The purpose of this work is to study the classification and construction of (k,3)-arcs in the projective plane PG(2,7). We found that there are two (5,3)-arcs, four (6,3)-arcs, six (7,3)arcs, six (8,3)-arcs, seven (9,3)-arcs, six (10,3)-arcs and six (11,3)-arcs. All of these arcs are incomplete. The number of distinct (12,3)-arcs are six, two of them are complete. There are four distinct (13,3)-arcs, two of them are complete and one (14,3)-arc which is incomplete. There exists one complete (15,3)-arc.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

This research deals with leverage and its impact on the profitability of Islamic banks in Iraq for the years (2015-2018), the research variables of leverage have been analyzed and measured as an independent variable, profitability as a dependent variable, and the research is based on a main hypothesis: there is a moral relationship of statistical significance. Between leverage and profitability at The Islamic Cooperation Bank for the period (2015-2018). The results of the research showed that there are moral (exorcist) relationships between the ratio of leverage and profitability indicators, as the higher the leverage ratio, the higher the profitability indicators. In addition, The Islamic Cooperation Bank has adopted a conservative poli

This research aims to know the reality of succession planning in the researched organization and how it occupies the important jobs in the organization and its readiness for sudden and urgent events that lead to the vacancy of these jobs, and the importance of this research is that it is one of the rare Arab and Iraqi studies and research in this field, as it is one of the first researches It deals with the reality of succession planning in light of the retirement law No. (26) of 2019, and the research problem was the absence of consecutive planning programs and the weak preparation of suitable candidates to face sudden and urgent conditions as replacements for current leaders who occupy the leading and key positions in the depar

The kindergarten teacher play a role in fixing the children behavior so she must plant the value and the habits that make a positive behavior and accepted by the society so the teacher must know all the right educational psychological styles to fix the children behavior and make them accepted psychologically and socially so the problem of the research start from knowing the relation between the methods of dealing with the kindergarten’s teachers and the non right behavior appearance for the kindergarten children. The current research aims to measure the negative behavior appearance of the children of kindergarten and distinguish it according to (sex and levels) and to distinguish the most using styles by the teachers of kinderg

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med