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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
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Prediction of bearing capacity, angle of internal friction, cohesion, and plasticity index using ANN (case study of Baghdad, Iraq)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Publication Date
Sat Aug 01 2020
Journal Name
Key Engineering Materials
Compressive Strength Performance of Reactive Powder Concrete Using Different Types of Materials as a Partial Replacement of Fine Aggregate
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Reactive Powder Concrete (RPC) can be incorporate as a one of the most important and progressive concrete technology. It is a special type of ultra-high strength concrete (UHSC) that’s exclude the coarse aggregate from its constitutive materials. In this research an experimental study had been carried out to investigate the effect of using three types of materials (porcelain aggregate) and others sustainable materials (glass waste and granular activated carbon) as a partial replacement of fine aggregate. Four percentages had considered (0, 10, 15 and 20) % to achieve better understanding for the influence of these materials upon the compressive strength of RPC. Four curing ages had included in this study, these are; 7, 28, 60 and

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
PREDICTION OF BEARING CAPACITY, ANGLE OF INTERNAL FRICTION, COHESION, AND PLASTICITY INDEX USING ANN (CASE STUDY OF BAGHDAD, IRAQ)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
PREDICTION OF BEARING CAPACITY, ANGLE OF INTERNAL FRICTION, COHESION, AND PLASTICITY INDEX USING ANN (CASE STUDY OF BAGHDAD, IRAQ).
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Publication Date
Mon Feb 01 2021
Journal Name
Materials Science Forum
The Feasibility of Using Micro Silica Sand Powder as Partial Replacement of Cement in Production of Roller Compacted Concrete
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Roller compacted concrete (RCC) is a special type of concrete with zero or even negative slump consistency. In this work, it had aimed to produce an RCC mix suitable for roads paving with minimum cost and better engineering properties so, different RCC mixes had prepared i.e. (M1, M2, M3, and M4) using specified percentages of micro natural silica sand powder (SSP) as partial replacement of (0%, 5%, 10%, and 20%) by weight of sulfate resistant Portland cement. Additionally, M-sand, crushed stone, filler, and water had been used. The results had obtained after 28 days of water curing. The control mix (M1) had satisfied the required f ‘c with accepted results for the other tests. M2 mix with SSP of 5% had

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Reality Of Using Educational Technology In Teaching Mathematics From The Point Of View Of Mathematics Teachers In Amman
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The study aims to identify the reality of the use of educational technology in the teaching of mathematics from the point of view of mathematics teachers in Amman, where the researcher used the descriptive survey method. The sample included (67) female teachers working in public schools in Amman. In order to achieve the objectives of the study, the researcher used the questionnaire as a tool to collect data. The study concluded that many educational techniques are not available from the point of view of the study sample. Mathematics teachers also found that there are many obstacles that prevent the use of educational techniques in schools, most notably the lack of courses offered to teachers on the use of teaching techniques in teaching

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Methods of using the periodic chart in the case of the missing values of the stable AR model (2)
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In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

 

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Improving Reverse Engineering Processes by using Articulated Arm Coordinate Measuring Machine
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The invention relates to a coordinate measuring machine (CMM) for determining a measuring position of a probe. The AACMM isdepends on the robotkinematics (forward and reverse) in their measurementprinciple, i.e., using the AACMM links and joint angles todetermine the exact workspace or part coordinates. Hence, themeasurements are obtained using an AACMM will be extremely accurate and precise since that ismerely dependent on rigid structural parameters and the only source of measurement error is due to human operators. In this paper, a new AACMM design was proposed. The new AACMM design addresses common issues such as solving the complex kinematics, overcoming the workspace limitation, avoiding singularity, and eliminating the effects of

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile position estimation using artificial neural network in CDMA cellular systems
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research &amp; Development
Citric Acid Production Using Wheat Bran by <i>Aspergillus niger</i>
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This study aimed to obtain a local isolation of Aspergillus niger and then studied its ability to produce citric acid from raw materials available locally using solid state fermentation. Six local isolates were collected from different sources including some samples of the damaged fruits such as grapefruit, oranges and sindi. Wheat bran was used as a raw material or as culture medium for the production of citric acid from the collected isolates. The conditions for citric acid production were determined by humidity percentage of 1: 1 (water: culture medium), temperature of 28 C, pH 4 and inoculum dose with 5× 106 spore/ml and for 3 days of incubation. The orange was the best model for citric acid production with a concentration of 12.8 mg/m

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