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 based on the fusion of probabilities. Individually, the classifier based on PI achieved 93.1% accuracy, whereas the deep classifiers reached classification accuracies over 90% only in isolated cases. Overall, the average accuracy of the deep networks over the four corneal maps ranged from 86% (SfN) to 89.9% (AN). The classifier ensemble increased the accuracy of the deep classifiers based on corneal maps to values ranging (92.2% to 93.1%) for SqN and (93.1% to 94.8%) for AN. Including in the ensemble-specific combinations of corneal maps’ classifiers and PI increased the accuracy to 98.3%. Moreover, visualization of first learner filters in the networks and Grad-CAMs confirmed that the networks had learned relevant clinical features. This study shows the potential of creating ensembles of deep classifiers fine-tuned with a transfer learning strategy as it resulted in an improved accuracy while showing learnable filters and Grad-CAMs that agree with clinical knowledge. This is a step further towards the potential clinical deployment of an improved computer-assisted diagnosis system for KCN detection to help ophthalmologists to confirm the clinical decision and to perform fast and accurate KCN treatment.
This study aims to prepare educational sessions for the strategy (team-pair-solo) in practical volleyball lessons for female students and identifying its effect on learning the accuracy of the spiking skill in volleyball. An experimental design with experimental and control groups was employed on a purposive sample of (30) female students who were to constitute (42.254%) from their community represented by the sophomores at the College of Physical Education and Sports Sciences for Girls / University of Baghdad who are in good standing in the morning study for the academic year (2022-2023), whose total number is (71) students. According to the determinants of the experimental design, participants were divided into two equal groups, a
... Show MoreThe 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
... Show MoreThe study aimed to prepare a measure of metacognitive thinking commensurate with learning the skill, preparing educational units using the Claus Meyer model for metacognitive thinking, and learning the skill of defending the court in volleyball. To identify the effect of educational units using the model (and Claus Meyer) for metacognitive thinking and learning the skill of defending the court in volleyball. The two researchers used the experimental approach with the design of the experimental and control groups.The research community consisted of students of the second stage / College of Physical Education and Sports Sciences / University of Baghdad for the academic year 2021-2022, whose number is (385) st
... Show MoreA free convective heat transfer from the inside surface of a uniformly heated vertical circular tube has been experimentally investigated under a constant wall heat flux boundary condition for laminar air flow in the ranges of RaL from 6.9108 to 5109. The effect of the different sections (restrictions) lengths placed at the exit of the heated tube on the surface temperature distribution, the local and average heat transfer coefficients were examined. The experimental apparatus consists of aluminum circular tube with 900 mm length and 30 mm inside diameter (L/D=30). The exit sections (restrictions) were included circular tubes having the same inside diameter as the heated tube but with different lengths of
... Show MoreThis research presents a numerical study to simulate the heat transfer by forced convection as a result of fluid flow inside channel’s with one-sided semicircular sections and fully filled with porous media. The study assumes that the fluid were Laminar , Steady , Incompressible and inlet Temperature was less than Isotherm temperature of a Semicircular sections .Finite difference techniques were used to present the governing equations (Momentum, Energy and Continuity). Elliptical Grid is Generated using Poisson’s equations . The Algebraic equations were solved numerically by using (LSOR (.This research studied the effect of changing the channel shapes on fluid flow and heat transfer in two cases ,the first: cha
... Show MoreIn this research, an experimental study was conducted to high light the impact of the exterior shape of a cylindrical body on the forced and free convection heat transfer coefficients when the body is hold in the entrance of an air duct. The impact of changing the body location within the air duct and the air speed are also demonstrated. The cylinders were manufactured with circular, triangular and square sections of copper for its high thermal conductivity with appropriate dimensions, while maintaining the surface area of all shapes to be the same. Each cylinder was heated to a certain temperature and put inside the duct at certain locations. The temperature of the cylinder was then monitored. The heat transfer coefficient were then cal
... Show MoreThe present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in
... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreThe 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
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