Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Various theories on learning have been developed with increasing frequency in the last
few decades. In tandem with this, Multiple Intelligence theory appeared as a new approach to
education as well as an important theory in the field of language learning. Gardner explains
that all human beings have different intelligence fields and a potential to develop them. These
intelligences are (verbal-linguistic, logical-mathematical, visual-spatial, musical, bodilykinesthetic,
interpersonal, intrapersonal, naturalistic, and Existential).
This study aims at investigating Multiple Intelligences of Iraqi college EFL students. To
achieve the aims of the study, a questionnaire is adopted according to Birmingham model
which incl

The current research aims to detect the level of suicidal tendencies among secondary school students in terms of gender and educational stage (intermediate school students and high school students). The researcher adopted Al Hafeez's (2017) scale for suicidal tendencies, it consists of (57) items including six domains, namely: suicidal ideation, social motives for suicide, tendency to self-harm, desire for death, indifference and pessimism about life, willingness to commit suicide. The scale was modified to be (42) items after it was exposed to a group of experts. The scale was applied to a sample of (200) male and female students from secondary schools in Baghdad Governorate (Karkh - Rusafa) for the academic year 2021-2022. The results

The aimes of this study is to investigate Optimism and Pessimism among university undergraduates including the first and fourth stage students ,the sample of this stoudy contained (326) students ,(166) male and (160) female, The researcher adopted a scale of Dember et al (1889) translated and adjusted  to arabic version by Al-Dosoke (2001). The results have shown that   students have  optimism including the first and fourth stage and no significant difference between the students  as far as ncluding the first and fourth  study stage and gender, Implications of the results and recommendations for further research are discussed.

Find out the leadership ability among female university students.
The researcher made aquestionnaire consisting ofone open question for (50) female students of education college for women\ Baghdad university to mention main leadership abilities with leader student.
To achieve the aims of this study, the researcher made the following steps: 1- Collection and finalization the items of the scale Through literature review and previous studies and aquestionnaire consisting where (3) items have been extracted to make this questionnaire. 2- The test has been submitted to proffesionals of psychology to judge the valiidety of items of the scale where their opinion was they are good at (100%).The scale has been applied on statistical analysi