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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 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.</p>
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Simulation Study on Optically Designed Refractive Beam Expander for Nd: YAG Laser Harmonics for 7 Km Detection Range
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The simulation study has been conducted for the harmonics of Nd: YAG laser, namely the second harmonic generation SHG, the third harmonic generation THG, and the fourth harmonic generation FHG. Determination of beam expander's expansion ratio for specific wavelength and given detection range is the key in beam expander design for determining minimum laser spot size at the target. Knowing optimum expansion ratio decreases receiving unit dimensions and increases its performance efficiency. Simulation of the above mentioned parameters is conducted for the two types of refractive beam expander, Keplerian and Galilean. Ideal refractive indices for the lenses are chosen adequately for Nd: YAG laser harmonics wavelengths, so that increasing transm

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Photochemistry And Photobiology A: Chemistry
Construction of co-zeolitic imidazolate framework/Bi2WO6 heterojunction photocatalyst with improved adsorption and photodegradation of ciprofloxacin
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Publication Date
Mon Sep 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Volumetric Mass Transfer Capacity Coefficient in the RTL Extractor
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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
NATURAL CONVECTION HEAT TRANSFER IN AN INCLINED CIRCULAR CYLINDER
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Experiments were carried out to investigate natural convection heat transfer in an inclined uniformly heated circular cylinder . The effects of surface heat flux and angle of inclination on the temperature and local Nusselt number variations along the cylinder surface are discussed . The investigation covers heat flux range from 92 W/m² to 487 W/m², and angles of inclination 0° ( horizontal) , 30° , 60° and 90° (vertical) . Results show an increase in the natural convection as heat flux increases and as angle of inclination moves from vertical to horizontal position. An empirical equation of average Nusselt number as a function of Rayliegh number was deduced for each angle of inclination .

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Publication Date
Sun Jun 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Convective Heat Transfer of Fluid Flowing Across a Vertical Plate
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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Engineering
Numerical Simulation of Natural Convection Heat Transfer from Interrupted Rectangular Fins
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      Numerical simulations have been investigated to study the external free convective heat transfer from a vertically rectangular interrupted fin arrays. The continuity, Naver-Stockes and energy equations have been solved for steady-state, incompressible, two dimensional, laminar with Boussiuesq approximation by Fluent 15 software. The performance of interrupted fins was evaluated to gain the optimum ratio of interrupted length to fin length (

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Publication Date
Tue Jul 21 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Numerical Study of the Heat Transfer Behavior in Helical Microcoil Tube
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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Investigation of heat transfer phenomena and flow behavior around electronic chip
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Computational study of three-dimensional laminar and turbulent flows around electronic chip (heat source) located on a printed circuit board are presented. Computational field involves the solution of elliptic partial differential equations for conservation of mass, momentum, energy, turbulent energy, and its dissipation rate in finite volume form. The k-ε turbulent model was used with the wall function concept near the walls to treat of turbulence effects. The SIMPLE algorithm was selected in this work. The chip is cooled by an external flow of air. The goals of this investigation are to investigate the heat transfer phenomena of electronic chip located in enclosure and how we arrive to optimum level for cooling of this chip. These par

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Publication Date
Fri Jan 01 2021
Journal Name
دراسات قانونية
The Legal Nature of the Build-Operate- transfer-Ownership Contract (B.O.T.)
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The legal nature of the Build-Operate-Transfer-Ownership Contract (B.O.T) The Build, Operate, and Transfer of Ownership Contract (BOT) has emerged as the most successful and safest method for involving the private sector in public sector services. The major infrastructure projects that are built through the BOT contract are no longer financed by the state and its budget, but the private sector has played a major role in financing These projects, especially developing countries that need to establish infrastructure or modernize their existing infrastructure, especially in the areas of transport, communications, services, electricity, water ..... and other public utilities.