The aim of the research is to find out the effect of the SPAWN strategy on the life skills of second-intermediate-grade students. This study stage represented the research community within the intermediate and secondary governmental daytime schools affiliated with the Directorate of Education of Diwaniyah. The experiment was applied in Al-Razai Intermediate School on a sample of second-grade intermediate students, including 66 students distributed into two groups: (32) students within the experimental group and (34) students within the control group. The two groups were equivalent with a number of variables (chronological age, intelligence test, previous information test, life skills scale). The results indicated that the two groups were eq

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

The study aimed to investigate the relationship between the multiple intelligence and the numerical sense. The chosen population of the study was the 4^th secondary stage students. The sample consisted of 400 female and male student. The researcher utilized two test; multiple intelligence test which include three categories of intelligence (logical-mathematical, spatial, and linguistics) consisted of (36) item, and the numerical sense test that consisted of (44) item. The two tests were constructed by the researcher himself. The psychometric properties of the test were also verified. The results showed that there was a correlation between the multiple intelligence and the numerical sense as well as the students’ means scores

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Autoría: Jehan Faris Yousif. Localización: Opción: Revista de Ciencias Humanas y Sociales. Nº. 89, 2019. Artículo de Revista en Dialnet.

Background: Dental caries is generally given the highest priority in national oral health services for adult populations. Yet, there is no study which has explored the impact on quality of life specifically related to dental caries in samples of dental students. The purpose of the current study was to assess the impact of caries experience on quality of life among dental students in three governorates in Iraq. Materials and Methods: This observational study included 1364 dental students aged 18–22 years old, from three governorates. Information on quality of life was obtained from a structured, self-administered questionnaire from the students who were willing to participate in the study. The data was collected, summarized and sta

Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection