Abstract

This study aims to find the relationships between social capital (social network, social trust, shared goals) and knowledge sharing (knowledge Donating, knowledge collecting) as independent variables and their impact on improving the quality of educational services (academic staffs quality, Quality of teaching methods and study curriculums). This research is an important, because it attempts to identify the relationship between social capital and the knowledge sharing and their effect on improving the quality of educational service for universities. The study problem was determined in several questions related to the nature of the correlation relationship - the impact between the different independent variables (

According to the importance of the subject of research, and the importance of the surveyed organization as a dynamic sector of the country in general , The research attempts to suggest to service organizations in general reconsidering the currently adopted mechanisms in the redesign of its functions , and in the services provided industry . The data was collected from (98) Director Mangers , head of department and head of division . The research tool is the questionnaire , which included (50) items . The results show Significant Effect & Correlation relationship between the two variables due to their dimensions . These lead to he application of job enrichment technology will increase the organization's ability to possess efficient hu

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

A newly flow injection-turbidimetric method characterized by it is speed and sensitivity has been developed for the determination of Amiloride in pure and pharmaceutical preparations. It is based on the formation of yellowish white precipitate for the Amiloride-phosphomolybidic acid ion pair in aqueous medium. Turbidity was measured by Ayah 6Sx1-T-1D solar cell CFI analyser via the attenuation of incident light from the surfaces precipitated particles at 0-180. The Chemical and physical parameters were investigated. Linear dynamic range for the attenuation of incident light versus Amiloride concentration was of 0.005-10 mmol.L-1, with the correlation coefficient (r) of 0.9986 , while the percentage linearity (r2%) was 99.71%. The L.O.

A newly flow injection-turbidimetric method characterized by it is speed and sensitivity has been developed for the determination of Amiloride in pure and pharmaceutical preparations. It is based on the formation of yellowish white precipitate for the Amiloride-phosphomolybidic acid ion pair in aqueous medium. Turbidity was measured by Ayah 6Sx1-T-1D solar cell CFI analyser via the attenuation of incident light from the surfaces precipitated particles at 0-180. The Chemical and physical parameters were investigated. Linear dynamic range for the attenuation of incident light versus Amiloride concentration was of 0.005-10 mmol.L-1, with the correlation coefficient (r) of 0.9986 , while the percentage linearity (r2%) was 99.71%. The L.O.

      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

    Keywords provide the reader with a summary of the contents of the document and play a significant role in information retrieval systems, especially in search engine optimization and bibliographic databases. Furthermore keywords help to classify the document into the related topic. Keywords extraction included manual extracting depends on the content of the document or article and the judgment of its author. Manual extracting of keywords is costly, consumes effort and time, and error probability. In this research an automatic Arabic keywords extraction model based on deep learning algorithms is proposed. The model consists of three main steps: preprocessing, feature extraction and classification to classify the document

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

The Turks used the Ottoman Turkish language from the thirteenth century to the twentieth century.  During this period and under the influence of Islamic civilization, a large number of words and structures were used from the Arabic and Persian languages, Therefore, many Arabic grammatical structures were used in the Ottoman Turkish language, such as the definite article simply because it was widely used.

The paper is concerned with the use of the Arabic definite article in the Ottoman Turkish language, and the aim of this contrastive study is to find out the similarities and differences between the two languages ​​in terms of meaning and structure. Since linguistic studies depend on the practical side or applied approach, two