The current study aims to investigate the effect of (SWOM) strategy on acquiring the psychological concepts of educational psychology course and its retention among education college students. To do this, a sample of (57) male and female student were intentionally selected from first grade, Kurdish department / college of education / Ibin Rushd of human sciences. The sample distributed on two classes, whereby the experimental group consisted of (28) student were taught according to the (SWOM) strategy while the control group made up of (29) student were taught based on the tradition method. The two researchers designed a scale included (50) item to measure students' achievement. The experiment lasted for ten weeks, SPSS was used

The goal of current research to:1 - Know when aesthetic implications (Korchh)2 - To form the structure of systemic indicators and results that reflect the visions of intellectual, philosophical and aesthetic art for this study.The theoretical framework for the study of the search for the meaning of beauty, definition ( Krochh) being a philosopher, his views, his own aesthetic philosophy, knowledge, art and beauty, as well as a subject of artistic and aesthetic taste and Study in Art Education.The goals have been achieved during the search of Investigation theoretical framework for the search, which tried (INT) to form a clear vision check the second goal by the indicators reached.In light of this, the researcher recommended the need for

Emotional competence, is relatively a new concept, stands for the ability of people to perceive their feelings and emotions, and sharing them with others. It also refers to capability in optimizing these feeling and emotions, and managing them over various situations. Thus, this study aims to examine the efficiency of counseling program in developing an emotional competence among intermediate school students in Baghdad city. The sample included group of female students at intermediate stage. The findings revealed none of experimental and control groups have statistically significant differences in pre-posttests of emotional competence efficiency.

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

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l