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

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

Background: Polymeric composites have been widely used as dental restorative materials. A fundamental knowledge and understanding of the behavior of these materials in the oral cavity is essential to improve their properties and performance. The goal of this study was to measure water sorption of four composite resins containing different filler and resin matrix contents. Materials and method: Resin composite specimens giomer (Beautifil II) Filtek™ P90, Filtek™ Z350 XT, and Tetric N Ceram were prepared in a cylindrical mould of 3mm thickness and 6mm diameter (n=10) and light cured . All specimens placed in silica-gel desiccators at 37˚C for seven days, a constant weight was obtained. All samples were immersed in deionized distill

Background:Measurement of hemoglobin A1c (A1C) is a renowned tactic for gauging long-term glycemic control, and exemplifies an outstanding influence to the quality of care in diabetic patients.The concept of targets is open to criticism; they may be unattainable, or limit what could be attained, and in addition they may be economically difficult to attain. However, without some form of targeted control of an asymptomatic condition it becomes difficult to promote care at allObjectives: The present article aims to address the most recent evidence-based global guidelines of A1C targets intended for glycemic control in Type 2 Diabetes Mellitus (T2D).Key messages:Rationale for Treatment Targets of A1C includesevidence for microvascular and ma

Cancer is one of the critical health concerns. Health authorities around the world have devoted great attention to cancer and cancer causing factors to achieve control against the increasing rate of cancer. Carcinogens are the most salient factors that are accused of causing a considerable rate of cancer cases. Scientists, in different fields of knowledge, keep warning people of the imminent attack of carcinogens which are surrounding people in the environment and may launch their attack at any moment. The present paper aims to investigate the linguistic construction of the imminent carcinogen attack in English and Arabic scientific discourse. Such an investigation contributes to enhancing the scientists’ awareness of the linguistic co

     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb