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

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

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

على الرغم من التقدم العلمي والتكنولوجي للمعلومات فما زالت الذاكرة تقوم بالدور الاساس بغض النظر عن الامكانيات العلمية في العصر الحديث من حيث ان الكثير من مفرادات الثقافة الانسانية ينقل من جيل الى اخر بواستطتها, ومن الصعب تصور حياة نفسية مقصورة على الحافز فقط, اننا لو اقتصرنا على الحافز لكان التفكير غير ممكن لان الذاكرة هي التي تصل الحافز بالماضي وابسط صورها هي الذاكرة الاولية . فلولا الذاكرة لما تكونت ال

Historical concepts are among the concepts that are difficult to present to the pre-school child except by using modern techniques, as well as the difficulty of making visits to all historical monuments and going back to antiquity and the lack of studies in this area, therefore, we need an attractive medium that children love which is able to convey some abstract concepts that are difficult to teach to children using traditional methods, and among these activities that the kindergarten provides to children are the stories through which they develop their linguistic wealth, consolidate their religious and spiritual inclinations, refine their correct morals, and form their proper attitudes, knowledge and life concepts.

The

The research seeks to measure stigma on the children of kindergarten and get to know the differences between males and females and between kindergarten and preschool in social fear. Has been verified by the researcher was true scale of social fear after the drafting of paragraphs (43) items, and display it on a group of experts , has proven its validity after some amendments , bringing the number of paragraphs in its final form (29) items . was statistical analysis of the paragraphs of the brokered power-discriminatory , it is clear that all paragraphs distinct and statistically significant, as well as to find a relationship degree of para-class items consistency . was to ensure the stability of the scale in a re-test , as the stability

The current research was aimed at the following:
1. Measurement of   Boldness among the students of  university.

2. Identify the differences in Boldness between university students according to variable of Sex (male / female) and variable of Specialization (scientific / literary).

To achieve this aims of the research, the researcher set up the instrument is scale of the Boldness that consistent (34) item, and the researcher applying this scale on the sample amounted to (200) student of  University. Then   after data processing statistically, the researcher reached the following results: