The Child's theatre was and still is the most investing art for masks of all kinds (partial and total) for suspense, aesthetic and artistic purposes that meet the requirements of those performances. Here the actor's performance is associated with two tools, i.e. the body and the mask, where it has become a must to search for the performance transformations required in order to achieve the highest level of the right performance through this dualism. This urged the researcher to address this problem. Thus, the researcher has put forward an objective to identify the transformations of the character's performance between the body and the mask in the child's theatre shows. The research consists of a methodological framework and a theoretical

Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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

The process of evaluating business processes, complex, repetition of procurement processes, need for raw materials and frequency of demand, which makes dealing with suppliers in the evaluation process, making the need for a process intervention in the process. Lighter on the other hand.

Many Iraqi companies suffer from problems related to suppliers, and cases of administrative and financial corruption are often raised regarding this type of contract and from this reality the necessity of researching this problem and trying to develop some solutions to reduce its impact on the companies' work, by using a method that works according to the standards adopted in Evaluation and selection of the supplier in the

ABSTRACT

Learning vocabulary is a challenging task for female English as a foreign language (EFL) students. Thus, improving students’ knowledge of vocabulary is critical if they are to make progress in learning a new language. The current study aimed at exploring the vocabulary learning strategies used by EFL students at Northern Border University (NBU). It also aimed to identify the mechanisms applied by EFL students at NBU University to learn vocabulary. It also aimed at evaluating the approaches adopted by EFL female students at Northern Border University (NBU) to learn a language. The study adopted the descriptive-analytical method. Two research instruments were developed to collect data namely, a survey qu

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.