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

Background: Hypothyroidism is the most prevalent thyroid disorders worldwide.  Hypothyroidism manifestations are wide spectrum, affecting various systems in human body including the nervous system. Hypothyroidism can cause neuropsychiatric symptoms such as anxiety, depression and diminishing in attention, memory and executive function. Aim: to investigate the level of anxiety and depression in patients with hypothyroidism receiving levothyroxine treatment. Method: a cross-sectional study was conducted at Baghdad Center for Nuclear Medicine and Radiation Therapy from March to June 2022. The study population included patients of both genders, aged 18-65 years, diagnosed with hypothyroidism, were receiving levothyroxine treatment and

True random number generators are essential components for communications to be conconfidentially secured. In this paper a new method is proposed to generate random sequences of numbers based on the difference of the arrival times of photons detected in a coincidence window between two single-photon counting modules

The protozoan parasite Entamoeba histolytica is a causative agent of amoebiasis, where it causes millions of cases of dysentery and liver abscess each year. Metronidazole is a drug of choice against amoebiasis. The drug is a choice because of its efficacy and low cost, but at the same time it causes several adverse side effects; therefore, it is important to find effective medications to treat amoebiasis without any complications or any side effects. The aim of this study is to evaluate the effectiveness of different concentrations (50, 75 and 100 µg/ml) of silver nanoparticle (AgNPs) against trophozoites stages of E. histolytica in vitro. The results showed a significant decrease (p ? 0.05) in numbers of trophozoites stages after treated

The research aims to shed light on the role of artificial intelligence in achieving Ambidexterity performance, as banks work to take advantage of modern technologies, artificial intelligence is an innovation that is expected to have a long-term impact, as well as banks can improve the quality of their services and analyze data to ensure that customers' future needs are understood. . The Bank of Baghdad and the Middle East Bank were chosen as a community for the study because they had a role in the economic development of the country as well as their active role in the banking market. A sample of department managers was highlighted in collecting data and extracting results based on the checklist, which is the main tool for the stu