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ON-Line MRI Image Selection and Tumor Classification using Artificial Neural Network
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When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every property in the classification. The classifier is according to Feed Forward Back Propagation Artificial Neural Network (FP-ANN) in the classification stage. The properties thereafter derived to be implemented to teach a neural network based binary classifier that will be automatically able to conclude whether the image is that of a pathological, suffering from brain lesion, or a normal brain. The proposed algorithm obtained the sensitivity of 97.50%, specificity of 82.86% and accuracy of 94.3% for clinical Brain MRI database. This outcome proofs that the presented algorithm is robust and effective compared with other recent techniques.

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Publication Date
Sun Apr 22 2018
Journal Name
Acs Biomaterials Science & Engineering
Engineered coatings for titanium implants to present ultra-low doses of BMP-7
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The ongoing research to improve the clinical outcome of titanium implants has resulted in the implementation of multiple approaches to deliver osteogenic growth factors accelerating and sustaining osseointegration. Here we show the presentation of human bone morphogenetic protein 7 (BMP-7) adsorbed to titanium discs coated with poly(ethyl acrylate) (PEA). We have previously shown that PEA promotes fibronectin organization into nanonetworks exposing integrin- and growth-factor-binding domains, allowing a synergistic interaction at the integrin/growth factor receptor level. Here, titanium discs were coated with PEA and fibronectin and then decorated with ng/mL doses of BMP-7. Human mesenchymal stem cells were used to investigate cellular resp

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Publication Date
Tue Jan 12 2016
Journal Name
Wireless Networks
Low communication cost (LCC) scheme for localizing mobile wireless sensor networks
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In recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Intelligent H2/Hโˆž Robust Control of an Active Magnetic Bearings System
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Abstract

Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance.  This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H2/H controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS).  Simulatio

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fibrewise Multi-Perfect Topological Spaces
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The essential objective of this paper is to introduce new notions of fibrewise topological spaces on D that are named to be upper perfect topological spaces, lower perfect topological spaces, multi-perfect topological spaces, fibrewise upper perfect topological spaces, and fibrewise lower perfect topological spaces. fibrewise multi-perfect topological spaces, filter base, contact point, rigid, multi-rigid, multi-rigid, fibrewise upper weakly closed, fibrewise lower weakly closed, fibrewise multi-weakly closed, set, almost upper perfect, almost lower perfect, almost multi-perfect, fibrewise almost upper perfect, fibrewise almost lower perfect, fibrewise almost multi-perfect, upper* continuous fibrewise upper topol

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Publication Date
Wed Oct 15 2014
Journal Name
International Journal Of Advanced Research
A survey/ Development of Passive Optical Access Networks Technologies
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The bandwidth requirements of telecommunication network users increased rapidly during the last decades. Optical access technologies must provide the bandwidth demand for each user. The passive optical access networks (PONs) support a maximum data rate of 100 Gbps by using the Orthogonal Frequency Division Multiplexing (OFDM) technique in the optical access network. In this paper, the optical broadband access networks with many techniques from Time Division Multiplexing Passive Optical Networks (TDM PON) to Orthogonal Frequency Division Multiplex Passive Optical Networks (OFDM PON) are presented. The architectures, advantages, disadvantages, and main parameters of these optical access networks are discussed and reported which have many ad

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks
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The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
A Comparison of Different Estimation Methods to Handle Missing Data in Explanatory Variables
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Missing data is one of the problems that may occur in regression models. This problem is usually handled by deletion mechanism available in statistical software. This method reduces statistical inference values because deletion affects sample size. In this paper, Expectation Maximization algorithm (EM), Multicycle-Expectation-Conditional Maximization algorithm (MC-ECM), Expectation-Conditional Maximization Either (ECME), and Recurrent Neural Networks (RNN) are used to estimate multiple regression models when explanatory variables have some missing values. Experimental dataset were generated using Visual Basic programming language with missing values of explanatory variables according to a missing mechanism at random general pattern and s

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Research - Granthaalayah
CALCULATION OF MULTIPLE MIXING RATIOS OF GAMMA RAYS FROM ๐‘ต๐’…(๐’,๐’)๐Ÿ”๐ŸŽ ๐Ÿ๐Ÿ’๐Ÿโˆ’๐Ÿ๐Ÿ“๐ŸŽ ) ๐Ÿ”๐ŸŽ๐‘ต๐’… ๐Ÿ๐Ÿ’๐Ÿโˆ’๐Ÿ๐Ÿ“๐ŸŽ INTERACTION
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In the current research, multiple mixing ratios of gamma -transitions of the energy levels 60𝑁𝑑 142−150 isotopes populated in 𝑁𝑑(𝑛, 𝑛 ˊ 60 142−150 ) 60𝑁𝑑 142−150 interaction are calculated using the constant statistical tensor (CST) method. The results obtained are, in general, in good agreement or consistent, within the experimental error, with the results published in the previously researches. Existing discrepancies result from inaccuracies in the experimental results of previous works. The current results confirm the validity of the constant statistical tenser method of calculating the values of mixing ratios and its predictability of errors in experimental results

Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparative Study for the Early Detection of the most Important Factors Leading to Preeclampsia
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The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Further properties of the fuzzy complete a-fuzzy normed algebra
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    In this paper further properties of the fuzzy complete a-fuzzy normed algebra have been introduced. Then we found the relation between the maximal ideals of fuzzy complete a-fuzzy normed algebra and the associated multiplicative linear function space. In this direction we proved that if  is character on Z then ker is a maximal ideal in Z. After this we introduce the notion structure of the a-fuzzy normed algebra then we prove that the structure, st(Z) is -fuzzy closed subset of fb(Z, ) when  (Z,  , , ) is a commutative fuzzy complete a-fuzzy normed algebra with identity e.

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