This research aims to identify the impact of the selective model in acquiring the concepts of Kurdish grammar among female students in the eighth grade, and to achieve the goal of research, the researcher selected the experimental design with partial control  and dimensional testing; the sample includes basic schools in the Chim district of Chamal/ Sulaymaniyah and randomly selected the basic school (Maha Bad) to be the field of application of the experiment and the random drawing method was chosen: two out of three sections and the number of students of the two sections is (75) students; section (C) represents the experimental group that studied the rules according to the selective model and its number is (37) students, while secti

One of the scientific education aims, preparing a student able to keep up with the scientific developments and innovations around him and make him contribute, adapt, investment and continue development. The concepts of nanotechnology from scientific innovation open up an important area of thinking and intervention in the field of chemistry applications in daily life, the technological changes lead to social, political and economic changes which result that the students to have the knowledge, understanding, awareness, appreciation and sense in applications of modern technology for their use optimally, in order to cope with these scientific and technological changes. The research aims at finding out the correlation between the acquisi

Incorporating modern technology into education is becoming imperative. Numerous pharmacy institutions are incorporating virtual reality (VR) technology training into their curricula to enhance educational experience. This review examines the current state, historical evolution, and application of VR programs in pharmacy education and training. The review also provides details about the main challenges and limitations associated with the use of this technology. The VR technology, including virtual laboratories and simulations, significantly improves clinical training and educational outcomes. The utilization of VR in clinical teaching encounters numerous barriers, including ethical concerns and technological constraints, as well as other res

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

Title: Arabic Manuscript, Concepts and Terms and Their Impact on Determining Its Historical beginnings and extension of its existence.

Researcher: Dr. Atallah Madb Hammadi Zubaie.

Bn the name of Allah Most Merciful

The interest in manuscripts and rules  of their investigation and dissemination appeared soon, and the speech in editing terms and concepts appeared in sooner time.  When looking at the classified books  in the Arab manuscripts , we find the books of the first generation  did not allude definition for this term  , but rather  focused on  the importance of manuscripts and their  existence locations, indexing, care, and verification rules. The  reason for this is that the science of Arabic manuscrip

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class