There are great figures in our nation, who are famous for their encyclopedia in their sciences, and their fame spreads across the horizons for what they presented to their religion and nation.
So they became torches of guidance, advocates of goodness, and treasuries of knowledge until God inherits the earth and those on it.
Among these imams is Imam al-Qurtubi, who died in the year (671 AH), after whom he left a great legacy of valuable books, including this one, which is the subject of my research, his valuable interpretation (Al-Jami’ Li Ahkam Al-Qur’an). Taking from him and his approach in interpreting the verses of judgment, following the method of extrapolation, investigation and deduction to know his style, which he used in his authorship, and to stand on the sources that he relied on in his book.
There are many studies that discussed the famous museum's graveyards in the Islamic worlds, to study the lives of these figures, there are many difficulties for their studies because the first we need the regularity and history information, and many sciences support, such as in language, geography information.
I am studying the research from Maraqid Al-Maaraf book by Harz Aldeen, the book has large members about the persons have graved in Persian Country in the middle ages, there are more than (30) figures in my study, I have studied every figure in this research depending on the sources and references books.
A neutron induced deuteron emission spectra and double differential cross-sections (DDX), in 27Al (n, D) 26Mg, 51V (n, D)50Ti , 54Fe ( n, D)53Mn and 63Cu (n, D) 62Ni reactions, have been investigated using the phenomenological approach model of Kalbach. The pre-equilibrium stage of the compound nucleus formation is considered the main pivot in the discription of cross-section, while the equilibrium (pick up or knock out ) process is analyzed in the framework of the statistical theory of cluster reactions, Feshbach, Kerman, and Koonin (FKK) model. To constrain the applicable parameterization as much as possible and to assess the predictive power of these models, the calculated results have been compared with the experimental data and othe
... Show MoreGood governance of service quality through the adoption of sustainable energy the study of A1- Karkh historic center of in Baghdad city
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first
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Background: Low back pain is the most common health problem in men and women between the ages of 20 and 50 years. The lumbar disc prolapse has a major role in this condition. Treatment is either conservative or surgical. The most common surgical interventions are either laminectomy or interlaminar approach.
Objective: To determine which is the best surgical approach for the patient according to his/her type of disc herniation.
Patients and methods: A comparative clinical study conducted in the Neurosciences Hospital, Baghdad, Iraq from January 2016 to January 2018. In this paper we evaluated the clinical outcome following both approaches
Results:
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Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers. The experiment’s
... Show MoreFinding similarities in texts is important in many areas such as information retrieval, automated article scoring, and short answer categorization. Evaluating short answers is not an easy task due to differences in natural language. Methods for calculating the similarity between texts depend on semantic or grammatical aspects. This paper discusses a method for evaluating short answers using semantic networks to represent the typical (correct) answer and students' answers. The semantic network of nodes and relationships represents the text (answers). Moreover, grammatical aspects are found by measuring the similarity of parts of speech between the answers. In addition, finding hierarchical relationships between nodes in netwo
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The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe
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