rusul ali hussien mudhafer

In the last decade, the number of digital images has increased dramatically. Noise is unwanted particles or signals contaminating the image during the captured image and transmission. Image noise reduces the image quality and increases the processing failure ratio. It is highly recommended to remove the noise, and before removing the noise, we have to know the type of noise, which highly assists in suggesting the proper de -noise algorithm. This study introduces a method to effectively detect and recognize image noise of various types (Gaussian, lognormal, Rayleigh, Salt & Pepper, and Speckle). The proposed model consists of two stages: the first stage is detecting the noise in an image using Convolutional Neural Network. The second stage classifies the noisy images into one of five types of noise using a new method based on a combination of deep wavelet machine learning classifiers, we select five machine learning classifiers (support vector machine, decision tree, random forest, logistic regression, and K-nearest neighbor) to choose the more efficient classifier ultimately. The combination of wavelet with machine learning, specifically SVM, can highly enhance the results, where the accuracy was (91.30 %) through many experiments conducted to build a sturdy classification model.

The Department of Basic Sciences at the College of Nursing at the University of Kufa organized a workshop entitled “Enhancing Blended Learning with Effective Presentation Tools”, as part of the Deanship of the College’s ongoing efforts to develop teaching methods and improve the quality of education. The workshop aimed to provide faculty members with the skills needed to use modern presentation tools effectively, which contributes to achieving a distinguished educational experience that combines traditional education and e-learning. The workshop witnessed great interaction from the participants who expressed their desire to apply what they learned in the classroom. The workshop organizers stressed that improving presentation methods contributes to enhancing students’ understanding and increasing their motivation to learn, noting that blended learning has become an essential element in developing the academic system. At the end of the workshop, the floor was opened for discussion to answer questions and inquiries from the attendees, where fruitful discussions took place on best practices in using technology in education, and ways to overcome the challenges that faculty members may face in this field.