In this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied. The method of maximum likelihood is used for estimating the model parameters. Numerical illustration and an application to a real data set are given to show the flexibility and potentiality of the new model.

Owing to their remarkable characteristics, refractory molybdenum nitride (MoN x )-based compounds have been deployed in a wide range of strategic industrial applications. This review reports the electronic and structural properties that render MoN x materials as potent catalytic surfaces for numerous chemical reactions and surveys the syntheses, procedures, and catalytic applications in pertinent industries such as the petroleum industry. In particular, hydrogenation, hydrodesulfurization, and hydrodeoxygenation are essential processes in the refinement of oil segments and their conversions into commodity fuels and platform chemicals. N-vacant sites over a catalyst’s surface are a significant driver of diverse chemical phenomena. Studies

Owing to their remarkable characteristics, refractory molybdenum nitride (MoNx)-based compounds have been deployed in a wide range of strategic industrial applications. This review reports the electronic and structural properties that render MoNx materials as potent catalytic surfaces for numerous chemical reactions and surveys the syntheses, procedures, and catalytic applications in pertinent industries such as the petroleum industry. In particular, hydrogenation, hydrodesulfurization, and hydrodeoxygenation are essential processes in the refinement of oil segments and their conversions into commodity fuels and platform chemicals. N-vacant sites over a catalyst’s surface are a significant driver of diverse chemical phenomena. Studies on

The primary aim of this research was to study visual spatial attention and its impact on the accuracy of the diagonal spike in volleyball. A total of 20 volleyball players of Baghdad participated in this study. The sample was homogeneous in terms of height, weight and age of the players. The tests used in the present study were: 1) Visual Spatial Attention Test. 2) Volleyball Spike Test. Based on the findings of the study, the researcher concluded that visual spatial attention has a significant impact on the accuracy of the diagonal spike in volleyball.

This study investigates the effectiveness of mental games in enhancing shooting accuracy among young basketball players. Initially, baseline shooting accuracy was assessed through tests conducted prior to a three-week intervention involving mental games. A follow-up test revealed a significant improvement in participants' shooting accuracy following the intervention. Given the noticeable differences in the new shooting scores compared to the initial assessments, a second set of pre-intervention tests was conducted. These tests reaffirmed the significant enhancement in shooting accuracy, substantiating the hypothesis that mental games positively affect performance. The findings highlight the importance of these intervention programs

This study investigates the effectiveness of mental games in enhancing shooting accuracy among young basketball players. Initially, baseline shooting accuracy was assessed through tests conducted prior to a three-week intervention involving mental games. A follow-up test revealed a significant improvement in participants' shooting accuracy following the intervention. Given the noticeable differences in the new shooting scores compared to the initial assessments, a second set of pre-intervention tests was conducted. These tests reaffirmed the significant enhancement in shooting accuracy, substantiating the hypothesis that mental games positively affect performance. The findings highlight the importance of these intervention programs

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

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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