The research aims to find out the difficulties of studying the subject of modern and contemporary history and its proposed solutions from the point of view of the students of the literary sixth in the secondary schools of the Directorate of Education Rusafa I-Baghdad, the research community of students of the literary sixth stage, which Number(150) students,and to achieve the- And Fisher's equation-and percent weight).The results showed the existence of a number of real difficulties achieved for the study of modern and contemporary history of the sixth literature, and the data showed the existence of Unreal difficulties diagnosed from the students ' point of view .In light of this, the researcher dev

The current study aims to assess the ethical behavior among female students who are using a social media network in addition to describe the variables of interest (social media use and ethical behavior) among participants, in which to find out the effects of social media on the ethical behavior of high school female students. A quantitative approach was adopted to collect the relevant data for the study, six schools included in this study from the six directorates of education in Baghdad city. Subsequently, SPSS software was applied to analyze the relevant data of the study. To achieve the research objectives, a questionnaire was composed of three sections: Part I: deals with the student's demographic information. Part II: deals with inf

The aim of this research is to identify how to employ the social imagination and its representations in the paintings of the students of the Department of Art Education. Students of the Department of Art Education in the light of this tool, and the researcher reached a number of results, the most important of which are:
1. The indicator of the social imagination in the excitement of the artist and the recipient, because the representations are embodied in forms within the painting and close to reality.
2. An artistic sample of the representational imagination and the creative imagination was found to be more than the imaginary imagination.
3. Individual symptoms related to the term.
4. The representations of the socia

Effect of Using Computer in Getting and Remaining Information at Students of First Stage in Biology Subject MIAAD NATHIM RASHEED LECTURER Abstract The recent research goal is to know the influence of computer use to earn and fulfillment information for students of first class in biology material and to achieve that put many of the zeroing hypothesis by researcher as follow: There were no differences between statistical signs at level (0,05) between the average students' marks who they were study by using computer and between the average student ' marks who they were study in classical method of earning and fulfillment. The researcher chose the intentional of the medical technical institute that included of two branches the first class (A

This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be