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The Effects Of Pbl On Understanding Of Thermodynamics, Group Work And Self-Directed Learning Skills Among Physics Undergraduates
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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.

Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Possible Cardio-Protective Effects of Ethanolic Artichoke Extract against 5- Fluorouracil Induced Cardiac Toxicity in Rats
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Cardiac toxicity can occur during the therapy with several cytotoxic drugs, including 5- Fluorouracil (5- FU). It is an antimetabolite that acts during the S phase of the cell cycle and is activated by thymidine phosphorylase into fluorodeoxyuridylate (5 fluoro 2'deoxyuridine 5'monophosphate, 5-FdUMP) that inhibits thymidylate synthase, thus preventing DNA synthesis that leads to imbalanced cell growth and ultimately cell death. It is still a widely used anticancer drug, since 1957. The present study aimed to evaluate the possible cardio-protective effects of ethanolic artichoke extract (Cynara scolymus L.) against 5-fluorouracil (5-FU) induced cardio-toxicity in rats by evaluating serum levels of Alanine aminotransferase, aspartate amin

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Publication Date
Mon Apr 01 2019
Journal Name
Indian Journal Of Public Health Research And Development
Analysis of Serum Il-6 and CRP Levels among Autoimmune and Non- Autoimmune Hypothyroid Patients
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Hashimoto Thyroiditis (HT) is the most common autoimmune thyroid disease and the commonest cause ofhypothyroidism. C-reactive protein (CRP) is synthesized in hepatocyte in response to autoimmune disorders;strongly induced by IL-6. This study aimed to estimate serum IL-6 and CRP levels in autoimmune and non-autoimmune hypothyroidism. The present study included 60 Iraqi female hypothyroid patients divided to 30autoimmune and 30 non-autoimmune, with age ranged between 24-50 years and 30 healthy controls withage ranged between 27-52 years. Serum samples were collected from study groups. The levels of thyroidhormones (TSH, T4 and T3) were determined by using automated Chemiluminescence Immunoassay (CLIA)analysis system. Detection the levels of t

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Information Sources and their Role in E-learning from Iraqi College Students’ Viewpoint
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The study aims at identifying the sources of information and explaining their role in e-learning from the viewpoint of the Iraqi college students. The researchers relied on the descriptive method of the survey method to collect data and know the point of view of undergraduate students from the Department of Information in the College of Arts / Tikrit University and the Department of Quranic Studies at the College of Arts / University of Baghdad. The questionnaire was used as an instrument of the study, the research sample is (120) students; each section has (60) male and female students. The study concluded that there are many types and forms of information sources that students receive through electronic educational platforms from text con

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
Build and Implemented Learning Package for Prolog Programming Language Using Visual Basic.Net 2010
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E-Learning packages are content and instructional methods delivered on a computer
(whether on the Internet, or an intranet), and designed to build knowledge and skills related to
individual or organizational goals. This definition addresses: The what: Training delivered
in digital form. The how: By content and instructional methods, to help learn the content.
The why: Improve organizational performance by building job-relevant knowledge and
skills in workers.
This paper has been designed and implemented a learning package for Prolog Programming
Language. This is done by using Visual Basic.Net programming language 2010 in
conjunction with the Microsoft Office Access 2007. Also this package introduces several
fac

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Publication Date
Mon Mar 09 2026
Journal Name
Journal Of Asian Architecture And Building Engineering
Visual storytelling and place-based learning: a generative approach to architectural cultural awareness
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In architectural learning, it is difficult to stimulate cultural awareness through the traditional education approaches, which results in historic places being neglected as knowledge sources. This research explores the premise that sketch-based visual storytelling may act as a generative approach to connect cognition, emotion, and behavior in historical contexts. The study adopts a qualitative methodology to explore a learning experience comprising two phases: the first is a formal educational setting, and the second is a historical and cultural context, aiming to investigate the role of sketch-based storytelling in enhancing cultural awareness. MAXQDA was employed to code the students’ storyboards on three levels of cultural awareness, m

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