— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experiment, an achievement test was built, which is in its final form (25) test items and a practical intelligence test out of (20) test items of the objective type for both of them. Based on the findings, the students of the experimental group who studied according to deep learning strategies outperformed on those who by the traditional.
Abstract
This study identified the developing of a range of students' geography learning skills and the change in their attitudes toward fieldwork as a consequence of leaning experiences that occurred within a field trip. The sample of the study consisted of (27) students within a special topic course enrolled in Geography Department at Umm Al-Qura University in Saudi Arabia in semester 2, 2018. A range of students' geography learning skills were measured by the skills questionnaire that consisted of 12 geography skills after completing field work. Changes in students' at
... Show MoreOptimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni
... Show MoreHuman beings have an innate and natural aim to achieve their self-interests and to show their ability to overcome challenges in a better way, therefore the move towards self determination is expressed by intrinsic motivation. The desire of absorbing in this task is to enjoy the task in it self and benefitting from it such a motivation is the desire rooted in human nature to judge and choose in which individual is conscious in his self, abilities and adequacy that help him in control the different situations of life passed by him. His choices and actions are voluntary and non-restricted to intervention or external control because control is inner and subjective, while his behavior is self-regulated with the feeling of
... Show MoreThe study aims to identify the reality of the use of educational technology in the teaching of mathematics from the point of view of mathematics teachers in Amman, where the researcher used the descriptive survey method. The sample included (67) female teachers working in public schools in Amman. In order to achieve the objectives of the study, the researcher used the questionnaire as a tool to collect data. The study concluded that many educational techniques are not available from the point of view of the study sample. Mathematics teachers also found that there are many obstacles that prevent the use of educational techniques in schools, most notably the lack of courses offered to teachers on the use of teaching techniques in teaching
... Show MoreImage compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreThe complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra
... Show MoreThis study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
The research aims to identify the tax policy strategy adopted in Iraq after the change of the tax system in 2003 and beyond, and then make a comparison of the two strategies on corporate data whether they are charged with progressive tax rates and after the change of the system as the tax rates became fixed, and then indicate the changes In the tax proceeds, and knowing the imensions of the approved tax policy, is it a tax reform strategy or a strategy to attract investments.The research started from the problem of exposure of the Iraqi tax system to several changes, as this led to a reflection on the technical organization of taxes, in terms of the tax rate.The descriptive analytical approach was chosen to study the actual reality of th
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