Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

The game of volleyball requires the formation of new motor responses, which in turn requires special physical characteristics in the performance of that skill, and the correct and accurate performance during the performance of the skills of passing from the top and smash serve in volleyball cannot be developed or improved without a good level of accuracy and what is required to perform the movements in terms of responses to the defense and attack movements. Therefore, the researchers decided to identify the type of relationship between the motor response speed with the performance accuracy of the skills of passing from the top and the smash serve in volleyball. The research aims to: 1. Identifying the motor response speed of fourth-stage s

The research aims to find out the impact of cognitive strategies in the mathematical competence of the students of the fourth scientific in the preparatory mahmoudiyah in the Directorate General of The Education of Karkh 2. A post-test of the mathematical competence prepared by (Jassim, 2018) was applied to the sample of (65) students, distributed into two groups of (33) students as experimental group and (32) students as a control group. The results found there are significant differences between the experimental group and the control group in testing the mathematical competence of students for the experimental group.

The study deals with reactivity insertion linear and non linear and/or Ramp reactivity expressed as a polynomial in time in the presence of two Feedback mechanisms, using the neutronic-thermohydraulic coupling in order to predict the neutron behavior as a function of time in terms of reactor power. Also, a comparative study has been achieved in the case of the presence of the feedback mechanisms. Insertion of Ramp reactivities in terms of polynomial in time to study the behavior of power and reactivity as a function of time in the presence of two feedback mechanisms (fuel and coolant) has been carried out and the results are displayed as plots, and showed this results corresponding with international results. The present study shows t

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

The research aims to show the effect of some short-term debt instruments (central treasury transfers, cash credit granted to the government by commercial banks) on the production of the wheat crop in Iraq, through its effect on money supply during the period (1990-2018), As the study includes two models according to the statistical program (Eviews9), the first model included measuring the effect of short-term debt instruments on money supply, and the second measuring the extent of the money supply's impact on Wheat crop production, as the results of the standard analysis showed that the short-term debt instruments used in the model were Significant effect on wheat crop production indirectly through its effect on money supply, As