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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
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering &amp; Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning
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       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Mass-Transfer Characteristics of Air- Suction Type Fermentors
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Liquid-side mass-transfer coefficients (KLa) were measured in air-suction type fermentors using physical absorption of oxygen.  A fermentor of 0. 5 m i.d. was used with a working capacity of 60 liters of liquid. Tap water was used as the liquid phase, and air was used as the gas phase. The bioreactor mixing system consists of shrouded-disk/curved-blade turbine with six evacuated bending blades. The effect of liquid submergence (S) was investigated. Further, the effects of the ratio of the impeller diameter (D) to the tank diameter (T), and the clearance of the impeller from the tank bottom(C) were also studied.  The agitation speed (N) was varied in the range of 50-800 rpm. It was found that the value of  K

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Publication Date
Fri Aug 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Estimation of Volumetric Mass Transfer Coefficient in Bioreactor
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This study is concentrated to investigate the effects of aeration and stirring speed on the volumetric mass transfer coefficient (KLa). A dynamic technique was used in estimating KLa values in order to achieve the aim of this study.

This study was done in 10L bioreactor by using two medias:-

  1. Dionized water
  2. Xanthan solution (1 g /L)

Moreover, the research covered a comparison between the obtained values of KLa.

The Xanthan solution was used because of its higher viscosity in comparison with water. It behaves similarly to the cultivation medium when organisms are cultivated in a bioreactor. Growth of organisms in the reactor l

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Publication Date
Tue Apr 14 2020
Journal Name
Modern Sport
The Effect of Using the Bybee Strategy(5ES) according to Brain Control Patterns in Learning a Kinetic Series on Floor exercises in Artistic Gymnastics for men
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The aim of this study to identify patterns of cerebral control (right and left) for second grade students in the collage of physical education and sports science of the University of Baghdad, as well as identify the definition of theThe Effect of Using the Bybee Strategy(5ES) according to Brain Control Patterns in Learning a Kinetic Series on Floor exercises in Artistic Gymnastics for menمجلة الرياضة المعاصرةالمجلد 19 العدد 1 عام 2020effect using the (Bybee) strategy (5ES) according to brain control patterns inlearning a Kinetic series on floor exercises In artistic gymnastics for men, andidentify the best combination between the four research groups learn, use Finderexperimental method research sample consi

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Publication Date
Fri Dec 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Improved Method to Correlate and Predict Isothermal VLE Data of Binary Mixtures
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Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Improved thermal and mechanical properties of CdBa2-x SrxCa2Cu3O8+δ superconducting compounds
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Publication Date
Mon Oct 05 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval