This research aims toknow the learning styles according to the model of Felder and Silverman and its relationship to effectively self- perceived mathematicalamong students of the Faculty of Education Pure Sciences - Ibn al-Haytham. By answering the following questions: 1. What are the preferred methods of learning among students in the mathematics department according to the model Felder and Silverman? 2. What is the mathematicalself-perceived levelof the students at the Department of Mathematics effectiveness level? 3. What is the relationship between learning styles according to the Felder model and Silverman and the effectiveness of mathematical self-perceived of the students of the Department of Mathematics? The research sample consiste

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

Online learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.

Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential

The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

Objectives: To determine the impact of an educational program on nurses’ knowledge
and practices concerning neurogenic bladder rehabilitation for spinal cord injured persons
through a follow-up approach each two months post program implementation for six
months.
Methodology: "Follow-up" longitudinal design by using time series approach of data
analysis and the application of pre-post tests approach for the study and the control
groups. The study was carried out at Ibn Al-Kuff hospital for (SCI) in Baghdad governorate
from 5th of July 2010 to 15th of October 2011. To achieve the objectives of the study, a
non-probability (purposive) sample of (60) nurses (males and females) were working in SCI
units were selec

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The current study aims at investigating the effect of cooperative learning (Jigsaw) on motivation of female students. Department of kindergarten to learn Human biology. This is of be dove through verification of the hypothesis that there is no significant difference at the 0.05 level between the motivation of experiment of group subjects who study according to (Jigsaw) cooperative learning and that of the control group subjects who study traditionally.
The study is limited to female students al the first year-Department of kindergarten college of Education for women university of Baghdad during the academic year 2007-2008.
An experiment of design of partial control and post-test for two groups is used. The experiment groups consist

Objectives: The study aims to evaluate the effectiveness of the educational program on nurses’ knowledge towards nursing management for patients undergoing percutaneous coronary intervention (PCI), as well as to find out the relationship between nurses' knowledge and some of their demographic characteristics (age, gender, level of education, and years of experience in cardiac units).

Methodology:  A Quasi-experimental as one group (pre and post test) study was conducted at the Heart Center in Al-Diwaniyah city for the period from December 7, 2019 to February 23, 2020. A sample of (40) nurses working in the heart center was chosen from different nursing addresses. The sample covered one gro