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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
Thu Mar 01 2018
Journal Name
Nuclear Physics A
Determine the 134–140Nd isotopes identity using IBM and NEF
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TThe property of 134−140Neodymium nuclei have been studied in framework Interacting Boson Model (IBM) and a new method called New Empirical Formula (NEF). The energy positive parity bands of 134−140Nd have been calculated using (IBM) and (NEF) while the negative parity bands of 134−140Nd have been calculated using (NEF) only. The E-GOS curve as a function of the spin (I) has been drawn to determine the property of the positive parity yrast band. The parameters of the best fit to the measured data are determined. The reduced transition probabilities of these nuclei was calculated. The critical point has been determined for 140Nd isotope. The potential energy surfaces (PESs) to the IBM Hamiltonian have been obtained using the intrin

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Publication Date
Fri Nov 01 2013
Journal Name
Journal Of Drugs In Dermatology: Jdd
Melanocytes transplantation in patients with vitiligo using needling micrografting technique.
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KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Drugs in Dermatology: JDD, 2013 - Cited by 22

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Publication Date
Fri Aug 01 2008
Journal Name
2008 International Symposium On Information Technology
Generating pairwise combinatorial test set using artificial parameters and values
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Publication Date
Wed Jun 11 2003
Journal Name
Iraqi Journal Of Laser
Microdrop Size Measurement in a Mixing Unit Using Laser Technique
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One of the troublesome duties in chemical industrial units is determining the instantaneous drop size distribution, which is created between two immiscible liquids within such units. In this work a complete system for measuring instantaneous droplet size is constructed. It consists of laser detection system (1mW He-Ne laser), drop generation system (turbine mixer unit), and microphotography system. Two immiscible liquids, water and kerosene were mixed together with different low volume fractions (0.0025, 0.02) of kerosene (as a dispersed phase) in water (as a continuous phase). The experiments were carried out at different rotational speed (1180- 2090 r.p.m) of the turbine mixer. The Sauter mean diameter of the drops was determined by la

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Publication Date
Thu Dec 15 2016
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Building Words Dictionary List Using Symbol Enumeration and Hashing Methodology
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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research &amp; Development
Anterior Loop Presence and Extension Using Cone-Beam Computed Tomography
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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Digital Image Watermarking Using Arnold Scrambling and Berkeley Wavelet Transform
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Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

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Publication Date
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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Publication Date
Mon Jul 22 2019
Journal Name
Innovations In Pharmacy
Evaluate Factors Influencing Depression in Baghdad: Using Deck-Depression Inventory
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Objective: This study goal was to screen participants from different settings in Baghdad for depression using Beck Depression Inventory (BDI) scale and identify factors influencing the levels of depression. Methods: This cross-sectional study included a convenience sample of 313 people from four settings (teaching hospital, college of medicine, college of pharmacy, and high school) in Baghdad, Iraq. The participants were screened using paper survey relying on the BDI scale during spring 2018. Using multiple linear regression analysis, we measured the association between depression scores and six participant factors. Results: The overall prevalence of depression in our sample was 57.2%. Female participants had higher BDI

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
PHOTO DYNAMIC THERAPY (PDT) WITH BIOLOGICAL TISSUES USING ND:GLASS LASER
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A Photo Dynamic Therapy (PDT) is a technique which is used with Laser to treat many of cancer
tissues. This paper deals with the relatively new therapeutic technique (PDT) with pulsed Nd:glass Laser
which was applied to human soft tissues (Ovary and Kidney tissues), and to the hard tissues (freshly
extracted human teeth), with power density of 280 watt/mm2 and exposure time 330 usec. Different
dyes (Blue, methylene, eosin, and orange) were applied to the area before irradiation to study the effect
of the pigments on the laser interaction with biological tissues. The zone of treatment (Z-necrosis) with
aid of MATLAB was determined. The relationship of zone of treatment with exposure time,
accumulated damage and fracti

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