Preferred Language
Articles
/
YRb0j4oBVTCNdQwCT59C
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
...Show More Authors

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 and 579 KCN4) from Department of Ophthalmology and Visual Sciences, Paulista Medical School, Federal University of São Paulo, São Paulo in Brazil and 1531 eyes (Healthy = 400, KCN1 = 378, KCN2 = 285, KCN3 = 200, KCN4 = 88) from Department of Ophthalmology, Jichi Medical University, Tochigi in Japan and used several accuracy metrics including Precision, Recall, F-Score, and Purity. We compared the proposed method with three other standard unsupervised algorithms including k-means, Kmedoids, and Spectral cluster. Based on two independent datasets, the proposed model outperformed the other algorithms, and thus could provide improved identification of the corneal status of the patients with keratoconus.

Scopus Clarivate Crossref
View Publication
Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
...Show More Authors

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

... Show More
View Publication
Scopus (1)
Scopus Crossref
Publication Date
Thu Apr 08 1999
Journal Name
Abhath Al- Yarmouk [basic Sciences And Engineering]
Model for Predicting the Cracking Moment in Structural Concrete Members
...Show More Authors

Publication Date
Sat Jun 01 2019
Journal Name
Al-nahrain Journal Of Science
THREE DIMENSIONAL EXPLICIT MODEL FOR COMETARY TAIL IONSINTERACTIONSWITH SOLAR WIND
...Show More Authors

The different interactions between cometary tail and solar wind ions are studied in the present paper based on three-dimensional Lax explicit method. The model used in this research is based on the continuity equations describing the cometary tail-solar wind interactions. Three dimensional system was considered in this paper. Simulation of the physical system was achieved using computer code written using Matlab 7.0. The parameters studied here assumed Halley comet type and include the particle density , the particles velocity v, the magnetic field strength B, dynamic pressure p and internal energy E. The results of the present research showed that the interaction near the cometary nucleus is mainly affected by the new ions added to the

... Show More
Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
...Show More Authors

In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Geological Journal
Construction of Comprehensive Geological Model for an Iraqi Oil Reservoir
...Show More Authors

The paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie

... Show More
Preview PDF
Scopus (7)
Crossref (1)
Scopus Crossref
Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Statistical Model for Polarization Mode Dispersion in Single Mode Fibers
...Show More Authors

As the bit rate of fiber optic transmission systems is increased to more than , the system will suffer from an important random phenomena, which is called polarization mode dispersion. This phenomenon contributes effectively to: increasing pulse width, power decreasing, time jittering, and shape distortion. The time jittering means that the pulse center will shift to left or right. So that, time jittering leads to interference between neighboring pulses. On the other hand, increasing bit period will prevent the possibility of sending high rates. In this paper, an accurate mathematical analysis to increase the rates of transmission, which contain all physical random variables that contribute to determine the transmission rates, is presen

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Choose the best model for building life tables in Iraq
...Show More Authors

Demography or population studies or demography is the science that is based on the different characteristics of the population scientific study, and represent a population studies principled way to understand the population of society, in addition to verification of the population in a given area determine the reason for the increase or decrease this number from the previous statistical As these studies estimate future trends for the occurrence of demographic change in terms of birth, death and migration That the registration of deaths of paramount importance narrated that way can the demographic reality of the population analysis, and coverage of the health authorities' needs and enable government institutions of decision-making

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Nov 02 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Inducing the Health Promotion Model for Nursing Practice: Qualitative Study
...Show More Authors

Objective: To generate a model that conceptualizes the phenomenon of health promotion and its related factors.
Methodology: A grounded theory methodology is used as qualitative method to explore the health promotion as
phenomenon of interest and its other related factors from the perspectives of specialists in this field. The study is
carried out from January 2002 through September 2004. A sample of (20) specialists in health sciences are
selected and interviewed as experts in the area of health promotion. The investigators conducted intensive and
structured interviews with the specialists to collect the data. These interviews were transcribed verbatim,
analyzed and interpreted.
Results: Findings of the study indicat

... Show More
View Publication Preview PDF
Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Investigate Spectroscopic Experimental and Theoretical Model for Hemoglobin Nanoscale Solution
...Show More Authors

In the current study, haemoglobin analytes dissolved in a special buffer (KH2PO4(1M), K2HPO4(1M)) with pH of 7.4 were used to record absorption spectra measurements with a range of concentrations from (10-8 to 10-9) M and an absorption peak of 440nm using Broadband Cavity Enhanced Absorption Spectroscopy (BBCEAS) which is considered a simple, low cost, and robust setup. The principle work of this technique depends on the multiple reflections between the light source, which is represented by the Light Emitting Diode 3 W, and the detector, which is represented by the Avantes spectrophotomer. The optical cavity includes two high reflectivity  ≥99%  dielectric mirrors (dia

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (2)
Scopus Crossref
Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS
...Show More Authors

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

... Show More
View Publication Preview PDF