( MAP) , and as little as 0.02 mg of thiamine / ml in peptone- glycerol medium stimulated production of measurable amounts of prodigiosin. Phosphate saltes and another type of peptone decreased the thiamine- induced formation of prodigiosin ,yeast extract and glyc

Ghar Formation outcrop at the Iraqi western desert was studied by microfacies analysis
of (13) thin sections collected from wadi Al-Ratgha ( west of Qaim ) . According to
petrographic com position and organisms content ,rocks were subdivided into (4)
microfacies units :bioclastic wackestone , mudstone , miliolids wackestone , and grainstone
with aggregate grains microfacies .Microfacies units reflect shallow marine environment of
low circulation of very warm water at the middle part . The lower and middle part
interbedded with quite open marine environment below the wave base . The upper part was
deposited at shallow marine environment of low circulation . The main diagenetic processes
were the transformation ( ty

the films of cdse pure and doped with copper ratio glass substrate effect od cucomcentration technique thikness doped with copper is an anonmg and the density of state increases