The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on the understanding of thermodynamics, group work and self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq, for academic year 2011-2012. In this study, the pre and posttest were done and the instruments were administered to the students for data collection. Inferential statistics were employed to analyze data. The independent variables were the PBL, the PBL with lecture method, and the conventional teaching. Dependent variables of statistical analysis were posttest scores on the understanding of thermodynamics, group work skills, and self-directed learning skills. Covariates of statistical analysis were pretest scores of the understanding of thermodynamics, group work skills, and self-directed learning skills. The data were analyzed using statistical package social sciences (SPSS) version 19. Overall, the statistical results rejected all null hypotheses of this study. Thus, the use of PBL with lecture method enhances the understanding of thermodynamics better than using the PBL alone or using conventional teaching method. Using the PBL without or with lecture method promotes the skills of group work, and self-directed learning better than using the conventional teaching, among physics undergraduate.
This study aimed to explore the relationship between cyberbullying and levels of pessimism and optimism among female university students, emphasizing the significance of these variables in students' psychological well-being. The research problem was identified in the increasing rates of cyberbullying among female students and its negative impact on optimism and pessimism, alongside the lack of effective counseling programs addressing this issue. The study sample consisted of 30 third-year students from the College of Physical Education and Sports Sciences for Women during the academic year 2023--2024. The participants were deliberately selected through a lottery method. The researchers employed the descriptive survey method as it suited the
... Show More
This research is carried out to investigate the behavior of self-compacting concrete (SCC) two-way slabs with central square opening under uniformly distributed loads. The experimental part of this research is based on casting and testing six SCC simply supported square slabs having the same dimentions and reinforcement. One of these slabs was cast without opening as a control slab. While, the other five slabs having opening ratios (OR) of 2.78%, 6.25%, 11.11%, 17.36% and 25.00%. From the experimental results it is found that the maximum percentage decrease in cracking and ultimate uniform loads were 31.82% and 12.17% compared to control slab for opening ratios (OR
... Show MoreBackground: The purpose of this study was to assess the relation among the ramal length and width with various cervical and cranio-facial measurements for a sample of Iraqi adults with different skeletal classes. Materials and method: The sample composed of 71 Iraqi adults (36 females and 35 males) with an age ranged between 17-30 years and had different skeletal mal-relations using SNA, SNB and ANB to differentiate between them and assorting them into CL.I, CL.II and CL.III mal-relation. Each individual was subjected to clinical examination and digital true lateral cephalometric radiograph that had been analyzed using AutoCAD 2007 software computer program to determine sixteen linear and ten angular measurements. Descriptive statistics wer
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show More
(6)
(4)
The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
... Show More
(1)
A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
... Show More
(7)
(7)
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show More
(6)
(4)
Many studies have been made and still concerning the field of translation. Since the mid-90's a considerable amount of researches has tackled the problem of gender and its effect on the process and the product of translation. Simon (1996, p 508) points out that when comparing women and men as translators and writers through history, women seem to be the weaker side. This paves the way to feminist movements which produce prominent studies concerning gender as a concept and translator's gender as practice on the quality and the accuracy of the translation.
Flotow (in Meschia, 2012, p 1-4) outlines several issues that can be
... Show More
Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio
... Show More