The current study aimed to measure the attitudes of female teachers towards the use of digital learning and the degree of possessing their digital education skills. The study sample consisted of (180) workers with disabilities (mental disability، auditory impairment، visual disability، hyperactivity and distraction. To achieve the goals of the study, the transformation measure was used towards digital education for people with disabilities. The study reached the following results: the availability of digital learning skills among workers with disabilities. The study concluded with a series of recommendations including holding Training courses to keep up with the challenges of educational trends and modern technology in this area.

The current research aims to know the complementary use of the paper book and the digital book by defining the paper book and the digital book and knowing the methods and methods of obtaining each of them and indicating the extent of their use and for what purpose and knowing the difficulties that researchers face in using each of them and which is better using the paper book or the digital book in preparing research Studies and for no reason. The research relied on the descriptive approach and the questionnaire as a tool for data collection, and it was distributed to professors and students of Iraqi universities. The research sample reached (219) individuals and reached a set of results, the most important of which are: Preference for the

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

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

Background: The pandemic crisis prompted the world to adopt unexpected approaches to continue life as normally as possible. The education sector, including professors, students, and the overall teaching system, has been particularly affected. Objective: This study seeks to evaluate the benefits, challenges, and strategies related to COVID-19 from the perspectives of college students, particularly those in higher education in Iraq. Method: The online survey questionnaire was distributed via Google Forms and specifically aimed at undergraduate dental students. Results: A total of 348 students participated in the survey. There was a significant correlation (P > 0.01) between student satisfaction with hybrid learning and their experi

Due to their attractive properties, silver nanowires (Ag-NWs) are newly used as nanoelectrodes in continuous wave (CW) THz photomixer. However, since these nanowires have small contact area, the nanowires fill factor in the photomixer active region is low, which leads to reduce the nanowires conductivity. In this work, we proposed to add graphene nanoantenna array as nanoelectrodes to the silver nanowires-based photomixer to improve the conductivity. In addition, the graphene nanoantenna array and the silver nanowires form new hybrid nanoelectrodes for the CW-THz photomixer leading to improve the device conversion efficiency by the plasmonic effect. Two types of graphene nanoantenna array are proposed in two separate photomixer conf

In this work the fabrication and characterization of poly(3-hexylthiophene) P3HT-metallic nanoparticles (Ag, Al). Pulsed Laser Ablation (PLA) technique was used to synthesis the nanoparticles in liquid. The Fourier Transformer Infrared (FTIR) for all samples indicate the chemical interaction between the polymer and the nanoparticles. Scanning Electron Microscopic (SEM) analysis showed the particle size for P3HT-AgNps samples between 44.50 nanometers as well the spherical structure. While for P3HT-AlNps samples was flakes shape. Energy Dispersive X-ray (EDX) spectra show the existing of amount of metallic nanoparticles.