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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
Wed Feb 22 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETECTION OF ENTEROTOXINS OF Staphylococcus aureus IN MILK AND LOCOLLY SOFT CHEESES IN BAGHDAD CITY: DETECTION OF ENTEROTOXINS OF Staphylococcus aureus IN MILK AND LOCOLLY SOFT CHEESES IN BAGHDAD CITY
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This study aimed to detect of contamination of milk and local soft cheese with Staphylococcus aureus and their enterotoxins with attempt to detect the enterotoxin genes in some isolates of this bacteria. A total of 120 samples, 76 of raw milk and 44 of soft cheese were collected from different markets of Baghdad city. Enterotoxins in these samples were detected by VIDAS Set 2 system and it was found that enterotoxin A is present in a rate of 44.74% in milk samples and in a rate 54.50% in cheese samples. While other enterotoxins B, C, D, E were not found in any rate in any samples.
Through the study 60 isolates obtained from milk and cheeses were identified as Staphylococcus aureus by cultural, morphological and biochemical test by u

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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Educational And Psychological Researches
Developing Undergraduate Students' Geography Learning Skills during Fieldwork and Their Attitude toward It: Developing Undergraduate Students' Geography Learning Skills during Fieldwork and Their Attitude toward It
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Abstract

This study identified the developing of a range of students' geography learning skills and the change in their attitudes toward fieldwork as a consequence of leaning experiences that occurred within a field trip. The sample of the study consisted of (27) students within a special topic course enrolled in Geography Department at Umm Al-Qura University in Saudi Arabia in semester 2, 2018. A range of students' geography learning skills were measured by the skills questionnaire that consisted of 12 geography skills after completing field work. Changes in students' at

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Agriculture And Biology
Dietary Replacement with Food Waste and Black Soldier Fly Larvae Supplementation Improved Growth Performance, Nutrient Digestibility and Intestinal Microbial Population in Broilers
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This study was aimed to evaluate the effect of conventional ingredients replacement with alternative ingredients on growth performance, carcass quality, nutrient digestibility and intestinal microbial of broilers. One hundred twenty Cobb500 broiler chicks were randomly assigned to four diets. Corn, soybean meal and fish meal were replaced with rice waste, meat and bone waste and black soldier fly larvae (BSFL) at 0, 10, 30 and 50% to form four treatments. Body weight gain, feed conversion ratio and digestibility of crude protein and fat were improved in broilers fed the replacement diets. Feed intake was not affected by the treatments suggesting that the replacement diets were well accepted by the chicken. Escherichia coli was decre

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Publication Date
Tue Dec 06 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Blended Learning in Nursing Education at the Middle Region in Iraq
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Abstract

Objective(s): To evaluate blended learning in nursing education at the Middle Region in Iraq.

Methodology: A descriptive study, using evaluation approach, is conducted to evaluate blended learning in nursing education in Middle Region in Iraq from September 26th, 2021 to March 22nd, 2022. The study is carried out at two Colleges of Nursing at the University of Baghdad and University of Tikrit in Iraq. A convenient, non-probability, sample of (60) undergraduate nursing students is selected. The sample is comprised of (30) student from each college of nursing, Self-report questionnaire is constructed from the literature, for e

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Analysing errors in learning the preasent continuous tense:Associating interference with strategy of instruction
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Publication Date
Fri Mar 10 2023
Journal Name
Mathematics
Hamilton–Jacobi Inequality Adaptive Robust Learning Tracking Controller of Wearable Robotic Knee System
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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

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Publication Date
Tue Feb 19 2019
Journal Name
Heat And Mass Transfer
Mass transfer characteristics of a flow-by fixed bed electrochemical reactor composed of vertical stack stainless steel screens cathode
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Publication Date
Mon Dec 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Relationship Between Nusselt and Reynolds Number in Direct Contact Heat Transfer by Condensation of Light Hydrocarbons in Water
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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Study Effect of Central Rectangular Perforation on the Natural Convection Heat Transfer in an Inclined Heated Flat Plate
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Anumerical solutions is presented to investigate the effect of inclination angle (θ) , perforation ratio (m) and wall temperature of the plate (Tw) on the heat transfer in natural convection from isothermal square flat plate up surface heated (with and without concentrated hole). The flat plate with dimensions of (128 mm) length × (64 mm) width has been used five with square models of the flat plate that gave a rectangular perforation of (m=0.03, 0.06, 0.13, 0.25, 0.5). The values of angle of inclination were (0o, 15o 30o 45o 60o) from horizontal position and the values of wall temperature (50oC, 60 oC, 70 oC, 90 oC, 100o<

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Publication Date
Sun Feb 05 2023
Journal Name
Engineering, Technology & Applied Science Research
Performance Evaluation of Emulsion Liquid Membrane on Chlorpyrifos Pesticide Removal: Stability, Mass Transfer Coefficient, and Extraction Efficiency Studies
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Emulsion Liquid Membrane (ELM) is an emerging technology that removes contaminants from water and industrial wastewater. This study investigated the stability and extraction efficiency of ELM for the removal of Chlorpyrifos Pesticide (CP) from wastewater. The stability was studied in terms of emulsion breakage. The proposed ELM included n-hexane as a diluent, span-80 as a surfactant, and hydrochloric acid (HCl) as a stripping agent. Parameters such as mixing speed, aqueous feed solution pH, internal-to-organic membrane volume ratio, and external-to-emulsion volume ratio were investigated. A minimum emulsion breakage of 0.66% coupled with a maximum chlorpyrifos extraction and stripping efficiency were achieved at 96.1% and 95.7% at b

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