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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 05 2016
Journal Name
Baghdad Science Journal
Preparation of Unsaturated Polyester Nanocomposites and Studying Their Mechanical Properties Using some Inorganic Additives
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In this study three inorganic nano additives, namely; CaCO3, Al2O3 and SiO2 were used to prepare nanocomposites of unsaturated polyester in order to modify their mechanical properties, i.e. tensile strength, elongation, impact and hardness. The results indicated that all the three additives were effective to improve the mechanical properties up to 4% by weight. The effectiveness of them follows the order : CaCO3 > Al2O3 > SiO2 This is due to their particle size in which CaCO3 (13nm), Al2O3 (20-30nm) and SiO2 (15-20nm).

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Environmental Engineering And Science
Fenton-like degradation of direct blue dye using green synthesised Fe/Cu bimetallic nanoparticles
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This study relates to synthesis of bentonite-supported iron/copper nanoparticles through the biosynthesis method using eucalyptus plant leaf extract, which were then named E-Fe/Cu@B-NPs. The synthesised E-Fe/Cu@B-NPs were examined by a set of experiments involving a heterogeneous Fenton-like process that removed direct blue 15 (DB15) dye from wastewater. The resultant E-Fe/Cu@B-NPs were characterised by scanning electron microscopy, Brunauer–Emmet–Teller analysis, zeta potential analysis, Fourier transform infrared spectroscopy and atomic force microscopy. The operating parameters in batch experiments were optimised using Box–Behnken design. These parameters were pH, hydrogen peroxide (H2O2

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Comparative Study of Image Denoising Using Wavelet Transforms and Optimal Threshold and Neighbouring Window
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NeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Desulphurization of Simulated Oil Using SAPO-11 with CNT's as Adsorbent: A Kinetic Study
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In this study, sulfur was removed from imitation oil using oxidative desulfurization process. Silicoaluminophosphate (SAPO-11) was prepared using the hydrothermal method with a concentration of carbon nanotubes (CNT) of 0% and 7.5% at 190 °C crystallization temperature. The final molar composition of the as-prepared SAPO-11 was Al2O3: 0.93P2O5: 0.414SiO2. 4% MO/SAPO-11 was prepared using impregnation methods. The produced SAPO-11 was described using X-ray diffraction (XRD) and Brunauer-Emmet-Teller (N2 adsorption–desorption isotherms). It was found that the addition of CNT increased the crystallinity of SAPO-11. The results showed that the surface area of SAPO-11 cont

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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Study of Water Flux through Forward Osmosis Membrane Using Brine\Fresh Water System
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The present work aims to improve the flux of forward osmosis with the use of Thin Film Composite membrane by reducing the effect of polarization on draw solution (brine solution) side.This study was conducted in two parts. The first is under the effect of polarization in which the flux and the water permeability coefficient (A) were calculated. In the second part of the study the experiments were repeated using a circulating pump at various speeds to make turbulence and reduce the effect of polarization on the brine solution side.
A model capable of predicting water permeability coefficient has been derived, and this is given by the following equations:
Z=Z+C.R.T/9.8(d2/D2+1) [Exp. [-9.8(d

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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Simulation the Radiation Zone of Al-Mussaib Power Plant by using Monte Carlo Method
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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Engineering
Some Mechanical Properties of Concrete by using Manufactured Blended Cement with Grinded Local Rocks
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The  use  of  blended  cement  in  concrete  provides economic, energy savings,  and ecological  benefits, and also  provides. Improvement in the properties of materials incorporating blended cements. The  major  aim  of  this  investigation  is  to  develop  blended  cement  technology using  grinded local rocks . The research includes information on constituent materials, manufacturing processes and performance characteristics of blended cements made with replacement (10 and 20) % of grinded local rocks (limestone, quartzite and porcelinite) from cement.

The main conclusion of this study was that all ty

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

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Publication Date
Sun Dec 02 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Estimation of the Rock Mechanical Properties Using Conventional Log Data in North Rumaila Field
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Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate t

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Engineering
A Comparison Study of Brine Desalination using Direct Contact and Air Gap Membrane Distillation
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Membrane distillation (MD) is a hopeful desalination technique for brine (salty) water. In this research, Direct Contact Membrane Distillation (DCMD) and  Air Gap Membrane Distillation (AGMD) will be used. The sample used is from Shat Al –Arab water (TDS=2430 mg/l). A polyvinylidene fluoride (PVDF) flat sheet membrane was used as a flat sheet form with a plate and frame cell. Several parameters were studied, such as; operation time, feed temperature, permeate temperature, feed flow rate. The results showed that with time, the flux decreases because of the accumulated fouling and scaling on the membrane surface. Feed temperature and feed flow rate had a positive effect on the permeate flux, while permeate temperatu

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